Unknown

Dataset Information

0

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


ABSTRACT: After completing treatment for cancer, survivors may experience late effects: consequences of treatment that persist or arise after a latent period.To identify and describe all models that predict the risk of late effects and could be used in clinical practice.We searched Medline through April 2014.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.Three authors independently extracted data pertaining to patient characteristics, late effects, the prediction model and model evaluation.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.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.

SUBMITTER: Salz T 

PROVIDER: S-EPMC4518853 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Salz Talya T   Baxi Shrujal S SS   Raghunathan Nirupa N   Onstad Erin E EE   Freedman Andrew N AN   Moskowitz Chaya S CS   Dalton Susanne Oksbjerg SO   Goodman Karyn A KA   Johansen Christoffer C   Matasar Matthew J MJ   de Nully Brown Peter P   Oeffinger Kevin C KC   Vickers Andrew J AJ  

European journal of cancer (Oxford, England : 1990) 20150227 6


<h4>Background</h4>After completing treatment for cancer, survivors may experience late effects: consequences of treatment that persist or arise after a latent period.<h4>Purpose</h4>To identify and describe all models that predict the risk of late effects and could be used in clinical practice.<h4>Data sources</h4>We searched Medline through April 2014.<h4>Study selection</h4>Studies describing models that (1) predicted the absolute risk of a late effect present at least 1 year post-treatment,  ...[more]

Similar Datasets

| S-EPMC4219489 | biostudies-literature
| S-EPMC3702558 | biostudies-literature
| S-EPMC7746201 | biostudies-literature
| S-EPMC5608199 | biostudies-literature
| S-EPMC5931306 | biostudies-other
| S-EPMC4784870 | biostudies-literature
| S-EPMC8642244 | biostudies-literature
| S-EPMC7610622 | biostudies-literature
| S-EPMC10854942 | biostudies-literature
| S-EPMC3169543 | biostudies-literature