Cited by 598Frailty in Older AdultsNutrition and Health in AgingPharmaceutical Practices and Patient Outcomes

Validation of a prediction tool for chemotherapy toxicity in older adults with cancer

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Hurria, Arti, Mohile, Supriya, Gajra, Ajeet, Klepin, Heidi, Muss, Hyman, Chapman, Andrew, Feng, Tao, Smith, David +9 more·2016·Journal of Clinical Oncology

Abstract

Purpose: Older adults are at increased risk for chemotherapy toxicity, and standard oncology assessment measures cannot identify those at risk. A predictive model for chemotherapy toxicity was developed (N = 500) that consisted of geriatric assessment questions and other clinical variables. This study aims to externally validate this model in an independent cohort (N = 250). Patients and Methods: Patients age ≥ 65 years with a solid tumor, fluent in English, and who were scheduled to receive a new chemotherapy regimen were recruited from eight institutions. Risk of chemotherapy toxicity was calculated (low, medium, or high risk) on the basis of the prediction model before the start of chemotherapy. Chemotherapy-related toxicity was captured (grade 3 [hospitalization indicated], grade 4 [life threatening], and grade 5 [treatment-related death]). Validation of the prediction model was performed by calculating the area under the receiver-operating characteristic curve. Results: The study sample (N = 250) had a mean age of 73 years (range, 65 to 94 [standard deviation, 5.8]). More than one half of patients (58%) experienced grade ≥ 3 toxicity. Risk of toxicity increased with increasing risk score (36.7% low, 62.4% medium, 70.2% high risk; P < .001). The area under the curve of the receiver-operating characteristic curve was 0.65 (95% CI, 0.58 to 0.71), which was not statistically different from the development cohort (0.72; 95% CI, 0.68 to 0.77; P = .09). There was no association between Karnofsky Performance Status and chemotherapy toxicity (P = .25). Conclusion: This study externally validated a chemotherapy toxicity predictive model for older adults with cancer. This predictive model should be considered when discussing the risks and benefits of chemotherapy with older adults.

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Authors
Hurria, A., Mohile, S., Gajra, A., Klepin, H., Muss, H., Chapman, A., Feng, T., Smith, D., Sun, C.-L., De Glas, N., Cohen, H. J., Katheria, V., Doan, C., Zavala, L., Levi, A., Akiba, C., & Tew, W. P.
Affiliations
  • City Of Hope National Medical Center (US)
  • Arti Hurria, Tao Feng, David Smith, Can-Lan Sun, Vani Katheria, Caroline Doan, Laura Zavala, Abrahm Levi, and Chie Akiba, City of Hope Comprehensive Cancer Center and Beckman Research Institute, Duarte, CA; Supriya Mohile, University of Rochester Medical Center, Rochester; Ajeet Gajra, Upstate Medical University and Syracuse VA Medical Center, Syracuse; William P. Tew, Memorial Sloan Kettering Cancer Center, New York, NY; Heidi Klepin, Wake Forest University School of Medicine, Winston Salem; Hyman Muss,...
Corresponding author
Hurria, Arti
Venue
Journal of Clinical Oncology
Published
2016-07-10
Volume
34
Issue
20
Pages
2366-2371
ISSN
  • 0732-183X (ISSN-L)
  • 1527-7755
OpenAlex
W2398917392
Cited by
598
References
28
Citations by year
2026: 29 · 2025: 30 · 2024: 37 · 2023: 62 · 2022: 76 · 2021: 66 · 2020: 90 · 2019: 75 · 2018: 65 · 2017: 49 · 2016: 16 · 2015: 1
FWCI
39.09
Type
journal article
Language
en
Open access
Locations
  • Journal of Clinical Oncology (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health
  • National Institute on Aging (K23AG026749)
  • National Cancer Institute (UG1CA189961, P30CA008748, P30CA033572)
Topics
  • Health Sciences › Medicine › Geriatrics and Gerontology › Frailty in Older Adults
  • Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
  • Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
Keywords
chemotherapy toxicity, older adults, geriatric assessment, prediction model, external validation, solid tumors, risk stratification, Karnofsky performance status, non-relapse mortality, risk-benefit decision-making
MeSH terms
Aged, Antineoplastic Agents, Female, Humans, Male, Neoplasms, Geriatric Assessment

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