Methods for Handling Outcome Misclassification in Cancer Survival Analysis

Music City Center 

In epidemiological studies of cancer risk factors, the cancer subtype (i.e., fatal or nonfatal) is often determined by death at the end of the study, which is not always observed due to censoring before the end of the follow-up. There are five possible scenarios regarding the status of the cancer outcome: 1. censored before cancer diagnosis; 2. observed fatal cancer; 3. unobserved fatal cancer; 4. observed nonfatal cancer; 5. unobserved nonfatal cancer. In existing studies, for both scenario 3 and 5, the cancer status is considered as nonfatal cancer, leading to possible misclassification in the outcome status. In order to address the issue of outcome subtype misclassification due to censoring in the post-cancer-diagnosis survival data, we propose a weighted partial likelihood method for estimating the parameters in the cause-specific Cox proportional hazard models. In a simulation study, we compare the relative bias and efficiency of our proposed method and the existing method that ignores the potential misclassification issue. We illustrate the statistical method using a fatal cancer example in an ongoing cohort study.

fatal cancer

survival analysis

censoring

outcome misclassification 

Section on Statistics in Epidemiology