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Abstract：
Assessing frailty is integral to treatment decision-making for older adults with acute myeloid leukemia (AML). Prior electronic frailty indices (eFI) derive from an accumulated-deficit model and are associated with mortality in older primary care populations. We evaluated use of an embedded eFI in AML by describing baseline eFI categories by treatment type and exploring associations between eFI categories, survival, and treatment received.
This was a retrospective study of subjects ≥60 years old with new AML treated at an academic medical center from 1/2018-10/2020. The eFI requires ≥2 ambulatory visits over two years and uses demographics, vitals, ICD-10 codes, outpatient labs, and available functional information from Medicare Annual Wellness Visits. Frailty was defined as fit (eFI ≤ 0.10), pre-frail (0.10 < eFI ≤ 0.21), and frail (eFI > 0.21). Chemotherapy was intensive (anthracycline-based) or less-intensive (hypomethylating agent, low dose cytarabine +/- venetoclax). Therapy type, pre-treatment characteristics, and chemotherapy cycles were compared by eFI category using chi-square and Fisher\'s exact tests and ANOVA. Median survival was compared by eFI category using log-rank tests stratified by therapy type.
Among 166 older adults treated for AML (mean age 74 years, 61% male, 85% Caucasian), only 79 (48%) had a calculable eFI score before treatment. Of these, baseline eFI category was associated with treatment received (fit (n = 31): 68% intensive, 32% less intensive; pre-frail (n = 38): 37% intensive, 63% less intensive; frail (n = 10): 0% intensive, 100% less intensive; not calculable (n = 87): 48% intensive, 52% less-intensive; p < 0.01). The prevalence of congestive heart failure and secondary AML differed by frailty status (p < 0.01). Median survival did not differ between eFI categories for intensively (p = 0.48) or less-intensively (p = 0.09) treated patients. For those with less-intensive therapy who lived ≥6 months, eFI category was not associated with the number of chemotherapy cycles received (p = 0.97). The main reason for an incalculable eFI was a lack of outpatient visits in our health system prior to AML diagnosis.
A primary care-derived eFI was incalculable for half of older adults with AML at an academic medical center. Frailty was associated with chemotherapy intensity but not survival or treatment duration. Next steps include testing adaptations of the eFI to the AML setting.
This was a retrospective study of subjects ≥60 years old with new AML treated at an academic medical center from 1/2018-10/2020. The eFI requires ≥2 ambulatory visits over two years and uses demographics, vitals, ICD-10 codes, outpatient labs, and available functional information from Medicare Annual Wellness Visits. Frailty was defined as fit (eFI ≤ 0.10), pre-frail (0.10 < eFI ≤ 0.21), and frail (eFI > 0.21). Chemotherapy was intensive (anthracycline-based) or less-intensive (hypomethylating agent, low dose cytarabine +/- venetoclax). Therapy type, pre-treatment characteristics, and chemotherapy cycles were compared by eFI category using chi-square and Fisher\'s exact tests and ANOVA. Median survival was compared by eFI category using log-rank tests stratified by therapy type.
Among 166 older adults treated for AML (mean age 74 years, 61% male, 85% Caucasian), only 79 (48%) had a calculable eFI score before treatment. Of these, baseline eFI category was associated with treatment received (fit (n = 31): 68% intensive, 32% less intensive; pre-frail (n = 38): 37% intensive, 63% less intensive; frail (n = 10): 0% intensive, 100% less intensive; not calculable (n = 87): 48% intensive, 52% less-intensive; p < 0.01). The prevalence of congestive heart failure and secondary AML differed by frailty status (p < 0.01). Median survival did not differ between eFI categories for intensively (p = 0.48) or less-intensively (p = 0.09) treated patients. For those with less-intensive therapy who lived ≥6 months, eFI category was not associated with the number of chemotherapy cycles received (p = 0.97). The main reason for an incalculable eFI was a lack of outpatient visits in our health system prior to AML diagnosis.
