Measuring the Impact of New Risk Factors Within Survival Models

TL;DR

This paper introduces a projection-based method to evaluate the impact of new biomarkers on survival model discrimination, addressing issues with traditional model comparison in metastatic prostate cancer prognosis.

Contribution

It proposes a novel projection-based approach for assessing biomarker effects on survival models, overcoming scale-transformation model limitations.

Findings

New biomarkers influence model discrimination

Method justifies biomarker inclusion in risk models

Hunt for better models continues

Abstract

Survival is poor for patients with metastatic cancer, and it is vital to examine new biomarkers that can improve patient prognostication and identify those who would benefit from more aggressive therapy. In metastatic prostate cancer, two new assays have become available: one that quantifies the number of cancer cells circulating in the peripheral blood, and the other a marker of the aggressiveness of the disease. It is critical to determine the magnitude of the effect of these biomarkers on the discrimination of a model-based risk score. To do so, most analysts frequently consider the discrimination of two separate survival models: one that includes both the new and standard factors and a second that includes the standard factors alone. However, this analysis is ultimately incorrect for many of the scale-transformation models ubiquitous in survival, as the reduced model is misspecified if the full model is specified correctly. To circumvent this issue, we developed a projection-based approach to estimate the impact of the two prostate cancer biomarkers. The results indicate that the new biomarkers can influence model discrimination and justify their inclusion in the risk model; however, the hunt remains for an applicable model to risk-stratify patients with metastatic prostate cancer.