Evaluating a 4-marker signature of aggressive prostate cancer using time-dependent AUC

Abstract

Background: We previously identified a protein tumor signature of PTEN, SMAD4, SPP1, and CCND1 that, together with clinical features, was associated with lethal outcomes among prostate cancer patients. In the current study, we sought to validate the molecular model using time-dependent measures of AUC and predictive values for discriminating lethal from non-lethal prostate cancer.

Methods: Using data from the initial study, we fit survival models for men with prostate cancer who were participants in the Physicians' Health Study (PHS; n = 276). Based on these models, we generated prognostic risk scores in an independent population, the Health Professionals Follow-up Study (HPFS; n = 347) to evaluate external validity. In each cohort, men were followed prospectively from cancer diagnosis through 2011 for development of distant metastasis or cancer mortality. We measured protein tumor expression of PTEN, SMAD4, SPP1, and CCND1 on tissue microarrays.

Results: During a median of 11.9 and 14.3 years follow-up in the PHS and HPFS cohorts, 24 and 32 men (9%) developed lethal disease. When used as a prognostic factor in a new population, addition of the four markers to clinical variables did not improve discriminatory accuracy through 15 years of follow-up.

Conclusions: Although the four markers have been identified as key biological mediators in metastatic progression, they do not provide independent, long-term prognostic information beyond clinical factors when measured at diagnosis. This finding may underscore the broad heterogeneity in aggressive prostate tumors and highlight the challenges that may result from overfitting in discovery-based research.

Keywords: biomarker validation; prognostic biomarkers; prostate cancer.

Figure 1

Time-dependent AUC estimates through 15 years of follow-up when applying prognostic models built in the PHS cohort to the HPFS cohort. The shaded region provides a 95% confidence interval for the clinical factor model, while the dotted lines give a 95% interval for the model with clinical factors and the four markers.

Figure 2

Figure 3

Time-dependent AUC estimates through 15 years of follow-up when applying prognostic models built in the PHS cohort to the HPFS cohort among those men with non-missing PSA at diagnosis. PSA was included as a factor in both the clinical and marker models. The shaded region provides a 95% confidence interval for the clinical factor model, while the dotted lines give a 95% interval for the model with clinical factors and the four markers.