Guideline Systematic Review 2004

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(Systematic Reviews)

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”π—°æ—≤π“«‘™“°“√·æ∑¬å °√¡°“√·æ∑¬å, 2547.

150 Àπâ“.

1. ‡∑§‚π‚≈¬’∑“ß·æ∑¬å. 2. «‘∑¬“‡∑§π‘§°“√·æ∑¬å. I. √—µπ“

æ—π∏åæ“π‘™, ºŸâ·µàß√à«¡. II. ‚¬∏’ ∑Õß‡ªìπ„À≠à, ºŸâ·µàß√à«¡. III. ™◊ËÕ‡√◊ËÕß

W 74

ISBN 974-7740-62-1

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«∑.∫., æ.∫., «.«. °ÿ¡“√‡«™»“ µ√å, M. Trop Paed. (Liverpool)

¿“§«‘™“‡«™»“ µ√å™ÿ¡™π §≥–·æ∑¬»“ µ√å ¡À“«‘∑¬“≈—¬‡™’¬ß„À¡à

COCHRANE Reviewer (Infectious Disease Review Group ·≈–

Developmental, Psychosocial and learning Problems Group)

·≈– Thai COCHRANE Network

π“¬·æ∑¬å‚¬∏’ ∑Õß‡ªìπ„À≠à

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¢—ÈπµÕπ∑’Ë 1°“√°”Àπ¥ªí≠À“ (Problem formulation) 15

¢—ÈπµÕπ∑’Ë 2°“√√«∫√«¡¢âÕ¡Ÿ≈ (Data collection) 21

¢—ÈπµÕπ∑’Ë 3°“√ª√–‡¡‘π§ÿ≥¿“æ (Assessing the studies) 35

¢—ÈπµÕπ∑’Ë 4°“√ —ß‡§√“–Àåº≈ (Data synthesis) 59

¢—ÈπµÕπ∑’Ë 5°“√·ª≈º≈ (Interpretation of results) 69

Cochrane Collaboration 75

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1. ‡æ◊ËÕ„™â„π°“√®—¥°“√ª√‘¡“≥¢âÕ¡Ÿ≈ ∑’Ë‡°‘¥¢÷ÈπÕ¬à“ß¡“°¡“¬¡À“»“≈

„Àâæ√âÕ¡∑’Ë®–π”‰ª„™âª√–‚¬™πå‰¥â ‚¥¬°√–∫«π°“√∑’Ë„™â„π°“√‡¢â“∂÷ßÕ¬à“ß‡ªìπ

√–∫∫ ·≈–°“√ª√–‡¡‘π§ÿ≥§à“Õ¬à“ß¡’«‘®“√≥≠“≥ (critical appraisal) ®–‡ªìπ°“√

°√Õß¢âÕ¡Ÿ≈∑’Ë¥âÕ¬§ÿ≥¿“æÕÕ°‰ª

2. „™â‡ªìπ¢âÕ¡Ÿ≈ª√–°Õ∫°“√µ—¥ ‘π„®‡™‘ßπ‚¬∫“¬¢ÕßºŸâ∫√‘À“√ À√◊Õ

°“√®—¥∑”·π«∑“ß‡«™ªØ‘∫—µ‘ (Clinical Practice Guidelines)

3. ‡ªìπ‡§√◊ËÕß¡◊Õ∑“ß«‘∑¬“»“ µ√å∑’Ë¡’ª√– ‘∑∏‘¿“æ ‚¥¬∑—Ë«‰ª°“√∑”

°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫®–„™â‡«≈“ ·≈–§à“„™â®à“¬πâÕ¬°«à“°“√∑”°“√«‘®—¬

ª∞¡¿Ÿ¡‘ (primary research) „À¡à ‚¥¬‡©æ“–Õ¬à“ß¬‘Ëß°“√ª√—∫ª√ÿß (update)

°“√∑∫∑«πÕ¬à“ßµàÕ‡π◊ËÕß – ¡µ≈Õ¥‡«≈“®–∑”„Àâ°“√π”º≈°“√«‘®—¬‰ª Ÿà°“√

ªØ‘∫—µ‘¬‘Ëß„™â‡«≈“ —Èπ≈ß¡“°

4. “¡“√∂¡Õß‡ÀÁπ≈—°…≥–∑—Ë«‰ª (Generalizability) ‚¥¬∑—Ë«‰ª°“√

»÷°…“«‘®—¬·µà≈–‡√◊ËÕß®–‰¡à‡À¡◊Õπ°—π√âÕ¬‡ªÕ√å‡´πµå ¡’§«“¡·µ°µà“ß°—π„π√“¬

≈–‡Õ’¬¥∫â“ß ‡¡◊ËÕ¡“∑”°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫·≈â«®–¡Õß‡ÀÁπ∂÷ß≈—°…≥–

∑—Ë«‰ª‰¥â

5. ∫Õ°∂÷ß§«“¡ ¡Ë”‡ ¡Õ (Consistency) ¢Õßº≈°“√»÷°…“«‘®—¬·µà

≈–™‘Èπ ‚¥¬„π°“√»÷°…“«‘®—¬¬àÕ¬π—ÈπÊ Õ“®¡’¢π“¥¬“∑’Ë·µ°µà“ß°—π‰ª À√◊Õ„™â„π‚√§

∑’Ë·µ°µà“ß°—π ´÷Ëß®–∫Õ°∂÷ß§«“¡ ¡Ë”‡ ¡Õ¢Õßº≈°“√»÷°…“«à“ Õ¥§≈âÕß

‰ª„π∑“ß‡¥’¬«°—πÀ√◊Õ‰¡à

6. µ√ß°—π¢â“¡°—∫¢âÕ∑’ËÀâ“ Õ∏‘∫“¬∂÷ßº≈∑’Ë‰¡à ¡Ë”‡ ¡Õ À√◊Õº≈¢—¥·¬âß

°—π °“√∑’Ë¡’°“√»÷°…“„¥∑’Ë‰¡à Õ¥§≈âÕß‰ª°—∫°“√»÷°…“Õ◊ËπÊ ‡ªìπ ‘Ëß∑’Ë ¡§«√

æ‘®“√≥“À“§”Õ∏‘∫“¬

7. ‡æ‘Ë¡Õ”π“®°“√∑¥ Õ∫ (Power) ¢Õß°“√»÷°…“«‘®—¬ ∑”„Àâ‡ÀÁπ

∑‘»∑“ß ·π«‚πâ¡™—¥‡®π¡“°¢÷Èπ °“√»÷°…“‡¥’Ë¬«Ê ¢π“¥°≈ÿà¡µ—«Õ¬à“ß‡≈Á°Ê Õ“®‰¡à¡’


π—¬ ”§—≠∑“ß ∂‘µ‘ ‡¡◊ËÕ¡’°“√π”¢âÕ¡Ÿ≈¡“√«¡°—π¡’®”π«πµ—«Õ¬à“ß¡“°¢÷Èπ ∑”„Àâ

Õ”π“®°“√∑¥ Õ∫¡“°¢÷Èπ

8. ‡æ‘Ë¡§«“¡‡∑’Ë¬ß¢Õßº≈ ‡¡◊ËÕ¡’¢π“¥°≈ÿà¡µ—«Õ¬à“ß¡“°¢÷Èπ ∑”„Àâ™à«ß

§«“¡‡™◊ËÕ¡—Ëπ (Confidence Interval) ·§∫≈ß

9. ‡æ‘Ë¡§«“¡∂Ÿ°µâÕß¢Õßº≈ (Accuracy) À√◊ÕÕ¬à“ßπâÕ¬∑’Ë ÿ¥°Á –∑âÕπ

§«“¡‡ªìπ®√‘ß¡“°¢÷Èπ ‡π◊ËÕß®“°°√–∫«π°“√ ¢—ÈπµÕπµà“ßÊ ·®à¡™—¥ ≈¥§«“¡

º‘¥æ≈“¥¢Õß°“√∑∫∑«π·∫∫‡¥‘¡Ê –∑âÕπ§«“¡‡ªìπ®√‘ß‰¥â¡“°¢÷Èπ ·≈–À«—ß«à“

À“°¡’°“√∑”°“√∑∫∑«π´È”µ“¡¢—ÈπµÕπ‡¥‘¡·≈â«º≈≈—æ∏å§«√‡À¡◊Õπ‡¥‘¡ À√◊Õ∂â“¡’

§«“¡·µ°µà“ß°Á “¡“√∂√Ÿâ ‰¥â«à“·µ°µà“ß®“°Õ–‰√

¢âÕ§«√√–«—ß „π°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫°“√‡æ‘Ë¡ power À“°‰¡à√–¡—¥√–«—ß ®–™à«¬¢¬“¬Õ§µ‘ (bias) º≈∫“ßÕ¬à“ß

À√◊Õ¢âÕ∫°æ√àÕß ∑’Ë‡¥‘¡¢π“¥‡≈Á°„Àâ„À≠à¢÷Èπ ∑”„Àâ‡¢â“„®º‘¥æ≈“¥‰¥â

ª√–‡¥Áπªí≠À“„π°“√æ‘®“√≥“ Systematic reviews Õ¬à“ß‡ªìπ√–∫∫1. Systematic reviews π—Èπ®—¥∑”Õ¬à“ß‰¡à‡ªìπ√–∫∫ “¡“√∂ª√–‡¡‘π

§ÿ≥§à“ µ“¡À≈—°∑’Ë¡’‡ πÕ‰«â

2. «‘∏’°“√ —ß‡§√“–Àåº≈Õ¬à“ß‰¡à‡À¡“– ¡„π§«“¡·µ°µà“ß„π«‘∏’°“√

(intervention) ¢Õß·µà≈–¢âÕ¡Ÿ≈¬àÕ¬ À√◊Õ°≈ÿà¡µ—«Õ¬à“ß„π·µà≈–¢âÕ¡Ÿ≈¬àÕ¬∑’Ë‰¡à

‡À¡◊Õπ°—π ®–∑”„Àâº≈∑’Ë ”§—≠∫“ßÕ¬à“ß‰¡à “¡“√∂· ¥ßÕÕ°¡“‰¥â ‡™àπ º≈∑’Ë

™—¥‡®π „π subgroup Àπ÷ËßÊ Õ“®‰¡àª√“°Ø„π subgroup Õ◊ËπÊ

º≈∑’Ë‰¥â®“° systematic reviews Õ“®®–‰¡à Õ¥§≈âÕß°—∫º≈°“√»÷°…“

«‘®—¬¢π“¥„À≠à∑’ËÕÕ°·∫∫Õ¬à“ß¥’¡’§ÿ≥¿“æ‰¥â °“√ª√—∫ª√ÿß¢âÕ¡Ÿ≈„Àâ∑—π ¡—¬Õ¬à“ß

¡Ë”‡ ¡Õ®–™à«¬≈¥ªí≠À“π’È ‰¥â


√–¬–‡«≈“∑’Ë„™â„π°“√∑”°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫Allen IE, Olkin I.8 ‰¥â«‘‡§√“–Àå√–¬–‡«≈“∑’Ë„™â„π°“√∑∫∑«π·∫∫

meta-analysis æ∫«à“„™â‡«≈“‡©≈’Ë¬ª√–¡“≥ 1,139 ™—Ë«‚¡ß°“√∑”ß“π µàÕÀπ÷Ëß‡√◊ËÕß

‚¥¬·∫àß‡ªìπ

588 ™—Ë«‚¡ß ”À√—∫°“√«“ß·ºπ√Ÿª·∫∫°“√∑∫∑«π ·≈–

°“√ ◊∫§âπ¢âÕ¡Ÿ≈

144 ™—Ë«‚¡ß ”À√—∫°“√«‘‡§√“–Àå∑“ß ∂‘µ‘

206 ™—Ë«‚¡ß ”À√—∫°“√‡¢’¬π√“¬ß“π

201 ™—Ë«‚¡ß ”À√—∫°“√∫√‘À“√®—¥°“√

Õ¬à“ß‰√°Áµ“¡®”π«π™—Ë«‚¡ß°“√∑”ß“π ¬—ß¢÷ÈπÕ¬Ÿà°—∫®”π«π∫∑§«“¡

∑’Ë ◊∫§âπ‰¥â µ“¡ Ÿµ√

®”π«π™—Ë«‚¡ß°“√∑”ß“π = 721 + 0.243x - 0.0000123x2

´÷Ëß x = ®”π«π∫∑§«“¡∑’Ë§“¥«à“®– ◊∫§âπ‰¥â°àÕπ°“√§—¥°√ÕßÕÕ°

µ“¡‡°≥±å

‡Õ° “√Õâ“ßÕ‘ß1. Davidoff F, Haynes B, Sackett D, Smith R. Evidence based medicine. BMJ 1995;

310(6987):1085-6.2. Chalmers I, Haynes B. Repor ting, updating, and correcting systematic

reviews of the effects of health care. BMJ 1994; 309(6958):862-5.3. Cook DJ, Mulrow CD, Haynes RB. Systematic reviews: synthesis of best evidence for

clinical decisions. Ann Intern Med 1997; 126(5):376-80.4. Mulrow CD, Cook DJ, Davidoff F. Systematic reviews: critical links in the great chain

of evidence. Ann Intern Med 1997:126(5):389-91.5. Mulrow CD. The medical review article: state of the science. Ann Intern Med 1987;

106(3):485-8.6. Duley L. Systematic reviews: what can they do for you? J R Soc Med 1996: 89(5):

242-4.7. Mulrow CD. Rationale for systematic reviews. BMJ 1994:309 (6954):597-9.8. Allen IE, Olkin I. Estimating time to conduct a meta-analysis from number of citations

retrieved. JAMA 1999; 282(7):634-5.


P8«à“ß


°√–∫«π°“√„π°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫

π“¬·æ∑¬å ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬å

°“√°”Àπ¥ªí≠À“

°“√√«∫√«¡¢âÕ¡Ÿ≈

°“√ª√–‡¡‘π§ÿ≥¿“æ

°“√ —ß‡§√“–Àåº≈

°“√·ª≈º≈


¢—ÈπµÕπ„π°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫°àÕπ∑’Ë®–‡√‘Ë¡µâπ°“√∑∫∑«π§«√µâÕß«“ß√Ÿª·∫∫ ·≈–«‘∏’°“√∑∫∑«π

‚¥¬¡’«—µ∂ÿª√– ß§å™—¥‡®π∑’Ë®–µÕ∫ªí≠À“‡ ’¬°àÕπ ‚¥¬∑—Ë«‰ª®–¡’°√–∫«π°“√

„π°“√∑”ß“π‡ªìπ¢—ÈπÊ ¥—ßπ’È

¢—ÈπµÕπ∑’Ë 1 °“√°”Àπ¥ªí≠À“ (Problem formulation)

‡ªìπ°“√µ—Èß§”∂“¡µ“¡ªí≠À“∑’ËµâÕß°“√‰¥â§”µÕ∫ ·≈–µâÕß‡ªìπ§”∂“¡

∑’Ë “¡“√∂À“§”µÕ∫‰¥â °“√°”Àπ¥§”∂“¡„π‡™‘ß‡«™ªØ‘∫—µ‘„Àâ™—¥‡®π ·≈–

‡À¡“– ¡‡ªìπ°“√‡√‘Ë¡µâπ∑’Ë®”‡ªìπ„π°“√∑∫∑«π ‡æ√“–º≈ ÿ¥∑â“¬∑’Ë‰¥â¢âÕ √ÿª

®“°°“√∑∫∑«π®–π”‰ª„™âµàÕºŸâªÉ«¬„π∑“ßªØ‘∫—µ‘ ¢—ÈπµÕππ’È ”§—≠ ·≈–°“√µ—Èß

§”∂“¡„Àâ∂Ÿ°µâÕß‰¡àßà“¬1 ‘Ëß∑’ËµâÕß∂“¡µπ‡Õß°àÕπÀ≈“¬Ê §√—Èß°Á§◊Õ ç∑”‰¡®÷ß

”§—≠∑’ËµâÕßÀ“§”µÕ∫µàÕªí≠À“π’Èé ´÷Ëß®–∑”„Àâ°“√µ—Èß§”∂“¡µ√ß®ÿ¥¡“°¬‘Ëß¢÷Èπ

µ—«Õ¬à“ß‡™àπ ‡√“ π„®„π ç§«“¡∂Ÿ°µâÕß¢Õß°“√∑¥ Õ∫™π‘¥„À¡àπ’Èé ®√‘ßÊ

À√◊Õ«à“‡√“ π„®«à“ ç°“√∑¥ Õ∫™π‘¥„À¡à¡’§«“¡∂Ÿ°µâÕß¡“°°«à“°“√∑¥ Õ∫

™π‘¥‡¥‘¡∑’Ë‡ªìπ¡“µ√∞“πÕ¬Ÿà·≈â«é À“°‡ªìπ‰ªµ“¡π’È ·≈â«‡√“∑√“∫™—¥‡®πÀ√◊Õ¬—ß«à“

ç°“√∑¥ Õ∫™π‘¥‡¥‘¡∑’Ë‡ªìπ¡“µ√∞“πÕ¬Ÿà·≈â«π—Èπ§◊ÕÕ–‰√é

Õß§åª√–°Õ∫¢Õß§”∂“¡‡πâπ§«“¡™—¥‡®π„π 4 Õ¬à“ß§◊Õ °≈ÿà¡ª√–™“°√

°≈ÿà¡‡ª√’¬∫‡∑’¬∫ intervention ·≈– outcome2

√“¬≈–‡Õ’¬¥¢Õß¢—ÈπµÕππ’È Õ¬Ÿà„π¢—ÈπµÕπ∑’Ë 1 Àπâ“ 15

¢—ÈπµÕπ∑’Ë 2 °“√√«∫√«¡¢âÕ¡Ÿ≈ (Data collection)

°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫π—Èπ¡’®ÿ¥ª√– ß§å‡æ◊ËÕµÕ∫§”∂“¡‚¥¬„™â

æ◊Èπ∞“π¢Õß¢âÕ¡Ÿ≈À≈—°∞“π¥’∑’Ë ÿ¥∑’Ë¡’Õ¬Ÿà ÷Ëß¢âÕ¡Ÿ≈À≈—°∞“π¡’∑—Èß∑’Ë≈ßæ‘¡æå„π«“√ “√

∑“ß°“√·æ∑¬å ·≈–‰¡à‰¥â≈ßæ‘¡æå ®÷ß‰¡à “¡“√∂ ◊∫§âπ„π∞“π¢âÕ¡Ÿ≈¡“µ√∞“π

∑—Ë«‰ª‰¥â ‡Õ° “√‡À≈à“π’È∫“ß§√—Èß¡’§ÿ≥¿“æ¥’ ·µà‰¡à‰¥â√—∫°“√µ’æ‘¡æå„π«“√ “√


∑’ËÕ¬Ÿà„π∞“π¢âÕ¡Ÿ≈∑’Ë„™â„π°“√ ◊∫§âπ∑—Ë«‰ª ‡π◊ËÕß®“° publication bias

¢—ÈπµÕπ°“√√«∫√«¡¢âÕ¡Ÿ≈ ®÷ß‡ªìπ¢—ÈπµÕπ∑’Ë¬ÿàß¬“°¡“° ∑’Ë®–‰¥â¢âÕ¡Ÿ≈

∑’Ë§√∫∂â«π ®÷ß„™â§”«à“ ç‡∑à“∑’Ë¡’Õ¬Ÿàé °“√ ◊∫§âπ¢âÕ¡Ÿ≈ (searching the literature)

„Àâ ‰¥âª√–‡¥Áπ∑’Ë°”Àπ¥‰«â„Àâ§√∫∂â«π µâÕß°”Àπ¥‡°≥±å°“√À“¢âÕ¡Ÿ≈ ·À≈àß¢âÕ¡Ÿ≈

·≈–«‘∏’°“√„π°“√ ◊∫§âπ¢âÕ¡Ÿ≈ (search strategy) ‡æ◊ËÕ„Àâ ‰¥â¢âÕ¡Ÿ≈∑—Èß¥â“π∫«°

·≈–¥â“π≈∫ πÕ°®“°π’È∑’Ë ”§—≠§◊Õ °√–∫«π°“√ ¢—ÈπµÕπ √“¬≈–‡Õ’¬¥„π°“√ ◊∫§âπ

®–µâÕß‡ªî¥‡º¬ µ√«® Õ∫‰¥â ¬÷¥∂◊ÕÀ≈—°°“√«à“À“°¡’°“√ ◊∫§âπ¢âÕ¡Ÿ≈¥â«¬

°√–∫«π°“√´È”µ“¡¢—ÈπµÕπ∑’Ë°≈à“«‰«â ®–‰¥âº≈‡™àπ‡¥‘¡


¢—ÈπµÕπ∑’Ë 3 °“√ª√–‡¡‘π§ÿ≥¿“æ (Assessing the studies)

¢âÕ¡Ÿ≈∑’Ë√«∫√«¡‰¥â¡“π—Èπ Õ“®¡’§ÿ≥¿“æ ·≈–§«“¡πà“‡™◊ËÕ∂◊Õ·µ°µà“ß

°—π‰ª ¢—ÈπµÕππ’È®–‡ªìπ°“√µ√«® Õ∫§«“¡∂Ÿ°µâÕß·≈–§«“¡πà“‡™◊ËÕ∂◊Õ¢Õß¢âÕ¡Ÿ≈

√“¬™‘Èπµ“¡À≈—°‡°≥±å∑’Ë°”Àπ¥‰«â≈à«ßÀπâ“‡æ◊ËÕ≈¥Õ§µ‘µàÕ¢âÕ¡Ÿ≈π—ÈπÊ ·≈â«§—¥°√Õß

„Àâ‡À≈◊Õ·µà¢âÕ¡Ÿ≈∑’Ë‡™◊ËÕ∂◊Õ‰¥â 3, 4

°“√æ‘®“√≥“§ÿ≥¿“æ¢Õß¢âÕ¡Ÿ≈«à“¢âÕ¡Ÿ≈™‘Èπ„¥πà“‡™◊ËÕ∂◊ÕÀ√◊Õ‰¡à (critical

appraisal of evidences) ¡’·π«∑“ß„π°“√æ‘®“√≥“‚¥¬ The Evidence-Based

Medicine Working Group ≈ßæ‘¡æå„π«“√ “√ Journal of the American

Medical Association (JAMA)5 À√◊Õ¡’ºŸâ√«∫√«¡‰«â„π internet ∑’Ë URL6

http://www.cche.net/usersguides/main.asp



¢—ÈπµÕπ∑’Ë 4 °“√ —ß‡§√“–Àåº≈ (Data synthesis)

‡ªìπ°“√√«¡¢âÕ¡Ÿ≈À≈—°∞“π∑’Ëºà“π°“√§—¥°√Õß ·≈–¡’§ÿ≥¿“æ‡¢â“¥â«¬°—π

§«√„™â«‘∏’°“√ quantitative ∑’Ë‡√’¬°«à“ meta-analysis ‡∑à“∑’Ë “¡“√∂∑”‰¥â

À“°‰¡à‰¥âÕ“®„™â non-quantitative °“√®—¥∑”¡—°®–∑”‡ªìπµ“√“ß· ¥ßº≈ √ÿª

¢Õß·µà≈–¢âÕ¡Ÿ≈„πÀ—«¢âÕµà“ßÊ ‡™àπ √–‡∫’¬∫«‘∏’¢Õß°“√»÷°…“ ªï∑’Ë»÷°…“ ®”π«π

µ—«Õ¬à“ß º≈°“√»÷°…“ œ≈œ ‡ª√’¬∫‡∑’¬∫„π√Ÿª·∫∫∑’Ëßà“¬ ·≈–™—¥‡®π


¢—ÈπµÕπ∑’Ë 5 °“√·ª≈º≈ (Interpretation of results)

æ‘®“√≥“º≈„π∫√‘∫∑∑’Ë®–π”‰ª„™â (placing the findings in context)

‚¥¬æ‘®“√≥“¿“æ√«¡¢Õßº≈°“√∑∫∑«π∑—ÈßÀ¡¥«à“ µÕ∫ªí≠À“∑’Ëµ—Èß¢÷Èπ‰«âÀ√◊Õ‰¡à

§«“¡∂Ÿ°µâÕß‡∑’Ë¬ßµ√ß (internal validity) ¢Õß°“√∑∫∑«π‡ªìπÕ¬à“ß‰√ √–¥—∫¢Õß


¢âÕ¡Ÿ≈À≈—°∞“π¡“°πâÕ¬‡æ’¬ß„¥ °“√æ‘®“√≥“«à“„§√®–‡ªìπºŸâ„™âº≈°“√∑∫∑«π

¥â«¬«‘∏’°“√Õ¬à“ß‰√∑’Ë‡À¡“– ¡ ÷Ëß®–π”‰ª Ÿà°“√„Àâ§”·π–π” (recommendation)

·≈–πÈ”Àπ—°¢Õß°“√„Àâ§”·π–π”¥â«¬


°àÕπ∑’Ë®–‡√‘Ë¡°“√∑∫∑«π ®–µâÕß«“ß·ºπ‡ªìπ protocol „Àâ™—¥‡®π„π∑ÿ°

¢—ÈπµÕπ √«¡∂÷ß√–‡∫’¬∫«‘∏’∑’Ë®–¥”‡π‘π°“√∑∫∑«π¥â«¬ 7

‡Õ° “√Õâ“ßÕ‘ß1. National Health and Medical Research Council. How to review the evidence: systematic

identification and review of the scientific literature. Canberra: National Health and Medical

Research Council, 2000.

2. Counsell C. Formulating questions and locating primary studies for inclusion in

systematic reviews. Ann Intern Med 1997; 127(5):380-7.

3. Hunt DL, McKibbon KA. Locating and appraising systematic reviews. Ann Intern Med

1997; 126(7):532-8.

4. Meade MO, Richardson WS. Selecting and appraising studies for a systematic

review. Ann Intern Med 1997; 127(7):531-7.

5. Oxman AD, Sackett DL, Guyatt GH. Usersû guides to the medical literature. I. How

to get started. The Evidence-Based Medicine Working Group. JAMA 1993; 270(17):

2093-5.

6. Centres for Health Evidence [Web Page]. Available at http://www.cche.net/usersguides/

main.asp (Accessed 15 August 2004).

7. Mulrow CD, Oxman A. Cochrane Collaboration Handbook. [updated Sept 1997].

Oxford: The Cochrane Collaboration.


