Statistical approaches using longitudinal biomarkers for disease early detection: A comparison of methodologies

TL;DR

This study compares statistical models for early disease detection using longitudinal biomarkers, demonstrating that the pattern mixture model (PMM) generally outperforms other methods like SREM and ROCA in predicting ovarian cancer.

Contribution

The paper provides a comparative analysis of SREM, PMM, and ROCA for early detection of ovarian cancer using longitudinal biomarkers, highlighting the superior performance of PMM.

Findings

PMM outperforms SREM and ROCA in ovarian cancer prediction.

Simulation studies favor PMM unless biomarkers are very frequently measured.

Biomarker CA-125 improves early detection performance.

Abstract

Early detection of clinical outcomes such as cancer may be predicted based on longitudinal biomarker measurements. Tracking longitudinal biomarkers as a way to identify early disease onset may help to reduce mortality from diseases like ovarian cancer that are more treatable if detected early. Two general frameworks for disease risk prediction, the shared random effects model (SREM) and the pattern mixture model (PMM) could be used to assess longitudinal biomarkers on disease early detection. In this paper, we studied the predictive performances of SREM and PMM on disease early detection through an application to ovarian cancer, where early detection using the risk of ovarian cancer algorithm (ROCA) has been evaluated. Comparisons of the above three methods were performed via the analyses of the ovarian cancer data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial and extensive simulation studies. The time-dependent receiving operating characteristic (ROC) curve and its area (AUC) were used to evaluate the prediction accuracy. The out-of-sample predictive performance was calculated using leave-one-out cross-validation (LOOCV), aiming to minimize the problem of model over-fitting. A careful analysis of the use of the biomarker cancer antigen 125 for ovarian cancer early detection showed improved performance of PMM as compared with SREM and ROCA. More generally, simulation studies showed that PMM outperforms ROCA unless biomarkers are taken at very frequent screening settings.