CASP an evidence based approach in health and

CASP, an evidence based approach in health and social care, and its checklists 張哲浣報告

CASP, an evidence based approach in health and social care 整個CASP是一種包含EBM的方案 特色是在評讀方面 CASP 目標(for health and social care) ≧ an EBM program; 但策略類似, 特色使用的 checklists Ps: 是否可做為寫作的checklists?

何謂 CASP 為 Critical Appraisal Skills Programme 之 縮寫. Critical appraisal is the process of carefully and systematically examining research to judge its trustworthiness (可信賴), and its value (價� ) and relevance (關聯) in a particular context. 目的: 了解證據(Make sense of evidence).

CASP標準動作 Find Appraise (檢驗判斷) Act (做)

CASP 起源 CASP是由英國健保(ＮＨＳ)的公共衛生資源部門 所發展的文獻評讀 具，其中critical appraisal tools針對各種不同研究設計提供不 同的評讀表單資源 The Critical Appraisal Skills Programme (CASP) was developed in Oxford in 1993 and has since helped to develop an evidence based approach in health and social care, working with local, national and international partner organisations.

workshops and resources CASPs workshops and resources aim to help participants put knowledge into practice by learning how to 1. systematically formulate questions, 2. find research evidence, 3. appraise research evidence and 4. act on (照著. . . 做) what they find.

CASP─ Find, Appraise, Act The Critical Appraisal Skills Programme helps people acquire skills in making sense of scientific evidence about health care. This is because in order to make use of the best available evidence from scientific research, we need to be able to :

The CASP International Network (CASPin) A non-profit making organisation for people promoting skills in finding, critically appraising and acting on research evidence. CASPin has been an informal network since 1998, and members have developed similar critical appraisal skills programmes in Spain (CASPe), Hungary, Poland, Romania, Japan, Norway and India. Many individuals have organised CASP workshops in about 30 other countries, settings and audiences, particularly South America, and Central and Eastern Europe.

The Creative Commons License A set of eight critical appraisal tools to use when reading research, these include tools for Systematic Reviews. Randomised Controlled Trials, Cohort Studies, Case Control Studies, Economic Evaluations, Diagnostic Studies, Qualitative Studies and Clinical Prediction Rule. These are free to download and can be used by anyone under the Creative Commons License.

CASP八種checklists (討論前四項) CASP Randomised Controlled Trial CASP Systematic Review CASP Cohort Study CASP Case Control Study CASP Qualitative Research CASP Economic Evaluations CASP Diagnostic Test CASP Clinical Prediction Rule

Clinical trial-classifying clinical trials is by the way the researchers behave In an observational study, the investigators observe the subjects and measure their outcomes. The researchers do not actively manage the study in both the treatment and the assignment of subjects. In an interventional study, the investigators give the research subjects a particular medicine or other intervention. Usually, they compare the treated subjects to subjects who receive no treatment or standard treatment. Then the researchers measure how the subjects' health changes.

Observational study vs Experiment (randomized controlled trial) An observational study draws inferences about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator. This is in contrast with experiments, such as randomized controlled trials, where each subject is randomly assigned to a treated group or a control group.

Clinical trials─classified by their purpose Prevention trials Screening trials Diagnostic trials Treatment trials Quality of life trials (supportive care trials) Compassionate use trials or expanded access trials

Checklists 10 -12 questions to help you make sense of the studies. Critical appraisal幫助Systemic review之第四第 五步驟: 綜合分析及解讀

Three broad issues Are the results of the trial valid? (Section A) What are the results? (Section B) Will the results help locally? (Section C)

Screenging and detailed questions Screening─有關study design方面的問題 2 -3題; 之後會有圖示 "Is it worth continuing? " Or 若study design尚可接受, 才進入detailed critical appraisal.

