Are we ready to predict late effects? A systematic review of clinically useful prediction models

Eur J Cancer. 2015 Apr;51(6):758-66. doi: 10.1016/j.ejca.2015.02.002. Epub 2015 Feb 27.

Abstract

Background: After completing treatment for cancer, survivors may experience late effects: consequences of treatment that persist or arise after a latent period.

Purpose: To identify and describe all models that predict the risk of late effects and could be used in clinical practice.

Data sources: We searched Medline through April 2014.

Study selection: Studies describing models that (1) predicted the absolute risk of a late effect present at least 1 year post-treatment, and (2) could be used in a clinical setting.

Data extraction: Three authors independently extracted data pertaining to patient characteristics, late effects, the prediction model and model evaluation.

Data synthesis: Across 14 studies identified for review, nine late effects were predicted: erectile dysfunction and urinary incontinence after prostate cancer; arm lymphoedema, psychological morbidity, cardiomyopathy or heart failure and cardiac event after breast cancer; swallowing dysfunction after head and neck cancer; breast cancer after Hodgkin lymphoma and thyroid cancer after childhood cancer. Of these, four late effects are persistent effects of treatment and five appear after a latent period. Two studies were externally validated. Six studies were designed to inform decisions about treatment rather than survivorship care. Nomograms were the most common clinical output.

Conclusion: Despite the call among survivorship experts for risk stratification, few published models are useful for risk-stratifying prevention, early detection or management of late effects. Few models address serious, modifiable late effects, limiting their utility. Cancer survivors would benefit from models focused on long-term, modifiable and serious late effects to inform the management of survivorship care.

Keywords: Decision support techniques; Neoplasms; Risk; Secondary prevention; Survivors.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review

MeSH terms

  • Decision Support Techniques
  • Humans
  • Models, Statistical*
  • Neoplasms / mortality
  • Neoplasms / physiopathology*
  • Survivors