¢—ÈπµÕπ∑’Ë 1

°“√°”Àπ¥ªí≠À“ (Problem formulation)à

π“¬·æ∑¬å ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬åà

°“√°”Àπ¥ªí≠À“

°“√√«∫√«¡¢âÕ¡Ÿ≈

°“√ª√–‡¡‘π§ÿ≥¿“æ

°“√ —ß‡§√“–Àåº≈

°“√·ª≈º≈


¢—ÈπµÕπ°“√°”Àπ¥ªí≠À“π’È ‡æ◊ËÕ®”°—¥¢Õ∫‡¢µ„π°“√∑”ß“π„Àâ™—¥‡®π

·®à¡™—¥·≈–‡À¡“– ¡∑’Ë “¡“√∂À“§”µÕ∫‰¥â °“√°”Àπ¥§”∂“¡„π‡™‘ß‡«™ªØ‘∫—µ‘

‡ªìπ°“√‡√‘Ë¡µâπ∑’Ë®”‡ªìπ„π°“√∑∫∑«π

1.1 ≈—°…≥–¢Õßªí≠À“ªí≠À“∑’Ë®–π”¡“∑”°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫π—Èπ Õ“®¡’À≈“¬≈—°…≥–1,2

·≈â«·µà¡ÿ¡¡Õß ‡™àπ

Interventions: çº≈¢Õß°“√¥Ÿ·≈√—°…“‡ªìπÕ¬à“ß‰√é ‚¥¬∑—Ë«‰ª®–

‡ªìπ«‘∏’°“√¥Ÿ·≈√—°…“ ‡™àπ °“√√—°…“‚¥¬„™â¬“ °“√ºà“µ—¥ °“√∑”®‘µ

∫”∫—¥ ‡ªìπµâπ

Frequency or rate of a condition or disease: ç‚√§À√◊Õ ¿“«–

Àπ÷ËßÊ ¡’Õ—µ√“°“√‡°‘¥À√◊Õ§«“¡∂’Ë¡“°πâÕ¬‡æ’¬ß„¥é

Diagnostic test performance: ç«‘∏’°“√µ√«®Àπ÷ËßÊ ¡’‚Õ°“ «‘π‘®©—¬

∂Ÿ°µâÕß‡æ’¬ß„¥é

Etiology and risk factors: çµ—«·ª√Àπ÷ËßÊ ®–‡ªìπªí®®—¬‡ ’Ë¬ßÀ√◊Õ

“‡Àµÿ¢Õß°“√‡°‘¥‚√§‰¥âÀ√◊Õ‰¡àé

Prediction and prognosis: ç°“√æ¬“°√≥å‚√§¢ÕßºŸâªÉ«¬π—ÈπÊ ®–

‡ªìπÕ¬à“ß‰√é

Economics: ç§à“„™â®à“¬¢Õß°“√¥Ÿ·≈√—°…“‡ªìπÕ¬à“ß‰√é

°“√µÕ∫§”∂“¡„π·µà≈–≈—°…≥–µâÕß¡’°“√ÕÕ°·∫∫√–‡∫’¬∫«‘∏’„π°“√

À“§”µÕ∫∑’Ë·µ°µà“ß°—π ÷Ëß«‘∏’°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫°Á®–¡’«‘∏’°“√∑’Ë·µ°µà“ß

°—πµ“¡‰ª¥â«¬ „π°“√√«∫√«¡¢âÕ¡Ÿ≈À≈—°∞“π®“° primary research ∑’Ëµ—Èß§”∂“¡

¡“‡À¡◊ÕπÊ °—π ·≈â« —ß‡§√“–Àå¢âÕ¡Ÿ≈¢÷Èπ¡“„À¡à √–‡∫’¬∫«‘∏’¢Õß¢âÕ¡Ÿ≈À≈—°∞“π

·µà≈–™‘Èπ∑’Ëπ”¡“°ÁµâÕß¡’√–‡∫’¬∫«‘∏’∑’Ë Õ¥§≈âÕß°—∫≈—°…≥–¢Õß§”∂“¡¥â«¬ ·≈–

°“√ª√–‡¡‘π§ÿ≥¿“æ‡æ◊ËÕ°“√∑∫∑«π¡’®ÿ¥‡πâπ‡ª≈’Ë¬π·ª≈ß‰ª ®–‡ÀÁπ°“√‡ª√’¬∫‡∑’¬∫

°—πµ“¡µ“√“ß∑’Ë 1.1


µ“√“ß∑’Ë 1.1 Types of clinical and public health questions, ideal study

types and major appraisal issues1

√Ÿª·∫∫¢Õß√–‡∫’¬∫«‘∏’™π‘¥µà“ßÊ π—Èπ¡’√“¬≈–‡Õ’¬¥∑’ËµâÕß√ŸâÕ’°¡“°¡“¬

‡ª√’¬∫‡∑’¬∫Õ¬à“ß —ÈπÊ µ“¡µ“√“ß∑’Ë 1.2


µ“√“ß∑’Ë 1.2 Types of studies used for assessing clinical and public

health interventions1


1.2 Õß§åª√–°Õ∫¢Õß§”∂“¡§”∂“¡‡æ◊ËÕµÕ∫ªí≠À“‚¥¬∑—Ë«‰ª®–ª√–°Õ∫¥â«¬ 3 à«π1, 2, 3, 4

1.2.1 µ—«·ª√∑’Ë®–»÷°…“ (study factor) ‡™àπ intervention,

diagnostic test À√◊Õ exposure √–∫ÿ„Àâ‡©æ“–‡®“–®ß Õ“®®–

¡’°“√‡ª√’¬∫‡∑’¬∫¥â«¬°Á‰¥â °≈ÿà¡‡ª√’¬∫‡∑’¬∫Õ“®‡ªìπ¬“À≈Õ°

(placebo) À√◊Õ¡’ intervention ‡ª√’¬∫‡∑’¬∫°Á‰¥â

1.2.2 ª√–™“°√ (population) À√◊Õ participants À¡“¬∂÷ß °≈ÿà¡§π

∑’Ë‡ªìπªí≠À“„π‡√◊ËÕß∑’Ë°”≈—ßµ—Èß§”∂“¡ ‡™àπ „π°≈ÿà¡ºŸâªÉ«¬ À√◊Õ

°≈ÿà¡§πª°µ‘ °“√§‘¥ª√–‡¥Áππ’È Õ“®§‘¥‡ªìπ 2 ¢—Èπ Àπ÷Ëß ‚√§

À√◊Õ ¿“«–∑’Ë π„®Õ¬Ÿà Õß ≈—°…≥–À√◊Õ ¿“æ·«¥≈âÕ¡

Õ“®µâÕß§‘¥∂÷ßµ—«·ª√∑’ËÕ“®∑”„Àâ‡°‘¥Õ§µ‘‰¥â ‡™àπ ‡æ» Õ“¬ÿ

‡™◊ÈÕ™“µ‘ À√◊Õ ¿“æ·«¥≈âÕ¡ ‡™àπ „π™ÿ¡™π „π‚√ßæ¬“∫“≈

‡ªìπµâπ °“√®”°—¥π’ÈµâÕß§”π÷ß∂÷ß‡Àµÿº≈¥â«¬ ‡™àπ °“√∑∫∑«π

effectiveness ¢Õß°“√µ√«® mammographic screening

„πºŸâÀ≠‘ßÕ“¬ÿ 40-50 ªï ®– ¡‡Àµÿ ¡º≈ ‡æ√“–¡’À≈—°∞“π¡“

·≈â««à“¬—ß¡’¢âÕ‚µâ·¬âß°—πÕ¬Ÿà

1.2.3 º≈≈—æ∏å (outcomes) µâÕß‡ªìπ outcome ∑’Ë‡©æ“–‡®“–®ß

·≈– ”§—≠ ‰¡à§«√ π„® outcome ‡≈Á°Ê πâÕ¬Ê §«√§”π÷ß∂÷ß

°“√π”‰ª„™âª√–‚¬™πå„π°“√µ—¥ ‘π„®

Õß§åª√–°Õ∫∑—Èß 3 à«ππ’È§«√√–∫ÿ„Àâ™—¥‡®π‡∑à“∑’Ë∑”‰¥â à«π¢Õ∫‡¢µ®–

°«â“ß À√◊Õ‡©æ“–‡®“–®ß‡æ’¬ß„¥ ·≈â«·µà‡√◊ËÕß∑’Ë®–∑∫∑«π ·≈–µâÕß¡’°“√ª√—∫

„Àâ‡À¡“– ¡ ‡™àπ

§”∂“¡ ç°“√µ√«® cancer screening „πª√–™“°√∑—Ë«‰ª

‰¥â‡ªìπÕ¬à“ß‰√é ¢Õ∫‡¢µ¥Ÿ®–°«â“ß¡“°‡°‘π‰ª À“§”µÕ∫≈”∫“°

§”∂“¡ ç°“√µ√«® fecal occult blood screening ∑ÿ°ªï

„πª√–™“°√ ºŸâÀ≠‘ßÕ“¬ÿ 40-50 ªï ®–≈¥Õ—µ√“µ“¬®“°¡–‡√Áß√–∫∫


∑“ß‡¥‘πÕ“À“√ à«π≈à“ß‡∑à“‰√é °Á™—¥‡®π ·µà¢Õ∫‡¢µ¥Ÿ®–πâÕ¬‰ª‡À¡◊Õπ

‡ªìπ primary research ¡“°°«à“ ·≈–ª√–‚¬™πå®–πâÕ¬‰ª

ª√—∫§”∂“¡‡ªìπ ç°“√µ√«® fecal occult blood screening

„πª√–™“°√ºŸâ „À≠à ®–≈¥Õ—µ√“µ“¬®“°¡–‡√Áß√–∫∫∑“ß‡¥‘πÕ“À“√

à«π≈à“ß‡∑à“‰√é ®–‡À¡“– ¡¢÷Èπ ´÷Ëß‡ªìπ°“√∑∫∑«π¥Ÿº≈≈—æ∏å „π

ª√–‡¥Áπ‡√◊ËÕß √–¬–Àà“ß„π°“√ screen °≈ÿà¡Õ“¬ÿ·≈–‡æ»∑’Ë§«√∑”

1.3 ºŸâ„™âº≈°“√∑∫∑«π·¡â«à“ ‘Ëß∑’Ë ¡§«√‰¥â√—∫°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫π—Èπ¡’¡“°¡“¬ ·µà°Á§«√

§”π÷ß∂÷ßº≈∑’Ë‡°‘¥¢÷Èπ«à“®–π”‰ª„™âÕ–‰√ ‡æ√“–§ß‰¡à¡’∑√—æ¬“°√ (∑—Èß§π ∑ÿπ ‡«≈“)

¡“°¡“¬∑’Ë®–∑”°“√∑∫∑«π‰ª‡ ’¬∑ÿ°Õ¬à“ß À“°‰¥â„™â¡ÿ¡¡Õß¢ÕßºŸâ∑’Ë®–π”º≈

°“√∑∫∑«π‰ª„™âª√–‚¬™πåµàÕ‰ª°Á®–∑”„Àâ°“√°”Àπ¥§”∂“¡™—¥‡®π ·¡àπ¬”

¡“°¬‘Ëß¢÷Èπ

‡Õ° “√Õâ“ßÕ‘ß1. National Health and Medical Research Council. How to review the evidence:

systematic identification and review of the scientific literature. Canberra:

National Health and Medical Research Council, 2000.

2. NHS Centre for Review and Dissemination. Undertaking systematic review

of research on ef fectiveness: CRD guidelines for those carrying out or commissioning

reviews. York: NHS Centre for Reviews and Dissemination, 2nd Edition, 2001.

3. Goodman C. Literature searching and evidence interpretation for assessing health

care practices. Stockholm: Swedish Council of Technology Assessment in Health

Care,1993.

4. Clarke M , Oxman AD editors. Cochrane Reviewers Handbook. Oxford: Update

Software : The Cochrane Library, Issue 4, 2001.



°“√√«∫√«¡¢âÕ¡Ÿ≈ (Data collection)

π“¬·æ∑¬å ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬å

°“√°”Àπ¥ªí≠À“

°“√√«∫√«¡¢âÕ¡Ÿ≈

°“√ª√–‡¡‘π§ÿ≥¿“æ

°“√ —ß‡§√“–Àåº≈

°“√·ª≈º≈


°“√√«∫√«¡¢âÕ¡Ÿ≈ (Data collection) ¡’®ÿ¥ª√– ß§å‡æ◊ËÕ ◊∫§âπÀ“¢âÕ¡Ÿ≈

∑’Ë¥’∑’Ë ÿ¥ ·≈–§√∫∂â«π ‡∑à“∑’Ë¡’Õ¬Ÿà„πªí®®ÿ∫—π ‡æ◊ËÕµÕ∫§”∂“¡„πª√–‡¥Áπ∑’Ë°”Àπ¥‰«â

„π¢—ÈπµÕπ∑’Ë 1 ¢âÕ¡Ÿ≈¥—ß°≈à“«Õ“®®–¡’°“√≈ßæ‘¡æå„π«“√ “√«‘™“°“√ À√◊Õ‰¡à‰¥â

≈ßæ‘¡æå°Á‰¥â·µà¡’§ÿ≥¿“æ‡À¡“– ¡∑’Ë®–√«∫√«¡¡“„™â‡ªìπ¢âÕ¡Ÿ≈æ◊Èπ∞“π ®–‡ÀÁπ

‰¥â«à“°“√√«∫√«¡¢âÕ¡Ÿ≈„Àâ ‰¥â§√∫∂â«πµ“¡À≈—°°“√‰¡à„™à‡√◊ËÕßßà“¬ ¢âÕ¡Ÿ≈„π

ªí®®ÿ∫—π¡’°“√¢¬“¬µ—«¢÷ÈπÕ¬à“ß¡“°¡“¬ ∑—Èß„π«“√ “√«‘™“°“√∑’Ë‡°’Ë¬«¢âÕß ·≈–„π

Grey literature ‚¥¬‡©æ“–„π internet ÷Ëß‰¡à¡’°“√®—¥∑”¥√√™π’ ◊∫§âπ πÕ°®“°

π—Èπ·≈â« ‡¡◊ËÕ ◊∫§âπæ∫ ·µà‰¡à “¡“√∂‰¥â¢âÕ¡Ÿ≈®√‘ß ‡™àπ ‰¡à¡’ full text À√◊Õµ‘¥µàÕ

‰¡à‰¥â

2.1 ◊∫§âπ√“¬ß“π°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫∑’Ë¡’ºŸâ∑”‰«â·≈â«‡ªìπ°“√ ◊∫§âπ‡æ◊ËÕ®–„Àâ∑√“∫«à“À—«¢âÕ‡√◊ËÕß À√◊Õª√–‡¥Áπ§”∂“¡∑’Ë™—¥‡®π

®“°¢—ÈπµÕπ∑’ËÀπ÷Ëßπ—Èπ¡’ºŸâ®—¥∑”·≈â«À√◊Õ‰¡à À“°ª√–‡¥Áπ§”∂“¡µ√ß°—π∑—ÈßÀ¡¥·≈–

ª√–‡¡‘π«à“¡’§«“¡πà“‡™◊ËÕ∂◊Õ‰¥â °Á‰¡à¡’§«“¡®”‡ªìπµâÕß∑”´È” À“°‰¡àµ√ß∑—ÈßÀ¡¥

À√◊Õ¡’§«“¡„°≈â‡§’¬ß “¡“√∂π”¡“‡ªìπ¢âÕ¡Ÿ≈‰¥â ‚¥¬‡©æ“–Õ¬à“ß¬‘Ëß°“√ ◊∫§âπ

¢âÕ¡Ÿ≈À≈—°∞“π ®–ª√–À¬—¥‡«≈“ ·≈–∑√—æ¬“°√¡“°

ªí®®—¬∑’Ë‡°’Ë¬«¢âÕß„π¢—ÈπµÕππ’È1 §◊Õ

- √“¬ß“ππ—ÈπÊ ®–À“∑’Ë„¥

- √“¬ß“ππ—Èπ¡’Õ¬ŸàÀ√◊Õ‰¡à ‡ªìπ©∫—∫‡µÁ¡À√◊Õ‰¡à

- µ√ßª√–‡¥Áπ§”∂“¡∑’Ë°≈ÿà¡‰¥â°”Àπ¥‰«âÀ√◊Õ‰¡à

- °√–∫«π°“√®—¥∑”‡™◊ËÕ∂◊Õ‰¥âÀ√◊Õ‰¡à

- ®—¥∑”‰«âπ“π‡æ’¬ß„¥·≈â« µâÕß∑”°“√ update ¢âÕ¡Ÿ≈À√◊Õ‰¡à

√“¬≈–‡Õ’¬¥∞“π¢âÕ¡Ÿ≈°“√ ◊∫§âπ√“¬ß“π°“√∑∫∑«πÕ¬à“ß‡ªìπ√–∫∫

¥Ÿ‡æ‘Ë¡‡µ‘¡„π Àπâ“∑’Ë 89-96


2.2 °“√ ◊∫§âπ¢âÕ¡Ÿ≈„π«“√ “√ (Searching the literature)°“√ ◊∫§âπ¢âÕ¡Ÿ≈∑’Ë¡’°“√≈ßæ‘¡æå„π«“√ “√∑“ß°“√·æ∑¬å‚¥¬∑—Ë«‰ª‡ªìπ

∑’Ë§ÿâπ‡§¬ ·≈– –¥«° ‡π◊ËÕß®“°¡’°“√√«∫√«¡ ®—¥∑”‡ªìπ∞“π¢âÕ¡Ÿ≈∑’Ë√Ÿâ®—°°—π

‡ªìπÕ¬à“ß¥’ §◊Õ MEDLINE ·≈–„πªí®®ÿ∫—π National Library of Medicine (NLM)

ª√–‡∑» À√—∞Õ‡¡√‘°“ ‰¥âπ”¡“¢¬“¬∞“π¢âÕ¡Ÿ≈√à«¡°—∫«“√ “√∑’Ë‡°’Ë¬«¢âÕß ‡æ‘Ë¡

§«“¡ “¡“√∂„π°“√§âπÀ“„À¡àÊ ∑’Ë –¥«°°«à“‡¥‘¡ ·≈–‡ªî¥∫√‘°“√ºà“π‡§√◊Õ¢à“¬

internet ‚¥¬‰¡à‡ ’¬§à“„™â®à“¬ ‚¥¬„™â™◊ËÕ«à“ PubMed

°“√ ◊∫§âπ¢âÕ¡Ÿ≈Õ¬à“ß‡ªìπ√–∫∫∑’Ë°”≈—ß°≈à“«∂÷ßπ’È ¡’§«“¡¬“°≈”∫“°

°«à“ª°µ‘ „πª√–‡¥Áπ∑’Ë«à“ §«“¡§√∫∂â«π∑—Èß¥â“π∫«° ·≈–¥â“π≈∫ ·≈–ª√“»®“°

Õ§µ‘ (bias) ´÷ËßÀ≈—°°“√„π°“√ ◊∫§âπ∑’Ë ”§—≠§◊Õ

- Sensitivity ‡πâπ°“√ ◊∫§âπ„Àâ‰¥â ‘Ëß∑’ËµâÕß°“√§√∫∂â«π ‰¡àµ°À≈àπ

¢âÕ¡Ÿ≈∑’Ë§«√®–‰¥â

- Precision ‡πâπ°“√ ◊∫§âπ∑’Ë‰¥â‡©æ“–∑’ËµâÕß°“√ ·¬° ‘Ëß∑’Ë‰¡à

µâÕß°“√ÕÕ°‰ª ‰¡à¡’¢âÕ¡Ÿ≈∑’Ë‰¡àµ√ßª√–‡¥Áπµ‘¥ÕÕ°¡“

‡¡◊ËÕµâÕß°“√‰¥âµ“¡À≈—°°“√¥—ß°≈à“« ®÷ßµâÕß¡’°≈¬ÿ∑∏å „π°“√ ◊∫§âπ¢âÕ¡Ÿ≈

∑’Ë¡’ ‡ªìπº≈√«¡¢Õß°“√ ◊∫§âπÀ≈“¬Ê §√—Èß ‡√’¬°«à“ search strategy ®π‰¥â

sensitivity ·≈– precision ∑’Ë¥’ ¡’ª√‘¡“≥‰¡à¡“°®π‡°‘π∑’Ë®– “¡“√∂‰ª¥”‡π‘π

°“√„π¢—ÈπµÕπ∂—¥Ê ‰ª‰¥â

·À≈àß¢âÕ¡Ÿ≈∑’Ë®– ◊∫§âπ°ÁµâÕß¡’§«“¡À≈“°À≈“¬ ®“°À≈“¬·À≈àß∑’Ë

πÕ°‡Àπ◊Õ‰ª®“° Medline ‡™àπ

EMBASE (Excerpta Medica database) ÷Ëß‡ªìπ∞“π¢âÕ¡Ÿ≈¢Õß

°≈ÿà¡ª√–‡∑»„π¬ÿ‚√ª ·≈–¡’«“√ “√∑’ËπÕ°‡Àπ◊Õ®“°¿“…“Õ—ß°ƒ…¡“°¢÷Èπ

CINAHL (Cumulative Index to Nursing and Allied Health

Literature) À√◊Õ∞“π¢âÕ¡Ÿ≈‡©æ“–¥â“π∑’Ë‡°’Ë¬«¢âÕß ‡™àπ AIDLINE, Psyclit,

PsycInfo

°“√°”Àπ¥‡°≥±å°“√À“¢âÕ¡Ÿ≈ ·À≈àß¢âÕ¡Ÿ≈ ·≈–°≈¬ÿ∑∏å „π°“√ ◊∫§âπ


¢âÕ¡Ÿ≈µâÕßπ”· ¥ß√“¬≈–‡Õ’¬¥„Àâ™—¥‡®π ÷Ëß “¡“√∂∑”´È”‰¥â ·≈–‰¥âº≈‡À¡◊Õπ‡¥‘¡

°“√ √â“ß°≈¬ÿ∑∏å „π°“√ ◊∫§âπ¢âÕ¡Ÿ≈ (Search strategy)

‡ªìπ ‘Ëß∑’ËµâÕß°“√∑—Èß§«“¡√Ÿâ ∑—°…–·≈–°“√∑¥≈Õß„π°“√ ◊∫§âπ

´È”·≈â«´È”Õ’° Õ“®µâÕß°“√ºŸâ‡™’Ë¬«™“≠„π°“√ ◊∫§âπ (‡™àπ ∫√√≥“√—°…å) √à«¡°—∫

ºŸâ∑∫∑«π (reviewer) ∑”ß“π√à«¡°—π ÕÕ°·∫∫°“√ ◊∫§âπ ∑¥≈Õß ◊∫§âπ ·≈–

Õ¿‘ª√“¬º≈√à«¡°—π ·°â ‰¢ ‡æ‘Ë¡‡µ‘¡·≈â«∑¥≈Õß ◊∫§âπÕ’° ‘Ëß∑’Ë®–™à«¬ √â“ß

°≈¬ÿ∑∏å „π°“√ ◊∫§âπ ‡™àπ

- §”»—æ∑å∑’Ë „™â „π°“√ ◊∫§âπ À√◊Õ keyword Õ“®µâÕß¡’°“√

ª√÷°…“ºŸâ‡™’Ë¬«™“≠¥â“π‡π◊ÈÕÀ“∑’Ë‡°’Ë¬«¢âÕßπ—ÈπÊ ™à«¬„Àâ‡°‘¥

§«“¡§√∫∂â«π

- °“√„™â Truncation ‡ªìπ‡§√◊ËÕßÀ¡“¬·∑πµ—«Õ—°…√

‡§√◊ËÕßÀ¡“¬ * ®–·∑πÕ—°…√À√◊Õ™àÕß«à“ß∑’ËÕ¬Ÿàµ—Èß·µà

‡§√◊ËÕßÀ¡“¬ * ‡ªìπµâπ‰ª ‡™àπ thera* ®–‰¥â§”∑’Ë¢÷Èπµâπ¥â«¬

thera ‰¡à«à“®–‡ªìπ therapeutic À√◊Õ therapy À√◊ÕÕ◊Ëπ Ê

∑’Ë‡√“Õ“®‰¡à§‘¥∂÷ß·µà¢÷Èπµâπ¥â«¬ thera

- °“√„™â»—æ∑å∑’Ë¡’§«“¡À¡“¬§≈â“¬Ê °—π‡ªìπ keyword2

™à«¬„π°“√ ◊∫§âπ ‡™àπ screening °—∫ early detection,

colorectal °—∫ bowel, cancer °—∫ neoplasm ‡ªìπµâπ

- °“√„™â Thesaurus ‡ªìπ√“¬°“√§”∑’Ë¡’§«“¡À¡“¬‡À¡◊Õπ°—π

·µà„™â»—æ∑å·µ°µà“ß°—π

- °“√„™â MeSH term (Medical Subject Headings)

‡ªìπ°“√®—¥∞“π¢âÕ¡Ÿ≈µ“¡≈—°…≥–¢Õß∫∑§«“¡«à“¡’§«“¡

‡°’Ë¬«¢âÕß°—∫¥â“π„¥ °”Àπ¥‡ªìπ§”À√◊Õ term ¡“µ√∞“π®—¥

‡ªìπ°≈ÿà¡Ê ‡ªìπ™—ÈπÊ ‰«â °“√°”Àπ¥«à“∫∑§«“¡π—Èπ‡°’Ë¬«¢âÕß

°—∫‡√◊ËÕßÕ–‰√ ‡ªìπ¿“æ√«¡ Õ“®®–‰¡à¡’§”π—ÈπÊ Õ¬Ÿà„π∫∑§«“¡


‡≈¬°Á‰¥â MeSH ®—¥∑”‚¥¬ºŸâ‡™’Ë¬«™“≠ (indexer) ‡ªìπºŸâ‡≈◊Õ°

§”¡“µ√∞“π„Àâ ·µà≈–∫∑§«“¡Õ“®¡’À≈“¬ MeSH ·≈â«·µà

§«“¡‡°’Ë¬«¢âÕß¢Õß∫∑§«“¡π—Èπ Ê °“√„™â MeSH term

™à«¬„π°“√ ◊∫§âπ ®–‰¥â∫∑§«“¡∑’Ëµ√ß°—∫‡√◊ËÕß∑’ËµâÕß°“√¡“°

- °“√„™â Boolean operators ‡ªìπ°“√„™â§” —Ë ß ‡™◊ËÕ¡

(operator) ‡™àπ AND, OR, NOT ‡æ◊ËÕ√«¡º≈≈—æ∏å¢Õß°“√

◊∫§âπ·µà≈–·∫∫‡¢â“¥â«¬°—π

- °“√°√–®“¬§”∂“¡°“√ ◊∫§âπÕÕ°‡ªìπ à«πÊ3 ‡ªìπ°≈«‘∏’∑’Ë™à«¬

„Àâ‡ÀÁπ¿“æ¡“°¢÷Èπ¥—ßµ—«Õ¬à“ß„π√Ÿª∑’Ë 2.1

- «‘∏’°“√ Snowballing2 ‡ªìπ°“√ ◊∫§âπ®“°∫∑§«“¡∑’Ë¡’‡π◊ÈÕÀ“

µ√ß°—∫∑’ËµâÕß°“√·≈â« ‚¥¬¥Ÿ∑’Ë MeSH term Õ“®æ∫

keyword ∑’Ë‰¡à‰¥âπ÷°∂÷ß ·≈â«¬âÕπ‰ª„™â§”π—ÈπÊ ‡æ‘Ë¡‡µ‘¡„π°“√

◊∫§âπ´È”Õ’°§√—Èß À√◊ÕÕ“®„™â®“°‡Õ° “√Õâ“ßÕ‘ß¢Õß∫∑§«“¡

π—Èπ‡ªìπ‡§√◊ËÕßπ”∑“ß‰ª Ÿà∫∑§«“¡∑’Ë ◊∫§âπ„À¡à À√◊ÕÕ“® ◊∫§âπ

®“° Science citation index

‡¡◊ËÕ√«¡«‘∏’°“√ ◊∫§âπ·∫∫µà“ßÊ ‡¢â“¥â«¬°—π ‡√’¬ßµ“¡≈”¥—∫ ¡“„™â„π°“√

◊∫§âπ„π∞“π¢âÕ¡Ÿ≈ ´÷Ëß‡√’¬°«à“ search strategy ¥—ß· ¥ßµ—«Õ¬à“ß„π√Ÿª∑’Ë 2.2


√Ÿª∑’Ë 2.1 · ¥ßµ—«Õ¬à“ß°“√ √â“ß°≈¬ÿ∑∏å „π°“√ ◊∫§âπ¢âÕ¡Ÿ≈ (search

strategy) ‚¥¬°“√°√–®“¬§”∂“¡°“√ ◊∫§âπÕÕ°‡ªìπ à«πÊ3


√Ÿª∑’Ë 2.2 · ¥ßµ—«Õ¬à“ß°≈¬ÿ∑∏å „π°“√ ◊∫§âπ¢âÕ¡Ÿ≈ (search strategy)3


2.3 °“√ ◊∫§âπ¢âÕ¡Ÿ≈®“°·À≈àßÕ◊ËπÊ 2.3.1 Internet ¡’¡“°¡“¬‚¥¬ ◊∫§âπºà“π search engine µà“ßÊ

∑’Ë√Ÿâ®—°°—π¥’ ´÷Ëß search engine ∑’Ë¡’ª√–‚¬™πå¡“°∑“ß°“√·æ∑¬å ‰¥â·°à

- http://www.google.com

- http://www.webmedlit.com/

- http://www.medmatrix.org/index.asp

- http://www.tripdatabase.com

2.3.2 Grey literature4 ¡’¢âÕ¡Ÿ≈∫“ßÕ¬à“ß∑’Ë¡’ª√–‚¬™πå·µà‰¡à “¡“√∂

◊∫§âπ‰¥â®“°∞“π¢âÕ¡Ÿ≈µ“¡ª°µ‘‰¥â ¢âÕ¡Ÿ≈‡À≈à“π’ÈÕ“®®–Õ¬Ÿà„π≈—°…≥–‡Õ° “√

‡¬Á∫‡≈à¡ (monograph) ‡Õ° “√ª√–°Õ∫°“√ª√–™ÿ¡ (conference proceed-

ing) ·π«∑“ß‡«™ªØ‘∫—µ‘ ‡Õ° “√¢Õß ¡“§¡«‘™“™’æ ‡Õ° “√°“√ª√–™ÿ¡§≥–

°√√¡°“√ ‡Õ° “√¢Õß∫√‘…—∑ ‡ªìπµâπ ‡Õ° “√‡À≈à“π’È∫“ß§√—Èß¡’§ÿ≥¿“æ¥’ ·µà‰¡à‰¥â

√—∫°“√µ’æ‘¡æå„π «“√ “√∑’ËÕ¬Ÿà„π∞“π¢âÕ¡Ÿ≈∑’Ë„™â„π°“√ ◊∫§âπ∑—Ë«‰ª ÷Ëß¡’°“√æ∫«à“2,5

°“√»÷°…“∑’Ë‰¥âº≈∫«° (§◊Õº≈·µ°µà“ßÕ¬à“ß¡’π—¬ ”§—≠) ®–‰¥â√—∫°“√µ’æ‘¡æå

¡“°°«à“°“√»÷°…“∑’Ë‰¥âº≈≈∫ (§◊Õº≈·µ°µà“ß‰¡à¡’π—¬ ”§—≠) À√◊Õ„π∫“ß°√≥’

ºŸâ „Àâ∑ÿπ°“√»÷°…“«‘®—¬®–Õπÿ≠“µ„Àâ¡’°“√µ’æ‘¡æå‡©æ“–∑’Ë®–„Àâº≈¥’µàÕºŸâ„Àâ∑ÿπ

‘Ëß‡À≈à“π’È‡√’¬°«à“ publication bias ®÷ß¡’°≈ÿà¡∫ÿ§§≈∫“ß°≈ÿà¡æ¬“¬“¡∑’Ë®–®—¥

∑”∞“π¢âÕ¡Ÿ≈ Grey literature „Àâ ◊∫§âπ°—π‰¥â ‡™àπ SIGLE (System for

Information on Grey Literature in Europe)6

2.3.3 √“¬°“√®“°‡Õ° “√Õâ“ßÕ‘ß (reference lists) ‡ªìπ«‘∏’∑’Ë¥’∑’Ë®–

‰¥â¢âÕ¡Ÿ≈∑’Ëµ√ß°—∫‡√◊ËÕßπ—ÈπÊ ‡¡◊ËÕ‰¥â‡Õ° “√µ—Èßµâπ ‚¥¬‡©æ“–‡√◊ËÕß∑’Ë‡ªìπ≈—°…≥–

review articles ®–™à«¬‡æ‘Ë¡‡µ‘¡¢âÕ¡Ÿ≈„Àâ§√∫∂â«π¡“°¢÷Èπ

2.3.4 µ‘¥µàÕ à«π∫ÿ§§≈ ªí®®ÿ∫—π√“¬™◊ËÕºŸâ‡™’Ë¬«™“≠ À√◊ÕºŸâ«‘®—¬„π

«“√ “√µà“ßÊ ¡—°®–¡’ e-mail address Õ¬Ÿà¥â«¬ ÷ËßÕ“®µ‘¥µàÕ‡æ◊ËÕ¢Õ√“¬≈–‡Õ’¬¥

À√◊Õ¢âÕ¡Ÿ≈‡æ‘Ë¡‡µ‘¡‰¥â „π°√≥’∑’Ë‰¡à “¡“√∂ ◊∫§âπ¢âÕ¡Ÿ≈®“°·À≈àßÕ◊ËπÊ ‰¥â


2.4 °“√§—¥°√Õß¢âÕ¡Ÿ≈‡ªìπ°“√§—¥·¬°¢âÕ¡Ÿ≈∑’Ë‰¡à‡°’Ë¬«¢âÕß ‰¡àµ√ß§”∂“¡ ‰¡àµ√ßª√–‡¥ÁπÕÕ°‰ª

§«“¡ ”§—≠„π°“√§—¥°√Õß¢âÕ¡Ÿ≈ §◊Õ µâÕß°√–∑”‚¥¬ª√“»®“°Õ§µ‘ (bias)

