An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

J. Liu, T. Lichtenberg, K. A. Hoadley, L. M. Poisson, A. J. Lazar, A. D. Cherniack, A. J. Kovatich, C. C. Benz, D. A. Levine, A. V. Lee, L. Omberg, D. M. Wolf, C. D. Shriver, V. Thorsson, Cancer Genome Atlas Research Network, H. Hu, M. (come contributors) Marino

Research output: Contribution to journalArticlepeer-review


For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale.
Original languageEnglish
Pages (from-to)400-416.e11
Issue number2
Publication statusPublished - Apr 5 2018
Externally publishedYes


  • Cox proportional hazards regression model
  • TCGA
  • The Cancer Genome Atlas
  • clinical data resource
  • disease-free interval
  • disease-specific survival
  • follow-up time
  • overall survival
  • progression-free interval
  • translational research


Dive into the research topics of 'An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics'. Together they form a unique fingerprint.

Cite this