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

doi:10.1016/j.ejca.2015.02.002

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

Department of Clinical Medicine

13 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 language	English
Journal	European journal of cancer (Oxford, England : 1990)
Volume	51
Issue number	6
Pages (from-to)	758-66
Number of pages	9
ISSN	0959-8049
DOIs	https://doi.org/10.1016/j.ejca.2015.02.002
Publication status	Published - Apr 2015

Keywords

Decision Support Techniques
Humans
Models, Statistical
Neoplasms
Survivors

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.ejca.2015.02.002

Cite this

Salz, T., Baxi, S. S., Raghunathan, N., Onstad, E. E., Freedman, A. N., Moskowitz, C. S., Dalton, S. O., Goodman, K. A., Johansen, C., Matasar, M. J., de Nully Brown, P., Oeffinger, K. C., & Vickers, A. J. (2015). Are we ready to predict late effects? A systematic review of clinically useful prediction models. European journal of cancer (Oxford, England : 1990), 51(6), 758-66. https://doi.org/10.1016/j.ejca.2015.02.002

Salz, T, Baxi, SS, Raghunathan, N, Onstad, EE, Freedman, AN, Moskowitz, CS, Dalton, SO, Goodman, KA, Johansen, C, Matasar, MJ, de Nully Brown, P, Oeffinger, KC & Vickers, AJ 2015, 'Are we ready to predict late effects? A systematic review of clinically useful prediction models', European journal of cancer (Oxford, England : 1990), vol. 51, no. 6, pp. 758-66. https://doi.org/10.1016/j.ejca.2015.02.002

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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, Humans, Models, Statistical, Neoplasms, Survivors",

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

year = "2015",

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doi = "10.1016/j.ejca.2015.02.002",

language = "English",

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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

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

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DO - 10.1016/j.ejca.2015.02.002

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SN - 0959-8049

VL - 51

SP - 758

EP - 766

JO - European Journal of Cancer, Supplement

JF - European Journal of Cancer, Supplement

IS - 6

ER -