INTERPRETING TREATMENT DIFFERENCES WHEN PATIENTS DROP-OUT OF A CLINICAL-TRIAL

Clinical trials are the standard for identifying new drugs for the tre atment of disease, but results are dependent on patient compliance. Th e success of treatments for HIV disease in particular may be judged in part by their effect on immunologic, virologic, or clinical measures collected on patients at regular predefined intervals. If patients dro p out of a trial before study completion, the analysis of the repeated ly collected parameters needs to be undertaken and interpreted with ca re. The authors recommend using graphic techniques to assess the impac t of the missing data on the profiles of the parameters over time. To assess treatment differences, a variety of simple tests are proposed t hat allow different assumptions to be made regarding the reasons for t he incomplete data. A case study is presented providing an analysis of CD4 data from the Pediatric Aids Clinical Trials Group (PACTG) Protoc ol 051, in which only 52% of the patients completed the study while re maining on treatment; younger patients with lower CD4 counts were more likely to stop treatment earlier. This type of systematic missing dat a can lead to incorrect conclusions regarding different treatment effe cts on CD4 counts. With the data of PACTG 051, however, regardless of the methodology used, no treatment differences were found. Inconsisten t conclusions would have indicated the need for more sophisticated sta tistical techniques to adequately test for treatment differences.