Adverse outcome analyses of observational data: assessing cardiovascular risk in HIV disease

Clinical decisions are ideally based on randomized trials but must often rely on observational data analyses, which are less straightforward and more influenced by methodology. The authors, from a series of expert roundtables convened by the Forum for Collaborative HIV Research on the use of observational studies to assess cardiovascular disease risk in human immunodeficiency virus infection, recommend that clinicians who review or interpret epidemiological publications consider 7 key statistical issues: (1) clear explanation of confounding and adjustment; (2) handling and impact of missing data; (3) consistency and clinical relevance of outcome measurements and covariate risk factors; (4) multivariate modeling techniques including time-dependent variables; (5) how multiple testing is addressed; (6) distinction between statistical and clinical significance; and (7) need for confirmation from independent databases. Recommendations to permit better understanding of potential methodological limitations include both responsible public access to de-identified source data, where permitted, and exploration of novel statistical methods.