®÷ßµâÕß°”Àπ¥‡°≥±å°“√§—¥°√Õß‰«â‡ªìπ°“√≈à«ßÀπâ“ «à“®–‡Õ“¢âÕ¡Ÿ≈·∫∫„¥‡¢â“

‡Õ“¢âÕ¡Ÿ≈·∫∫„¥ÕÕ° ‡°≥±å°“√§—¥°√Õßπ’È§«√®—¥∑”µ—Èß·µà™à«ß°“√«“ß·ºπ„π°“√

∑∫∑«π ·≈–µâÕß Õ¥§≈âÕß°—∫§”∂“¡„π¢—ÈπµÕπ∑’ËÀπ÷Ëß ¥Ÿµ—«Õ¬à“ß„π√Ÿª∑’Ë 2.3

√Ÿª∑’Ë 2.3 µ—«Õ¬à“ß°“√°”Àπ¥‡°≥±å°“√§—¥°√Õß inclusion criteria ·≈–

exclusion criteria3


°“√®”°—¥¢âÕ¡Ÿ≈À≈—°∞“π∑’Ëµ’æ‘¡æå‡©æ“–¿“…“„¥π—Èπ Õ“®®–∑”„Àâº≈

√«¡º‘¥æ≈“¥‰¥â ‡π◊ËÕß®“° publication bias ‡™àπ °“√µ’æ‘¡æå„π∫“ßª√–‡∑»

‡ªìπ°“√»÷°…“∑’Ë¡’º≈∫«°¡“°°«à“7 „πÕ’°¥â“πÀπ÷ËßºŸâ«‘®—¬¡’·π«‚πâ¡∑’Ë®– àß‡√◊ËÕß

∑’Ë‡ªìπº≈≈∫ ‰ª≈ßæ‘¡æå„π«“√ “√∑âÕß∂‘Ëπ¡“°°«à“

¢âÕ¡Ÿ≈À≈—°∞“π∑’Ë‰¥â¡“Õ“®¡’°“√≈ßæ‘¡æå´È”‚¥¬„™â¢âÕ¡Ÿ≈™ÿ¥‡¥‘¡ ≈ßæ‘¡æå

„π«“√ “√·µ°µà“ß°—π‰ª À√◊Õ·¡â·µàÕ“®„™â™◊ËÕºŸâ∑”«‘®—¬·µ°µà“ß°—πÕÕ°‰ª §«√

√–¡—¥√–«—ß ·≈–µ—¥¢âÕ¡Ÿ≈∑’Ë´È”´âÕπ‡À≈à“π—ÈπÕÕ°

°“√§—¥°√ÕßÕÕ°®–∑”‡ªìπ¢—ÈπÊ µ—Èß·µà°“√ ◊∫§âπ¢âÕ¡Ÿ≈∑“ß§Õ¡æ‘«‡µÕ√å

µ“¡ search strategy ∑’Ë«“ß·ºπ‰«â ´÷Ëß‡¡◊ËÕ‰¥â™◊ËÕ‡√◊ËÕß·≈–‡√◊ËÕß¬àÕ¡“·≈â« Õ“®

µâÕß§—¥ÕÕ° ‡æ√“–‡√◊ËÕßπ—ÈπÊ ‰¡à‡°’Ë¬«¢âÕß ‡¡◊ËÕ®–À“‡Õ° “√©∫—∫‡µÁ¡ Õ“®¡’

∫“ß‡√◊ËÕß ∑’ËÀ“‡Õ° “√‰¡à‰¥â °“√§—¥ÕÕ°‡ªìπ¢—ÈπÊ π’È ‰ª®π∂÷ß°“√ª√–‡¡‘π§ÿ≥¿“æ

Velasco et al8 ‰¥â·π–π”¢—ÈπµÕπ„π°“√ ◊∫§âπ«“√ “√Õ¬à“ß‡ªìπ√–∫∫§√∫∂â«π‰«â

¥—ß· ¥ß „π√Ÿª∑’Ë 2.4

¢—ÈπµÕπ‡À≈à“π’ÈµâÕß· ¥ß√“¬≈–‡Õ’¬¥‰«â„π‡Õ° “√©∫—∫ ¡∫Ÿ√≥å «à“§—¥

ÕÕ°¥â«¬‡Àµÿº≈Õ–‰√ ®”π«π‡∑à“„¥ °“√§—¥°√Õß„π∫“ß¢—ÈπµÕπÕ“®µâÕß„™â

§«“¡‡ÀÁπ¢ÕßºŸâ∑∫∑«π¡“°°«à“ 1 §π¢÷Èπ‰ª3 À√◊ÕÕ“®µâÕß¡’°“√ªî¥∫—ß ™◊ËÕºŸâ∑”

«‘®—¬ ∂“∫—π∑’Ë«‘®—¬ ™◊ËÕ«“√ “√ ªï∑’Ëæ‘¡æå ‡æ◊ËÕªÑÕß°—πÕ§µ‘∑’ËÕ“®‡°‘¥¢÷Èπ‰¥â


√Ÿª∑’Ë 2.4 ·ºπ¿Ÿ¡‘¢—ÈπµÕπ°“√ ◊∫§âπ«“√ “√Õ¬à“ß‡ªìπ√–∫∫8


√ÿªª√–‡¥Áπ ”§—≠„π°“√√«∫√«¡¢âÕ¡Ÿ≈ °“√ ◊∫§âπµâÕß¡’°“√«“ß·ºπÕ¬à“ß¥’ ‡ªìπ√–∫∫ ‡æ◊ËÕªÑÕß°—πÕ§µ‘

(bias)

§«√¡’°“√√à«¡¡◊Õ„π°“√∑”ß“π√–À«à“ß ºŸâ∑∫∑«π ·≈–∫√√≥“√—°…å

„π°“√«“ß·ºπ ·≈–°“√ ◊∫§âπ

°“√ ◊∫§âπµâÕß¡’§«“¡À≈“°À≈“¬ ‡™àπ À≈“°À≈“¬·À≈àß∞“π¢âÕ¡Ÿ≈

„™âÀ≈“°À≈“¬√Ÿª·∫∫ (computer, manual) À≈“°À≈“¬§√—Èß

‡ªìπµâπ

Õ“®µâÕß¡’°“√ª√÷°…“ºŸâ‡™’Ë¬«™“≠¥â“π‡π◊ÈÕÀ“ “√–¢Õß‡√◊ËÕßπ—ÈπÊ

‡æ◊ËÕ‰¥â keyword ¢âÕ¡Ÿ≈∑’Ë¡‘‰¥â≈ßæ‘¡æå„π«“√ “√«‘™“°“√

µâÕß¡’°“√∫—π∑÷° «‘∏’°“√®—¥°“√°—∫¢âÕ¡Ÿ≈∑’Ë ‰¥â¡“Õ¬à“ß‡ªìπ√–∫∫

„π∑ÿ°¢—ÈπµÕπ „Àâ “¡“√∂µ√«® Õ∫¬âÕπ°≈—∫‰¥â

°“√§—¥°√ÕßµâÕßª√“»®“°Õ§µ‘ ‚¥¬°“√µ—Èß‡°≥±å inclusion

criteria ·≈– exclusion criteria ·≈–„™âºŸâ∑∫∑«πµ“¡‡°≥±å

¥—ß°≈à“«¡“°°«à“ 1 §π ‡ªìπÕ‘ √–µàÕ°—π À“°‰¥âº≈‰¡àµ√ß°—π „Àâ„™â

©—π∑“¡µ‘ À√◊Õ„™â«‘∏’°“√ sensitivity analysis „π¢—ÈπµÕπ°“√

«‘‡§√“–Àåº≈

‡Õ° “√Õâ“ßÕ‘ß1. ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬å. °√–∫«π°“√„π°“√ª√–‡¡‘π‡∑§‚π‚≈¬’∑“ß°“√·æ∑¬å. ™“µ√’ ∫“π™◊Ëπ,

¡‡°’¬√µ‘ ‚æ∏‘ —µ¬å, ∫√√≥“∏‘°“√. §Ÿà¡◊Õ°“√ª√–‡¡‘π‡∑§‚π‚≈¬’∑“ß°“√·æ∑¬å (Technology

Assessment). ππ∑∫ÿ√’: ”π—°æ—≤π“«‘™“°“√·æ∑¬å °√¡°“√·æ∑¬å, 2545.

2. National Health and Medical Research Council. How to review the evidence:

systematic identification and review of the scientific literature. Canberra: National

Health and Medical Research Council, 2000.

3. NHS Centre for Review and Dissemination. Undertaking systematic review of

research on effectiveness: CRD guidelines for those carrying out or commissioning





Care, 1993.

5. Stern JM, Simes RJ. Publication bias: evidence of delayed publication in a cohort

study of clinical research projects. BMJ 1997; 315(7109): 640-5.

6. SIGLE (System for Information on Grey Literature in Europe) [Web Page]. Available

at http://www.fiz-informationsdienste.de/en/DB/sigle/index.html (Accessed 15

August 2004).

7. Vickers A, Goyal N, Harland R, Rees R. Do certain countries produce only positive

results? A systematic review of controlled trials. Control Clin Trials 1998; 19(2):

159-66.

8. Velasco M, Perleth M, Drummond M. et al. Best practice in undertaking and

reporting health technology assessments. Working group 4 report. Int J Technol

Assess Health Care 2002; 18(2): 361-422.



°“√ª√–‡¡‘π§ÿ≥¿“æ (Assessing the studies)

π“¬·æ∑¬å ‚¬∏’ ∑Õß‡ªìπ„À≠à

π“¬·æ∑¬å ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬åà

°“√°”Àπ¥ªí≠À“

°“√√«∫√«¡¢âÕ¡Ÿ≈

°“√ª√–‡¡‘π§ÿ≥¿“æ

°“√ —ß‡§√“–Àåº≈

°“√·ª≈º≈


®ÿ¥ª√– ß§å¢Õß¢—ÈπµÕππ’È ‡æ◊ËÕª√–‡¡‘π§ÿ≥¿“æ¢Õß¢âÕ¡Ÿ≈À≈—°∞“π

∑’Ë√«∫√«¡ ·≈–ºà“π‡°≥±å°“√§—¥°√Õß‡¢â“¡“·≈â« µâÕß ”√«® µ√«® Õ∫§ÿ≥¿“æ

¢Õß°“√»÷°…“«‘®—¬π—ÈπÊ «à“ §ÿ≥¿“æ‡À¡“– ¡∑’Ë®–„™â‡ªìπ¢âÕ¡Ÿ≈æ◊Èπ∞“π ‡æ◊ËÕ°“√

—ß‡§√“–ÀåµàÕ‰ªÀ√◊Õ‰¡à °“√»÷°…“«‘®—¬∫“ß©∫—∫Õ“®¡’§ÿ≥¿“æ‰¡àπà“‡™◊ËÕ∂◊Õ∑’Ë®–

π”¡“„™â ·¡â«à“®–∑”„π‡√◊ËÕß∑’Ëµ√ßµ“¡‡°≥±å§—¥°√Õß¡“·≈â«°Áµ“¡

3.1 √–¥—∫¢Õß¢âÕ¡Ÿ≈À≈—°∞“π‡ªìπ°“√®—¥√–¥—∫§«“¡πà“‡™◊ËÕ∂◊Õ¢Õß¢âÕ¡Ÿ≈À≈—°∞“π∑’Ëºà“π°“√§—¥°√Õß

¡“·≈â«‚¥¬¥Ÿ®“°√–‡∫’¬∫«‘∏’„π°“√»÷°…“«‘®—¬¢Õß¢âÕ¡Ÿ≈™‘Èππ—Èπ ¡’«‘∏’°“√„π°“√®—¥

√–¥—∫Õ¬ŸàÀ≈“¬·∫∫ ¡’À≈—°°“√∑—Ë«‰ª §◊Õ

Prospective studies √–¥—∫§«“¡πà“‡™◊ËÕ∂◊Õ¡“°°«à“

retrospective studies

Controlled studies √–¥—∫§«“¡πà“‡™◊ËÕ∂◊Õ¡“°°«à“ uncontrolled

studies

Randomized studies √–¥—∫§«“¡πà“‡™◊ËÕ∂◊Õ¡“°°«à“

nonrandomized studies

Large studies (i.e., involving enough patients to detect with

acceptable confidence levels any true treatment effects)

√–¥—∫§«“¡πà“‡™◊ËÕ∂◊Õ¡“°°«à“ small studies

Contemporaneous controls √–¥—∫§«“¡πà“‡™◊ËÕ∂◊Õ¡“°°«à“

historical studies

Blinded studies (patients, clinicians, analysts) √–¥—∫§«“¡πà“

‡™◊ËÕ∂◊Õ¡“°°«à“ unblinded studies

√–‡∫’¬∫«‘∏’æ◊Èπ∞“π„π°“√»÷°…“«‘®—¬®–¡’§«“¡πà“‡™◊ËÕ∂◊Õ‡√’¬ß≈”¥—∫®“°

¡“°‰ªπâÕ¬ ¥—ßπ’È

Large randomized controlled trial (RCT)


Small RCT

Nonrandomized trial with contemporaneous controls

Nonrandomized trial with historical controls

Cohort study

Case-control study

Cross-sectional study

Surveillance (e.g., using databases, registers, or surveys)

Series of consecutive cases

Single case report

„π°“√®—¥√–¥—∫§«“¡πà“‡™◊ËÕ∂◊Õ¢Õß¢âÕ¡Ÿ≈À≈—°∞“π¡’À≈“¬√–∫∫ ‡™àπ

NHS Centre for Reviews and Dissemination, University of York11

µ“¡µ“√“ß∑’Ë 3.1 ·≈– Oxford Centre for Evidence-based Medicine12

‰¥â‡ πÕ«‘∏’°“√®—¥√–¥—∫ ∑’Ë§àÕπ¢â“ß´—∫´âÕπ µ“¡µ“√“ß∑’Ë 3.2

µ“√“ß∑’Ë 3.1 √–¥—∫¢Õß¢âÕ¡Ÿ≈À≈—°∞“π¢Õß°“√»÷°…“™π‘¥ Effectiveness11

√–¥—∫ ¢âÕ¡Ÿ≈À≈—°∞“π

1 Experimental studies (e.g. RCT with concealed allocation)2 Quasi-experimental studies (e.g. experimental study

without randomisation)3 Controlled observational studies

3a. Cohort studies3b. Case control studies

4 Observational studies without control groups5 Expert opinion based on pathophysiology, bench research

or consensus. (CRD Report Number 4,NHS Centre for Reviews and Dissemination, University of York, 2001.)


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3.2 °“√ª√–‡¡‘π§«“¡∂Ÿ°µâÕß‡À¡“– ¡¢Õß¢âÕ¡Ÿ≈À≈—°∞“π∑“ß°“√ ·æ∑¬å (Critical appraisal of evidences)

°“√√«∫√«¡À≈—°∞“π∑“ß°“√·æ∑¬å∑’Ë§âπ‰¥â„π·µà≈–§”∂“¡∑’Ë‡°’Ë¬«‡π◊ËÕß

°—∫°“√¥Ÿ·≈√—°…“ºŸâªÉ«¬π—Èπ®–¡’®”π«π¡“°¡“¬ ·µà„™à«à“∑ÿ°§«“¡√Ÿâ∑’Ë‰¥â¡“®–

“¡“√∂π”¡“„™â‡ªìπ¢âÕ¡Ÿ≈æ◊Èπ∞“π‰¥â∑—ÈßÀ¡¥ ∫“ßß“π«‘®—¬®–¡’ªí≠À“„π‡√◊ËÕß

§«“¡∂Ÿ°µâÕß‡∑’Ë¬ßµ√ß‡™◊ËÕ∂◊Õ‰¥â¢Õß√–‡∫’¬∫«‘∏’«‘®—¬∑’Ë„™â (methodology) ∫“ßß“π

«‘®—¬®–¡’ªí≠À“‡√◊ËÕß‡§√◊ËÕß¡◊ÕÀ√◊Õ«‘∏’°“√∑’Ë„™â ‰¡à “¡“√∂π”¡“ªØ‘∫—µ‘‰¥âµ“¡

∂“π°“√≥å∑’Ëµ—Èß‰«â (applicability) ∫“ßß“π‡ªìπ°“√«‘®—¬„πºŸâªÉ«¬‡©æ“–°≈ÿà¡∑’Ë‰¡à

“¡“√∂π”¡“ª√–¬ÿ°µå„™â‡ªìπ·∫∫·ºπ¢ÕßºŸâªÉ«¬∑—Ë«‰ª‰¥â (generalizability)

®÷ßµâÕß¡’°√–∫«π°“√∑’Ë®–ª√–‡¡‘π§«“¡∂Ÿ°µâÕß‡À¡“– ¡¢ÕßÀ≈—°∞“π∑“ß°“√

·æ∑¬å ∑’Ë‡√’¬°«à“ critical appraisal of evidences ®ÿ¥¡ÿàßÀ¡“¬ §◊Õ°“√æ‘®“√≥“

°“√»÷°…“«‘®—¬Õ¬à“ßæ‘π‘®æ‘‡§√“–Àå „Àâ∑√“∫«à“¢âÕ®”°—¥¢Õß·µà≈–ß“π«‘®—¬Õ¬Ÿà∑’Ë„¥

‡¡◊ËÕ·ª≈º≈ À√◊Õπ”¡“„™âß“π®–‰¥â√–«—ß„π°“√ª√–¬ÿ°µå„™â

À≈—°‡°≥±å„π°“√æ‘®“√≥“°àÕππ”¢âÕ¡Ÿ≈À≈—°∞“π∑“ß°“√·æ∑¬å¡“„™â

¡’Õ¬à“ßπâÕ¬ 3 ª√–°“√

1. æ‘®“√≥“§«“¡∂Ÿ°µâÕß‡∑’Ë¬ßµ√ß (validity) ¢Õß¢âÕ¡Ÿ≈À≈—°∞“π∑“ß

°“√·æ∑¬å

2. æ‘®“√≥“§«“¡ ”§—≠·≈–πÈ”Àπ—°¢Õß¢âÕ¡Ÿ≈À≈—°∞“π

3. §«“¡ Õ¥§≈âÕß “¡“√∂π”¡“ª√–¬ÿ°µå„™â°—π‰¥â¢Õß¢âÕ¡Ÿ≈À≈—°∞“π

∑“ß°“√·æ∑¬åπ—ÈπÊ °—∫ ∂“π°“√≥å∑’Ë‡ªìπÕ¬Ÿà

‚¥¬∑—Ë«‰ªÀ≈—°°“√æ‘®“√≥“¢âÕ¡Ÿ≈À≈—°∞“π∑“ß°“√·æ∑¬å∑’ËÕ“®¡’¢âÕ

∫°æ√àÕß „π√–‡∫’¬∫«‘∏’«‘®—¬®–æ‘®“√≥“„π®ÿ¥µàÕ‰ªπ’È §◊Õ °“√‡≈◊Õ°·∫∫ß“π«‘®—¬

(study design) ∑’Ë‰¡à‡À¡“– ¡°—∫≈—°…≥–¢Õß§”∂“¡«‘®—¬π—ÈπÊ ÷Ëß‡À¡◊Õπ°—∫°“√

‡≈◊Õ° Ÿµ√„π°“√§”π«≥‰¡à∂Ÿ°µâÕß §”µÕ∫∑’Ë‰¥â¡“®÷ß‡™◊ËÕ∂◊Õ‰¡à‰¥â °“√‡≈◊Õ°ºŸâªÉ«¬

∑’Ë ‰¡àµ√ß°—∫∑’ËµâÕß°“√À√◊Õ‰¡à‡≈◊Õ°‚¥¬«‘∏’ ÿà¡ ∑”„Àâ ‰¥âµ—«Õ¬à“ß„πß“π«‘®—¬‰¡à

‡À¡“– ¡ ¡’Õ§µ‘ °“√‡≈◊Õ°µ—«™’È«—¥·≈–‡§√◊ËÕß¡◊Õ∑’Ë„™â„π°“√«‘®—¬∑’Ë‰¡à‡À¡“– ¡


∑”„Àâ ‰¡à “¡“√∂«—¥ ‘Ëß∑’ËµâÕß°“√®–«—¥‰¥âÕ¬à“ß‡∑’Ë¬ßµ√ß‡™◊ËÕ∂◊Õ‰¥â °“√„Àâ°“√√—°…“

„π°“√»÷°…“«‘®—¬ ‰¡à¡’§«“¡≈”‡Õ’¬ß„π√–À«à“ß°≈ÿà¡∑¥≈Õß°—∫°≈ÿà¡§«∫§ÿ¡ §«“¡

√–¡—¥√–«—ß„π°“√‡°Á∫√«∫√«¡ ·≈–°“√„™â ∂‘µ‘«‘‡§√“–Àå¢âÕ¡Ÿ≈∑’Ë∂Ÿ°µâÕßµ“¡

≈—°…≥–¢âÕ¡Ÿ≈ §«“¡ —¡æ—π∏å¢Õß¢âÕ¡Ÿ≈ ·≈–®ÿ¥¡ÿàßÀ¡“¬¢Õß°“√«‘‡§√“–Àå

πÕ°®“°¢âÕ§«√√–«—ß„π‡√◊ËÕß√–‡∫’¬∫«‘∏’«‘®—¬·≈â« ¬—ßµâÕß§”π÷ß∂÷ß§«“¡

”§—≠¢Õß¢âÕ¡Ÿ≈«à“¡’º≈°√–∑∫∑’Ë ”§—≠®√‘ßÀ√◊Õ‰¡à °“√ª√–¬ÿ°µå„™â¢âÕ¡Ÿ≈À≈—°∞“π

∑“ß°“√·æ∑¬åµ√ß°—∫ ∂“π°“√≥å∑’Ëµ—Èß§”∂“¡‰«âÀ√◊Õ‰¡à

„π∫∑π’È®–‡πâπ°“√ª√–‡¡‘π§«“¡∂Ÿ°µâÕß‡∑’Ë¬ßµ√ß¢Õß¢âÕ¡Ÿ≈À≈—°∞“π

∑“ß°“√·æ∑¬å„π¥â“π

- °“√«‘π‘®©—¬ (diagnosis)

- °“√æ¬“°√≥å‚√§ (prognosis)

- °“√√—°…“ (treatment)

3.2.1 ‡°≥±åæ‘®“√≥“¢âÕ¡Ÿ≈À≈—°∞“π∑“ß°“√·æ∑¬å‡°’Ë¬«°—∫°“√«‘π‘®©—¬

(diagnosis) «à“∂Ÿ°µâÕß‡∑’Ë¬ßµ√ßÀ√◊Õ‰¡à

1. °“√»÷°…“π—Èπ∑”‡ª√’¬∫‡∑’¬∫°—∫ ç‡°≥±å∑¥ Õ∫¡“µ√∞“πé (gold

standard) Õ¬à“ß√–¡—¥√–«—ß ·≈–ª√“»®“°Õ§µ‘À√◊Õ‰¡à

2. °“√»÷°…“∑”„π°≈ÿà¡§πª√–‡¿∑‡¥’¬«°—∫„π§”∂“¡∑’Ëµ—Èß¢÷ÈπÀ√◊Õ‰¡à

¡’§«“¡√ÿπ·√ß„°≈â‡§’¬ß°—πÀ√◊Õ‰¡à

3. ¡’°“√π”‡ πÕ√“¬≈–‡Õ’¬¥∑“ß ∂‘µ‘∑’Ë· ¥ß§«“¡ ”§—≠¢Õß°“√»÷°…“

À√◊Õ‰¡à

®–‡ÀÁπ‰¥â«à“§«“¡∂Ÿ°µâÕß‡∑’Ë¬ßµ√ß¢Õß°“√«‘π‘®©—¬®–µâÕß‡∑’¬∫°—∫‡°≥±å

∑¥ Õ∫¡“µ√∞“π ‚¥¬∑’Ë°“√‡ª√’¬∫‡∑’¬∫π—Èπ ®–µâÕß∑”‚¥¬ºŸâ∑”°“√∑¥ Õ∫∑’Ë‰¡à∑√“∫

º≈¢Õß°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√¡“µ√∞“π ·≈–‰¡à„™â¢âÕ¡Ÿ≈Õ¬à“ßÕ◊Ëπ Ê ‡æ◊ËÕ°“√

™à«¬„π°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√πÕ°«‘∏’°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√π—Èπ‡Õß

‡æ√“–®–∑”„Àâ‡°‘¥Õ§µ‘‰¥â πÕ°®“°π—Èπ°“√«‘π‘®©—¬¬—ßµâÕß∑”„π°≈ÿà¡§π∑’Ë¡’≈—°…≥–

‡À¡◊Õπ°—∫°≈ÿà¡§πª√–‡¿∑‡¥’¬«°—∫„π§”∂“¡∑’Ëµ—Èß¢÷Èπ ¥—ßµ—«Õ¬à“ß¢Õß°“√µ√«®∑“ß


ÀâÕßªØ‘∫—µ‘°“√°“√«‘π‘®©—¬™π‘¥„À¡à„πºŸâªÉ«¬∑’Ë¡’ ‚Õ°“ ∑’Ë®–‡ªìπ‚√§π—ÈπÕ¬Ÿà·≈â«

Ÿß (pre-test probability) ®–¡’‚Õ°“ „Àâº≈∫«°‰¥â¡“°°«à“°“√µ√«®∑“ßÀâÕß

ªØ‘∫—µ‘°“√„πª√–™“°√∑—Ë«‰ª ∑”„Àâ‡°‘¥§«“¡‡¢â“„®«à“°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√

π—Èπ¡’§«“¡‰« (sensitivity) ·≈–§«“¡®”‡æ“– (specificity) ¢Õß°“√µ√«®∑“ß

ÀâÕßªØ‘∫—µ‘°“√π—Èπ Ÿß°«à“∑’Ëπà“®–‡ªìπ „π∑”πÕß‡¥’¬«°—π°—∫°“√„™â°“√µ√«®

∑“ßÀâÕßªØ‘∫—µ‘°“√∑’Ë‰¡à„™à°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√™π‘¥‡¥’¬« §◊Õ ‡ªìπ°“√

µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√ À≈—ß®“°°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√Õ◊ËπÊ ÷Ëß®–∑”„Àâ

‰¥â·µàºŸâ∑’Ëπà“®–„Àâº≈∫«°¡“∑”°“√∑¥ Õ∫µàÕ ∑”„Àâ‰¥âº≈¥’°«à“°“√µ√«®∑“ßÀâÕß

ªØ‘∫—µ‘°“√„πª√–™“°√∑—Ë«‰ª

§«“¡ ”§—≠¢Õß°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√®–‰¥â®“°°“√æ‘®“√≥“§à“

µà“ßÊ ∑’Ë°“√»÷°…“«‘®—¬§«√„Àâ¡“À√◊Õ§«√„Àâ¢âÕ¡Ÿ≈∑’ËºŸâÕà“π “¡“√∂π”¡“

«‘‡§√“–ÀåµàÕ‰¥â¥—ß„πµ“√“ß∑’Ë 3.3


µ“√“ß∑’Ë 3.3 º≈°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√

Sensitivity (Sn) = a/(a+c) = 90/(90+10)=90%

Specificity (Sp) = d/(b+d) = 80/(20+80) =80%

LR+(Likelihood ratio) = Sn/(1-Sp) = 90/20 = 4.5

LR- = (1-Sn)/Sp = 10/80 = 0.13

Positive predictive value = a/(a+b) =90/110 = 81%

Negative predictive value = d/(c+d) =80/90 = 88%

Prevalence = (a+c)/(a+b+c+d) = 100/200 = 50%

Pre-test odds = prevalence/(1-prevelence) = 50/50 = 1


§à“µà“ßÊ ∑’Ë‰¥â®“°°“√§”π«≥®–‡ªìπ‡§√◊ËÕß¡◊Õ∑’Ë®–™à«¬„π°“√«‘π‘®©—¬‚√§

°≈à“«§◊Õ ‡§√◊ËÕß¡◊Õ∑’Ë¡’§«“¡‰« (sensitivity) Ÿß „™â‡æ◊ËÕµ√«® Õ∫§—¥°√Õß

ºŸâ∑’Ëπà“®–‡ªìπ‚√§ ·≈–‡§√◊ËÕß¡◊Õ∑’Ë¡’§«“¡®”‡æ“– (specificity) Ÿß „™â‡æ◊ËÕ™à«¬

„π°“√µ—¥ ‘π«à“‡ªìπ‚√§À√◊Õ‰¡à ¡’À≈—°°“√„π°“√«‘π‘®©—¬∑’Ë David Sackett

‰¥â‡ πÕ‰«â §◊Õ Snnout ·≈– SPpin ÷Ëß¡’«‘∏’°“√„™â¥—ßπ’È À≈—°°“√ Snnout „™âæ‘®“√≥“

Õ“°“√ Õ“°“√· ¥ß À√◊Õº≈∑“ßÀâÕßªØ‘∫—µ‘°“√∑’ËºŸâªÉ«¬‚√§π—ÈπÊ ‡°◊Õ∫∑ÿ°§π

µâÕß¡’ (high sensitivity : Sn) ·µàºŸâªÉ«¬‰¡à¡’ ‘Ëßπ—Èπ (negative: n) ®÷ß “¡“√∂

µ—¥‚√§π—ÈπÕÕ°®“° ¡¡ÿµ‘∞“π‰¥â (rule out : out) ®÷ß‡√’¬° —ÈπÊ «à“ Snnout

¬°µ—«Õ¬à“ß‡™àπ ºŸâªÉ«¬‚√§‰¢â‡≈◊Õ¥ÕÕ°∑ÿ°√“¬®–¡’‰¢â„π√–¬– 4-7 «—π ·√°¢Õß‚√§

·µà∂â“ºŸâªÉ«¬∑’Ë‰¡à‡§¬¡’‰¢â‡≈¬ °Á§«√µ—¥ ¡¡ÿµ‘∞“π‡√◊ËÕß‰¢â‡≈◊Õ¥ÕÕ°‰¥â

à«πÀ≈—°°“√ Sppin ‡ªìπÀ≈—°°“√∑’Ë®–™à«¬„Àâ¡—Ëπ„®„π°“√µ—¥ ‘π„®

«à“ºŸâªÉ«¬‡ªìπ‚√§π—Èπ¡“°¢÷Èπ °≈à“«§◊Õ „π∫“ß‚√§®–¡’Õ“°“√ Õ“°“√· ¥ß À√◊Õ

º≈∑“ßÀâÕßªØ‘∫—µ‘°“√∫“ß™π‘¥æ∫‰¥â‡©æ“–„πºŸâªÉ«¬ ·µà‰¡àæ∫„πºŸâ∑’Ë‰¡àªÉ«¬ (high

specificity : Sp) ·≈–ºŸâªÉ«¬¡’ ‘Ëßπ—Èπ (positive: p) “¡“√∂ √ÿª‰¥â∑—π∑’«à“

ºŸâªÉ«¬‡ªìπ‚√§π—Èπ (rule in : in) ‡√’¬° —ÈπÊ «à“ Sppin µ—«Õ¬à“ß‡™àπ Koplikûs

spots æ∫‰¥â‡©æ“–„π‚√§À—¥‡∑à“π—Èπ‰¡àæ∫„π‚√§Õ◊ËπÊ ‡¡◊ËÕµ√«®√à“ß°“¬æ∫

Koplikûs spots „πºŸâªÉ«¬®÷ß “¡“√∂ √ÿª‰¥â«à“ºŸâªÉ«¬‡ªìπ‚√§À—¥

„π°“√∑¥ Õ∫∑’Ë‰¥âº≈‡ªìπ§à“µàÕ‡π◊ËÕß ‡™àπ °“√µ√«®√–¥—∫πÈ”µ“≈ ¡’«‘∏’

