A literature-based approach to evaluate the predictive capacity of a marker using time-dependent summary receiver operating characteristics

Stat Methods Med Res. 2016 Apr;25(2):674-85. doi: 10.1177/0962280212464542. Epub 2012 Nov 1.

Abstract

Meta-analyses are popular tools to summarize the results of publications. Prognostic performances of a marker are usually summarized by meta-analyses of survival curves or hazard ratios. These approaches may detect a difference in survival according to the marker but do not allow evaluation of its prognostic capacity. Time-dependent receiver operating characteristic curves evaluate the ability of a marker to predict time-to-event. In this article, we describe an adaptation of time-dependent summary receiver operating characteristic curves from published survival curves. To achieve this goal, we modeled the marker and the time-to-event distributions using non-linear mixed models. First, we applied this methodology to individual data in kidney transplantation presented as aggregated data, in order to validate the method. Second, we re-analyzed a published meta-analysis, which focused on the capacity of KI-67 to predict the overall survival of patients with breast cancer.

Keywords: Meta-analyses; prognostic marker; time-dependent ROC curve.

MeSH terms

  • Biomarkers / analysis*
  • Biomarkers, Tumor / analysis
  • Breast Neoplasms / diagnosis
  • Breast Neoplasms / metabolism
  • Breast Neoplasms / pathology
  • Humans
  • Ki-67 Antigen / analysis
  • Kidney Transplantation
  • Meta-Analysis as Topic
  • Prognosis
  • ROC Curve*
  • Survival Analysis

Substances

  • Biomarkers
  • Biomarkers, Tumor
  • Ki-67 Antigen