A primary care-derived eFI was incalculable for half of older adults with AML at an academic medical center. Frailty was associated with chemotherapy intensity but not survival or treatment duration. Next steps include testing adaptations of the eFI to the AML setting.
摘要：
背景：对老年急性髓系白血病（AML）患者的治疗决策进行评估是不可或缺的。先前的电子虚弱指数（eFI）来自累积赤字模型，并与老年初级保健人群的死亡率相关。我们通过描述治疗类型的基线eFI类别并探索eFI类别之间的关联来评估嵌入式eFI在AML中的使用。生存,和接受的治疗。
方法：这是一项回顾性研究，对1/2018-10/2020在学术医学中心治疗的≥60岁的新AML受试者进行研究。eFI要求在两年内进行≥2次门诊就诊，并使用人口统计信息，生命体征,ICD-10代码,门诊实验室,以及来自Medicare年度健康访问的可用功能信息。脆弱定义为适合(eFI≤0.10)，预脆弱(0.100.21）。化疗是密集的（以蒽环类为基础）或强度较低的（低甲基化剂，低剂量阿糖胞苷+/-维奈托克）。治疗类型,预处理特性，使用卡方和Fisher精确检验和方差分析，按eFI类别比较化疗周期。使用按治疗类型分层的对数秩检验，按eFI类别比较中位生存期。
结果：在166名接受AML治疗的老年人中（平均年龄74岁，61%男性,85%高加索人)，治疗前只有79例(48%)的eFI评分可计算.其中,基线eFI类别与接受的治疗相关(拟合(n=31)：68%强化，减少32%的密集；预脆弱(n=38)：37%的密集，减少63%；脆弱(n=10)：0%密集，100%不那么密集；不可计算(n=87)：48%密集，52%的强度较低；p<0.01)。充血性心力衰竭和继发性AML的患病率因虚弱状态而异（p<0.01）。对于密集治疗（p=0.48）或较不密集治疗（p=0.09）的患者，eFI类别之间的中位生存率没有差异。对于那些接受不那么密集的治疗且寿命≥6个月的人，eFI类别与接受的化疗周期数无关（p=0.97）。无法计算的eFI的主要原因是在AML诊断之前，我们的卫生系统中缺乏门诊就诊。
结论：在学术医疗中心，对于一半患有AML的老年人，初级护理衍生的eFI是无法估量的。虚弱与化疗强度相关，但与生存或治疗持续时间无关。接下来的步骤包括测试eFI对AML设置的适应性。
方法：这是一项回顾性研究，对1/2018-10/2020在学术医学中心治疗的≥60岁的新AML受试者进行研究。eFI要求在两年内进行≥2次门诊就诊，并使用人口统计信息，生命体征,ICD-10代码,门诊实验室,以及来自Medicare年度健康访问的可用功能信息。脆弱定义为适合(eFI≤0.10)，预脆弱(0.10
结果：在166名接受AML治疗的老年人中（平均年龄74岁，61%男性,85%高加索人)，治疗前只有79例(48%)的eFI评分可计算.其中,基线eFI类别与接受的治疗相关(拟合(n=31)：68%强化，减少32%的密集；预脆弱(n=38)：37%的密集，减少63%；脆弱(n=10)：0%密集，100%不那么密集；不可计算(n=87)：48%密集，52%的强度较低；p<0.01)。充血性心力衰竭和继发性AML的患病率因虚弱状态而异（p<0.01）。对于密集治疗（p=0.48）或较不密集治疗（p=0.09）的患者，eFI类别之间的中位生存率没有差异。对于那些接受不那么密集的治疗且寿命≥6个月的人，eFI类别与接受的化疗周期数无关（p=0.97）。无法计算的eFI的主要原因是在AML诊断之前，我们的卫生系统中缺乏门诊就诊。
结论：在学术医疗中心，对于一半患有AML的老年人，初级护理衍生的eFI是无法估量的。虚弱与化疗强度相关，但与生存或治疗持续时间无关。接下来的步骤包括测试eFI对AML设置的适应性。