A. Case control study

(A) Are the results of the study valid? 1 -6題

1. Did the study address a clearly focused issue? Yes Can’t tell No HINT: A question can be focused in terms of • The population studied • The risk factors studied • Whether the study tried to detect a beneficial or harmful effect?

2. Did the authors use an appropriate method to answer their question? Yes Can’t tell No HINT: Consider • Is a case control study an appropriate way of Answering the question under the circumstances? (Is the outcome rare or harmful) • Did it address the study question?

Is it worth continuing? or

3. Were the cases recruited in an acceptable way? Yes Can’t tell No HINT: We are looking for selection bias which might compromise validity of the findings • Are the cases defined precisely? • Were the cases representative of a defined population? (geographically and/or temporally? ) • Was there an established reliable system for selecting all the cases • Are they incident or prevalent? • Is there something special about the cases? • Is the time frame of the study relevant to disease/exposure? • Was there a sufficient number of cases selected? • Was there a power calculation?

4. Were the controls selected in an acceptable way? Yes Can’t tell No HINT: We are looking for selection bias which might compromise The generalisibilty of the findings • Were the controls representative of defined population (geographically and/or temporally) • Was there something special about the controls? • Was the non-response high? Could non-respondents be different in any way? • Are they matched, population based or randomly selected? • Was there a sufficient number of controls selected?

5. Was the exposure accurately measured to minimise bias? Yes Can’t tell No HINT: We are looking for measurement, recall or classification bias • Was the exposure clearly defined and accurately measured? • Did the authors use subjective or objective measurements? • Do the measures truly reflect what they are supposed to measure? (Have they been validated? ) • Were the measurement methods similar in the cases and controls? • Did the study incorporate blinding where feasible? • Is the temporal relation correct? (Does the exposure of interest precede the outcome? )

6. (a) What confounding factors have the authors accounted for? List: HINT: List the ones you think might be important, that The author missed. • Genetic • Environmental • Socio-economic

6. (b) Have the authors taken account of the potential confounding factors in the design and/or in their analysis? Yes Can’t tell No HINT: Look for • Restriction in design, and techniques e. g. modelling stratified-, regression-, or sensitivity analysis to correct, control or adjust for confounding factors

(B) What are the results? 7 -9題

7. What are the results of this study? HINT: Consider • What are the bottom line results? • Is the analysis appropriate to the design? • How strong is the association between exposure and outcome (look at the odds ratio)? • Are the results adjusted for confounding, and might confounding still explain the association? • Has adjustment made a big difference to the OR?

8. How precise are the results? How precise is the estimate of risk? HINT: Consider • Size of the P-value • Size of the confidence intervals • Have the authors considered all the important variables? • How was the effect of subjects refusing to participate evaluated?

9. Do you believe the results? Yes Can’t tell No HINT: Consider • Big effect is hard to ignore! • Can it be due to chance, bias or confounding? • Are the design and methods of this study sufficiently flawed to make the results unreliable? • Consider Bradford Hills criteria for causality (e. g. time sequence, dose-response gradient, strength, biological plausibility)

(C) Will the results help locally? 10 -11題

10. Can the results be applied to the local population? Yes Can’t tell No HINT: Consider whether • The subjects covered in the study could be sufficiently different from your population to cause concern • Your local setting is likely to differ much from that of the study • Can you quantify the local benefits and harms?

11. Do the results of this study fit with other available evidence? Yes Can’t tell No HINT: Consider all the available evidence from RCT’s, systematic reviews, cohort studies and case-control studies as well for consistency.

Remember One observational study rarely provides sufficiently robust evidence to recommend changes to clinical practice or within health policy decision making. However, for certain questions observational studies provide the only evidence. Recommendations from observational studies are always stronger when supported by other evidence.

B. RCT

(A) Are the results of the study valid? 1 -6題

1. Did the trial address a clearly focused issue? Yes Can’t tell No HINT: An issue can be ‘focused’ In terms of The population studied The intervention given The comparator given The outcomes considered

2. Was the assignment of patients to treatments randomised? Yes Can’t tell No HINT: Consider How was this carried out? Was the allocation sequence concealed from researchers and patients?

