Therapy-Related-Myeloid-Neoplasm-Risk score (TMNRS): a convenient score for tMN risk assessment in adult cancer patients.

IF 4.1 Q2 ONCOLOGY
Abhay Singh, Megan M Herr, Rahul Mishra, Rusina Karia, Theresa Hahn, Swapna Thota
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引用次数: 0

Abstract

Background: A prediction model for estimating risk of therapy-related myeloid neoplasms (tMN), a late effect with a high mortality after chemotherapy and/or radiation, is currently unavailable. Ability to predict risk at initial cancer presentation can be key for early detection and risk mitigation.

Methods: Using SEER-Medicare linked database, 970,390 adults diagnosed with first primary cancer from 2000-2011 (with follow-up through 2015) were selected. The sample was divided into training (n = 582,234) and validation cohorts (n = 388,156). Various tMN risk factors were utilized for the development of tMN prediction model: The Therapy-Related Myeloid Neoplasm Risk Score (TMNRS). TMNRS was created as a simple arithmetic sum of independent predictors of tMN weighted according to the adjusted hazard ratio from the Cox proportional hazards analysis.

Results: In addition to the known risk factors of chemotherapy and radiation exposure, history of autoimmune disease and G-CSF exposure emerged as consistent predictors of tMN after each of the five cancers in the study. Cancer survivors were categorized into distinct risk groups with variable risk of tMN.

Conclusion: TMNRS provides a simple and convenient office-based mechanism to identify solid cancer patients at variable risks of tMN development. This risk assessment tool provides preliminary insights that may contribute to future research on the management of patients, particularly those receiving adjuvant therapies. Further investigation is required to fully evaluate its clinical utility and potential effects on patient care.

治疗相关髓系肿瘤风险评分(TMNRS):用于成人癌症患者tMN风险评估的便捷评分。
背景:治疗相关性髓系肿瘤(tMN)是一种化疗和/或放疗后死亡率高的晚期效应,目前尚无预测其风险的模型。在癌症最初表现时预测风险的能力是早期发现和降低风险的关键。方法:使用SEER-Medicare关联数据库,选择2000-2011年(随访至2015年)确诊为原发性癌症的970390名成年人。样本分为训练组(n = 582,234)和验证组(n = 388,156)。利用各种tMN危险因素建立tMN预测模型:治疗相关髓系肿瘤风险评分(the Therapy-Related Myeloid tumour risk Score, TMNRS)。TMNRS是根据Cox比例风险分析中调整后的风险比加权的tMN独立预测因子的简单算术和。结果:除了已知的化疗和放射暴露的危险因素外,自身免疫性疾病史和G-CSF暴露成为研究中五种癌症后tMN的一致预测因素。癌症幸存者被分为不同的危险组,具有不同的tMN风险。结论:TMNRS提供了一种简单方便的基于办公室的机制来识别具有tMN发展可变风险的实体癌患者。这种风险评估工具提供了初步的见解,可能有助于未来对患者管理的研究,特别是那些接受辅助治疗的患者。需要进一步的研究来充分评估其临床应用和对病人护理的潜在影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JNCI Cancer Spectrum
JNCI Cancer Spectrum Medicine-Oncology
CiteScore
7.70
自引率
0.00%
发文量
80
审稿时长
18 weeks
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