An alternative approach for the analysis of time-to-event and survival outcomes in pulmonary medicine

For many pulmonary illnesses, the time to an event, such as death, is of primary interest. Visually, the Kaplan-Meier survival curve is an essential tool to assess time-to-event data. However, summarizing the difference of a time-to-event outcome between study groups can be challenging. For example, although the log-rank test compares survival curves, this test does not provide an estimate of the effect of an exposure (i.e., treatment effect estimate). The Cox proportional hazards regression model does provide an effect estimate in terms of the hazard ratio (HR), defined as the ratio of two instantaneous rates of an event at any time during follow-up. However, without knowing the event rate in the reference group, the HR can be difficult to interpret and place into context. Further, a key assumption of the Cox proportional hazards model is that the HR is constant between study groups over time (i.e., the proportional hazards assumption). When this assumption is violated, a situation that is not uncommon, results can become distorted and misleading. Another common metric, the median survival time, requires sufficient follow-up for survival to be less than 50% to be estimated.

To illustrate the RMST approach, we examined unadjusted differences in survival in two cohorts of patients with pulmonary illnesses. These analyses were for illustrative purposes only and do not represent formal assessments of clinical hypotheses. The first sample included individuals in the London chronic obstructive pulmonary disease (COPD) cohort with moderate to very severe COPD, and we compared survival among those who chronically produced sputum with that among those who did not. The second sample included individuals who received a single lung transplant in the United States between 2005 and 2016 (after implementation of the lung allocation score in May 2005), using the United Network for Organ Sharing registry, and we compared posttransplant survival based on age at transplantation.

Health Resources and Services Administration