3. Were all of the patients who entered the trial properly accounted for at its Conclusion? Yes Can’t tell No HINT: Consider Was the trial stopped early? Were patients analysed in the groups to which they were randomised?

Is it worth continuing? or

4. Were patients, health workers and study personnel ‘blind’ to treatment? Yes Can’t tell No HINT: Think about Patients? Health workers? Study personnel?

5. Were the groups similar at the start of the trial? Yes Can’t tell No HINT: Look at Other factors that might affect the outcome such as age, sex, social class

6. Aside from the experimental intervention, were the groups treated equally? Yes Can’t tell No

(B) What are the results? 7 -8題

7. How large was the treatment effect? HINT: Consider What outcomes were measured? Is the primary outcome clearly specified? What results were found for each outcome?

8. How precise was the estimate of the treatment effect? HINT: Consider What are the confidence limits?

(C) Will the results help locally? 9 -11題

9. Can the results be applied in your context? (or to the local population? ) Yes Can’t tell No HINT: Consider whether Do you think that the patients covered by the trial are similar enough to the patients to whom you will apply this? , if not how to they differ?

10. Were all clinically important outcomes considered? Yes Can’t tell No HINT: Consider Is there other information you would like to have seen? If not, does this affect the decision?

11. Are the benefits worth the harms and costs? Yes Can’t tell No HINT: Consider Even if this is not addressed by the review, what do you think?

C. Systemic review

(A) Are the results of the review valid? 1 -5題

1. Did the review address a clearly focused question? Yes Can’t tell No HINT: An issue can be ‘focused’ In terms of • The population studied • The intervention given • The outcome considered

2. Did the authors look for the right type of papers? Yes Can’t tell No HINT: ‘The best sort of studies’ would • Address the reviews question • Have an appropriate study design (usually RCTs for papers evaluating interventions)

Is it worth continuing? or

3. Do you think the important, relevant studies were included? Yes Can’t tell No HINT: Look for • Which bibliographic databases were used • Follow up from reference lists • Personal contact with experts • Search for unpublished as well as published studies • Search for non-English language studies

4. Did the review’s authors do enough to assess the quality of the included studies? Yes Can’t tell No HINT: The authors need to consider the rigour (logical validity or accuracy? ) of the studies they have identified. Lack of rigour may affect the studies’ results. (“All that glisters is not gold” Merchant of Venice – Act II Scene? )

5. If the results of the review have been combined, was it reasonable to do so? Yes Can’t tell No HINT: Consider whether • The results were similar from study to study • The results of all the included studies are clearly displayed • The results of the different studies are similar • The reasons for any variations in results are discussed

(B) What are the results? 6 -7題

6. What are the overall results of the review? HINT: Consider • If you are clear about the review’s ‘bottom line’ results • What these are (numerically if appropriate) • How were the results expressed (NNT, odds ratio etc) *NNT: number needed to treat 益一 需治數

7. How precise are the results? HINT: Look at the confidence intervals, if given

(C) Will the results help locally? 8 -10題

8. Can the results be applied to the local population? Yes Can’t tell No HINT: Consider whether • The patients covered by the review could be sufficiently different to your population to cause concern • Your local setting is likely to differ much from that of the review

9. Were all important outcomes considered? Yes Can’t tell No HINT: Consider whether • Is there other information you would like to have seen

10. Are the benefits worth the harms and costs? Yes Can’t tell No HINT: Consider • Even if this is not addressed by the review, what do you think?

D. Cohort study

(A) Are the results of the study valid? 1 -6題

1. Did the study address a clearly focused issue? Yes Can’t tell No HINT: A question can be ‘focused’ In terms of • The population studied • The risk factors studied • The outcomes considered • Is it clear whether the study tried to detect a beneficial or harmful effect?