°“√∑’Ë„™â§«“¡ —¡æ—π∏å√–À«à“ß §«“¡‰« ·≈–§«“¡®”‡æ“– √â“ß‡ªìπ‡ âπ‚§âß∑’Ë‡√’¬°

ROC curve (Receiver Operator Characteristic curve) ¥â«¬«‘∏’π’È ®–∑”„Àâ

‰¥â®ÿ¥∑’Ë„Àâ§à“∑’Ë¡’∑—Èß§«“¡‰« ·≈–§«“¡®”‡æ“– Ÿß ÿ¥ §◊Õ®ÿ¥∑’Ë„°≈â¡ÿ¡´â“¬∫π

¥—ß„π√Ÿª∑’Ë 3.1 ·≈–¥â«¬ ROC curve “¡“√∂‡ª√’¬∫‡∑’¬∫«à“°“√∑¥ Õ∫

„¥¥’°«à“°—π‰¥â¥—ß„π√Ÿª∑’Ë 3.2 Test A ¥’°«à“ Test B


√Ÿª∑’Ë 3.1 ROC curve ¢Õß blood sugar10


√Ÿª∑’Ë 3.2 °“√‡ª√’¬∫‡∑’¬∫ ROC curve

Likelihood ratio ‡ªìπ°“√§”π«≥Õ—µ√“ à«π√–À«à“ß‚Õ°“ ∑’Ëπà“®–‡ªìπ

‚√§

°—∫‚Õ°“ ∑’Ë‰¡à‡ªìπ‚√§

LR+ §◊ÕÕ—µ√“ à«π√–À«à“ß‚Õ°“ ∑’Ëπà“®–‡ªìπ‚√§°—∫ ‚Õ°“ ∑’Ë‰¡à‡ªìπ‚√§

∂â“º≈°“√∑¥ Õ∫‡ªìπ∫«° ·≈–

LR- §◊ÕÕ—µ√“ à«π√–À«à“ß‚Õ°“ ∑’Ëπà“®–‡ªìπ‚√§°—∫ ‚Õ°“ ∑’Ë‰¡à‡ªìπ‚√§

∂â“º≈°“√∑¥ Õ∫‡ªìπ≈∫

§à“∑’Ë¡’≈—°…≥–§≈â“¬°—π§◊Õ

positive predictive value À¡“¬∂÷ß‚Õ°“ ∑’Ëπà“®–‡ªìπ‚√§∂â“º≈∑¥ Õ∫

‡ªìπ∫«° ·≈– negative predictive value À¡“¬∂÷ß‚Õ°“ ∑’Ë‰¡àπà“®–‡ªìπ‚√§


‡¡◊ËÕº≈∑¥ Õ∫‡ªìπ≈∫

§à“µà“ßÊ ∑’Ë°≈à“«¡“·≈â«®– —ß‡°µ‰¥â«à“¢÷Èπ°—∫§«“¡‰« ·≈–§«“¡

®”‡æ“–¢Õß test ·µà¡’ ‘Ëß∑’Ë§«√§”π÷ß‰«â«à“∑—ÈßÀ¡¥®–¢÷ÈπÕ¬Ÿà°—∫ prevalence

¢Õß‚√§¥â«¬ ¥—ß„π√Ÿª∑’Ë 3.3 ¥—ßπ—Èπ°“√∑¥ Õ∫∑’Ë∑”„π ∂“π°“√≥å¡’‚√§¡“°

°«à“ª°µ‘ ®–∑”„Àâº≈¥’°«à“°“√∑¥ Õ∫„π ∂“π°“√≥å∑’Ë¡’‚√§πâÕ¬

√Ÿª∑’Ë 3.3 Positive predictive value µ“¡ sensitivity ·≈– specificity

prevalence ¢Õß‚√§

πÕ°®“°°“√µ√«® Õ∫§«“¡∂Ÿ°µâÕß§«“¡ ”§—≠¢Õß°“√∑¥ Õ∫·≈â«

¬—ßµâÕß§”π÷ß∂÷ß§«“¡ “¡“√∂π”¡“ª√–¬ÿ°µå„™â°—∫ºŸâªÉ«¬µ“¡§”∂“¡∑’Ëµ—Èß‰«â ‚¥¬¡’

¢âÕ§«√§”π÷ß¥—ßπ’È

1. °“√«‘π‘®©—¬ “¡“√∂∑”‰¥â ‡∑’Ë¬ßµ√ß √“§“‰¡à·æß‡°‘π‰ª µ“¡

∂“π°“√≥åÀ√◊Õ‰¡à

2. “¡“√∂ª√–‡¡‘π§«“¡¡’ª√–‚¬™πå¢Õß°“√µ√«®∑“ßÀâÕßªØ‘∫—µ‘°“√


‚¥¬ª√–‡¡‘π®“° pre-test probability ¢ÕßºŸâªÉ«¬µ“¡§”∂“¡∑’Ëµ—Èß

‰«â ‰¥âÀ√◊Õ‰¡à °“√§”π«≥ pre-test probability ‰¥â®“° Ÿµ√

probability = odds/(odds+1) §◊Õ∂â“‰¥â§à“ pre-test probability

∑’ËµË” ‚Õ°“ ∑’Ë®–‡°‘¥ª√–‚¬™πå„π ∂“π°“√≥å¢ÕßºŸâªÉ«¬µ“¡§”∂“¡

∑’Ëµ—Èß‰«â®–¡’πâÕ¬

3. post-test probability ®“°º≈°“√µ√«®∑”„Àâ‡ª≈’Ë¬π°“√√—°…“

À√◊Õ™à«¬‡À≈◊ÕºŸâªÉ«¬À√◊Õ‰¡à ‡æ√“–°“√∑’Ë‰¥â§à“πâÕ¬¬àÕ¡®–∑”„Àâ¡’

ª√–‚¬™πåπâÕ¬ ‰¡à “¡“√∂π”¡“ª√–¬ÿ°µå„™â°—∫ºŸâªÉ«¬µ“¡§”∂“¡∑’Ë

µ—Èß‰«â‰¥â

3.2.2 ‡°≥±åæ‘®“√≥“¢âÕ¡Ÿ≈À≈—°∞“π∑“ß°“√·æ∑¬å‡°’Ë¬«°—∫°“√æ¬“°√≥å‚√§

(prognosis) «à“∂Ÿ°µâÕß‡∑’Ë¬ßµ√ßÀ√◊Õ‰¡à

- ‰¥â»÷°…“ºŸâªÉ«¬™π‘¥ inception cohort §◊Õµ—Èß·µà‡√‘Ë¡‡ªìπ‚√§À√◊Õ‰¡à

- ‰¥â∑”°“√»÷°…“ºŸâªÉ«¬π“πæÕÀ√◊Õ‰¡à

- ºŸâªÉ«¬∑’Ë∑”°“√»÷°…“‡ªìπºŸâªÉ«¬∑’Ë∂Ÿ° àßµàÕ¡“À√◊Õ‰¡à

- °“√ª√–‡¡‘π outcome ‰¥â„™â«‘∏’ª√–‡¡‘πÕ¬à“ß blinded À√◊Õ‰¡à

- ∂â“¡’°“√«‘‡§√“–Àå‡©æ“– subgroups ∑’Ë¡’ªí®®—¬∑’Ë∑”„Àâ‡°‘¥

prognosis ∑’Ë·µ°µà“ß‰¥â¡’°“√ adjustment ”À√—∫ prognosis


factors Õ◊ËπÊ ∑’Ë ”§—≠À√◊Õ‰¡à

√Ÿª∑’Ë 3.4 °“√¥”‡π‘π‚√§¢Õß‚√§™π‘¥µà“ßÊ

°“√»÷°…“‡æ◊ËÕ∫Õ° prognosis ¢Õß‚√§π—Èπ¡’§«“¡ ”§—≠∑’Ë®–µâÕß∑”°“√

»÷°…“ºŸâªÉ«¬µ—Èß·µà·√°¢Õß°“√ªÉ«¬ ‡æ√“–‰¡à‡™àππ—Èπ®–‰¡à “¡“√∂∫Õ°∂÷ß°“√

¥”‡π‘π‚√§‰¥âÕ¬à“ß ¡∫Ÿ√≥å ºŸâªÉ«¬∫“ß§πÕ“®À“¬°àÕπ∑’Ë®–∂Ÿ°»÷°…“ À√◊Õ∂â“‡√‘Ë¡

»÷°…“‡¡◊ËÕºŸâªÉ«¬Õ¬Ÿà„π™à«ß∑â“¬¢Õß‚√§ Õ“®®– √ÿª«à“º≈≈—æ∏å¢Õß‚√§®–‡ªìπ‰ª„π

∑“ß∑’Ë‰¡à¥’ ·≈–¥â«¬‡Àµÿº≈‡¥’¬«°—π°“√∑’Ë‰¡à “¡“√∂µ‘¥µ“¡ºŸâªÉ«¬‰¥âπ“πæÕ ®–

∑”„Àâ ‰¡à “¡“√∂ √ÿªº≈≈—æ∏å¢Õß‚√§‰¥âÕ¬à“ß∂Ÿ°µâÕß „π√Ÿª∑’Ë 3.4 °“√¥”‡π‘π‚√§

¢Õß‚√§™π‘¥µà“ßÊ ®–‡ÀÁπ‰¥â«à“∂÷ß·¡â®–¡’®ÿ¥ ÿ¥∑â“¬∑’Ë‡À¡◊Õπ°—π·µà®–¡’§«“¡

·µ°µà“ß°—π ‡¡◊ËÕ¡’°“√µ‘¥µ“¡Õ¬à“ßµàÕ‡π◊ËÕß §◊Õ‰¡à§«√æ‘®“√≥“‡©æ“–®ÿ¥„¥®ÿ¥Àπ÷Ëß

¢Õß survival rate (‡™àπ 2-year or 5-year survival rate) Õ¬à“ß‡¥’¬« ·µà§«√

æ‘®“√≥“„π√Ÿª¢Õß survival curve ∑’Ë®–„Àâ√“¬≈–‡Õ’¬¥¡“°°«à“ ‡™àπ “¡“√∂

∫Õ°∂÷ß√–¬–‡«≈“∑’Ëµà“ß°—π∑’ËºŸâªÉ«¬‡ ’¬™’«‘µ 50% „π·µà≈–‚√§‰¥âÕ¬à“ß™—¥‡®π


‘Ëß∑’ËµâÕß√–«—ß∑’Ë ”§—≠Õ’°ª√–‡¥ÁπÀπ÷Ëß§◊Õ°“√ blinded „π°“√ª√–‡¡‘π

outcome À√◊Õ‰¡à ‡æ√“–«à“®–∑”„Àâ‡°‘¥ bias ‰¥âßà“¬ bias ∑’ËÕ“®‡°‘¥„π

cohort study ‡™àπ diagnosis-suspicious bias ‡æ√“–‡¡◊ËÕºŸâ∑”°“√»÷°…“ ∑√“∫

«à“ºŸâ„¥‡ªìπºŸâªÉ«¬®–∑”„Àâ¡’°“√®—∫µ“¡ÕßÀ“ prognostic outcome ‡ªìπæ‘‡»… à«π

expectation bias ®–‡°‘¥‡¡◊ËÕºŸâª√–‡¡‘π√Ÿâ≈—°…≥–¢ÕßºŸâªÉ«¬ (clinical

feature) ®–∑”„ÀâºŸâª√–‡¡‘π‡°‘¥ bias „π°“√„Àâ°“√«‘π‘®©—¬‰¥â referral filter

bias ‡ªìπ bias ∑’Ë‡°‘¥®“°»÷°…“„πºŸâªÉ«¬∑’Ë∂Ÿ° àßµ—«¡“√—°…“µàÕ ¡—°¡’°“√¥”‡π‘π

‚√§πà“®–√ÿπ·√ß°«à“ºŸâªÉ«¬∑—Ë«‰ª ¥—ßµ—«Õ¬à“ß°“√»÷°…“Õ—µ√“°“√™—°´È”„πºŸâªÉ«¬

febrile convulsion „π referral center ®–¡“°°«à“Õ—µ√“°“√™—°´È”„πºŸâªÉ«¬

febrile convulsion ∑’Ë»÷°…“„π™ÿ¡™π

°“√«‘‡§√“–Àå‡©æ“– subgroups µâÕßæ‘®“√≥“«à“ prognostic factor

π—ÈπÊ ¡’§«“¡‡ªìπ‰ª‰¥â∑—Èß„π¥â“π‡Àµÿº≈·≈–∑“ß§≈‘π‘°À√◊Õ‰¡à ∑—ÈßµâÕß¡’°“√

adjustment ”À√—∫ prognostic factor Õ◊ËπÊ ∑’Ë ”§—≠¥â«¬ ‡æ√“–‰¡à‡™àππ—Èπ

º≈∑’Ë‡°‘¥Õ“®‰¡à „™à®“°ªí®®—¬∑’Ë»÷°…“‡Õß ·µà‡°‘¥®“°ªí®®—¬∑’Ë ‰¡à ‰¥â adjust

”À√—∫§«“¡ ”§—≠·≈–°“√ª√–¬ÿ°µå„™â¢Õß°“√»÷°…“ª√–‡¿∑°“√

æ¬“°√≥å‚√§ Õ¬Ÿà∑’Ë√“¬≈–‡Õ’¬¥ §«“¡‡∑’Ë¬ßµ√ß¢Õß°“√»÷°…“π—Èπ ·≈–§«“¡

§≈â“¬§≈÷ß¢ÕßºŸâªÉ«¬„π°“√»÷°…“°—∫ºŸâªÉ«¬∑’Ëµ—Èß§”∂“¡

3.2.3 ‡°≥±åæ‘®“√≥“¢âÕ¡Ÿ≈À≈—°∞“π∑“ß°“√·æ∑¬å‡°’Ë¬«°—∫°“√√—°…“

(treatment) «à“∂Ÿ°µâÕß‡∑’Ë¬ßµ√ßÀ√◊Õ‰¡à

1. °“√·∫àß°≈ÿà¡ºŸâªÉ«¬‡ªìπ·∫∫ randomized ·≈– blinded À√◊Õ‰¡à

2. °≈ÿà¡ºŸâªÉ«¬∑—Èß Õß°≈ÿà¡¡’≈—°…≥–∑’Ë‡À¡◊Õπ°—π‡¡◊ËÕ‡√‘Ë¡°“√»÷°…“À√◊Õ‰¡à

3. °≈ÿà¡ºŸâªÉ«¬∑—Èß Õß°≈ÿà¡‰¥â√—∫°“√√—°…“Õ◊ËπÊ (πÕ°‡Àπ◊Õ®“°°“√√—°…“

∑’Ë∑¥≈Õß) ‡À¡◊Õπ°—πÀ√◊Õ‰¡à

4. ºŸâªÉ«¬∑—ÈßÀ¡¥‰¥â√—∫°“√µ‘¥µ“¡º≈·≈–π”¡“ √ÿªº≈À√◊Õ‰¡à

5. ∂â“º≈°“√∑¥≈Õß‰¥âº≈‡ªìπ≈∫ µâÕß§”π÷ß∂÷ß power ¢Õß°“√»÷°…“


«à“¡“°æÕÀ√◊Õ‰¡à

°“√∑’Ë°≈ÿà¡∑¥≈Õß·≈–°≈ÿà¡§«∫§ÿ¡‰¡à∂Ÿ°·∫àß°≈ÿà¡‚¥¬∑’ËºŸâªÉ«¬·µà≈–√“¬

¡’‚Õ°“ ∑’Ë®–Õ¬Ÿà„π°≈ÿà¡„¥°≈ÿà¡Àπ÷ËßÕ¬à“ß‡∑à“‡∑’¬¡°—π (randomized) ·≈–°“√

‰¡àª°ªî¥«à“ºŸâªÉ«¬Õ¬Ÿà„π°≈ÿà¡„¥®–∑”„Àâ‡°‘¥Õ§µ‘„π∑ÿ°¢—ÈπµÕπ¢Õß°“√»÷°…“‰¥â ®÷ß

‡ªìπª√–‡¥Áπ∑’Ë§«√√–«—ß≈—°…≥–¢ÕßºŸâªÉ«¬∑’Ë‰¡à‡À¡◊Õπ°—πµ—Èß·µàµâπ ·≈–°“√ „Àâ°“√

√—°…“∑’Ë ‰¡à‡∑à“°—π¢ÕßºŸâªÉ«¬ Õß°≈ÿà¡ ‡™àπ ∫“ß°≈ÿà¡‰¥â√—∫°“√√—°…“‡æ‘Ë¡‡µ‘¡

(cointervention) ∑”„Àâ ‰¡à “¡“√∂‡™◊ËÕ¡—Ëπ‰¥âÕ¬à“ß‡µÁ¡∑’Ë«à“ º≈∑’Ë‡°‘¥¢÷Èπ‡ªìπº≈¢Õß

°“√√—°…“∑’Ë°”≈—ß∑¥≈ÕßÕ¬Ÿà ¢âÕ§«√√–«—ß„π§«“¡∂Ÿ°µâÕß§◊Õ ®”π«πºŸâªÉ«¬∑’Ëπ”¡“

√ÿªº≈ „π∫“ß°“√»÷°…“ ¡’ºŸâªÉ«¬∑’ËÕÕ°®“°°“√∑¥≈Õß®”π«π¡“° ∑”„Àâ √ÿªº≈

º‘¥æ≈“¥‰¥âÀ√◊Õ¡’°“√‡≈◊Õ° √ÿª·µà„π°≈ÿà¡∑’Ë‰¥âº≈¥’

§«“¡ ”§—≠¢Õßº≈°“√√—°…“„πªí®®ÿ∫—π¡’°“√æ‘®“√≥“„πÀ≈“¬¡ÿ¡¡Õß

°≈à“«§◊Õ

a. Relative risk reduction (RRR)

b. Absolute risk reduction (ARR)

c. Number needed to treated (NNT)

Relative risk reduction §◊Õ Õ—µ√“ à«π¢Õß§«“¡‡ ’Ë¬ß∑’Ë≈¥≈ß§‘¥‡ªìπ

√âÕ¬≈– ‚¥¬§”π«≥®“° (CER-EER)/CER ‚¥¬∑’Ë CER = Control Event

Rate ·≈– EER = Experiment Event Rate

[√–«—ß! Õ¬à“ —∫ π°—∫§”«à“ Relative risk (RR) ∑’ËÀ¡“¬∂÷ß risk

¢Õß°“√‡°‘¥‚√§¢ÕßºŸâ∑’Ë expose °—∫ªí®®—¬‡ ’Ë¬ß ‡¡◊ËÕ‡∑’¬∫°—∫ºŸâ‡ªìπ‚√§∑’Ë‰¡à‰¥â

expose „π°“√»÷°…“ª√–‡¿∑ cohort study ÷Ëß Ÿµ√„π§”π«≥§◊Õ RR = a/a+b)/

c/(c+d) ·≈– Odds ratio (OR) ∑’Ë¡’§«“¡À¡“¬∑”πÕß‡¥’¬«°—π·µà„π°“√»÷°…“

ª√–‡¿∑ Case-Control study ÷Ëß Ÿµ√„π°“√§”π«≥§◊Õ OR = ad/bc]

Absolute risk reduction §◊Õ §à“§«“¡‡ ’Ë¬ß∑’Ë≈¥≈ß‡ªìπ√âÕ¬≈–¢Õß

°≈ÿà¡§«∫§ÿ¡°—∫°≈ÿà¡∑¥≈Õß‚¥¬§”π«≥®“° CER-EER

Number needed to treated §◊Õ ®”π«πºŸâªÉ«¬ ∑’Ë®”‡ªìπµâÕß„Àâ°“√


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µ“√“ß∑’Ë 3.4 º≈°“√√—°…“‚√§

®“°µ“√“ß∑’Ë 3.4 ®–‡ÀÁπ‰¥â«à“º≈°“√√—°…“™π‘¥Àπ÷Ëß ‡¡◊ËÕ‡ª√’¬∫‡∑’¬∫

º≈ °“√√—°…“„π≈—°…≥–µà“ßÊ ∂â“º≈°“√√—°…“®√‘ß¢Õß°“√√—°…“ Õß™π‘¥„π°“√

ªÑÕß°—π°“√‡°‘¥‚√§Õ¬Ÿà∑’Ë√–¥—∫ 8% ·≈– 4% ‡¡◊ËÕ§”π«≥ RRR ®–‡ÀÁπ«à“

Õ—µ√“°“√‡°‘¥‚√§≈¥≈ß 50% ‡À¡◊Õπ°—∫Õ—µ√“°“√≈¥≈ß ‡¡◊ËÕ ¡¡ÿµ‘«à“º≈°“√√—°…“

∑’Ë√–¥—∫ 80% ≈¥≈ß‡À≈◊Õ 40% À√◊Õ∑’Ë√–¥—∫ 0.08% ≈¥≈ß‡À≈◊Õ 0.04%

·µà∂â“¥Ÿº≈°“√√—°…“¥â«¬ ARR §◊Õ§à“°“√≈¥≈ß¢Õß‚√§∑’Ë·∑â®√‘ß«à“¡’¢π“¥¡“°πâÕ¬

‡æ’¬ß‰√ ®–‡ÀÁπ«à“ ∑’Ëº≈°“√√—°…“®√‘ß ‚√§®–≈¥≈ß 4% „π¢≥–∑’Ë∂â“°“√√—°…“

∑’Ë‰¥âº≈¥’¡“°‚√§®–≈¥≈ß∂÷ß 40% ·≈–„π°“√√—°…“∑’Ë‰¥âº≈‰¡à¥’ ‚√§®–≈¥≈ß

0.04% §à“¢Õß ARR Õ“®®–‰¡à‡ÀÁπ¿“æ§«“¡ ”§—≠¢Õß°“√√—°…“™π‘¥µà“ßÊ

„π¥â“π®”π«πºŸâªÉ«¬‰¥â ®÷ß¡’°“√‡ πÕ§à“ NNT ´÷Ëß„πµ—«Õ¬à“ßπ’È§◊Õ ∑’Ëº≈°“√

√—°…“®√‘ß ∂â“®–‡ª≈’Ë¬π°“√√—°…“™π‘¥ A ‡ªìπ™π‘¥ B µâÕß√—°…“ºŸâªÉ«¬ 25 √“¬

®÷ß®–‡ÀÁπ«à“ºŸâªÉ«¬‡°‘¥‚√§πâÕ¬≈ß 1 √“¬ „π¢≥–∑’Ë∂â“º≈°“√√—°…“ ¥’¡“°

√—°…“ºŸâªÉ«¬‡æ’¬ß 3 √“¬ ®–‡ÀÁπ°“√≈¥≈ß¢Õß‚√§ 1 √“¬ ‡¡◊ËÕ‡ª≈’Ë¬π°“√

√—°…“®“°™π‘¥ A ‡ªìπ™π‘¥ B ·≈–∂â“º≈°“√√—°…“‰¡à¥’ µâÕß√—°…“ºŸâªÉ«¬∂÷ß

2,500 √“¬ ®÷ß®–∑”„Àâ≈¥°“√‡ªìπ‚√§‰¥â 1 √“¬ ¥â«¬«‘∏’«‘‡§√“–Àå‡™àππ’È®–

‡ÀÁπ‰¥â∂÷ß§«“¡ ”§—≠¢Õß°“√√—°…“«à“°àÕ„Àâ‡°‘¥°“√‡ª≈’Ë¬π·ª≈ß¡“°πâÕ¬‡æ’¬ß„¥

°“√„™â§à“ RRR ‡æ’¬ßÕ¬à“ß‡¥’¬«‚¥¬‰¡à§”π÷ß∂÷ß§à“Õ◊ËπÊ ®–∑”„ÀâÀ≈ß∑“ß‰¥â

‡¡◊ËÕ∑√“∫§«“¡ ”§—≠¢Õß°“√√—°…“·≈â« À≈—°∑’Ë®–„™âæ‘®“√≥“„π¥â“π°“√

ª√–¬ÿ°µå´÷Ëß§àÕπ¢â“ßµ√ß‰ªµ√ß¡“ §◊Õ

1. ≈—°…≥–¢ÕßºŸâªÉ«¬„π°“√»÷°…“§≈â“¬§≈÷ß°—∫ºŸâªÉ«¬∑’Ëµ—Èß§”∂“¡

‰«âÀ√◊Õ‰¡à

2. ‡ªìπ°“√√—°…“∑’Ë “¡“√∂∑”‰¥â„π ∂“π°“√≥å∑’Ë‡ªìπÕ¬ŸàÀ√◊Õ‰¡à

°“√»÷°…“ª√–‡¿∑º≈°“√√—°…“π—Èπ ∫“ß§√—Èß®–¡’°“√»÷°…“∑’Ë‡πâπ°“√


«‘‡§√“–Àå¥â“π‡»√…∞»“ µ√å (economic analysis) Õ¬Ÿà¥â«¬

‡°≥±åæ‘®“√≥“¢âÕ¡Ÿ≈À≈—°∞“π°“√«‘‡§√“–Àå∑“ß‡»√…∞»“ µ√å

«à“∂Ÿ°µâÕß ‡∑’Ë¬ßµ√ß À√◊Õ‰¡ à

1. ¡’°“√‡ª√’¬∫‡∑’¬∫°—∫«‘∏’∑’Ë‡ªìπ∑“ß‡≈◊Õ° (alternative programs)

À√◊Õ‰¡à

2. ¡’°“√‡ª√’¬∫‡∑’¬∫∑’Ë· ¥ß¡ÿ¡¡Õß (viewpoint) ¢Õß°≈ÿà¡µà“ßÊ ‡™àπ

ª√–™“™π ‚√ßæ¬“∫“≈ ºŸâ∫√‘À“√

3. ¡’°“√°≈à“«∂÷ß√“¬≈–‡Õ’¬¥¢Õß alternative programs Õ¬à“ß

™—¥‡®πÀ√◊Õ‰¡à

4. ¡’°“√· ¥ß∂÷ß cost ·≈– effected ∑’Ë‡°’Ë¬«¢âÕßÕ¬à“ß§√∫∂â«π

À√◊Õ‰¡à

5. ‡§√◊ËÕß¡◊Õ∑’Ë„™â„π°“√ª√–‡¡‘π‡À¡“– ¡ ‡∑’Ë¬ßµ√ßÀ√◊Õ‰¡à

6. ¡’°“√ª√–‡¡‘π effect ‚¥¬ sensitivity analysis À√◊Õ‰¡à

„π°“√æ‘®“√≥“¢âÕ¡Ÿ≈À≈—°∞“π®“°°“√«‘‡§√“–Àå∑“ß‡»√…∞»“ µ√å

®–µâÕß¥Ÿ«à“°“√»÷°…“π—ÈπÊ ‰¥â‡ πÕ°“√§‘¥§”π«≥∑“ß‡»√…∞»“ µ√å¢Õß«‘∏’°“√

√—°…“ ™π‘¥∑’Ëπ”‡ πÕ ‡ª√’¬∫‡∑’¬∫°—∫«‘∏’∑’Ë‡ªìπ∑“ß‡≈◊Õ°‰¥âÕ¬à“ß‡À¡“– ¡À√◊Õ‰¡à

‚¥¬°≈à“«∂÷ß√“¬≈–‡Õ’¬¥¢Õß·µà≈–∑“ß‡≈◊Õ° ¡’°“√· ¥ß¡ÿ¡¡Õß¢Õß°≈ÿà¡µà“ßÊ

Õ¬à“ß§√Õ∫§≈ÿ¡ „π°“√«‘‡§√“–Àå cost ·≈– effected ‚¥¬°“√ª√–‡¡‘π®–µâÕß

· ¥ß cost ·≈– effected ∑ÿ°Ê Õ¬à“ß∑’Ë‡°‘¥¢÷Èπ·≈–„™â‡§√◊ËÕß¡◊Õ∑’Ë‡À¡“– ¡

‡∑’Ë¬ßµ√ß economic analysis ‰¡à„™à¡’·µà°“√∑”°“√ª√–‡¡‘π cost-benefit

analysis ‡æ’¬ßÕ¬à“ß‡¥’¬« ¬—ß¡’°“√ª√–‡¡‘π™π‘¥Õ◊Ëπ¥â«¬ ‡™àπ cost-effectiveness,

cost-utility ¥—ßπ—Èπ°“√‡≈◊Õ°„™â‡§√◊ËÕß¡◊Õ·≈–«‘∏’°“√ª√–‡¡‘π®÷ßµâÕß∑”¥â«¬

§«“¡‡À¡“– ¡ √«¡∑—Èß§«√∑”°“√ª√–‡¡‘π‡æ◊ËÕ· ¥ß cost ·≈– effected „π°“√

§–‡π¿“æ∑’Ë¥’·≈–‰¡à¥’ ∑’Ë‡√’¬°«à“°“√∑” sensitivity analysis

”À√—∫§«“¡ ”§—≠·≈–°“√ª√–¬ÿ°µå„™â¢âÕ¡Ÿ≈À≈—°∞“π°“√«‘‡§√“–Àå

∑“ß‡»√…∞»“ µ√å ¢÷ÈπÕ¬Ÿà°—∫§«“¡‡¢â“°—π‰¥â¢Õß ‘Ëß∑’Ë article ‰¥âπ”‡ πÕ°—∫


∂“π°“√≥åµ“¡§”∂“¡∑’Ëµ—Èß‰«â«à“ §≈â“¬§≈÷ß°—πÀ√◊Õ‰¡à ¡’ ‘Ëß∑’Ë§«√§”π÷ß«à“°“√

ª√–‡¡‘π§à“¢Õß ‘Ëßµà“ßÊ ‡ªìπ‡ß‘ππ—Èπ‡ªìπ‡√◊ËÕß∑’ËÕ“®‰¡à∂Ÿ°µâÕß ¥—ßπ—Èπ«‘∏’°“√

ª√–‡¡‘π§à“®÷ßµâÕß‡≈◊Õ°«‘∏’∑’Ë‡À¡“– ¡

‚¥¬ √ÿªÀ≈—°°“√∑—Ë«‰ª„π°“√«‘‡§√“–Àå¢âÕ¡Ÿ≈À≈—°∞“π∑“ß°“√·æ∑¬å§◊Õ

§”∂“¡∑’ËµâÕß°“√§”µÕ∫π—Èπ‡ªìπ§”∂“¡∑’Ë‡À¡“– ¡À√◊Õ‰¡à °“√‡≈◊Õ°√Ÿª·∫∫°“√

«‘®—¬‡À¡“–°—∫§”∂“¡°“√«‘®—¬À√◊Õ‰¡à „§√§◊ÕºŸâªÉ«¬ Õ–‰√§◊Õ outcome „™âÕ–‰√

‡ªìπ‡§√◊ËÕß¡◊Õ„π°“√«—¥ ¡’°“√ªÑÕß°—π bias ∑’Ë®–‡°‘¥¢÷ÈπÀ√◊Õ‰¡à º≈∑’Ë‡°‘¥®“°°“√

»÷°…“¡’§«“¡ ”§—≠À√◊Õ‰¡à º≈‡°‘¥®“°§«“¡∫—ß‡Õ‘≠À√◊Õ‰¡à

¡’¢âÕ§«√√–«—ß«à“°“√∑” critical appraisal ‡ªìπ°“√æ‘®“√≥“¢âÕ¡Ÿ≈

À≈—°∞“π∑“ß°“√·æ∑¬å™π‘¥µà“ßÊ ‰¡à„™à‡æ◊ËÕ°“√®—∫º‘¥ (fault finding) ·µà‡ªìπ°“√

æ‘®“√≥“Õ¬à“ßæ‘π‘®æ‘‡§√“–Àå¡“°°«à“ (careful quality assessment) ‡æ◊ËÕ®–

‰¥âπ”º≈®“°°“√»÷°…“¡“„™â —ß‡§√“–Àå‡ªìπ¢âÕ¡Ÿ≈„À¡à ‡æ◊ËÕª√–‚¬™πå¢ÕßºŸâªÉ«¬

µ“¡∑’Ëµ—Èß§”∂“¡‰«â

√ÿªª√–‡¥Áπ ”§—≠„π°“√ª√–‡¡‘π§ÿ≥¿“æ °“√ª√–‡¡‘π§ÿ≥¿“æ ‡ªìπ°“√ª√–‡¡‘π∂÷ß§«“¡∂Ÿ°µâÕß‡∑’Ë¬ßµ√ß

¿“¬„π ·≈–¿“¬πÕ°¢Õß·µà≈–¢âÕ¡Ÿ≈À≈—°∞“π ÷Ëß¡’À—«¢âÕª√–‡¥Áπ

·µ°µà“ß°—π‰ª·≈â«·µà≈—°…≥–¢Õß¢âÕ¡Ÿ≈À≈—°∞“ππ—ÈπÊ

°“√ª√–‡¡‘π§ÿ≥¿“æ‡ªìπ°“√µ√«® Õ∫¢âÕ¡Ÿ≈À≈—°∞“π√“¬™‘Èπ

‡æ◊ËÕπ”¢âÕ¡Ÿ≈À≈—°∞“π∑’Ëºà“π‡°≥±å∑’Ë°”Àπ¥‰«â‰ª„™â„π°“√ —ß‡§√“–Àå

º≈µàÕ‰ª

°“√∑” checklist À—«¢âÕª√–‡¥Áπµà“ßÊ ‡æ◊ËÕ„™â„π°√–∫«π°“√∑”ß“π


®–™à«¬∑”„Àâß“πßà“¬¢÷Èπ·≈–¡’§ÿ≥¿“æ (¥Ÿ‡Õ° “√ „π¿“§ºπ«° 3)

‡Õ° “√Õâ“ßÕ‘ß

1. ‚¬∏’ ∑Õß‡ªìπ„À≠à. Evidence-Based Medicine (EBM) ∫∑∑’Ë 1 : °“√„™â IT

„π°“√»÷°…“§âπ§«â“∑“ß°“√·æ∑¬å. ‡«™ “√‚√ßæ¬“∫“≈¡À“√“™π§√√“™ ’¡“ 2541 ; 22:

77-83.

