Comparing Treatments in the Presence of Competing Risks Based on Life Years Lost

Theodore Karrison () and James Dignam
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Theodore Karrison: University of Chicago and NRG Oncology
James Dignam: University of Chicago and NRG Oncology

2019 Stata Conference from Stata Users Group

Abstract: Competing risks are frequently encountered in medical research. Examples are clinical trials in head-and-neck and prostate cancer where deaths from cancer and deaths from other causes are competing risks. Andersen (Stat in Med, 2013) showed that the area under the cause j cumulative incidence curve from 0 to t* can be interpreted as the number of life years lost (LYL) due to cause j before time t*. LYL can be estimated and compared in Stata using either the pseudo-observations approach described in Overgaard, Andersen, and Parner (Stata Journal, 2015) or by modification of a routine by Pepe and Mori (Stat in Med, 1993) for testing the equality of cumulative incidence curves. We describe an application of the method to the DeCIDE trial, a phase III randomized clinical trial of induction chemotherapy plus chemoradiotherapy vs. chemoradiotherapy alone in patients with locally advanced head-and-neck cancer. We present simulation results demonstrating that the pseudo-observations and Pepe-Mori approaches yield similar results. We also evaluate the power obtained from comparing life years lost relative to standard procedures for analyzing competing risks data, including cause-specific logrank tests (Freidlin and Korn; Stat in Med, 2005) and the Fine-Gray model (Fine and Gray; JASA, 1999).

Date: 2019-08-02
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