Clinical Trials

Clinical Trials: A Practical Guide ■❚❙❘Figure 3. Examination of proportionality assumption: log–log survival plots for the two treatment groupsin the pancreatic cancer trial data.3Treatment A (new)Treatment B (standard)-In(-In[survival probability])210–10 6 12 18 24 30 36 42 48Time (months)ConclusionSurvival analysis is the study of the duration of time to the occurrence of eventoutcomes, and is a means of determining the influence of covariates on theoccurrence and timing of events. It is a set of techniques that utilize all of theinformation on survival time, including censored (or incomplete) data. KM curvesare a powerful way of showing data and visually displaying differences betweenthe study groups.We can test the data by looking at the event history of subjects, with respect totreatment, by using the log-rank test, and then extend the analysis further toestimate treatment effects by using the Cox proportional hazards model. Whenanalyzing and reporting clinical trials with time-to-event outcomes, it isrecommended that the treatment effect is given as the hazard ratio estimated bythe Cox proportional hazards model, unless the proportionality assumption isclearly violated, where alternative approaches may be necessary.251