2. ‚¬∏’ ∑Õß‡ªìπ„À≠à. Evidence-Based Medicine (EBM) ∫∑∑’Ë 2 : °“√„™â EBM

„π°“√¥Ÿ·≈√—°…“ºŸâªÉ«¬. ‡«™ “√‚√ßæ¬“∫“≈¡À“√“™ π§√√“™ ’¡“ 2541 ; 22: 137-140.

3. ‚¬∏’ ∑Õß‡ªìπ„À≠à. Evidence-Based Medicine (EBM) ∫∑∑’Ë 3 : ·π«∑“ß°“√

√—°…“ºŸâªÉ«¬‰¢â‡≈◊Õ¥ÕÕ° (Clinical Practice Guidelines for Dengue Hemorrhagic Fever) :

µ—«Õ¬à“ß°“√„™â EBM „π°“√ √â“ß·π«∑“ß√—°…“‚√§. ‡«™ “√‚√ßæ¬“∫“≈¡À“√“™π§√√“™ ’¡“

2541 ; 22: 191-199.

4. ‚¬∏’ ∑Õß‡ªìπ„À≠à. Evidence-Based Medicine (EBM) ∫∑∑’Ë 4 : °“√ ª√–‡¡‘π§«“¡

∂Ÿ°µâÕß‡À¡“– ¡¢ÕßÀ≈—°∞“π∑“ß°“√·æ∑¬å (Critical appraisal of evidence). ‡«™ “√

‚√ßæ¬“∫“≈¡À“√“™π§√√“™ ’¡“ 2543 ; 24: 39-49.

5. ‚¬∏’ ∑Õß‡ªìπ„À≠à. °“√§âπ Medline ¥â«¬‚ª√·°√¡ WinSPIRS. ‡«™ “√‚√ßæ¬“∫“≈

¡À“√“™π§√√“™ ’¡“ 2542 ; 23: 57-66.

6. Tongpenyai Y. The effectiveness of clinical practice guidelines and a health

care improvement program for Dengue Hemor rhagic Fever. McMaster

University thesis for the Degree Master of science September 1992.

7. Sackett DL, Richardson WS, Rosenberg W, Haynes RB. Evidence-Based Medicine:

How to practice and teach EBM. New York: Churchill Livingstone; 1997.

8. Sackett DL, Haynes RB, Guyatt GH, Tugwell P. Clinical epidemiology: abasic science

for clinical medicine, 2nd ed. Boston : Little Brown: 1991.

9. Sackett DL, Rosenberg W, Haynes RB, Gray JM, Richardson WS. Evidence-Based

Medicine Glossary. [Web Page]. Available at http://www.cebm.net/glossary.asp.

(Accessed 15 August 2004).

10. Fletcher RH, Fletcher SW, Wagner EH. Clinical Epidemiology: The Essentials,


3rd ed. Baltimore: Williams & Wilkins: 1996.

11. NHS centre for Reviews and Dissemination [Web Page]. Available at http://www.

york.ac.uk/inst/crd/report4.htm. (Accessed 15 August 2004).

12. Levels of Evidence and Grades of Recommendations [Web Page]. Available at

http://www.cebm.net/levels of evidence.asp (Accessed 15 August 2004).



°“√ —ß‡§√“–Àåº≈ (Data synthesis)

π“¬·æ∑¬å ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬å

°“√°”Àπ¥ªí≠À“

°“√√«∫√«¡¢âÕ¡Ÿ≈

°“√ª√–‡¡‘π§ÿ≥¿“æ

°“√ —ß‡§√“–Àåº≈

°“√·ª≈º≈


®ÿ¥ª√– ß§å¢Õß¢—ÈπµÕπ°“√ —ß‡§√“–Àåº≈π’È ‡æ◊ËÕπ”¢âÕ¡Ÿ≈À≈—°∞“π®“°

∑’Ë‰¥âºà“π°“√§—¥°√Õß·≈–ª√–‡¡‘π§ÿ≥¿“æ¡“¥’·≈â«π—Èπ —ß‡§√“–Àå√«¡°—π‡ªìπ

¢âÕ √ÿª„Àâ¡’º≈≈—æ∏å„À¡à

4.1 Data extraction‡æ◊ËÕªÑÕß°—πÕ§µ‘ ®÷ß§«√∑” protocol „π°“√π”¢âÕ¡Ÿ≈®“°·µà≈–

paper Õ–‰√∫â“ß ∑’Ë‡ªìπ·∫∫ data extraction form °√Õ°¢âÕ¡Ÿ≈‰«â‡≈¬ ¢âÕ¡Ÿ≈∑’Ë®–

π”¡“ §«√‡ªìπ‡©æ“–∑’Ëµ√ß°—∫§”∂“¡ À—«¢âÕ∑’Ë ”§—≠„π·∫∫ data extraction

form ¥Ÿµ—«Õ¬à“ß„π√Ÿª∑’Ë 4.1 ·≈– 4.2

°“√ extract ¢âÕ¡Ÿ≈ §«√∑”‚¥¬ºŸâ∑∫∑«πÕ¬à“ßπâÕ¬ 2 §π À“°§«“¡

‡ÀÁπ‰¡àµ√ß°—π®–Õ¿‘ª√“¬°—π·≈â«À“©—π∑“¡µ‘ ¢âÕ¡Ÿ≈À≈—°∞“π∑’Ë¢“¥À“¬‰ª

‰¡à “¡“√∂À“ full paper ‰¥â Õ“®µâÕß¡’°“√µ‘¥µàÕ°—∫ºŸâ»÷°…“«‘®—¬∂â“‡ªìπ‰ª‰¥â

·≈–∂â“¢âÕ¡Ÿ≈¢“¥À“¬‰ª®√‘ßÊ µâÕßπ”º≈°√–∑∫‰ªæ‘®“√≥“„π°“√∑” sensitivity

analysis


√Ÿª∑’Ë 4.1 À—«¢âÕ∑’Ë ”§—≠„π·∫∫ data extraction form ”À√—∫°“√»÷°…“™π‘¥

effectiveness studies1


√Ÿª∑’Ë 4.2 µ—«Õ¬à“ß·∫∫§—¥°√Õß ”À√—∫ test accuracy study2


4.2 °“√ —ß‡§√“–Àå¢âÕ¡Ÿ≈°“√ —ß‡§√“–Àå¢âÕ¡Ÿ≈3,4,5,6 ∑”‚¥¬

- Non quantitative À√◊Õ descriptive synthesis

- Quantitative À√◊Õ meta-analysis

4.2.1 Non quantitative À√◊Õ descriptive synthesis

§«√∫√√¬“¬≈—°…≥–·≈–º≈≈—æ∏å‚¥¬ √ÿª ‡æ◊ËÕ∑’Ë®–„Àâ‡¢â“„®·≈–

¡’§«“¡À¡“¬ Õ“®∑”‡ªìπµ“√“ß À—«¢âÕ∑’Ë§«√®–¡’ ‰¥â·°à

- ª√–™“°√

- Interventions

- Setting

- °“√«—¥º≈ ·≈–≈—°…≥–‚¥¬∏√√¡™“µ‘¢Õß°“√«—¥º≈

- ¿“æ·«¥≈âÕ¡∑’Ë¡’º≈µàÕº≈≈—æ∏å

- Validity ¢Õß¢âÕ¡Ÿ≈

- ¢π“¥µ—«Õ¬à“ß

°“√ —ß‡§√“–Àåº≈‡ªìπ°“√§”π«≥º≈‚¥¬‡©≈’Ë¬¢Õß¢âÕ¡Ÿ≈∑—ÈßÀ¡¥

Õ“®¡’°“√„ÀâπÈ”Àπ—°°—∫¢âÕ¡Ÿ≈À≈—°∞“π∫“ß™‘Èπ∑’Ë¡’§«“¡ ”§—≠ ‡™àπ ¡’¢π“¥

µ—«Õ¬à“ß¡“° ¡’ precision Ÿß ‡ªìπµâπ

à«π¢Õß descriptive π’È®–™à«¬„π°“√«“ß·ºπ°“√∑¥ Õ∫ heteroge-

neity

4.2.2 Quantitative synthesis À√◊Õ meta-analysis

‡ªìπ°“√ —ß‡§√“–Àå¢âÕ¡Ÿ≈‚¥¬„™â«‘∏’∑“ß ∂‘µ‘ ®–∑”‰¥â‡¡◊ËÕ‡ÀÁπ·π«‚πâ¡®“°

descriptive ·≈â« ·≈–∂â“µ√«® Õ∫æ∫§«“¡·ª√ª√«π¢Õßº≈ (heterogeneity)

§«√µâÕßæ‘®“√≥“ characteristics ¢Õß°“√»÷°…“


Heterogeneity ¡’ 3 ·∫∫

- Clinical heterogeneity (Characteristics)

- Methodology heterogeneity (Quality)

- Heterogeneity of result (Effect)

‚§√ß √â“ß¢Õß°“√∫√√¬“¬‡æ◊ËÕ°“√∑” quantitative synthesis

- §«√®–∫Õ°‰¥â«à“ °“√ —ß‡§√“–Àå·∫∫ quantitative “¡“√∂‡ªìπ‰ª‰¥â

(§◊Õ¡’¢âÕ¡Ÿ≈) ·≈–¢âÕ¡Ÿ≈¡’§«“¡‡À¡“– ¡ (‰¡à¡’ heterogeneity ¡“°‡°‘π‰ª)

- ‡¡◊ËÕ¡’¢âÕ¡Ÿ≈·≈–¢âÕ¡Ÿ≈¡’§«“¡‡À¡“– ¡·≈â« ¬—ßµâÕß‡≈◊Õ°Õ’° 3 ∑“ß‡≈◊Õ°

§◊Õ

1. ®–‡ª√’¬∫‡∑’¬∫Õ–‰√

2. ‡§√◊ËÕß«—¥ outcome Õ—π‰Àπ∑’Ë®–π”¡“ —ß‡§√“–Àå

3. ®–‡Õ“‡§√◊ËÕß«—¥º≈≈—æ∏å (effect measure) ‰Àπ ‡ªìπµ—«∫Õ°

effectiveness ´÷Ëß°“√‡≈◊Õ° effect measure (¥Ÿ√Ÿª∑’Ë 4.3) ¡’

ª√–‡¥Áπ ”§—≠ 4 ‡√◊ËÕß

outcome ∑’Ë®–«—¥‡ªìπ¢âÕ¡Ÿ≈™π‘¥„¥

ºŸâ„™âº≈°“√ review “¡“√∂·ª≈º≈°“√«—¥π—ÈπÊ ‰¥âÀ√◊Õ‰¡à

°“√«—¥π—Èπ¡’ consistency ·≈– transferable ‰À¡

°“√«—¥π—Èπ¡’§ÿ≥ ¡∫—µ‘„πµ—«‡Õß∑’Ë®–∫Õ°§”µÕ∫∑’Ë∂Ÿ°µâÕß‰¥â

À√◊Õ‰¡à

°“√π”‡ πÕº≈¢Õß quantitative synthesis ¡—°∑”‡ªìπ√Ÿª°√“ø ¥—ßµ—«Õ¬à“ß

„π√Ÿª∑’Ë 4.4


√Ÿª∑’Ë 4.3 Measures of effects of healthcare interventions6


√Ÿª∑’Ë 4.4 µ—«Õ¬à“ß°“√π”‡ πÕº≈ß“π6


√ÿªª√–‡¥Áπ ”§—≠„π Data extraction ·≈– Data synthesis Data extraction ¡’‚Õ°“ ®–‡°‘¥ human error ¡“° ´÷Ëß≈¥ bias

‚¥¬ÕÕ°·∫∫ data extraction form ·≈– „™âºŸâ∑∫∑«π¡“°°«à“ 1 §π

¢âÕ¡Ÿ≈∑’Ë¢“¥À“¬‰ª µâÕßæ¬“¬“¡À“‡æ‘Ë¡‡µ‘¡‡∑à“∑’Ë∑”‰¥â ‡™àπ

°“√µ‘¥µàÕºŸâ«‘®—¬ À√◊Õ °“√§”π«≥¬âÕπ°≈—∫®“°¢âÕ¡Ÿ≈∑’Ë¡’Õ¬Ÿà

º≈¢Õß¢âÕ¡Ÿ≈∑’Ë¢“¥À“¬‰ª µâÕß¡’°“√∑¥ Õ∫‚¥¬ sensitivity analysis

°“√ —ß‡§√“–Àåº≈ Õ“®∑”‡ªìπµ“√“ß · ¥ß≈—°…≥– ·≈–º≈≈—æ∏å

(non quantitative synthesis) ·≈–„™â«‘∏’∑“ß ∂‘µ‘ (quantitative

synthesis) ∂â“ “¡“√∂°√–∑”‰¥â

º≈®“° non quantitative synthesis ®–™à«¬‡ √‘¡°“√«“ß·ºπ¢Õß

quantitative synthesis ‰¥â ·≈–„π∫“ß°√≥’®–™à«¬„π°“√·ª≈º≈¥â«¬

quantitative synthesis ‡ªìπ°“√√«¡º≈„π∑“ß ∂‘µ‘ ∑¥ Õ∫

heterogeneity ·≈–ª√–‡¡‘π publication bias ¥â«¬

‡Õ° “√Õâ“ßÕ‘ß1. Khan KS, Kleijnen J. Data extraction and monitoring progress. Undertaking

systematic review of research on effectiveness: CRD guidelines for those carrying

out or commissioning reviews. 2nd edition. York: NHS Centre for Reviews and

Dissemination, 2001.

2. APPENDIX 3: Example data extraction sheets. In Undertaking systematic review

of research on effectiveness: CRD guide lines for those carrying out or

commissioning reviews. 2nd edition. York: NHS Centre for Reviews and

Dissemination, 2001. Report No.: CRD report 4. Available at URL: http://www.

york.ac.uk/inst/crd/crd4-app3.pdf

3. Clarke M, Oxman AD, editors. Cochrane Reviewers Handbook 4.1.4 [updated

October 2001]. In: The Cochrane Library, Issue 4, 2001. Oxford: Update Software.

Updated quarterly.




Care, 1993.




6. Deeks J , Khan KS , Song F , Popay J , Nixon J , Kleijnen J. Data synthesis.

Undertaking systematic review of research on effectiveness: CRD guidelines for

those carrying out or commissioning reviews. 2nd edition. York: NHS Centre for

Reviews and Dissemination, 2001.



°“√·ª≈º≈ (Interpretation of results)

π“¬·æ∑¬å ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬å

°“√°”Àπ¥ªí≠À“

°“√√«∫√«¡¢âÕ¡Ÿ≈

°“√ª√–‡¡‘π§ÿ≥¿“æ

°“√ —ß‡§√“–Àåº≈

°“√·ª≈º≈


®ÿ¥ª√– ß§å¢Õß¢—ÈπµÕπ°“√·ª≈º≈π’È §◊Õ°“√æ‘®“√≥“·≈–

Õ¿‘ª√“¬º≈∑’Ë —ß‡§√“–Àå¢÷Èπ‰¥â ‰ª„π∫√‘∫∑∑’Ë®–π”‰ª„™â ‡¡◊ËÕ‰¥âº≈°“√∑∫∑«π

§√∫¢—ÈπµÕπ·≈â« §«√µ√«® Õ∫µπ‡Õß„πª√–‡¥Áπµà“ßÊ ·≈– √ÿª‡ªìπ§”·π–π”

(recommendation)

5.1 µÕ∫§”∂“¡∑’Ëµ—Èààß¢÷Èπ‰«âÀ√◊Õ‰¡à‡ªìπ°“√æ‘®“√≥“¬âÕπ°≈—∫‰ª∂÷ß§”∂“¡∑’Ëµ—Èß¢÷Èπ‰«â „π¢—ÈπµÕπ∑’Ë 1

‚¥¬æ‘®“√≥“‡ªìπ¿“æ√«¡«à“ º≈∑’Ë‰¥â®“°°“√ —ß‡§√“–Àåπ—Èπæ∫Õ–‰√

5.2 §«“¡∂Ÿ°µâÕß‡∑’Ë¬ßµ√ß (Internal validity) ¢Õß°“√∑∫∑«πæ‘®“√≥“¿“æ√«¡§«“¡∂Ÿ°µâÕß‡∑’Ë¬ßµ√ß¢Õß primary research ·≈–

º≈°“√∑∫∑«π‚Õ°“ ∑’Ë®–‡°‘¥ bias µà“ßÊ (√«¡∑—Èß publication bias) ´÷Ëß‰¥â

√–¡—¥√–«—ßµ—Èß·µà°“√«“ß·ºπÕÕ°·∫∫°“√∑∫∑«ππ—Èπ º≈‡ªìπÕ¬à“ß‰√ ¡’®ÿ¥ÕàÕπ

®ÿ¥·¢ÁßÕ–‰√∫â“ß ‡ª√’¬∫‡∑’¬∫°—∫º≈∑∫∑«πÕ◊ËπÊ ∑’Ë„°≈â‡§’¬ß°—π ¡’§«“¡§≈â“¬§≈÷ß

À√◊Õ·µ°µà“ß°—πÕ¬à“ß‰√

5.3 Applicability À√◊Õ External validity ¢Õß°“√∑∫∑«π1

‡ªìπ°“√π”º≈°“√∑∫∑«π‰ª„™â ¢÷ÈπÕ¬Ÿà°—∫ effect ∑’Ë°”Àπ¥‰«â„π°“√

∑∫∑«π ®– –∑âÕπ ‘Ëß∑’Ë‡ªìπ®√‘ßÊ „π‡«™ªØ‘∫—µ‘À√◊Õ‰¡à «‘∏’Àπ÷Ëß„π°“√æ‘®“√≥“

applicability §◊Õ°“√‡ª√’¬∫‡∑’¬∫√–À«à“ß benefits °—∫ harms ´÷Ëß∂â“

outcomes ∑’Ë ”§—≠Ê (√«¡∑—Èß adverse outcomes) ‰¥â∂Ÿ°æ‘®“√≥“Õ¬Ÿà·≈â«„π

¢—ÈπµÕπ°“√ —ß‡§√“–Àåº≈ °Á®– “¡“√∂‡ª√’¬∫‡∑’¬∫ benefits °—∫ harms ‰¥â

5.4 Recommendation‡ªìπ°“√ª√–‡¡‘πº≈√«¡¢Õß¢âÕ¡Ÿ≈À≈—°∞“π∑’Ëπ”¡“ —ß‡§√“–Àåπ—Èπ

∫Õ°µàÕºŸâ „™âº≈°“√∑∫∑«π2, 3 ‚¥¬∑—Ë«‰ª·∫àß‡ªìπ 4 √–¥—∫ (A, B, C, D) ‚¥¬Õ‘ßµ“¡


√–¥—∫¢Õß¢âÕ¡Ÿ≈À≈—°∞“π ·µà¡’§«“¡·µ°µà“ß„π√“¬≈–‡Õ’¬¥‰ª∫â“ß ‡™àπ NHS

centre for Reviews and Dissemination, University of York4 µ“¡µ“√“ß∑’Ë

5.1 ·≈– Oxford Centre for Evidence-based Medicine5 „πµ“√“ß∑’Ë 5.2

µ“√“ß∑’Ë 5.1 Grading of practice recommendations4

(CRD Report Number 4,NHS Centre for Reviews and Dissemination, University of York, 2001.)


Level Evidences

A consistent level 1 studies

B consistent level 2 or 3 studies or extrapolations

from level 1 studies

C level 4 studies or extrapolations from level 2 or 3

studies

D level 5 evidence or troublingly inconsistent or

inconclusive studies of any level

5.5 §”∂“¡∑’Ë¬—ß‰¡à‰¥â§”µÕ∫º≈ √ÿª®“°°“√ —ß‡§√“–Àå¢âÕ¡Ÿ≈ Õ“®æ∫«à“ ç‰¡à¡’À≈—°∞“π«à“ ‰¥âº≈

À√◊Õ‰¡à‰¥âº≈é (´÷Ëß¡’§«“¡·µ°µà“ß®“° ç¡’À≈—°∞“π«à“ ‰¡à‰¥âº≈é) ºŸâ∑∫∑«π®–

‡ÀÁπ‚Õ°“ «à“µâÕß°“√ °“√«‘®—¬‡æ‘Ë¡‡µ‘¡„π area „¥6 §«√√–∫ÿ„Àâ™—¥‡®π ‡æ◊ËÕºŸâ π„®

∑” primary research µàÕ‰ª

‡Õ° “√Õâ“ßÕ‘ß1. Clarke M, Oxman AD, editors. Cochrane Reviewers Handbook 4.1.4 [updated

October 2001]. In: The Cochrane Library, Issue 4, 2001. Oxford: Update Software.

Updated quarterly.

2. National Health and Medical Research Council. How to use the evidence:

assessment and application of scientific evidence. Canberra: National Health and

Medical Research Council, 2000.

µ“√“ß∑’Ë 5.2 Grades of Recommendation ¢Õß Oxford Centre for

Evidence-based Medicine5




Care, 1993.




5. Levels of Evidence and Grades of Recommendations [Web Page]. Available at

http://www.cebm.net/levels-of-evidence.asp. (Accessed 15 August 2004).





Cochrane Collaborationà

·æ∑¬åÀ≠‘ß√—µπ“ æ—π∏åæ“π‘™

π“¬·æ∑¬å ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬å

Cochrane Collaboration ‡ªìπ§«“¡√à«¡¡◊Õ√–¥—∫π“π“™“µ‘∑’Ë¡’

®ÿ¥ª√– ß§å„π°“√√à«¡°—π®—¥°“√√«∫√«¡Õß§å§«“¡√Ÿâ∑’Ë‰¥â®“°ß“π«‘®—¬Õ¬à“ß‡ªìπ

√–∫∫ „π‡√◊ËÕß∑’Ë‡°’Ë¬«°—∫°“√¥Ÿ·≈√—°…“ºŸâªÉ«¬ ‡æ◊ËÕ™à«¬„ÀâºŸâ‡°’Ë¬«¢âÕß “¡“√∂π”

¢âÕ¡Ÿ≈‰ª„™â ‰¥âßà“¬ ‡√‘Ë¡µâπµ—Èß·µàªï §.». 1979 Dr. Archie Cochrane ·æ∑¬å

π—°√–∫“¥«‘∑¬“ ™“«Õ—ß°ƒ… ‰¥â‡√’¬°√âÕß„Àâ«ß°“√·æ∑¬å π„®µàÕ°“√√«∫√«¡·≈–

—ß‡§√“–ÀåÕß§å§«“¡√Ÿâ∑’Ë‡°’Ë¬«°—∫°“√¥Ÿ·≈ºŸâªÉ«¬∑’Ë¡’°“√»÷°…“«‘®—¬‰«â„πÕ¥’µ

‚¥¬‡¢’¬π‰«â„πÀπ—ß ◊Õ ‡≈à¡Àπ÷Ëß¢Õß‡¢“«à“ 1

çIt is surely a great criticism of our profession that we have not

organised a critical summary, by specialty or subspecialty, adapted

periodically, of all relevant randomised controlled trials.é

ªï §.». 1987 Archie Cochrane ‰¥â°≈à“«¬°¬àÕßº≈ß“π°“√∑∫∑«π

Õß§å§«“¡√ŸâÕ¬à“ß‡ªìπ√–∫∫ (Systematic reviews) ¥â“π°“√¥Ÿ·≈√–À«à“ßµ—Èß§√√¿å

·≈–°“√§≈Õ¥∑’Ë°≈ÿà¡ Ÿµ‘·æ∑¬å„πª√–‡∑»Õ—ß°ƒ…‰¥â∑”‰«â ‚¥¬°“√ª√–¡«≈·≈–

—ß‡§√“–Àåº≈®“°ß“π«‘®—¬‡™‘ß∑¥≈Õß∑“ß§≈‘π‘° (randomized controlled

trials) ∑—ÈßÀ¡¥∑’Ë¡’Õ¬Ÿà«à“‡ªìπ ‘Ëß¥’ ·≈–®”‡ªìπÕ¬à“ß¬‘Ëß∑’Ë°“√·æ∑¬å “¢“Õ◊ËπÊ §«√®–

‰¥â¥”‡π‘π°“√¥â«¬«‘∏’°“√‡™àπ‡¥’¬«°—π „π°“√√«∫√«¡ª√–¡«≈º≈®“°ß“π«‘®—¬∑’Ë¡’

ºŸâ∑”‰«â¡“°¡“¬„π‡√◊ËÕß∑’Ë‡°’Ë¬«°—∫ª√– ‘∑∏‘º≈¢Õß¬“ À√◊Õ«‘∏’°“√¥Ÿ·≈√—°…“ºŸâªÉ«¬

‡æ◊ËÕºŸâ∑’Ë‡°’Ë¬«¢âÕß®– “¡“√∂π”¢âÕ¡Ÿ≈‰ª„™â ‰¥âßà“¬„π°“√µ—¥ ‘π„®„π‡«™ªØ‘∫—µ‘

À≈—ß®“°∑’Ë Archie Cochrane ‡ ’¬™’«‘µ‰ª„πªï §.».1988 ‰¥â¡’°“√ “πµàÕ

§«“¡§‘¥·≈–À≈—°°“√¥—ß°≈à“« ¡’æ—≤π“°“√¿“¬„πª√–‡∑»Õ—ß°ƒ… ‡ªî¥ çThe


Cochrane Centreé ∑’Ë Oxford „π‡¥◊Õπµÿ≈“§¡ §.».1992 ·≈–‡√‘Ë¡°“√ª√–™ÿ¡

§√—Èß·√°¢Õß Cochrane Colloquia „πªï §.». 1993 ‚¥¬ºŸâ‡¢â“√à«¡ 77 §π®“°

11 ª√–‡∑» °àÕµ—Èß çThe Cochrane Collaborationé ‡ªìπÕß§å°√π“π“™“µ‘∑’Ë‰¡à

À«—ßº≈°”‰√ ‰¥â√—∫§«“¡√à«¡¡◊Õ®“°π—°«‘®—¬ π—°«‘™“°“√ ºŸâ π„® ·≈–ºŸâ‡°’Ë¬«¢âÕß

Õ¬à“ß°«â“ß¢«“ß2,3 ‡µ‘∫‚µÕ¬à“ß√«¥‡√Á« ¢¬“¬‡§√◊Õ¢à“¬ÕÕ°‰ª„πª√–‡∑»µà“ßÊ

‡°◊Õ∫∑—Ë«‚≈° ‡ªÑ“À¡“¬„π°“√∑”ß“π¢ÕßÕß§å°√¬—ß§ß¬◊πÀ¬—¥‡™àπ‡¥‘¡§◊Õ ª√–¡«≈

Õß§å§«“¡√Ÿâ ‚¥¬°“√∑” systematic reviews ¢Õßß“π«‘®—¬∑“ß§≈‘π‘° ‚¥¬¡’

