Critique of May 10, 2000 Report on the Yale Hemorrhagic Stroke Project (HSP) Brian L. Strom, M.D., M.P.H. Chair and Professor, Department of Biostatistics and Epidemiology Director, Center for Clinical Epidemiology and Biostatistics Professor of Biostatistics and Epidemiology, Professor of Medicine Professor of Pharmacology University of Pennsylvania School of Medicine Consultant, Whitehall-Robins Healthcare

Critique of May 10, 2000 Report on the Yale Hemorrhagic Stroke Project (HSP) Initiated due to spontaneous reports –Appropriate, because of severe limitations of spontaneous reports in evaluating cause Huge, ambitious study Thoughtfully designed Methodologically problematic –Chance –Confounding –Bias

Chance Marginal power: designed to detect OR=5.0 with a 1-tailed test Very small numbers of exposed cases = fragile results 3 (or 5) co-equal aims  alpha should be (0.01) Inconsistent results in subgroups by gender and indication, suggest chance as an explanation “Dose-response relationship” never tested statistically

Key Results-All PPA Not exposed Exposed CVA No CVA Adj OR = 1.49 (p>0.05)

Key Results-By Indication Not exposed Exposed CVA No CVA CVA Cough/Cold Appetite Suppressants 664 Adj OR = 1.23 (p>0.05)Adj OR = (p=0.013)

Key Results-Among Women Not exposed Exposed CVA No CVA CVA All PPA: First Use Appetite Suppressants 355 Adj OR = 3.13 (p=0.042)Adj OR = (p=0.011)

Confounding Controlled using conditional logistic regression, but sample size too small for valid modeling Better approach would have used stratification and/or exclusion

Misclassification Bias ?valid to combine subarachnoid hemorrhage and primary intracerebral hemorrhage?

Information Bias Valid drug histories always difficult to collect retrospectively Valid drug histories would be much harder to collect from stroke patients, resulting in unequal recall Great effort taken to collect good data, but validation procedure assures specificity, not sensitivity, and very few missed exposures in controls would eliminate association

Selection Bias Properly done case-control studies should be population-based Cases –not representative of the entire population, unlike controls: ?increased exposures –?completeness of identified –Only 41% of those identified, were enrolled Controls: –no info given on process and success of RDD

Conclusions Ambitious and well described Major risk of information bias and selection bias Underpowered  fragile, subject to change in results with even small errors At best, this study suggests the possibility of an association between use of this common drug and this very uncommon outcome. It does not prove it. This association remains uncertain.