2. Was the cohort recruited in an acceptable way? Yes Can’t tell No HINT: Look for selection bias which might compromise the generalisibility of the findings: • Was the cohort representative of a defined population? • Was there something special about the cohort? • Was everybody included who should have been included?

Is it worth continuing? or

3. Was the exposure accurately measured to minimise bias? Yes Can’t tell No HINT: Look for measurement or classification bias: • Did they use subjective or objective measurements? • Do the measurements truly reflect what you want them to (have they been validated)? • Were all the subjects classified into exposure groups using the same procedure

4. Was the outcome accurately measured to minimise bias? Yes Can’t tell No HINT: Look for measurement or classification bias: • Did they use subjective or objective measurements? • Do the measures truly reflect what you want them to (have they been validated)? • Has a reliable system been established for detecting all the cases (for measuring disease occurrence)? • Were the measurement methods similar in the different groups? • Were the subjects and/or the outcome assessor blinded to exposure (does this matter)?

5. (a) Have the authors identified all important confounding factors? Yes Can’t tell No, List the ones you think might be important, that the author missed. (b) Have they taken account of the confounding factors in the design and/or analysis? Yes Can’t tell No, List: HINT: Look for restriction in design, and techniques e. g. modelling, stratified-, regression-, or sensitivity analysis to correct, control or adjust for confounding factors • Were the measurement methods similar in the cases and controls? • Did the study incorporate blinding where feasible? • Is the temporal relation correct? (Does the exposure of interest precede the outcome? )

6. (a) Was the follow up of subjects complete enough? Yes Can’t tell No (b) Was the follow up of subjects long enough? Yes Can’t tell No HINT: Consider • The good or bad effects should have had long enough to reveal themselves • The persons that are lost to follow-up may have different outcomes than those available for assessment • In an open or dynamic cohort, was there anything special about the outcome of the people leaving, or the exposure of the people entering the cohort?

(B) What are the results? 7 -9題

7. What are the results of this study? HINT: Consider • What are the bottom line results? • Have they reported the rate or the proportion between the exposed/unexposed, the ratio/the rate difference? • How strong is the association between exposure and outcome (RR, )? • What is the absolute risk reduction (ARR)?

8. How precise are the results? HINT: Look for the range of the confidence intervals, if given.

9. Do you believe the results? Yes Can’t tell No HINT: Consider • Big effect is hard to ignore! • Can it be due to bias, chance or confounding? • Are the design and methods of this study sufficiently flawed to make the results unreliable? • Bradford Hills criteria (e. g. time sequence, dose-response gradient, biological plausibility, consistency)

(C) Will the results help locally? 10 -12題

10. Can the results be applied to the local population? Yes Can’t tell No HINT: Consider whether • A cohort study was the appropriate method to answer this question • The subjects covered in this study could be sufficiently different from your population to cause concern • Your local setting is likely to differ much from that of the study • You can quantify the local benefits and harms

11. Do the results of this study fit with other available evidence? Yes Can’t tell No

12. What are the implications of this study for practice? HINT: Consider • One observational study rarely provides sufficiently robust evidence to recommend changes to clinical practice or within health policy decision making • For certain questions observational studies provide the only evidence • Recommendations from observational studies are always stronger when supported by other evidence

Process: an important field assessing quality in the Donabedian Model Include the execution of activity and the statistical analysis etc. Systemic error (or bias; influencing validity): technique problem, instrumental measuring procedure, sample collection procedure, or diagnostic procedure etc. Non responsive rate or responsive rate Analytic process: calculate including withdrawals or not; intent-to treat (ITT) vs. Per protocol

Bias A statistic is biased if it is calculated in such a way that is systematically different from the population parameter of interest.

Error and residual In statistics and optimization, statistical errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "theoretical value". The error of an observed value is the deviation of the observed value from the (unobservable) true function value, while the residual of an observed value is the difference between the observed value and the estimated function value.