°√–∫«π°“√∑∫∑«π∑’Ë¡’§ÿ≥¿“æ ¡’√–‡∫’¬∫«‘∏’∑’Ë™—¥‡®π ‡™◊ËÕ∂◊Õ‰¥â‡æ◊ËÕ‡º¬·æ√à·°à

∫ÿ§≈“°√∑“ß°“√·æ∑¬å „Àâ “¡“√∂π”‰ª„™â‡ªìπ¢âÕ¡Ÿ≈ª√–°Õ∫°“√µ—¥ ‘π„®„π°“√

¥Ÿ·≈√—°…“ºŸâªÉ«¬

„π°“√¥”‡π‘πß“π4 Õß§å°√ Cochrane ¡’À≈—° 10 ª√–°“√ ∑’Ë∂◊ÕªØ‘∫—µ‘

§◊Õ

1. °“√√à«¡¡◊Õ°—π (collaboration)

2. àß‡ √‘¡ªí®‡®°∫ÿ§§≈∑’Ë¡’§«“¡°√–µ◊Õ√◊Õ√âπ„π°“√∑”ß“π (building

on the enthusiasm of individuals)

3. À≈’°‡≈’Ë¬ß°“√∑”´È”´âÕπ (avoiding duplication)

4. ¡’Õ§µ‘À√◊Õ≈”‡Õ’¬ßπâÕ¬∑’Ë ÿ¥ (minimizing bias)

5. ¢âÕ¡Ÿ≈µâÕß∑—π ¡—¬µ≈Õ¥‡«≈“ (keeping up to date)

6. ‡πâπ°“√ª√–‡¡‘πº≈∑’Ë ”§—≠·≈–™à«¬„π°“√µ—¥ ‘π„®∑“ß§≈‘π‘°

(ensuring relevance)

7. „ÀâºŸâ„™â “¡“√∂‡¢â“∂÷ß¢âÕ¡Ÿ≈‰¥âßà“¬ (ensuring access)

8. ª√—∫ª√ÿß§ÿ≥¿“æµ≈Õ¥‡«≈“ (continually improving the

quality of its work)

9. ¡’§«“¡µàÕ‡π◊ËÕß (continuity)

10. “¡“√∂‡¢â“¡’ à«π√à«¡‚¥¬‰¡à®”°—¥ (enabling wide participation)


Cochrane Collaboration4 ¡’‚§√ß √â“ß Àπà«¬ß“π ·≈–¢Õ∫‡¢µ§«“¡

√—∫º‘¥™Õ∫ ¢Õß·µà≈–ΩÉ“¬‰«âÕ¬à“ß™—¥‡®π ·≈–¡’°“√ª√– “πß“π°—π¿“¬„πÕß§å°√

Õ¬à“ß‡ªìπ√–∫∫ ‰¥â·°à Cochrane Center, Collaborative Review Groups,

Cochrane Methods Groups, Cochrane Fields/Networks ·≈– Consumer

Network ¥—ß· ¥ß„π√Ÿª∑’Ë 6.1

Cochrane Center ∑”Àπâ“∑’Ëª√– “πß“π„π°‘®°√√¡À≈—°¢ÕßÕß§å°√

‰¥â·°à °“√§âπÀ“¢âÕ¡Ÿ≈ß“π«‘®—¬‡™‘ß∑¥≈Õß®“°·À≈àßµà“ßÊ °“√®—¥∑”∑–‡∫’¬πß“π

«‘®—¬ ‡æ◊ËÕ√«∫√«¡‰«â„π∞“π¢âÕ¡Ÿ≈ The Cochrane Central Register of

Controlled Trials (CENTRAL) ÷Ëß‡ªìπ∞“π¢âÕ¡Ÿ≈¬àÕ¬„π∞“π¢âÕ¡Ÿ≈ The Cochrane

Library ·≈–„Àâ°“√ π—∫ πÿπ°≈ÿà¡µà“ßÊ (Collaborative Review Groups) „π

°“√®—¥∑” Cochrane Systematic reviews √«¡∑—Èßª√– “πß“π°—∫ ¡“™‘°

Àπà«¬ß“π ·≈–Õß§å°√¿“¬πÕ°∑’Ë‡°’Ë¬«¢âÕß √«¡∑—Èß°“√Ωñ°Õ∫√¡ ·≈–°“√‡º¬·æ√à

º≈ß“π „Àâ¡’°“√π”‰ª„™â„Àâ‡°‘¥ª√–‚¬™πå„π‡«™ªØ‘∫—µ‘ ªí®®ÿ∫—π¡’ Cochrane Center

12 ·Ààß °√–®“¬Õ¬Ÿà„πª√–‡∑»µà“ßÊ ∑—Ë«‚≈° µ“¡√Ÿª∑’Ë 6.2

Collaborative Review Groups ‡°‘¥®“°°“√√«¡°—π¢Õß ¡“™‘° Õ“ “

¡—§√∑’Ë‡ªìπ·æ∑¬å π—°«‘®—¬ ∑’Ë π„®„π “¢“‡¥’¬«°—πªí®®ÿ∫—π¡’ 51 °≈ÿà¡ ·µà≈–°≈ÿà¡

¡’Àπâ“∑’Ë√—∫º‘¥™Õ∫À≈—°§◊Õ °“√®—¥∑” systematic reviews „πÀ—«¢âÕµà“ßÊ

∑’ËÕ¬Ÿà„π¢Õ∫‡¢µ¢Õß “¢“«‘™“π—Èπ ¥—ß√Ÿª∑’Ë 6.3 systematic reviews ∑’Ë°≈ÿà¡®—¥

∑”¢÷Èπ∑—ÈßÀ¡¥®–‡º¬·æ√àÕ¬Ÿà„π∞“π¢âÕ¡Ÿ≈ The Cochrane Library √–‡∫’¬∫«‘∏’

„π°“√∑” systematic reviews ‰¥â¡’°“√°”Àπ¥¢—ÈπµÕπ ·≈–¡“µ√∞“π¢Õß

Cochrane „π°“√§âπ§«â“§—¥‡≈◊Õ° ·≈–°“√«‘‡§√“–Àåº≈‰«â™—¥‡®π ‡æ◊ËÕ„Àâ¡’Õ§µ‘À√◊Õ

§«“¡≈”‡Õ’¬ßπâÕ¬∑’Ë ÿ¥ ¢≥–‡¥’¬«°—π Review Group ·µà≈–°≈ÿà¡°ÁµâÕß

√—∫º‘¥™Õ∫„π°“√‡æ‘Ë¡‡µ‘¡¢âÕ¡Ÿ≈„À¡àÊ „Àâ∑—π ¡—¬Õ¬Ÿà‡ ¡Õ ‡æ◊ËÕ„Àâ¡’°“√ √ÿªº≈

∑’Ë∂Ÿ°µâÕß‡ªìπªí®®ÿ∫—π ·≈–µâÕß “¡“√∂‡º¬·æ√à ‰ª ŸàºŸâ∑’Ë®”‡ªìπµâÕß„™â ‰¥â

∑—π‡«≈“ ‡æ◊ËÕ‡ªìπ¢âÕ¡Ÿ≈™à«¬„π°“√µ—¥ ‘π„®¢Õß·æ∑¬å∑’Ë¥Ÿ·≈ºŸâªÉ«¬ Õ’°∑—Èß‡æ◊ËÕ

ª√–‚¬™πå„π°“√∫Õ°∑‘»∑“ß¢Õß°“√«‘®—¬∑’Ë®”‡ªìπ À√◊Õ„πª√–‡¥Áπ∑’Ë¬—ß‰¡à¡’§”µÕ∫


Cochrane Method Group ª√–°Õ∫¥â«¬ºŸâ‡™’Ë¬«™“≠¥â“π√–‡∫’¬∫

«‘∏’«‘®—¬·≈– ∂‘µ‘ ®–¡’Àπâ“∑’Ë√—∫º‘¥™Õ∫„π°“√°”Àπ¥°Æ‡°≥±å æ—≤π“§âπ§«â“

√–‡∫’¬∫«‘∏’ ·≈–«‘∏’°“√ —ß‡§√“–Àå¢âÕ¡Ÿ≈‡æ◊ËÕ„Àâ¡’§«“¡∂Ÿ°µâÕß¡“°∑’Ë ÿ¥ √–‡∫’¬∫

«‘∏’∑’Ë°”Àπ¥∂◊Õ‡ªìπ ‘Ëß∑’Ë Cochrane reviewer ®–µâÕß¬÷¥∂◊Õ‡ªìπ·π«∑“ßªØ‘∫—µ‘

„π°“√®—¥∑” systematic reviews ‡æ◊ËÕ„Àâ‡ªìπ¡“µ√∞“π‡¥’¬«°—π Cochrane

Method Group ‰¥â¡’°“√ √â“ß·≈–æ—≤π“ software ∑’Ë„™â„π°“√∑” systematic

reviews §◊Õ Review Manager program (Revman) ÷Ëß‡ªìπ ‚ª√·°√¡∑’Ë„™âßà“¬

·≈– –¥«° ”À√—∫ reviewer ‚¥¬‡ªìπ‚ª√·°√¡∑’Ë„™â ‰¥â„π∑ÿ°¢—ÈπµÕπ¢Õß°“√∑”

systematic reviews µ—Èß·µà°“√®—¥∑” protocol °“√¥”‡π‘π °“√∑∫∑«π √«¡∂÷ß

°“√«‘‡§√“–Àå¢âÕ¡Ÿ≈·≈–°“√‡ πÕº≈¢Õß meta-analysis ‚ª√·°√¡π’È “¡“√∂

download æ√âÕ¡§Ÿà¡◊Õ°“√„™âß“π‰¥âø√’ ∑’Ë http://www. cc-ims.net/Revman//

Fields π„®„π¡‘µ‘°“√∫√‘°“√ “∏“√≥ ÿ¢¡“°°«à“ªí≠À“ “∏“√≥ ÿ¢ ‡™àπ

√Ÿª·∫∫°“√∫√‘°“√ ™π‘¥¢Õß°≈ÿà¡ºŸâ∫√‘‚¿§ ‡ªìπµâπ ™à«¬®—¥≈”¥—∫§«“¡ ”§—≠

¡ÿ¡¡Õß Õ¿‘ª√“¬ ·≈–„Àâ‡ ’¬ß –∑âÕπß“π¢Õß Collaborative Review Groups

The Cochrane Consumer Network ®–„Àâ¢âÕ¡Ÿ≈ ®—¥ª√–™ÿ¡ ·≈–

‡ªìπ®ÿ¥ª√– “πß“π‡§√◊Õ¢à“¬ºŸâ∫√‘‚¿§∑’Ë‡°’Ë¬«¢âÕß°—∫ Collaboration ∑—Ë«‚≈°


√Ÿª∑’Ë 6.1 Cochrane Collaboration5

√Ÿª∑’Ë 6.2 Cochrane Collaboration Centers6


√Ÿª∑’Ë 6.3 Cochrane Collaborative Review Groups7

Cochrane Acute Respiratory Infections GroupCochrane Airways GroupCochrane Anaesthesia GroupCochrane Back GroupCochrane Breast Cancer GroupCochrane Colorectal Cancer GroupCochrane Consumers & Communication GroupCochrane Cystic Fibrosis and Genetic Disorders GroupCochrane Dementia and Cognitive Improvement GroupCochrane Depression, Anxiety and Neurosis GroupCochrane Developmental, Psychosocial and Learning Problems GroupCochrane Drugs and Alcohol GroupCochrane Ear, Nose and Throat Disorders GroupCochrane Effective Practice and Organisation of Care GroupCochrane Epilepsy GroupCochrane Eyes and Vision GroupCochrane Fertility Regulation GroupCochrane Gynaecological Cancer GroupCochrane Haematological Malignancies GroupCochrane Heart GroupCochrane Hepato-Biliary GroupCochrane HIV/AIDS GroupCochrane Hypertension GroupCochrane Incontinence GroupCochrane Infectious Diseases GroupCochrane Inflammatory Bowel Disease GroupCochrane Injuries GroupCochrane Lung Cancer GroupCochrane Menstrual Disorders and Subfertility GroupCochrane Metabolic and Endocrine Disorders GroupCochrane Movement Disorders GroupCochrane Multiple Sclerosis GroupCochrane Musculoskeletal GroupCochrane Musculoskeletal Injuries GroupCochrane Neonatal GroupCochrane Neuromuscular Disease GroupCochrane Oral Health GroupCochrane Pain, Palliative Care and Supportive Care GroupCochrane Peripheral Vascular Diseases GroupCochrane Pregnancy and Childbirth GroupCochrane Prostatic Diseases and Urologic Cancers GroupCochrane Renal GroupCochrane Schizophrenia GroupCochrane Sexually Transmitted Diseases GroupCochrane Skin GroupCochrane Stroke GroupCochrane Tobacco Addiction GroupCochrane Upper Gastrointestinal and Pancreatic Diseases GroupCochrane Wounds Group


∞“π¢âÕ¡Ÿ≈ The Cochrane LibraryThe Cochrane Library ‡ªìπ∞“π¢âÕ¡Ÿ≈Õ‘‡≈§‚∑√π‘§ „π√Ÿª·∫∫ CD

ROM À√◊Õ ºà“π internet ‡∑à“π—Èπ ‰¡à¡’°“√®—¥æ‘¡æå‡ªìπÀπ—ß ◊Õ ¡’∞“π¢âÕ¡Ÿ≈¬àÕ¬

Õ¬ŸàÀ≈“¬™ÿ¥ ‰¥â·°à

The Cochrane Database of Systematic Reviews (CDSR)

‡ªìπ∞“π¢âÕ¡Ÿ≈À≈—°¢Õß The Cochrane Library ´÷Ëß∫√√®ÿ√“¬ß“π

systematic reviews ∑’Ë Collaborative Review Groups °≈ÿà¡µà“ßÊ ‰¥â∑”‰«â

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ß“π«‘®—¬‡™‘ß∑¥≈Õß∑“ß§≈‘π‘°∑’Ë‡ªìπ randomized controlled trials „π‡√◊ËÕßµà“ßÊ

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(NHS CRD) √à«¡°—∫ University of York ¡’¢âÕ¡Ÿ≈¢Õß°“√∑∫∑«π systematic

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(CENTRAL)

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The Cochrane Methodology Register (CMR)

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systematic reviews

Health Technology Assessment Database (HTA)

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ÿ¢¿“æ∑’Ë®—¥∑”‚¥¬ INAHTA (International Network of Agencies of Health

Technology Assessment) ·≈–Õß§å°√ Health Technology Assessment Õ◊ËπÊ


NHS Economic Evaluation Database (NHS EED)

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health care interventions µà“ßÊ

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2. √à«¡· ¥ß§«“¡§‘¥‡ÀÁπ Õ∫∂“¡ „Àâ§”·π–π” ·≈–¢âÕ¡Ÿ≈‡æ‘Ë¡‡µ‘¡

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e-mail address ª√“°ØÕ¬Ÿà„π·µà≈–‡√◊ËÕß ·≈–·µà≈–°≈ÿà¡

3. ‡ªìπºŸâ∑∫∑«π„π Collaborative Review Groups °≈ÿà¡µà“ßÊ

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°“√‡º¬·æ√à„π The Cochrane Library ·≈â« ®–µâÕß¡’ Commitment „π°“√¥Ÿ·≈

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network

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Central Register of Controlled Trials (CENTRAL)

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Search strategy

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√Ÿª∑’Ë 6.4 µ—«Õ¬à“ß‡√◊ËÕß¬àÕ¢Õß Cochrane Systematic Reviews7

Antibiotics for treating scrub typhus

Panpanich R, Garner P

ABSTRACT

A substantive amendment to this systematic review was last

made on 04 March 2002. Cochrane reviews are regularly checked

and updated if necessary.

Background: Scrub typhus is a bacterial disease in regions of

Asia and the Pacific. Antibiotics (chloramphenicol, tetracycline,

and doxycycline) have been used to treat the disease. Resistance

to these antibiotics has been reported.

Objectives: To evaluate antibiotic regimens for treating scrub

typhus.

Search strategy: We searched the Cochrane Infectious Diseases

Group specialized trials register (March 2002); the Cochrane

Controlled Trials Register (The Cochrane Library, Issue 1, 2002);

MEDLINE (1966 to March 2002); EMBASE (1988 to January 2002);

LILACS (2001, 40a Edition CD-ROM). We checked references and

contacted authors for additional data.

Selection criteria: Randomized and quasi-randomized studies

comparing antibiotic regimens in people diagnosed with scrub

typhus.

Data collection and analysis: One reviewer screened the search

results; both reviewers assessed eligibility, quality and extracted


data. We used Review Manager (Version 4.1), and expressed

results as Relative Risk (binary) or weighted mean difference

(continuous), with 95% confidence intervals.

Main results: Four trials involving 451 adults met the inclusion

criteria. One small study did not demonstrate a difference between

tetracycline with chloramphenicol (participants afebrile after 48

hours, Relative Risk 1.00; 95% confidence interval 0.07 to 15.26).

Two small trials did not show a difference between doxycycline

and tetracycline (participants afebrile after 48 hours, Relative Risk

0.46; 95% confidence interval 0.12 to 1.75). One trial showed

rifampicin to be more effective than doxycycline (for eliminating

fever, Relative Risk 0.41; 95% confidence interval 0.22 to 0.77; no

relapses in either group).

Reviewersû conclusions: Limited data has not demonstrated a

difference between tetracycline and doxycycline. Limited data

suggest rifampicin is effective in areas where scrub typhus

appears to respond poorly to standard anti-rickettsial drugs. .

(Citation: Panpanich R, Garner P. Antibiotics for treating scrub

typhus (Cochrane Review). In: The Cochrane Library, Issue 3, 2004.

Chichester, UK: John Wiley & Sons, Ltd.



1. Cochrane Brochure [Web Page]. Available at http://www.cochrane.org/docs/

archieco.htm. (Accessed 15 August 2004).

2. Bero L, Rennie D. The Cochrane Collaboration. Preparing, maintaining, and

disseminating systematic reviews of the effects of health care. JAMA 1995;

274(24):1935-8.

3. Chalmers I. The Cochrane collaboration: preparing, maintaining, and disseminating

systematic reviews of the effects of health care. Ann N Y Acad Sci 1993; 703:156-

63; discussion 163-5.

4. The Cochrane collaboration : Cochrane Collaboration Leaflet [Web Page]. Available

at http://www.cochrane.org/resources/leaflet.htm. (Accessed 15 August 2004).

5. Introduction to the Cochrane Collaboration [Web Page]. Available at http:// www.

cochrane.org/software/training/cochrane.ppt (Accessed 15 August 2004).

6. Cochrane centres and branches [Web Page]. Available at http://www.cochrane.org/

contact/centresmap.htm#. (Accessed 15 August 2004).

7. Cochrane entities. [Web Page]. Available at http://www.cochrane.org/contact/

entities.htm#CRGLIST (Accessed 15 August 2004).

8. Alphabetical list of titles of Cochrane Reviews [Web Page]. Available at http://

www.cochrane.org/cochrane/revabstr/mainindex.htm. (Accessed 15 August 2004).

9. COCHRANE INFECTIOUS DISEASES GROUP: Abstracts of Cochrane Reviews [Web

Page]. Available at http://www.cochrane.org/cochrane/revabstr/ab002150.htm.

(Accessed 15 August 2004).


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systematic reviews ∑’Ë‰¥â√—∫§«“¡‡™◊ËÕ∂◊Õ¡“° ‡π◊ËÕß®“°¡’√–‡∫’¬∫«‘∏’∑’Ë¥’ ·≈–

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‡ªìπ¢âÕ¡Ÿ≈∑“ß°“√·æ∑¬å∑’Ë —ß‡§√“–Àå®“°«“√ “√µà“ßÊ update ∑ÿ° 4 ‡¥◊Õπ


7.2 Search strategy „π°“√ ◊∫§âπ Systematic reviews°“√ ◊∫§âπ¢âÕ¡Ÿ≈∑’Ë‡ªìπ systematic reviews „π·µà≈–∞“π¢âÕ¡Ÿ≈ ‡æ◊ËÕ

∑’Ë®–„Àâ ‰¥â systematic reviews µ“¡∑’ËµâÕß°“√π—Èπ Õ“®®–¡’°≈¬ÿ∑∏å (search

strategy) ·µ°µà“ß°—π‰ª µâÕß»÷°…“√“¬≈–‡Õ’¬¥¢Õß§Ÿà¡◊Õ¢Õß∞“π¢âÕ¡Ÿ≈π—ÈπÊ ‡™àπ

- Greenhalgh4 ‰¥â·π–π”°≈¬ÿ∑∏å°“√ ◊∫§âπ MEDLINE ∑’Ë¡’§«“¡‰«

Ÿßµ“¡√Ÿª∑’Ë 7.1

√Ÿª∑’Ë 7.1 Maximally sensitive qualifying string for identifying

systematic reviews4


- NHS Centre for Reviews and Dissemination at the

University of York ·π–π”™ÿ¥§”„π°“√ ◊∫§âπ„π MEDLINE ÷Ëß “¡“√∂°√Õß

„Àâ ‰¥â Systematic reviews ∑’Ë¡’ Precision ·≈– Sensitivity ª“π°≈“ß5

√Ÿª∑’Ë 7.2 Search Strategies to Identify Reviews and Meta-analysis in

MEDLINE and CINAHL (Developed by NHS Centre for

Reveiws and Dissemination at the University of York)5

- „π Pubmed ¡’«‘∏’°“√∑’Ë∑”„Àâ‡°‘¥§«“¡ –¥«°¡“°¢÷Èπ ‚¥¬„™â§”«à“

systematic[sb] AND (search terms or subject area) ‡™àπ systematic[sb]

AND mammogr* ®–¡’°“√·ª≈‚¥¬Õ—µ‚π¡—µ‘ ‡ªìπ systematic[sb] AND

mammogram À√◊Õ mammograph À√◊Õ§” mammogr.. ÷Ëß≈ß∑â“¬¥â«¬§”Õ◊ËπÊ

∑’Ë‡°’Ë¬«¢âÕß¡“°¡“¬ ÷Ëß¥Ÿ¢âÕ§«“¡√“¬≈–‡Õ’¬¥„π°“√ ◊∫§âπ ‰¥â‚¥¬§≈‘Í°∑’Ë Details


7.3 À≈—°°“√ª√–‡¡‘π§ÿ≥¿“æ Systematic reviews‡¡◊ËÕ ◊∫§âπæ∫ systematic reviews µ√ß°—∫∑’ËµâÕß°“√π”‰ª„™âª√–‚¬™πå

·≈â«§«√®–ª√–‡¡‘π§ÿ≥¿“æ¢Õß systematic reviews °àÕπ ‰¥â¡’ºŸâ«“ß·π«∑“ß

‰«â¡“°¡“¬ 6, 7, 8 æÕ √ÿª‡ªìπ§”∂“¡ µ“¡À—«¢âÕµàÕ‰ªπ’È

1. Problem formulation

- ¡’°“√°”Àπ¥À—«¢âÕ‡√◊ËÕß‰«â™—¥‡®πÀ√◊Õ‰¡à ÷Ëß√«¡∂÷ß§«“¡™—¥‡®π

¢Õß intervention °≈ÿà¡ºŸâªÉ«¬ µ≈Õ¥®π outcome ∑’ËµâÕß°“√

∑∫∑«π

2. Data collection

- ¡’°“√ ◊∫§âπ¢âÕ¡Ÿ≈Õ¬à“ß‡ªìπ√–∫∫§√∫∂â«πÀ√◊Õ‰¡à

- ¡’°“√∫Õ°√“¬≈–‡Õ’¬¥°√–∫«π°“√ ◊∫§âπÀ√◊Õ‰¡à

- ¡’°“√ ◊∫§âπ·À≈àß¢âÕ¡Ÿ≈∑’ËπÕ°‡Àπ◊Õ®“°¿“…“Õ—ß°ƒ…À√◊Õ‰¡à

¡’°“√ ◊∫§âπ®“°·À≈àßÕ◊Ëπ∑’Ë‡√’¬°«à“ Grey literature À√◊Õ‰¡à


- ‡°≥±å°“√°√Õß∑’Ë®–‡≈◊Õ°√—∫¢âÕ¡Ÿ≈„¥ (inclusion criteria) À√◊Õ§—¥¢âÕ¡Ÿ≈„¥ÕÕ° (exclusion criteria) ™—¥‡®πÀ√◊Õ‰¡à

- ¡’°“√ª√–‡¡‘π§«“¡‡∑’Ë¬ßµ√ß (validity) ¢Õß¢âÕ¡Ÿ≈À√◊Õ‰¡à3. Data synthesis

- «‘∏’°“√„π°“√ —ß‡§√“–Àå¢âÕ¡Ÿ≈™—¥‡®πÀ√◊Õ‰¡à- „™â qualitative À√◊Õ quantitative À“°‡ªìπ quantitative

¡’°“√ª√—∫Àπà«¬¢Õß output „Àâ‡À¡◊Õπ°—πÀ√◊Õ‰¡à4. Interpretation of results

- ¢âÕ √ÿª¡“®“°¢âÕ¡Ÿ≈À≈—°∞“π∑’Ë‰¥â∑∫∑«π¡“À√◊Õ‰¡à- ¢âÕ·π–π”·π«∑“ßªØ‘∫—µ‘‡™◊ËÕ¡‚¬ß°—∫√–¥—∫¢Õß¢âÕ¡Ÿ≈À≈—°∞“π

À√◊Õ‰¡à- ¡’°“√«‘‡§√“–Àå subgroup À√◊Õ‰¡à- ‡°≥±å°“√µ—¥ ‘π„®™—¥‡®π ‚ª√àß„ À√◊Õ‰¡à

πÕ°®“°π’È Oxman, Cook, et al9 ‰¥â·π–π”∂÷ß°“√æ‘®“√≥“∫∑§«“¡™π‘¥ review ‰«â„π§Ÿà¡◊Õ°“√Õà“π∫∑§«“¡ ´÷Ëß¡’‡π◊ÈÕÀ“ Õ¥§≈âÕß°—∫∑’Ë°≈à“«¡“·≈â«·µà®—¥µ“¡≈”¥—∫§«“¡ ”§—≠ ‰«â¥—ßπ’È (√Ÿª∑’Ë 7.3)I. º≈¢Õß°“√∑∫∑«ππ—Èπ‡∑’Ë¬ßµ√ß (Valid) À√◊Õ‰¡à

Systematic review π—ÈπÊ µ—Èß°√Õ∫§”∂“¡™—¥‡®πÀ√◊Õ‰¡à- ª√–‡¥Áπ§”∂“¡µâÕß¡’§«“¡™—¥‡®πµ—Èß·µà™◊ËÕ¢Õß systematic

reviews ‡≈¬ Õß§åª√–°Õ∫¢Õß§”∂“¡ ®–¡’ 3 à«π ¥—ß∑’Ë°≈à“«·≈â«„πÀπâ“∑’Ë 19

‡°≥±å°“√°√Õß∑’Ë®–‡≈◊Õ°√—∫¢âÕ¡Ÿ≈„¥ (inclusion criteria) ¡’§«“¡‡À¡“– ¡À√◊Õ‰¡à- ‡°≥±å°“√°√Õß∑’Ë®–‡≈◊Õ°√—∫¢âÕ¡Ÿ≈„¥§«√™—¥‡®π∑—Èß patient

exposure ·≈– outcome √«¡∑—ÈßµâÕß· ¥ß«‘∏’¡“µ√∞“π„π°“√§—¥‡≈◊Õ° ÷Ëß§«√ Õ¥§≈âÕß°—∫‡°≥±å§«“¡‡∑’Ë¬ßµ√ß¢Õß

·µà≈–ß“π«‘®—¬ (¥Ÿ√Ÿª∑’Ë 7.4)


¡’‚Õ°“ ∑’Ëß“π«‘®—¬∑’Ëµ√ßª√–‡¥Áπ ·≈– ”§—≠ À≈ÿ¥√Õ¥‰ªÀ√◊Õ‰¡à

- µâÕß¥”‡π‘π°“√ ◊∫§âπÕ¬à“ß‡ªìπ√–∫∫µ“¡ inclusion criteria

®“°·À≈àß¢âÕ¡Ÿ≈∑—Èßµ’æ‘¡æå·≈–‰¡à ‰¥âµ’æ‘¡æå„π∞“π¢âÕ¡Ÿ≈

∑’ËÀ≈“°À≈“¬

‰¥â¡’°“√ª√–‡¡‘π§«“¡‡∑’Ë¬ßµ√ß¢Õßß“π«‘®—¬∑’Ëπ”¡“‡ªìπ¢âÕ¡Ÿ≈

À≈—°∞“π À√◊Õ‰¡à

- µâÕß¡’°“√ª√–‡¡‘π§ÿ≥¿“æß“π«‘®—¬∑’Ëπ”¡“‡ªìπ¢âÕ¡Ÿ≈À≈—°∞“π

„π review π—Èπ ·¡â«à“®–‡ªìπ randomized controlled

trial °Áµ“¡ ·≈–°“√µ’æ‘¡æå„π«“√ “√∑’Ë¡’ peer review

°Á‰¡à‰¥âª√–°—π«à“®–¡’§ÿ≥¿“æ¥’‡ ¡Õ‰ª §”∂“¡∑’Ë ”§—≠„π

°“√ª√–‡¡‘π§«“¡‡∑’Ë¬ßµ√ß µ“¡µ—«Õ¬à“ß„π√Ÿª∑’Ë 7.4

«‘∏’°“√„π°“√ª√–‡¡‘π§ÿ≥¿“æß“π«‘®—¬ “¡“√∂∑” È”

(reproducible) ‰¥âÀ√◊Õ‰¡à

- °“√ª√–‡¡‘π§ÿ≥¿“æß“π«‘®—¬‚¥¬ºŸâ∑∫∑«π¡’‚Õ°“ ∑’Ë®–‡°‘¥

§«“¡º‘¥æ≈“¥ ·≈–‡°‘¥Õ§µ‘‰¥â °“√∑’Ë¡’ºŸâ∑∫∑«π√à«¡°—π

¡“°°«à“Àπ÷Ëß§π®–™à«¬∑”„Àâº≈°“√∑∫∑«π¡’§«“¡πà“‡™◊ËÕ∂◊Õ¢÷Èπ

¢âÕ¡Ÿ≈À≈—°∞“π∑’Ëπ”¡“√«¡°—π¡’§«“¡§≈â“¬§≈÷ß°—π (homogenous)

À√◊Õ‰¡à

- ·¡â«à“®–ºà“π inclusion criteria ¡“·≈â«°Áµ“¡ √“¬≈–‡Õ’¬¥

¢Õß°“√»÷°…“«‘®—¬·µà≈–™‘ÈπÕ“®·µ°µà“ß°—π ¡’«‘∏’°“√∑“ß

∂‘µ‘„π°“√∑¥ Õ∫‡√’¬°«à“ çTests of homogeneityé

II. º≈¢Õß°“√∑∫∑«ππ—Èπ∫Õ°«à“Õ–‰√

º≈¢Õß°“√∑∫∑«ππ—Èπ§◊ÕÕ–‰√

- º≈¢Õß°“√∑∫∑«π§«√‡ªìπ quantitative ‡∑à“∑’Ë∑”‰¥â æ√âÕ¡

· ¥ß¢âÕ¡Ÿ≈∑“ß ∂‘µ‘∑’Ë‡°’Ë¬«¢âÕß ‡™àπ °“√∑∫∑«π‡°’Ë¬«°—∫

therapy §«√· ¥ß Relative risk, Absolute risk reduction


À√◊Õ°“√∑∫∑«π diagnostic test §«√· ¥ß Likelihood

ratios ‡ªìπµâπ

º≈¢Õß°“√∑∫∑«ππ—Èπ·¡àπµ√ß (precise) À√◊Õ‰¡à

- ‚¥¬¥Ÿ∑’Ë§à“ 95% CI (Confidence intervals)

III. º≈¢Õß°“√∑∫∑«ππ—Èπ®–™à«¬„π°“√µ—¥ ‘π„®„π°“√¥Ÿ·≈ºŸâªÉ«¬À√◊Õ‰¡à

º≈¢Õß°“√∑∫∑«ππ—Èπ„™â ‰¥âµ√ß°—∫ºŸâªÉ«¬∑’Ë¥Ÿ·≈Õ¬ŸàÀ√◊Õ‰¡à

º≈≈—æ∏å∑“ß§≈‘π‘°∑’Ë ”§—≠Ê ‰¥â√—∫°“√æ‘®“√≥“∑—ÈßÀ¡¥À√◊Õ‰¡à

°“√‡ª√’¬∫‡∑’¬∫º≈ª√–‚¬™πå∑’Ë‡°‘¥¢÷Èπ¡’‡Àπ◊Õ°«à“Õ—πµ√“¬ À√◊Õ

§à“„™â®à“¬À√◊Õ‰¡à

°“√∑” Checklist À—«¢âÕª√–‡¥Áπµà“ßÊ ®–™à«¬∑”„Àâß“πßà“¬¢÷Èπ10 ¥Ÿµ—«Õ¬à“ß·∫∫

worksheet „π√Ÿª∑’Ë 7.5


√Ÿª∑’Ë 7.3 ·π«∑“ß„πª√–‡¡‘π∫∑§«“¡·∫∫ systematic reviews9


√Ÿª∑’Ë 7.4 ·π«∑“ß„πª√–‡¡‘π§«“¡‡∑’Ë¬ßµ√ß (validity) ¢Õß∫∑§«“¡·∫∫µà“ßÊ11


√Ÿª∑’Ë 7.5 Worksheet ”À√—∫°“√ª√–‡¡‘π§ÿ≥¿“æ systematic reviews12


√Ÿª∑’Ë 7.5 (µàÕ)



1. Bero L, Rennie D. The Cochrane Collaboration. Preparing, maintaining, and

disseminating systematic reviews of the effects of health care. JAMA 1995; 274

(24):1935-8.

