Evidence-Based Practice Observational studies and more

1. Evidence-Based Practice Observational studies and more Dr Carl Heneghan BM, Bch MA, MRCGP Clinical Lecturer, University of Oxford Deputy Director CEBM

2. Qualitative Understanding Interview/observation Discovering frameworks Textual (words) Theory generating Quality of informant more important than sample size Subjective Embedded knowledge Models of analysis: fidelity to text or words of interviewees Quantitative Prediction Survey/questionnaires Existing frameworks Numerical Theory testing (experimental) Sample size core issue in reliability of data Objective Public Model of analysis: parametric, non-parametric Comparison

3. THE LANCET 2002;359:57- 61 Basic principles of study design

4. Quantitative designs • Observational: studies that do not involve any intervention or experiment. • Experimental: studies that entail manipulation of the study factor (exposure) and randomization of subjects to treatment (exposure) groups

5. Observational Designs • Exploratory: used when the state of knowledge about the phenomenon is poor: small scale; of limited duration. • Descriptive: used to formulate a certain hypothesis: small / large scale. Examples: case-studies; cross-sectional studies • Analytical: used to test hypotheses: small / large scale. Examples: case-control, cross-sectional, cohort.

8. Case reports

9. Case series: what to look for • The diagnosis (case definition) or, for mortality, the cause of death • The date when the disease or death occurred (time) • The place where the person lived, worked etc (place) • The characteristics of the population (person) • The opportunity to collect additional data from medical records (possibly by electronic data linkage) or the person directly • The size and characteristics of the population at risk

10. Analytical Studies

11. Comparison of the Characteristics of Cohort Study & Usually very expensive Complete source population denominator Can calculate incidence rates or risks and their differences and ratios Convenient for studying many diseases Case-Control Studies Usually less expensive Sampling from source population Can usually calculate only the ratio of incidence rates or risks Convenient for studying many exposures

12. Cohort Design disease Factor present no disease Study population free of disease disease Factor absent no disease present future time Study begins here

13. Kidlington • Kidlington & Yarnton Surgery Exeter Surgery City Centre Bartlemas Surgery 19 Beaumont St Berinsfield The Health Centre Abingdon Malthouse Surgery Marcham Rd Family Health Centre Abingdon Surgery Stert St Wantage Church St practice Nine general practices in Oxfordshire 91,075 patients

14. Menigitis Exposure Control group

15. Thompson et al. Clinical recognition of meningococcal disease in children and adolescents. Lancet. 2006 Feb 4;367(9508):397-403

16. Problem:adequate control group (matching) and recall bias. Because case-control studies lack denominators, incidence rates, relative risks or attributable risks cannot be calculated. Instead odds ratios are the measures of association.

17. Although easier to do, they are also easier to do wrong: • Define the criteria for diagnosis of a case and any eligibility criteria used for selection. • Controls should come from the same population as the cases, and their selection should be independent of the exposures of interest. • Blind the data gatherers to the case or control status of participants or, if impossible, at least blind them to the main hypothesis of the study. • Data gatherers need to be thoroughly trained to elicit exposure in a similar manner from cases and controls (memory aids) • Address confounding in case-control studies, either in the design stage or with analytical techniques.

18. Lancet 2002;349-248-253 Is selection bias present ? In a cohort study, are participants in the exposed and unex-posed groups similar in all important aspects except for the exposure ? In a case-control study, are cases and controls similar in all important aspects except for the disease in question ?

19. Is information bias present ? In a cohort study, is information about outcome obtained in the same way for those exposed and unexposed ? In a case-control study, is information about exposure gathered in the same way for cases and controls ? Is confounding present ? Could the results be accounted for by the presence of a factor e.g. age, smoking, inflammation, diet-associated with both the exposure and the outcome but not directly involved in the causal pathway ?

20. If the results cannot be explained by these three biases, could they be the result of chance ? What are the relative risk or odds ratio and 95% CI If the results still cannot be explained, then (and only then) might the findings be real and worthy of note !

21. Choose the right study design

22. Apply the results Studies need to have both internal and external validity: Results should be both correct and capable of extrapolation. A simple checklist for bias (selection, information, and confounding) can help readers decipher research reports.

24. Thank you