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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
The need for double-sampling designs in survival studies: an application to monitor PEPFAR
Ming-Wen An1, Constantine E Frangakis, Beverly S Musick
1Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland 21205, USA. man@jhsph.edu
Abstract:
In 2007, there were 33.2 million people around the world living with HIV/AIDS (UNAIDS/WHO, 2007). In May 2003, the U.S. President announced a global program, known as the President's Emergency Plan for AIDS Relief (PEPFAR), to address this epidemic. We seek to estimate patient mortality in PEPFAR in an effort to monitor and evaluate this program. This effort, however, is hampered by loss to follow-up that occurs at very high rates. As a consequence, standard survival data and analysis on observed nondropout data are generally biased, and provide no objective evidence to correct the potential bias. In this article, we apply double-sampling designs and methodology to PEPFAR data, and we obtain substantially different and more plausible estimates compared with standard methods (1-year mortality estimate of 9.6% compared to 1.7%). The results indicate that a double-sampling design is critical in providing objective evidence of possible nonignorable dropout and, thus, in obtaining accurate data in PEPFAR. Moreover, we show the need for appropriate analysis methods coupled with double-sampling designs.
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