2. NHS Centre for Reviews and Dissemination [Web Page]. Available at http:// www.

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180-3.

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11. Oxman AD, Sackett DL, Guyatt GH. Usersû guides to the medical literature.

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1993; 270(17):2093-5.

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commissioning reviews. 2nd edition. York: NHS Centre for Reviews and

Dissemination, 2001.

107¿“§ºπ«° 1

¿“§ºπ«° 1

∫√√≥“πÿ°√¡(√«∫√«¡√“¬™◊ËÕ‡Õ° “√Õà“πª√–°Õ∫∑’Ëπà“ π„®)

107¿“§ºπ«° 1

¿“§º

π«°

1108

109¿“§ºπ«° 1

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Spitzer WO (ed). The Potsdam international consultation on meta-analysis. T Clin Epidemiol1995; 48 : 1-172

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®√‘¬“ ‡≈‘»Õ√√¶¬¡≥’ , ª√–¥‘…∞å ¡ª√–°‘® , Õÿ∫≈√—µπå —πµ«—µ√ ∫√√≥“∏‘°“√. ß“π«‘®—¬∑“ß§≈‘π‘§. °√ÿß‡∑æ:§≥–·æ∑¬»“ µ√å»‘√‘√“™æ¬“∫“≈, 2543.

™“µ√’ ∫“π™◊Ëπ, ¡‡°’¬√µ‘ ‚æ∏‘ —µ¬å ∫√√≥“∏‘°“√.§Ÿà¡◊Õ°“√ª√–‡¡‘π‡∑§‚π‚≈¬’ ∑“ß°“√·æ∑¬å (TechnologyAssessment). ππ∑∫ÿ√’: ”π—°æ—≤π“ «‘™“°“√·æ∑¬å °√¡°“√·æ∑¬å, 2545.

∏’√æ√ «ÿ≤¬«π‘™ , π‘¡‘µ√ ¡√°µ , °‘µµ‘°“ °“≠®π√—µπ“°√ ∫√√≥“∏‘°“√. «‘®—¬∑“ß°“√·æ∑¬å (Medical Research).‡™’¬ß„À¡à :§≥–·æ∑¬»“ µ√å ¡À“«‘∑¬“≈—¬‡™’¬ß„À¡à, 2542.

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Centres for Health Evidencehttp://www.york.ac.uk/inst/crd

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Centre for Evidence-Based Medicine, NSH Research and Development

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XVI. Guyatt GH, Sinclair J, Cook DJ, Glasziou P. Usersû guides to the medical literature:XVI. How to use a treatment recommendation. Evidence-Based Medicine WorkingGroup and the Cochrane Applicability Methods Working Group. JAMA 1999; 281:1836-43.

XVII. Barratt A, Irwig L, Glasziou P, Cumming RG, Raffle A, Hicks N et al. Usersû guides tothe medical literature: XVII. How to use guidelines and recommendations aboutscreening. Evidence-Based Medicine Working Group. JAMA 1999;281:2029-34.

XVIII. Randolph AG, Haynes RB, Wyatt JC, Cook DJ, Guyatt GH. Usersû Guides to theMedical Literature: XVIII. How to use an article evaluating the clinical impact of acomputer-based clinical decision support system. JAMA 1999;282:67-74.

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XIX.(A) Bucher HC, Guyatt GH, Cook DJ, Holbrook A, McAlister FA. Usersû guides to themedical literature: XIX. Applying clinical trial results. A. How to use an article measuringthe effect of an intervention on surrogate end points. Evidence-Based MedicineWorking Group. JAMA 1999; 282:771-8.

XIX.(B) McAlister FA, Laupacis A, Wells GA, Sackett DL. Usersû Guides to the MedicalLiterature: XIX. Applying clinical trial results B. Guidelines for determining whether adrug is exerting (more than) a class effect. JAMA1999;282:1371-7.

XX. McAlister FA, Straus SE, Guyatt GH, Haynes RB. Usersû guides to the medicalliterature: XX. Integrating research evidence with the care of the individual patient.Evidence-Based Medicine Working Group. JAMA 2000;283:2829-36.

XXI. Hunt DL, Jaeschke R, McKibbon KA. Usersû guides to the medical literature: XXI.Using electronic health information resources in evidence-based practice. Evidence-Based Medicine Working Group. JAMA 2000;283:1875-9.

XXII. McGinn TG, Guyatt GH, Wyer PC, Naylor CD, Stiell IG, Richardson WS. Usersû guidesto the medical literature: XXII: how to use articles about clinical decision rules.Evidence-Based Medicine Working Group. JAMA 2000;284:79-84.

XXIII.(A)Giacomini MK,.Cook DJ. Usersû guides to the medical literature: XXIII. Qualitativeresearch in health care A. Are the results of the study valid? Evidence-BasedMedicine Working Group. JAMA 2000; 284:357-62.

XXIII.(B)Giacomini MK,.Cook DJ. Usersû guides to the medical literature: XXIII. Qualitativeresearch in health care B. What are the results and how do they help me care for mypatients? Evidence-Based Medicine Working Group. JAMA 2000;284:478-82.

XXIV. Richardson WS, Wilson MC, Williams JW Jr, Moyer VA, Naylor CD. Userûs guides tothe medical literature: XXIV. How to use an article on the clinical manifestations ofdisease. Evidence-Based Medicine Working Group. JAMA 2000;284:869-75.

XXV. Guyatt GH, Haynes RB, Jaeschke RZ, Cook DJ, Green L, Naylor CD et al. Usersûguides to the Medical Literature: XXV. Evidence-based medicine: principles forapplying the Usersû Guides to patient care. Evidence- Based Medicine WorkingGroup. JAMA 2000;284:1290-6.

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GLOSSARY(selected and adapted

fromNational Information Center on Health Services

Research and Health Care Technology(NICHSR)

http://www.nlm.nih.gov/nichsr/ta101/ta10108.htmand

Cochrane Reviewerûs Handbook Glossary)

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Absolute risk reduction (ARR): a measure of treatment effect that compares the probability (ormean) of a type of outcome in the control group with that of a treatment group, [i.e.: Pc - Pt (orµc - µt)]. Forinstance, if the results of a trial were that the probability of death in a control groupwas 25% and the probability of death in a treatment group was 10%, the absolute risk reductionwould be (0.25 -0.10) = 0.15. (See also number needed to treat, odds ratio, and relative riskreduction.)

Accuracy: the degree to which a measurement (e.g., the mean estimate of atreatment effect) is true or correct. An estimate can be accurate, yet not be precise, if it is basedupon an unbiased method that provides observations having great variation (i.e., not close inmagnitude to each other).(Contrast with precision.)

Alpha (a): the probability of a Type I (false-positive) error. In hypothesis testing, thea-level is the threshold for defining statistical significance. For instance, setting a at a level of 0.05implies that investigators accept that there is a 5% chance of concluding incorrectly that anintervention is effective when it has no true effect. The a-level is commonly set at 0.01 or 0.05 or0.10.

Beta (b): the probability of a Type II (false-negative) error. In hypothesis testing, b is theprobability of concluding incorrectly that an intervention is not effective when it has true effect.(1-b) is the power to detect an effect of an intervention if one truly exists.

Bias: in general, any factor that distorts the true nature of an event or observation. In clinicalinvestigations, a bias is any systematic factor other than the intervention of interest that affectsthe magnitude of (i.e., tends to increase or decrease) an observed difference in the outcomes ofa treatment group and a control group. Bias diminishes the accuracy (though not necessarily theprecision) of an observation. Randomization is a technique used to decrease this form of bias.Biasalso refers to a prejudiced or partial viewpoint that would affect someoneûs interpretation ofa problem. Double blinding is a technique used to decrease this type of bias.

Blinding: the concealment of group assignment (to either the treatment or control group) from theknowledge of patients and/or investigators in a clinical trial. Blinding eliminates the possibility thatknowledge of assignment may affect patient response to treatment or investigator behaviors thatmay affect outcomes. Blinding is not always practical (e.g. when comparing surgery to drugtreatment), but it should be used whenever it is possible and compatible with optimal patientcare. Asingle-blind trial is one in which knowledge of group assignment is withheld only frompatients; a double-blind trial is one in which the knowledge is withheld from patients andinvestigators.

Case-control study: a retrospective observational study in which investigators identify a groupof patients with a specified outcome (cases) and a group of patients without the specifiedoutcome (controls). Investigators then compare the histories of the cases and the controls todetermine the extent to which each was exposed to the intervention of interest.

Case study: an uncontrolled (prospective or retrospective) observational studyinvolving an intervention and outcome in a single patient. (Also known as a single case report oranecdote.)

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Clinical practice guidelines: a systematically developed statement to assist practitioner andpatient decisions about appropriate health care for one or more specific clinical circumstances.The development of clinical practice guidelines can be considered to be a particular type ofHCTA; or, it can be considered to be one of the types of policymaking that is informed orsupported by HCTA.

Clinical significance: a conclusion that an intervention has an effect that is of practical meaningto patients and health care providers. Even though an intervention is found to have a statisticallysignificant effect, this effect might not be clinically significant. In a trial with a large number ofpatients, a small difference between treatment and control groups may be statistically significantbut clinically unimportant. In a trial with few patients, an important clinical difference may beobserved that does not achieve statistical significance. (A larger trial may be needed to confirmthat this is a statistically significant difference.)

Cohort study: an observational study in which outcomes in a group of patients that received anintervention are compared with outcomes in a similar group i.e., the cohort, either contemporaryor historical, of patients that did not receive the intervention. In an adjusted- (or matched-) cohortstudy, investigators identify (or make statistical adjustments to provide) a cohort group that hascharacteristics (e.g., age, gender, disease severity) that are as similar as possible to the groupthat experienced the intervention.

Compliance: a measure of the extent to which patients undergo an assigned treatment orregimen, e.g., taking drugs, undergoing a medical or surgical procedure, doing an exerciseregimen, or abstaining from smoking.

Concurrent nonrandomized control: a control group that is observed by investigators at thesame time as the treatment group, but that was not established using random assignment ofpatients to control and treatment groups. Differences in the composition of the treatment andcontrol groups may result.

Confidence interval: depicts the range of uncer tainty about an estimate of atreatment effect. It is calculated from the observed differences in outcomes of the treatment andcontrol groups and the sample size of a study. The confidence interval is the range of valuesabove and below the point estimate that is likely to include the true value of the treatment effect.The use of confidence intervals assumes that a study provides one sample of observations outof many possible samples that would be derived if the study were repeated many times. Inves-tigators typically use confidence intervals of 90%, 95%, or 99%. For instance, there is a 95%probability that a 95% confidence intervalcalculated from a particular study includes the truevalue of a treatment effect. If the interval includes a null treatment effect (usually 0.0 but 1.0 if thetreatment effect measure used is an odds ratio or relative risk), the null hypothesis of no truetreatment effect cannot be rejected.

Consensus development: various forms of group judgment in which a group (or panel) ofexperts interacts in assessing an intervention and formulating findings by vote or other processof reaching general agreement. These process may be informal or formal, involving suchtechniques as the nominal group and Delphi techniques.

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Control Event Rate (CER): see Event Rate.

Control group: a group of patients that serves as the basis of comparison when assessing theeffects of the intervention of interest that is given to the patients in the treatment group.Depending upon the circumstances of the trial, a control group may receive no treatment, açusualé or çstandardé treatment, or a placebo. To make the comparison valid, the composition ofthe control group should resemble that of the treatment group as closely as possible. (See alsohistorical control and concurrent nonrandomized control.)

Cost-benefit analysis: a comparison of alternative interventions in which costs and outcomesare quantified in common monetary units.

Cost-effectiveness analysis: a comparison of alternative interventions in which costs are mea-sured in monetary units and outcomes are measured in non-monetary units, e.g., reduced mor-tality or morbidity.

Cost-minimization analysis: a determination of the least costly among alternative interventionsthat are assumed to produce equivalent outcomes.

Cost-utility analysis: a form of cost-effectiveness analysis of alternative interventions in whichcostsare measured in monetary units and outcomes are measured in terms of their utility, usually tothe patient, e.g., using QALYs.

Cost of illness analysis: a determination of the economic impact of an disease or healthcondition, including treatment costs; this form of study does not address benefits/outcomes.

Critical appraisal: a technique which increases the effectiveness of your reading by enablingyou to exclude research studies that are too poorly designed to inform practice.

Crossover design: a clinical trial design in which patients receive, in sequence, the treatment (orthe control), and then, after a specified time, switch to the control (or treatment). In this design,patients serve as their own controls, and randomization is used to determine the order in whicha patient receives the treatment and control.

Cross-sectional study: a (prospective or retrospective) observational study in which a group ischosen (sometimes as a random sample) from a certain larger population, and the exposures ofpeople in the group to an intervention and outcomes of interest are determined.

Decision analysis: an approach to decision making under conditions of uncertainty that involvesmodeling of the sequences or pathways of multiple possible strategies (e.g., of diagnosis andtreatment for a particular clinical problem) to determine which is optimal. It is based uponavailable estimates (drawn from the literature or from experts) of the probabilities that certainevents and outcomes will occur and the values of the outcomes that would result from eachstrategy. A decision tree is a graphical representation of the alternate pathways.

Delphi technique: an iterative group judgment technique in which a central source forwardssurveys or questionnaires to isolated, anonymous (to each other) participants whose responses

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are collated/summarized and recirculated to the participants in multiple rounds for furthermodification/critique, producing a final group response (sometimes statistical).

Disability-adjusted life years (DALYs): a unit of health care status that adjusts age-specific lifeexpectancy by the loss of health and years of life due to disability from disease or injury. DALYsare often used to measure the global burden of disease.

Dissemination: any process by which information is transmitted (made available or accessible)to intended audiences or target groups.

Effect size: same as treatment effect. Also, a dimensionless measure of treatment effect that istypically used for continuous variables and is usually defined as the difference in mean outcomesof the treatment and control group divided by the standard deviation of the outcomes of thecontrol group. One type of meta-analysis involves averaging the effect sizes from multiplestudies.

Effectiveness: the benefit (e.g., to health outcomes) of using a technology for a particularproblem under general or routine conditions, for example, by a physician in a community hospitalor by a patient at home.

Effectiveness research: see outcomes research.

Efficacy: the benefit of using a technology for a particular problem under ideal conditions, forexample, in a laboratory setting, within the protocol of a carefully managed randomizedcontrolled trial, or at a çcenter of excellence.é

EMBASE (Excerpta Medica database): A European-based electronic database ofpharmacological and biomedical literature covering 3,500 journals from 110 countries. Years ofcoverage - 1974 to present.

Endpoint: a measure or indicator chosen for determining an effect of an intervention.

Event Rate: the proportion of patients in a group in whom an the event is observed. Thus, if outof 100 patients, the event is observed in 27, the event rate is 0.27. Control Event Rate (CER) andExperimental Event Rate (EER) are used to refer to this in control and experimental groups ofpatients respectively.

Evidence-based medicine: the use of current best evidence from scientific and medicalresearch to make decisions about the care of individual patients. It involves formulating questionsrelevant to the care of particular patients, searching the scientific and medical literature,identifying and evaluating relevant research results, and applying the findings to patients.

Evidence table: a summary display of selected characteristics (e.g., of methodological design,patients, outcomes) of studies of a particular intervention or health problem.

Experimental Event Rate (EER): see Event Rate.

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External validity: the extent to which the findings obtained from an investigation conductedunder particular circumstances can be generalized to other circumstances. To the extent that thecircumstances of a particular investigation (e.g., patient characteristics or the manner ofdelivering a treatment) differ from the circumstances of interest, the external validity of thefindings of that investigation may be questioned.

False negative error: occurs when the statistical analysis of a trial detects no difference inoutcomes between a treatment group and a control group when in fact a true difference exists.This is also known as a Type II error. The probability of making a Type II error is known as b.

False positive error: occurs when the statistical analysis of a trial detects a difference inoutcomes between a treatment group and a control group when in fact there is no difference.This is also known as a Type I error. The probability of a Type I error is known as a.

Follow-up: the ability of investigators to observe and collect data on all patients who wereenrolled in a trial for its full duration. To the extent that data on patient events relevant to the trialare lost, e.g., among patients who move away or otherwise withdraw from the trial, the resultsmay be affected, especially if there are systematic reasons why certain types of patientswithdraw. Investigators should report on the number and type of patients who could not beevaluated, so that the possibility of bias may be considered.

Funnel plot: A graphical display of sample size plotted against effect size that can be used toinvestigate publication bias.

Grey literature (or Gray literature): research reports that are not found in traditional peer-reviewedpublications, for example: government agency monographs, symposium proceedings, andunpublished company reports.

Healthcare technology assessment (HCTA): the systematic evaluation of properties, effects,and/or impacts of health care technology. It may address the direct, intended consequences oftechnologies as well as their indirect, unintended consequences. Its main purpose is to informtechnology-related policymaking in health care. HCTA is conducted by interdisciplinary groupsusing explicit analytical frameworks drawing from a variety of methods.

Health-related quality of life (HRQL) measures: patient outcome measures that extend beyondtraditional measures of mortality and morbidity, to include such dimensions as physiology,function, social activity, cognition, emotion, sleep and rest, energy and vitality, health perception,and general life satisfaction. (Some of these are also known as health status, functional status, orquality of life measures.)

Heterogeneity: In systematic reviews heterogeneity refers to variability or differences betweenstudies in the estimates of effects. A distinction is sometimes made between çstatisticalheterogeneityé (differences in the reported effects), çmethodological heterogeneityé (differencesin study design) and çclinical heterogeneityé (differences between studies in key characteristicsof the participants, interventions or outcome measures). Statistical tests of heterogeneity areused to assess whether the observed variability in study results (effect sizes) is greater than thatexpected to occur by chance. However, these tests have low statistical power.

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Homogeneity: In systematic reviews homogeneity refers to the degree to which the results ofstudies included in a review are similar. çClinical homogeneityé means that, in trials included in areview, the participants, interventions and outcome measures are similar or comparable. Studiesare considered çstatistically homogeneousé if their results vary no more than might be expectedby the play of chance.

Historical control: a control group that is chosen from a group of patients who were observedat some previous time. The use of historical controls raises concerns about valid comparisonsbecause they are likely to differ from the current treatment group in their composition, diagnosis,disease severity, determination of outcomes, and/or other important ways that would confoundthe treatment effect. It may be feasible to use historical controls in special instances where theoutcomes of a standard treatment (or no treatment) are well known and vary little for a givenpatient population.

Hypothesis testing: a means of interpreting the results of a clinical trial that involves determiningthe probability that an observed treatment effect could have occurred due to chance alone if aspecified hypothesis were true. The specified hypothesis is normally a null hypothesis, made priorto the trial, that the intervention of interest has no true effect. Hypothesis testing is used todetermine if the null hypothesis can or cannot be rejected.

Incidence: the rate of occurrence of new cases of a disease or condition in a population at riskduring a given period of time, usually one year.

Internal validity: the extent to which the findings of a study accurately represent the causalrelationship between an intervention and an outcome in the particular circumstances of thatstudy. The internal validity of a trial can be suspect when certain types of biases in the design orconduct of a trial could have affected outcomes, thereby obscuring the true direction, magnitude,or certainty of the treatment effect.

Large, simple trials: prospective, randomized controlled trials that use large numbers ofpatients, broad patient inclusion criteria, multiple study sites, minimal data requirements, andelectronic registries; their purposes include detecting small and moderate treatment effects,gaining effectiveness data, and improving external validity.

Likelihood ratio (LR): the likelihood that a given test result would be expected in a patient withthe target disorder compared to the likelihood that that same result would be expected in apatient without the target disorder. For example, you have a patient with anaemia and a serumferritin of 60mmol/l and you find in an article that 90 per cent of patients with iron deficiencyanaemia have serum ferritins in the same range as your patient (= sensitivity) and that 15 percent of patients with other causes for anaemia have serum ferritins in the same range as yourpatient (1 - specificity). This means that your patientûs result would be six times as likely (90/15)to be seen in someone with, as opposed to someone without, iron deficiency anaemia, and thisis called the LR for a positive test result.

LR+ = sensitivity / (1-specificity)LR- = (1-sensitivity) / specificity

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Literature review: a summary and interpretation of research findings reported in the literature.May include unstructured qualitative reviews by single authors as well as various systematic andquantitative procedures such as meta-analysis. (Also known as overview.)

MEDLINE: a bibliographic database that is the most used of about 40 MEDLARS databasesmanaged by the U.S. NLM. It is the computer version of the printed Index Medicus. Citations for12 million articles published since 1966 from about 4,500 health and biomedical journals arecompiled in MEDLINE, which is updated at a rate of 6,600 articles every week. About 75% ofcitations are for English-language articles.

MeSH: Medical Subject Headings, the controlled vocabulary of about 16,000 terms used forMEDLINE and certain other MEDLARS databases.

Meta-analysis: systematic methods that use statistical techniques for combining results fromdifferent studies to obtain a quantitative estimate of the overall effect of a particular interventionor variable on a defined outcome. This combination may produce a stronger conclusion than canbe provided by any individual study. (Also known as data synthesis or quantitative overview.)

N of 1 trial: a clinical trial in which a single patient is the total population for the trial, includinga single case study. An N of 1 trial in which random allocation is used to determine the order inwhich an experimental and a control intervention are given to a patient is an N of 1 RCT.

Null hypothesis: in hypothesis testing, the hypothesis that an intervention has no effect, i.e., thatthere is no true difference in outcomes between a treatment group and a control group. Typically,if statistical tests indicate that the P value is at or above the specified a-level (e.g., 0.01 or 0.05),then any observed treatment effect is not statistically significant, and the null hypothesis cannotbe rejected. If the P value is less than the specified a-level, then the treatment effect isstatistically significant, and the null hypothesis is rejected. If a confidence interval (e.g., of 95% or99%) includes zero treatment effect, then the null hypothesis cannot be rejected.

Number needed to treat (NNT): a measure of treatment effect that provides the number ofpatients who need to be treated to prevent one outcome event. It is the inverse of absolute riskreduction (1 / absolute risk reduction); i.e., 1.0 / (Pc - Pt). For instance, if the results of a trial werethat the probability of death in a control group was 25% and the probability of death in atreatment group was 10%, the number needed to treat would be 1.0 / (0.25 - 0.10) = 6.7 patients.(See also absolute risk reduction, relative risk reduction, and odds ratio.)

Observational study: a study in which the investigators do not manipulate the use of anintervention (e.g., do not randomize patients to treatment and control groups), but only observepatients who are (and sometimes patients who are not) exposed to the intervention, and interpretthe outcomes.

Odds ratio: a measure of treatment effect that compares the probability of a type of outcome in thetreatment group with the outcome of a control group, i.e., [Pt / (1 - Pt)] / [Pc / (1 - Pc)]. Forinstance, if the results of a trial were that the probability of death in a control group was 25% andthe probability of death in a treatment group was 10%, the odds ratio of survival would be [0.10/ (1.0 - 0.10)] / [(0.25 / (1.0 - 0.25)] = 0.33. (See also absolute risk reduction, number needed totreat, and relative risk.)

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Outcomes research: evaluates the impact of health care on the health outcomes of patients andpopulations. It may also include evaluation of economic impacts linked to health outcomes, suchas cost effectiveness and cost utility. Outcomes research emphasizes health problem- (ordisease-) oriented evaluations of care delivered in general, real-world settings; multidisciplinaryteams; and a wide range of outcomes, including mortality, morbidity, functional status, mentalwell-being, andother aspects of health-related quality of life. It may entail any in a range ofprimary data collection methods and synthesis methods that combine data from primary studies.

P value: in hypothesis testing, the probability that an observed difference between the interven-tion and control groups is due to chance alone if the null hypothesis is true. If P is less than thea-level (typically 0.01 or 0.05) chosen prior to the study, then the null hypothesis is rejected.

Patient selection bias: a bias that occurs when patients assigned to the treatment group differfrom patients assigned to the control group in ways that can affect outcomes, e.g., age ordisease severity. If the two groups are constituted differently, it is difficult to attribute observeddifferences in their outcomes to the intervention alone. Random assignment of patients to thetreatment and control groups minimizes opportunities for this bias.

Peer review: the process by which manuscripts submitted to health, biomedical, and otherscientifically oriented journals and other publications are evaluated by experts in appropriatefields (usually anonymous to the authors) to determine if the manuscripts are of adequate qualityfor publication.

Placebo: an inactive substance or treatment given to satisfy a patientûs expectation fortreatment. In some controlled trials (particularly investigations of drug treatments) placebos thatare made to be indistinguishable by patients (and providers when possible) from the true inter-vention are given to the control group to be used as a comparative basis for determining theeffect of the investigational treatment.

Placebo effect: the effect on patient outcomes (improved or worsened) that may occur due to theexpectation by a patient (or provider) that a particular intervention will have an effect. Theplacebo effect is independent of the true effect (pharmacological, surgical, etc.) of a particularintervention. To control for this, the control group in a trial may receive a placebo.

Power: the probability of detecting a treatment effect of a given magnitude when a treatmenteffect of at least that magnitude truly exists. For a true treatment effect of a given magnitude,power is the probability of avoiding Type II error, and is generally defined as (1 - b).

Precision: the degree to which a measurement (e.g., the mean estimate of a treatment effect) isderived from a set of observations having small variation (i.e., close in magnitude to each other).A precise estimate is not necessarily an accurate one. (Contrast with accuracy.)

Predictive value negative: an operating characteristic of a diagnostic test; predictive valuenegative is the proportion of persons with a negative test who truly do not have the disease,determined as: [true negatives / (true negatives + false negatives)]. It varies with the prevalenceof the disease in the population of interest. (Contrast with predictive value negative.)

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Predictive value positive: an operating characteristic of a diagnostic test; predictive valuepositive is the proportion of persons with a positive test who truly have the disease, determinedas: [true positives / (true positives + false positives)]. It varies with the prevalence of the diseasein the population of interest. (Contrast with predictive value negative.)

Prevalence: the number of people in a population with a specific disease or condition at a giventime, usually expressed as a ratio of the number of affected people to the total population.

Primary study: an investigation that collects original (primary) data from patients, e.g.,randomized controlled trials, observational studies, series of cases, etc. (Contrast with synthetic/integrative study).

