Analysing adverse events by time-to-event models: the CLEOPATRA study.
When analysing primary and secondary endpoints in a clinical trial with patients suffering from a chronic disease, statistical models for time-to-event data are commonly used and accepted. This is in contrast to the analysis of data on adverse events where often only a table with observed frequencies and corresponding test statistics is reported. An example is the recently published CLEOPATRA study where a three-drug regimen is compared with a two-drug regimen in patients with HER2-positive first-line metastatic breast cancer. Here, as described earlier, primary and secondary endpoints (progression-free and overall survival) are analysed using time-to-event models, whereas adverse events are summarized in a simple frequency table, although the duration of study treatment differs substantially. In this paper, we demonstrate the application of time-to-event models to first serious adverse events using the data of the CLEOPATRA study. This will cover the broad range between a simple incidence rate approach over survival and competing risks models (with death as a competing event) to multi-state models. We illustrate all approaches by means of graphical displays highlighting the temporal dynamics and compare the obtained results. For the CLEOPATRA study, the resulting hazard ratios are all in the same order of magnitude. But the use of time-to-event models provides valuable and additional information that would potentially be overlooked by only presenting incidence proportions. These models adequately address the temporal dynamics of serious adverse events as well as death of patients. Copyright © 2016 John Wiley & Sons, Ltd.
Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.|Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany.
Tanja
T
Proctor
Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
Martin
M
Schumacher
D061067:Antibodies, Monoclonal, Humanized / Q000009:adverse effects; D000970:Antineoplastic Agents / Q000009:adverse effects*; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000009:adverse effects; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000235:genetics / Q000401:mortality*; D004311:Double-Blind Method; D064420:Drug-Related Side Effects and Adverse Reactions / Q000175:diagnosis / Q000235:genetics / Q000401:mortality*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008962:Models, Theoretical; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000235:genetics; D015996:Survival Rate / Q000639:trends; D013997:Time Factors
D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents; D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human; C485206:pertuzumab
adverse events; competing risks; incidence rate; multi-state models; time-to-event