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Multicenter Study
. 2012 Jul 1;118(13):3377-86.
doi: 10.1002/cncr.26646. Epub 2011 Nov 9.

Predicting the risk of chemotherapy toxicity in older patients: the Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) score

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Free article
Multicenter Study

Predicting the risk of chemotherapy toxicity in older patients: the Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) score

Martine Extermann et al. Cancer. .
Free article

Abstract

Background: Tools are lacking to assess the individual risk of severe toxicity from chemotherapy. Such tools would be especially useful for older patients, who vary considerably in terms of health status and functional reserve.

Methods: The authors conducted a prospective, multicentric study of patients aged ≥70 years who were starting chemotherapy. Grade 4 hematologic (H) or grade 3/4 nonhematologic (NH) toxicity according to version 3.0 of the Common Terminology Criteria for Adverse Events was defined as severe. Twenty-four parameters were assessed. Toxicity of the regimen (Chemotox) was adjusted using an index to estimate the average per-patient risk of chemotherapy toxicity (the MAX2 index). In total, 562 patients were accrued, and 518 patients were evaluable and were split randomly (2:1 ratio) into a derivation cohort and a validation cohort.

Results: Severe toxicity was observed in 64% of patients. The Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) score was constructed along 2 subscores: H toxicity and NH toxicity. Predictors of H toxicity were lymphocytes, aspartate aminotransferase level, Instrumental Activities of Daily Living score, lactate dehydrogenase level, diastolic blood pressure, and Chemotox. The best model included the 4 latter predictors (risk categories: low, 7%; medium-low, 23%; medium-high, 54%; and high, 100%, respectively; P(trend) < .001). Predictors of NH toxicity were hemoglobin, creatinine clearance, albumin, self-rated health, Eastern Cooperative Oncology Group performance, Mini-Mental Status score, Mini-Nutritional Assessment score, and Chemotox. The 4 latter predictors provided the best model (risk categories: 33%, 46%, 67%, and 93%, respectively; P(trend) < .001). The combined risk categories were 50%, 58%, 77%, and 79%, respectively; P(trend) < .001). Bootstrap internal validation and independent sample validation demonstrated stable risk categorization and P(trend) < .001.

Conclusions: The CRASH score distinguished several risk levels of severe toxicity. The split score discriminated better than the combined score. To the authors' knowledge, this is the first score systematically integrating both chemotherapy and patient risk for older patients and has a potential for future clinical application.

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