Probability distribution: portrays the relative likelihood that a range of values is the true value ofa treatment effect. This distribution is typically shown in the form of a bell-shaped curve. Anestimate of the most likely true value of the treatment effect is the value at the highest point ofthe distribution. The area under the curve between any two points along the range gives theprobability that the true value of the treatment effect lies between those two points. Thus, aprobability distribution can be used to determine an interval that has a designated probability(e.g., 95%) of including the true value of the treatment effect.

Prospective study: a study in which the investigators plan and manage theintervention of interest in selected groups of patients. As such, investigators do not know whatthe outcomes will be when they undertake the study. (Contrast with retrospective study.)

Publication bias: unrepresentative publication of research reports that is not due to the qualityof the research but to other characteristics, e.g., tendencies of investigators to submit, andpublishers to accept, positive research reports (i.e., ones with results showing a beneficialtreatment effect of a new intervention).

Quality-adjusted life year (QALY): a unit of health care outcomes that adjusts gains (or losses)in years of life subsequent to a health care intervention by the quality of life during those years.QALYs can provide a common unit for comparing cost-utility across different interventions andhealth problems. Analogous units include disability-adjusted life years (DALYs).

Quality assurance: activities intended to ensure that the best available knowledge concerningthe use of health care to improve health outcomes is properly implemented. This involves theimplementation of health care standards, including quality assessment and activities to correct,reduce variations in, or otherwise improve health care practices relative to these standards.

Quality of care: the degree to which health care is expected to increase the likelihood of desiredhealth outcomes and is consistent with standards of health care. (See also quality assessmentand quality assurance.)

Random variation (or random error): the tendency for the estimated magnitude of a parameter(e.g., based upon the average of a sample of observations of a treatment effect) to deviaterandomly from the true magnitude of that parameter. Random variation is independent of the

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effects of systematic biases. In general, the larger the sample size is, the lower the randomvariation is of the estimate of a parameter. As random variation decreases, precision increases.

Randomization: a technique of assigning patients to treatment and control groups that is basedonly on chance distribution. It is used to diminish patient selection bias in clinical trials. Properrandomization of patients is an indifferent yet objective technique that tends to neutralize patientprognostic factors by spreading them evenly among treatment and control groups. Randomizedassignment is often based on computer-generated tables of random numbers.

Randomized controlled trial (RCT): a true prospective experiment in which investigatorsrandomly assign an eligible sample of patients to one or more treatment groups and a controlgroup and follow patiensû outcomes. (Also known as randomized clinical trial.)

Receiver operating characteristic (ROC) curve: a graphical depiction of the relationshipbetweenthe true positive ratio (sensitivity) and false positive ratio (1 - specificity) as a function of thecutoff level of a disease (or condition) marker. ROC curves help to demonstrate how raising orlowering the cutoff point for defining a positive test result affects tradeoffs between correctlyidentifying people with a disease (true positives) and incorrectly labeling a person as positivewho does not have the condition (false positives).

Reliability: the extent to which an observation that is repeated in the same, stable populationyields the same result (i.e., test-retest reliability). Also, the ability of a single observation todistinguish consistently among individuals in a population.

Relative risk (RR): see Risk Ratio

Relative risk reduction (RRR): a type of measure of treatment effect that compares theprobability of a type of outcome in the treatment group with that of a control group, i.e.: (Pc - Pt)/Pc. For instance, if the results of a trial show that the probability of death in a control group was25% and the probability of death in a control group was 10%, the relative risk reduction wouldbe: (0.25 - 0.10) / 0.25 = 0.6. (See also absolute risk reduction, number needed to treat, and oddsratio.)

Retrospective study: a study in which investigators select groups of patients that have alreadybeen treated and analyze data from the events experienced by these patients. These studies aresubject to bias because investigators can select patient groups with known outcomes. (Contrastwith prospective study.)

Risk Ratio (RR) : (synonym: Relative risk) the ratio of risk in the treated group (EER) to the riskin the control group (CER). Risk Ratio = EER/CER. Risk Ratio is used in randomised trials andcohort studies.

Safety: a judgment of the acceptability of risk (a measure of the probability of an adverseoutcome and its severity) associated with using a technology in a given situation, e.g., for apatient with a particular health problem, by a clinician with certain training, or in a specifiedtreatment setting.

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Sample size: the number of patients studied in a trial, including the treatment and controlgroups, where applicable. In general, a larger sample size decreases the probability of making afalse-positive error (a) and increases the power of a trial, i.e., decreases the probability of makinga false-negative error (b). Large sample sizes decrease the effect of random variation on theestimate of a treatment effect.

Sensitivity: an operating characteristic of a diagnostic test that measures the ability of a test todetect a disease (or condition) when it is truly present. Sensitivity is the proportion of all diseasedpatients for whom there is a positive test, determined as: [true positives / (true positives + falsenegatives)]. (Contrast with specificity.)

Sensitivity analysis: a means to determine the robustness of a mathematical model or analysis(such as a cost-effectiveness analysis or decision analysis) that tests a plausible range ofestimates of key independent variables (e.g., costs, outcomes, probabilities of events) todetermine if such variations make meaningful changes the results of the analysis. Sensitivityanalysis also can be performed for other types of study; e.g., clinical trials analysis (to see ifinclusion/exclusion of certain data changes results) and meta-analysis (to see if inclusion/exclusion of certain studies changes results).

Series: an uncontrolled study (prospective or retrospective) of a series (succession) of consecu-tive patients who receive a particular intervention and are followed to observe their outcomes.(Also known as clinical series or series of consecutive cases.)

SnNout: When a sign, test or symptom has a high sensitivity, a negative result rules out thediagnosis. For example, the sensitivity of the loss of retinal vein pulsation in diagnosing highintracranial pressure is 100 per cent. Therefore, if a person displays retinal vein pulsation, it rulesout important increases in intracranial pressure.

SpPin: When a sign, test or symptom has an extremely high specificity (say, over 95%), apositive result tends to rule in the diagnosis. For example, the specificity of 3 or more positiveresponses on a CAGE questionnaire in diagnosing alcoholism is >99% among internal medicinepatients. Therefore, if a person does answer éyesé to 3 or 4 of the CAGE questions, it rules in thediagnosis of alcohol dependency.

Specificity: an operating characteristic of a diagnostic test that measures the ability of a test toexclude the presence of a disease (or condition) when it is truly not present. Specificity is theproportion of nondiseased patients for whom there is a negative test, expressed as: [truenegatives / (true negatives + false positives)]. (Contrast with sensitivity.)

Statistical significance: a conclusion that an intervention has a true effect, based uponobserved differences in outcomes between the treatment and control groups that are sufficientlylarge so that these differences are unlikely to have occurred due to chance, as determined by astatistical test. Statistical significance indicates the probability that the observed difference wasdue to chance if the null hypothesis is true; it does not provide information about the magnitudeof a treatment effect. (Statistical significance is necessary but not sufficient for clinicalsignificance.)

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Statistical test: a mathematical formula (or function) that is used to determine if the differencein outcomes of a treatment and control group are great enough to conclude that the differenceis statistically significant. Statistical tests generate a value that is associated with a particularP value. Among the variety of common statistical tests are: F, t, Z, and chi-square. The choice ofa test depends upon the conditions of a study, e.g., what type of outcome variable used, whetheror notthe patients were randomly selected from a larger population, and whether it can beassumed that the outcome values of the population have a normal distribution or other type ofdistribution.

Surrogate endpoint: an outcome measure that is used in place of a primary endpoint (outcome).Examples are decrease in blood pressure as a predictor of decrease in strokes and heart attacksin hypertensive patients, and increase in T-cell (a type of white blood cell) counts as an indicatorof improved survival of AIDS patients. Use of a surrogate endpoint assumes that it is a reliablepredictor of the primary endpoint(s) of interest.

Synthetic (or integrative) study: a study that does not generate primary data but that involvesthe qualitative or quantitative consolidation of findings from multiple primary studies. Examplesare literature review, meta-analysis, decision analysis, and consensus development. (Contrastwith primary study.)

Technology: the application of scientific or other organized knowledge (including any tool,technique, product, process, method, organization or system) to practical tasks. In health care,technology includes drugs; diagnostics, indicators and reagents; devices, equipment andsupplies; medical and surgical procedures; support systems; and organizational and managerialsystems used in prevention, screening, diagnosis, treatment and rehabilitation.

Treatment effect: the effect of a treatment (intervention) on outcomes, i.e., attributable only tothe effect of the intervention. Investigators seek to estimate the true treatment effect using thedifference between the observed outcomes of a treatment group and a control group. (See effectsize.)

Type I error: same as false-positive error.

Type II error: same as false-negative error.

Utility: the relative desirability or preference (usually from theperspective of a patient) for a specific health outcome or level of health status.

Validity: The extent to which a measure accurately reflects the concept that it is intended tomeasure.

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WORKSHEETS(From NSH Research and Development,

Centre for Evidence-Based Medicine)

http://www.cebm.net/downloads/worksheets.rtf

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µ—«Õ¬à“ß Systematic Reviews‡√◊ËÕß

Antibiotics for treating scrub typhus

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Antibiotics for treating scrub typhusPanpanich R, Garner P

This review should be cited as: Panpanich R, Garner P. Antibiotics for treating scrub typhus(Cochrane Review). In: The Cochrane Library, Issue 2, 2004 Chichester, UK: John Wiley & Sons, Ltd.Background

Scrub typhus is a bacterial disease caused by Rickettsia tsutsugamushi (Orientiatsutsugamushi). It is transmitted by larval Leptotrombidium mites, which are commonly calledchiggers (Jagar 2001). Infection can cause widespread inflammation of the blood vessels in manyorgans, especially the lungs, kidneys, and central nervous system (Silpapojakul 1997). Peoplewith scrub typhus often do not have specific clinical features, but present with fever, headache,and a cough. An eschar makes the diagnosis much more likely; this occurs at the site of the bite,and starts as a large pimple (ùpapuleû), before the centre part of the skin dies and turns black,giving it the appearance of a cigarette burn. However, eschars are uncommon (Brown 1976,Sirisanthana 1989). Laboratory tests are not widely available: the Weil-Felix test (withProteus OX-K) is insensitive (Sirisanthana 1989), and serodiagnostic tests are only available inreference centres.INCIDENCE/PREVALENCE

Scrub typhus is common in the western Pacific region and many parts of Asia. It islisted as one of the differential diagnoses of fever of unknown origin in people in endemic areas.In Thailand, some estimates suggest that 10% of people with fever have scrub typhus (Silpapojakul1997). A seroprevalence study among 200 febrile people attending some malaria clinics inwestern Thailand has indicated that 59.5% had serology (immunoglobulin M and/orimmunoglobulin G) positive for scrub typhus infection (Chanyasanha 1998).RISK FACTORS

The risk of scrub typhus is closely related to occupation. Most cases in Asia areacquired through agricultural exposure in oil palm and rubber plantations in Malaysia, or in ricefields in Thailand. Scrub typhus is also associated with travel activities such as camping,rafting, or trekking in endemic areas (Silpapojakul 1997). A number of cases has been reportedin ùeco-travellersû from Europe and America (McDonald 1988, Watt 1994). In addition, scrubtyphus is an important disease in military personnel undertaking field duties in endemic areas(Deller 1967, Berman 1973). Recently, severe, life threatening scrub typhus has been reported inneonates as a result of the infection being transmitted from their mothers (Wang infection beingtransmitted from their mothers (Wang 1992, Suntharasaj 1997).PROGNOSIS AND TREATMENT

The severity of the disease is thought to depend on the virulence of the Rickettsiastrain, age and genetic factors of infected person, and whether the person has previously beeninfected. Antibiotic treatment is thought to shorten the illness and reduce mortality. It is usuallypresumptive, being given to cases who are febrile in an area where the disease is endemic.Chloramphenicol was the first drug described in a series of studies to reduce the morbidity andmortality associated with the disease (Smadel 1950). Tetracycline and doxycycline have alsobeen used.

We systematically searched for case series of people treated for scrub typhus (Table01). In one study involving 42 adults treated with a single dose of 200 mg doxycycline, 88%became afebrile and all clinical symptoms disappeared within 72 hours, and no relapsesoccurred in the month following treatment (Supparatpinyo 1990). In children, a good response totetracycline and chloramphenicol treatment was described in 25 cases, who all became afebrile

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in 48 hours. Relapse occurred in two children and fever subsided spontaneously in one of themwithin four days (Sirisanthana 1989).

In a case series from Chiangrai, northern Thailand, a poor response to a 7 day courseof doxycycline was reported; only 5/12 (40%) patients were afebrile at 72 hours. Moreover, theresult of doxycycline susceptibility testing in mouse fibroblast cell culture showed that only 39%of the patients had strains that were fully susceptible to doxycycline (Watt 1996) (Table 01).

The new macrolide antibiotic, azithromycin, was recently evaluated in vitro against R.tsutsugamushi. Azithromycin was effective against some strains of R. tsutsugamushi, particularlydoxycycline-resistant strains. Azithromycin is considered safer than other antibiotics for use inyoung children and pregnant women. It has advantages over chloramphenicol, whichoccasionally causes bone marrow suppression, and tetracycline, which affects the growing bonesand teeth of children and fetuses (Strickman 1995).CURRENT DEBATES

The appropriate length of antibiotic treatment to minimise recrudescence has not beenestablished. The potential advantage of alternative drugs (azithromycin, clarithromycin, andciprofloxacin) has not been directly established.

This review aims to summarise the information about the effects of antibiotics onscrub typhus, and examine the effects of doxycycline and other antibiotics in comparison totetracycline or chloramphenicol.Objectives

To evaluate antibiotic regimens for treating scrub typhus.Criteria for considering studies for this reviewTypes of studies

Randomized and quasi-randomized controlled trials.Types of participants

People diagnosed with scrub typhus, as defined by the trial authors.Types of intervention

Any antibiotic treatment that aims to treat scrub typhus, compared with anotherantibiotic regimens.Types of outcome measuresPRIMARY OUTCOMES

Death.Fever still present 72 hours after treatment started.Relapse within 3 months (return of fever or other symptoms during follow up).

SECONDARY OUTCOMESTreatment failures (persistence of symptoms, fever, and laboratory abnormalities at

end of treatment).Duration of illness.Duration of fever.Number of adverse events.

Search strategy for identification of studiesSee: Collaborative Review Group search strategy

We attempted to identify all relevant studies regardless of language or publicationstatus (published, unpublished, in press, and in progress).

We used the following search terms for all trial registers and databases: scrub typhus;Rickettsia tsutsugamushi; and Orientia tsutsugamushi.We searched the Cochrane InfectiousDiseases Group (CIDG) specialized trials register for relevant trials up to March 2002. Full details

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of the CIDG methods and the journals hand searched are published in The Cochrane Library inthe section on Collaborative Review Groups.We searched The Cochrane Controlled Trials Regis-ter, published in The Cochrane Library (Issue 1, 2002). This contains mainly reference information torandomized controlled trials and controlled clinical trials in health care.

We also searched the following electronic databases using the topic search terms incombination with the search strategy developed by the Cochrane Collaboration and detailed inthe Cochrane Reviewersû Handbook (Clarke 2000):(1) MEDLINE (1966 to March 2002);(2) EMBASE (1988 to January 2002);(3) LILACS (La Literatura Latinoamericana y del Caribe de Informacion en Ciencias de la Salud)database (2001; 40a Edition CD-ROM).

We checked the reference lists of all trials identified by the above methods.We contacted individual researchers in Thailand working in the field for unpublished data.

Methods of the reviewRatana Panpanich screened the results of the search strategy to identify potentially

relevant trials. We (Ratana Panpanich and Paul Garner) obtained the full reports of these trialsand applied the inclusion criteria to assess their eligibility for inclusion in the review. We resolveddisagreements by consulting a third person and have given the reason for excluding trials in theCharacteristics of excluded studiesû. We independently assessed the quality of the includedstudies using the generation of allocation sequence, concealment of treatment allocation,blinding, and completeness of the trial. We resolved disagreements through discussion. RPextracted data using a standardized data extraction form and PG independently cross checkedthe data; we checked the data sources to avoid multiple publication based on the same data. Weextracted data to allow for an intention-to-treat analysis where possible.

We analysed the data using Review Manager (Version 4.1). For binary data, wecalculated Relative Risk and 95% confidence intervals using the fixed effect model; for continuousdata, we calculated weighted mean difference and 95% confidence intervals.

We assessed heterogeneity by visually examining the forest plot and through the Chi-square test for heterogeneity using a 10% level of statistical significance. In the event ofheterogeneity, we planned to investigate it using the following subgroups: (1) type of antibiotic;(2) dose and length of administration; and (3) whether the trial was conducted before or afterantibiotic resistance had been reported.Description of studiesFour trials met the inclusion criteria.

Sheehy 1973 reported on military servicemen who acquired scrub typhus in Vietnam,and were evacuated çat randomé to one of two military hospitals. Participants were recruited in1966 although the study was not published until 1973. It is not entirely clear whether it was theevacuation that was random or the hospital allocation; pending clarification, we have included thestudy. A total of 63 participants were enrolled, and 3 with malaria were then excluded. Participantsevacuated to hospital A were given chloramphenicol (n = 30), and those to hospital B were giventetracycline (n = 30); both groups were followed up for 3 weeks. The outcomes measured by theresearchers were participants afebrile by 48 hours, and duration of fever.

Brown 1978 enrolled 149 adult participants in Malaysia presumed to have scrubtyphus. They were randomly assigned to receive either doxycycline or tetracycline. In theiranalysis, the authors then excluded participants with no serological evidence of infection, orparticipants with serological changes but a co-infection. This left 55 participants (doxycycline n= 31; tetracycline n = 24) with clinical and serological evidence of scrub typhus infection (see

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Characteristics of included studies). The outcomes measured by the researchers were disappearanceof symptoms, participants afebrile by 48 hours, and any adverse drug effects.

Song 1995 conducted a multicentre study in Korea, and enrolled 129 adultparticipants. Of these, 116 met their serological diagnostic criteria (see Characteristics ofincluded studies). They were randomly allocated to either doxycycline (n = 66) or tetracycline (n= 50) groups, and followed up for 4 weeks. The outcomes measured by the researchers werefailure of treatment and relapse.

Watt 2000 enrolled 126 adult participants in Thailand who were diagnosed with mildscrub typhus. They were randomly assigned to receive either doxycycline, rifampicin, or combinedregimen of rifampicin and doxycycline. During the first year of the study there were a number ofparticipants in one arm of the study who had protracted fever more frequently than the others.This leaded the researchers to perform an interim analysis. The fever clearance time wassignificantly different between the three treatment groups: 88 h (n = 8); 35 h (n = 5); and 24 h (n= 9). They decided to break the code of the group with the 88 h and found that it was acombination group. This regimen was discontinued and participants subsequently recruited tothis group were assigned high dose rifampicin (900 mg/day). During the study, the authorsexcluded participants with adverse treatment effects and those who had illness other than scrubtyphus. In their analysis, the participants who had no serological evidence of infection wereexcluded. This left 78 participants (doxycycline n = 28; standard rifampicin dose n = 26 and highrifampicin dose n = 24). The outcomes measured were duration of fever, participants febrile at 48hours, relapse, and side effects.Methodological quality

See: Table of included studiesThe method of random allocation was not clear in Sheehy 1973. The diagnosis of

scrub typhus was based on clinical criteria, and only 19/60 participants were tested using theWeil-Felix test with Proteus OX-K agglutinins. This test was the only one available at this time, butis not specific for the disease. While all participants received drugs for at least 3 days, the totallength of treatment was decided by clinicians and not reported. All participants were followed upfor 3 weeks. The random allocation was not clear in Brown 1978, but entry criteria were morerigorously applied. The authors excluded a large proportion of participants who did not haveserological evidence of scrub typhus. Clinicians also had discretion to alter treatment after 48hours if there was no clinical improvement.

In Song 1995, 129 adult participants were enrolled. They were allocated at random bycomputer generated numbers, but allocation was not concealed. In total, 76/129 met thediagnostic laboratory criteria. Both groups were similar in relation to severity of disease andclinical manifestations. All participants were followed up for 4 weeks.

The method of random allocation and concealment was not clear in Watt 2000. Thediagnosis of scrub typhus was based on clinical criteria and positive serological dipstick test.After enrolment, a large number of participants were excluded. The protocol was changed duringthe first year of the study. One intervention group was discontinued and replaced with the othernew treatment group. These factors meant the number of participants completing the study ineach treatment group was small.

An intention-to-treat analysis was not possible in any of the studies.Results

List of comparisons Tables of other data Additional tables

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One trial compared tetracycline with chloramphenicol (Sheehy 1973). In eachtreatment group, 1/30 participants were febrile after 48 hours (Relative Risk 1.00; 95% confidenceinterval 0.07 to 15.26). Mean duration of fever was 28 hours (range 14 to 68 hours) in thetetracycline group, and 35 hours (range 16 to 94 hours) in the chloramphenicol group. Theauthors did not report the standard deviation or any statistical tests performed on the durationof fever data. Relapse was reported in 2/30 participants in the tetracycline group and in 5/30 in thechloramphenicol group (Relative Risk 0.40; 95% confidence interval 0.08 to 1.90).

Two trials compared doxycycline with tetracycline (Brown 1978, Song 1995). In Brown1978, 3/31 participants in the doxycycline group and 5/24 in the tetracycline group, remainedfebrile at 48 hours (Relative Risk 0.46; 95% confidence interval 0.12 to 1.75). Relapse was notreported in either group. Song 1995 reported treatment failure in 4/66 participants in thedoxycycline group and 0/50 in the tetracycline group (Relative Risk 6.85; 95% confidence interval0.38 to 124.38). The length of fever between the two treatment groups was similar 34.0 (standarddeviation 26.5) hours compared to 37.0 (standard deviation 26.6) hours, respectively, but notstatistically significantly different. No relapses were reported in either study over the 3 to 4 weekfollow-up period. One trial compared doxycycline and rifampicin (Watt 2000). A lower proportionof participants remained febrile after 48 hours in the rifampicin group (11/50) compared to thedoxycycline group (15/28) (Relative Risk 0.41; 95% confidence interval 0.22 to 0.77). This resultwas calculated by combining the standard and high dose rifampicin groups. There was nostatistically significant difference of effect on participants being febrile after 48 hours betweenhigh rifampicin dose and standard rifampicin dose (Relative Risk 0.90; 95% confidence interval0.32 to 2.58). The median fever clearance time in doxycycline group was 52 hours (range 4 to108) compared to 27.5 hours (range 4 to 84) in the standard rifampicin group, and 22.5 hours (3to 76) in high rifampicin group (P = 0.01). Relapse was reported only in a doxycycline group (2/28) over a one month period of follow up. Mild gastrointestinal symptoms were common in allgroups (50% in doxycycline group; 31% in standard rifampicin group and 43% in high rifampicingroup).

No trials reported death and serious complications.Discussion

There are few trials in this area. The diagnostic criteria for scrub typhus in Sheehy1973 study was based on mostly clinical features, so it is not clear how many participantsactually had scrub typhus. The other two trials (Brown 1978 and Song 1995) had more strictlaboratory diagnostic criteria, although the Weil-Felix test with Proteus OX-K is relativelyinsensitive. In Watt 2000, a serological dipstick test was used to screen mild scrub typhus forenrollment. The researchers then conducted a separate test to confirm the diagnosis. This led tosome participants being excluded from the study after randomization.

The uncertainty around diagnosis causes problems in clinical decision making, as wellas in evaluating antibiotics. It appears in these studies participants with other infectious diseaseswere excluded, increasing the certainty of the diagnosis, but this remains a problem until bettertests are more widely available.

Unfortunately the studies included in this review did not use intention-to-treatanalysis, which may influence effect estimates. In addition, the concealment of allocation waspoorly reported, and studies were small.

The role of previous exposure to the disease on clinical manifestations and severityhas been poorly studied. Thus it is not clear whether antibiotic regimens should be moreaggressive in people visiting endemic areas and subsequently developing the disease.

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Reviewersû conclusionsImplications for practice

At present, there is insufficient evidence from trials of comparative effects of differentbroad spectrum antibiotics.

Doxycycline and tetracycline are similar drugs, both have been used to treat thiscondition, and both appeared to cure the small number of patients studied.

Rifampicin seem to be more effective than doxycycline in areas where scrub typhusappears to respond poorly to standard anti-rickettsial drugs.Clinicians should monitor the progress of patients in the light of reports of drug resistance.Implications for research

Further research is required to evaluate antibiotics. Trials would be more easily intepretedif reliable diagnostic tests were available. Such research could examine whether a single dose ofdoxycycline is as effective as a three to five day course of treatment.

Regimens for severe disease need to be evaluated, for example, comparingintravenous chloramphenicol with intravenous tetracycline.

Studies are also needed to evaluate alternative antibiotics (eg, azithromycin andciprofloxacin), particularly in areas where scrub typhus appears to respond poorly to standardanti-rickettsial drugs.Acknowledgements

We wish to thank Prof Virat Sirisanthana, Dr George Watt, and Dr George Wyatt fortheir advice and comments.

This review was supported by grants from the Department for International Development(UK) and the European Union DG XII.

The authors take sole responsibility for the data presented and the views expressed.Potential conflict of interest

We certify that we have no affiliations with or involvement in any organisation or entitywith a direct financial interest in the subject matter of the review (e.g. employment, consultancy,stock ownership, honoraria, expert testimony).NotesREVIEW HISTORY (started 4 March 2002)

4 March 2002: Updated review received by editorial base. This includes a new trial(Watt 2000), and responses to comments from Assistant Editor and statistician: (1) slight changeoutcomes changed from çNumber and seriousness of side effectsé to çNumber of adverseeventsé; Relative Risk used for binary outcomes (previously Peto odds ratio).References to studies included in this review Brown GW, Saunders JP, Singh SL, Haxsoll DL, Shirai A. Single dose doxycycline therapy for

scrub typhus. Transactions of the Royal Society Tropical Medicine and Hygiene1978;72(4):413-6.

Sheehy TW. Tetracycline therapy for scrub typhus. Alabama Journal of Medical Sciences1971;8(1):75-81.

Sheehy TW, Hazlett AD, Turk RE. Scrub typhus: A comparison of chloramphenical andtetracycline in its treatment. Archives of Internal Medicine 1973;132:77-80.

Song JH, Lee C, Chang LW, Choi SW, Choi JE, Kim YS, et al. Short-course doxycyclinetreatment versus conventional tetra cycline therapy for scrub typhus: A multiplerandomized trial. Clinical Infectious Diseases 1995;21:506-10.

Watt G, Kantipong P, Jongsakul K, Watcharapichat P, Phulsuksombati D, Strickman D.Doxycycline and rifampicin for mild scrub typhus infections in northern Thailand:a randomised trial. Lancet 2000;356:1057-61.

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References to studies excluded from this review Olson JG, Bourgeois AL, Fang RCY, Coolbaugh JC, Dennes DT. Prevention of scrub typhus:

prophylactic administration of doxycycline in a randomized double blind trial. Journalof Tropical Medicine and Hygiene 1980;29(5):989-97.

Twartz JC, Selvarju SG, Saunders JP, Huxsoll DL, Groves MG. Doxycycline prophylaxis forhuman scrub typhus. Journal of Infectious Diseases 1982;146(6):811-8.

Additional references Berman ST, Kundin WD. Scrub typhus in South Vietnam: a study of 87 cases. Annals of

Internal Medicine 1973;79:26-30. Brown GW, Robinson DM, Huxsoll DL. Scrub typhus: a common cause of illness in indigenous

populations. Transactions of the Royal Society of Tropical Medicine and Hygiene 1976;70:516:444-8. Chanyasanha C, Kaeburong K, Chenchittikul M, Sujirarat D. Seroprevalence of scrub typhus

infection in patients with pyrexia at some malaria clinics in three western provinces inThailand. Asian Pacific Journal of Allergy and Immunology 1998;16(2-3):119-25.

Clarke M, Oxman AD, editors. Optimal search strategy. Cochrane Reviewersû Handbook 4.1[updated June 2000]; Appendix 5c. In: The Cochrane Library [database on disk andCDROM]. The Cochrane Collaboration. Oxford: Update Software; 2001, issue 2.

Deller JJ, Russell PK. An analysis of fever of unknown origin in American soldiers in Vietnam.Annals of Internal Medicine 1967;66:1129-43.

Jagar C, Schwartz RA. Scrub typhus. eMedicine Journal 2001;2(11). Mcdonald JC, MacLean JD, McDade JE. Imported rickettsial disease: clinical and

epidemiologic features. American Journal of Medicine 1988;85:799-805. Silpapojakul K. Scrub typhus in the western Pacific Regian.Annals of the Academy of Medicine,

Singapore 1997;26:794-800. Sirisanthana V, Poneprasert B. Scrub typhus in children at Chiang Mai University Hospital.

Journal of Infectious Disease and Antimicrobial Agents 1989;6(1):22-7. Smadel JE, Traub R, Frick LP, Dierck FH, Bailey CA. Chloram phenicol (chloromycetin) in the

chemoprophylaxis of scrub typhus (Tsutsugamushi disease). American Journal ofHygiene 1950;51:216-28.

Strickman D, Sheer T, Salata K, Hershey J, Dasch G, Kelly D, et al. In vitro effectiveness ofazithromycin against doxycycline resistant and susceptible strains of Rickettsia tsutsugamushi, etiologic agent of scrub typhus. Antimicrobial Agents and Chemotherapy. 1995;2406-10.

Suntharasaj T, Janjindamai W, Krisanapan S. Pregnancy with scrub typhus and verticaltransmission: a case report. Journal of Obstetric and Gynaecology Research1997;23(1):75-8.

Supparatpinyo K, Horsin P, Hirunsri P. Scrub typhus: Single oral doxycycline therapy in mildto moderately severe cases. Journal of Infectious Disease and Antimicrobial Agents1990;7(3):135-37.

Wang CL, Yand KD, Cheng SN, Chu ML. Neonatal scrub typhus: a case report. Pediatrics1992;89:965-8.

Watt G, Strickman D. Life-threatening scrub typhus in a traveller returning from Thailand. ClinicalInfectious Diseases 1994;18:624-6.

Watt G, Chouriyagune C, Ruangweerayud T, Watcharapichat P, Phulsuksombati D, JongasakulK, et al. Scrub typhus infections poorly responsive to antibiotics in northern Thailand.Lancet 1996;348:86-9.

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