Abstract
BackgroundThe evaluation of the proportional hazards (PH) assumption in survival analysis is an important issue when Hazard Ratio (HR) is chosen as summary measure. The aim is to assess the appropriateness of statistical methods based on the PH assumption in oncological trials.MethodsWe selected 58 randomised controlled trials comparing at least two pharmacological treatments with a time-to-event as primary endpoint in advanced non-small-cell lung cancer. Data from Kaplan–Meier curves were used to calculate the relative hazard at each time point and the Restricted Mean Survival Time (RMST). The PH assumption was assessed with a fixed-effect meta-regression.ResultsIn 19% of the trials, there was evidence of non-PH. Comparison of treatments with different mechanisms of action was associated (P = 0.006) with violation of the PH assumption. In all the superiority trials where non-PH was detected, the conclusions using the RMST corresponded to that based on the Cox model, although the magnitude of the effect given by the HR was systematically greater than the one from the RMST ratio.ConclusionAs drugs with new mechanisms of action are being increasingly employed, particular attention should be paid on the statistical methods used to compare different types of agents.
Highlights
In many clinical and observational studies, especially in oncology, the quantity of main interest is the length of time before an event occurs
Presentation:This work has been presented at the 2015 Italian Stata Users Group meeting in Florence on 12 November 2015
We focused on non-small cell lung cancer (NSCLC) since this is the most common cause of cancer deaths worldwide[18] and recent preclinical studies have improved the knowledge of the molecular mechanism governing the cancer cell, the majority of oncologic patients still do not benefit from new clinical therapy
Summary
In many clinical and observational studies, especially in oncology, the quantity of main interest is the length of time before an event occurs. Especially in phase III trials, the outcomes of interest are death, progression or relapse of the disease. In this setting, a time-to-event endpoint is used and survival analysis is performed to analyse the data. The evaluation of the proportional hazards (PH) assumption in survival analysis is an important issue when Hazard. Ratio (HR) is chosen as summary measure. The aim is to assess the appropriateness of statistical methods based on the PH assumption in oncological trials
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