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

Talya Salz, Shrujal S Baxi, Nirupa Raghunathan, Erin E Onstad, Andrew N Freedman, Chaya S Moskowitz, Susanne Oksbjerg Dalton, Karyn A Goodman, Christoffer Johansen, Matthew J Matasar, Peter de Nully Brown, Kevin C Oeffinger, Andrew J Vickers

Research output: Contribution to journalReviewResearchpeer-review

21 Citations (Scopus)

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.

Original languageEnglish
JournalEuropean journal of cancer (Oxford, England : 1990)
Volume51
Issue number6
Pages (from-to)758-66
Number of pages9
ISSN0959-8049
DOIs
Publication statusPublished - Apr 2015

Keywords

  • Decision Support Techniques
  • Humans
  • Models, Statistical
  • Neoplasms
  • Survivors

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