A method for using real world data in breast cancer modeling

J Biomed Inform. 2016 Apr:60:385-94. doi: 10.1016/j.jbi.2016.01.017. Epub 2016 Feb 8.

Abstract

Objectives: Today, hospitals and other health care-related institutions are accumulating a growing bulk of real world clinical data. Such data offer new possibilities for the generation of disease models for the health economic evaluation. In this article, we propose a new approach to leverage cancer registry data for the development of Markov models. Records of breast cancer patients from a clinical cancer registry were used to construct a real world data driven disease model.

Methods: We describe a model generation process which maps database structures to disease state definitions based on medical expert knowledge. Software was programmed in Java to automatically derive a model structure and transition probabilities. We illustrate our method with the reconstruction of a published breast cancer reference model derived primarily from clinical study data. In doing so, we exported longitudinal patient data from a clinical cancer registry covering eight years. The patient cohort (n=892) comprised HER2-positive and HER2-negative women treated with or without Trastuzumab.

Results: The models generated with this method for the respective patient cohorts were comparable to the reference model in their structure and treatment effects. However, our computed disease models reflect a more detailed picture of the transition probabilities, especially for disease free survival and recurrence.

Conclusions: Our work presents an approach to extract Markov models semi-automatically using real world data from a clinical cancer registry. Health care decision makers may benefit from more realistic disease models to improve health care-related planning and actions based on their own data.

Keywords: Cancer registry; Disease model; Markov model; Real world data; Secondary use.

MeSH terms

  • Algorithms
  • Antineoplastic Agents / therapeutic use
  • Breast Neoplasms / drug therapy*
  • Breast Neoplasms / pathology
  • Cohort Studies
  • Cost-Benefit Analysis
  • Data Collection
  • Databases, Factual
  • Decision Making
  • Economics, Medical
  • Female
  • Humans
  • Markov Chains
  • Medical Informatics / methods*
  • Models, Statistical
  • Neoplasm Metastasis
  • Neoplasm Recurrence, Local
  • Probability
  • Registries
  • Trastuzumab / therapeutic use

Substances

  • Antineoplastic Agents
  • Trastuzumab