CASP for case control studies

https://casp-uk.net/checklists/casp-case-control-study-checklist-fillable.pdf

1. Did the study address a clearly focused issue?

HINT: An issue can be ‘focused’ in terms of the population studied, whether the study tried to detect a beneficial or harmful effect, and the risk factors studied.

2. Did the authors use an appropriate method to answer their question?

HINT: Consider whether a case control study is an appropriate way of answering the question under the circumstances and whether it addresses the study question.

3. Were the cases recruited in an acceptable way?

HINT: Look for selection bias which might compromise the validity of the findings, such as whether the cases were defined precisely, representative of a defined population, selected through an established reliable system, incident or prevalent, and whether there was a sufficient number of cases selected.

4. Were the controls selected in an acceptable way?

HINT: Look for selection bias which might compromise the generalisability of the findings, such as whether the controls were representative of the defined population, matched, population-based or randomly selected, and whether there was a sufficient number of controls selected.

5. Was the exposure accurately measured to minimise bias?

HINT: Look for measurement, recall or classification bias, such as whether the exposure was clearly defined and accurately measured, whether subjective or objective measurements were used, and whether the measurement methods were similar in the cases and controls.

6. (a) Aside from the experimental intervention, were the groups treated equally?

HINT: List the ones you think might be important that the author may have missed, such as genetic, environmental, and socio-economic factors.

6. (b) Have the authors taken account of the potential confounding factors in the design and/or in their analysis?

HINT: Look for techniques such as restriction in design, and techniques such as modelling, stratified-, regression-, or sensitivity analysis to correct, control or adjust for confounding factors.

7. How large was the treatment effect?

HINT: Consider what the bottom line results are, whether the analysis is appropriate to the design, and how strong the association is between exposure and outcome.

8. How precise was the estimate of the treatment effect?

HINT: Consider the size of the p-value, size of the confidence intervals, and whether the authors considered all the important variables.

9. Do you believe the results?

HINT: Consider whether the results can be due to chance, bias, or confounding, whether the design and methods of the study are sufficiently flawed to make the results unreliable, and whether the results fit with other available evidence.

10. Can the results be applied to the local population?

HINT: Consider whether the subjects covered in the study could be sufficiently different from your population to cause concern, whether your local setting is likely to differ much from that of the study, and whether you can quantify the local benefits and harms.

11. Do the results of this study fit with other available evidence?

HINT: Consider all the available evidence from RCTs, systematic reviews, cohort studies, and case control studies for consistency.