Measuring clinically significant chemotherapy-related toxicities using Medicare claims from Cancer and Leukemia Group B (CALGB) trial participants

利用癌症和白血病B组(CALGB)试验参与者的医疗保险索赔数据来衡量具有临床意义的化疗相关毒性

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Abstract

BACKGROUND: Because the elderly are underrepresented on clinical trials, physicians have few sources of information to estimate the risks (ie, toxicities) and benefits of chemotherapy administration to the elderly. OBJECTIVE: Our goal was to determine whether the standard measures of toxicity used in clinical trials could be captured from observational Medicare claims data. METHODS: We identified 175 elderly clinical trial patients treated on 2 Cancer and Leukemia Group B (CALGB) trials (9344, adjuvant breast study and 9730, advanced lung cancer study) and merged participants' CALGB data with their Medicare data. From CALGB data, we identified the most frequent Extended Clinical Toxicity Critieria grade III/IV toxicities. We reviewed diagnostic and procedure codes from Medicare manuals, developed algorithms to measure the toxicities, and then finalized the algorithms after empiric review of patients' codes. We compared results of Medicare algorithms to gold standard CALGB toxicity information to calculate test characteristics. RESULTS: CALGB data documented that 15 grade III/IV chemotherapy-related toxicities occurred in > or =3% of the 175 patients: white blood cell, hemoglobin, platelets, anorexia, nausea, vomiting, diarrhea, stomatitis, sensory neuropathy, motor neuropathy, motor or sensory neuropathy, dyspnea, hyperglycemia, infection, and malaise. Vomiting was the only toxicity identified by the Medicare-based algorithm with a sensitivity, specificity, and area under the receiver operator curve of > or =80%. CONCLUSIONS: The results of this preliminary study suggest that Medicare diagnostic and procedure codes may be of only limited value in measuring clinically significant chemotherapy-related toxicities in elderly Medicare beneficiaries. Future research includes confirming these findings in a larger and more diverse sample.

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