TY - JOUR
T1 - Are we ready to predict late effects?
T2 - A systematic review of clinically useful prediction models
AU - Salz, Talya
AU - Baxi, Shrujal S
AU - Raghunathan, Nirupa
AU - Onstad, Erin E
AU - Freedman, Andrew N
AU - Moskowitz, Chaya S
AU - Dalton, Susanne Oksbjerg
AU - Goodman, Karyn A
AU - Johansen, Christoffer
AU - Matasar, Matthew J
AU - de Nully Brown, Peter
AU - Oeffinger, Kevin C
AU - Vickers, Andrew J
N1 - Copyright © 2015 Elsevier Ltd. All rights reserved.
PY - 2015/4
Y1 - 2015/4
N2 - 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.
AB - 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.
KW - Decision Support Techniques
KW - Humans
KW - Models, Statistical
KW - Neoplasms
KW - Survivors
U2 - 10.1016/j.ejca.2015.02.002
DO - 10.1016/j.ejca.2015.02.002
M3 - Review
C2 - 25736818
VL - 51
SP - 758
EP - 766
JO - European Journal of Cancer, Supplement
JF - European Journal of Cancer, Supplement
SN - 0959-8049
IS - 6
ER -