Estimating lead-time bias in lung cancer diagnosis of patients with prior cancers

• Activity Number: 299 - Survival and Recurrent Events in Epidemiology
• Type: Contributed
• Date/Time: Tuesday, August 1, 2017 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Zhiyun Ge* and Daniel F. Heitjan and Sandi Pruitt and Lei Xuan and David Gerber
• Companies: Southern Methodist University & University of Texas Southwestern Medical Center and Southern Methodist University and University of Texas Southwestern Medical Center and University of Texas Southwestern Medical Center and University of Texas Southwestern Medical Center
• Keywords: lead time ; prior cancer ; lung cancer ; sensitivity analysis

Abstract

Surprisingly, the duration of survival from the time of a lung cancer diagnosis has been found to be longer for prior cancer survivors than for those with no prior cancer. A possible explanation is lead-time bias, which confers an extension of the survival on those with prior cancer diagnoses. We propose a discrete semiparametric model to jointly describe survival in both no-prior-cancer group and prior-cancer group. We model the lead time with a negative binomial distribution and the post-lead-time survival with a linear spline on the logit hazard scale, which allows for survival to differ between prior-cancer groups even in the absence of bias. We fit the model to data from the SEER-Medicare linked data set, conducting a sensitivity analysis to assess the potential effects of lead-time bias on estimates of the survival difference between groups. With lung-cancer death as the endpoint, mean lead time is estimated as roughly 9 months for stage I&II patients. For patients with higher-stage lung cancers, the lead-time bias is on the order of one month or less. Even accounting for lead-time bias, there are modest but statistically significant survival differences between the groups.