A comparison of three different approaches to defining frailty in older patients with multiple myeloma.
A comparison of three different approaches to defining frailty in older patients with multiple myeloma.
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DOI：
10.1016/j.jgo.2019.07.004
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发表时间：
2020-03
影响因子：
3
通讯作者：
Wildes TM
中科院分区：
文献类型：
--
作者：
Isaacs A;Fiala M;Tuchman S;Wildes TM
随着人口老龄化的增长，将脆弱的概念应用于老年癌症患者的兴趣也在增加。本研究使用三种虚弱模型检测老年多发性骨髓瘤患者虚弱的患病率。在这项前瞻性队列研究的次要分析中，40名年龄≥65岁的骨髓瘤成人在初次诊断后3个月内完成了癌症和衰老研究组老年评估。根据三个指数：国际骨髓瘤工作组（IMWG）虚弱指数、修订的骨髓瘤合并症指数（R-MCI）和卡罗莱纳虚弱指数（CFI），使用老年评估数据对患者的虚弱状态进行分类。使用Cohen kappa检验指数之间的一致性。28名患者被至少一种模型归类为虚弱。然而，只有轻微的协议之间的指数存在的脆弱性的分类，模型之间的一致性很小（Kappa 0.03-0.12）。只有三名患者被所有三种模型归类为虚弱。在40名新诊断的多发性骨髓瘤老年人的队列中，三种虚弱指数具有不同的方法来操作虚弱，导致不同的患者被归类为虚弱。模型之间几乎没有一致性。需要进一步的研究来探索这些模型在预测治疗毒性和预后方面的效用。
As the aging population grows, interest in applying the concept of frailty to older adults with cancer has increased. This study examines the prevalence of frailty in older patients with multiple myeloma using three frailty models. In this secondary analysis of a prospective cohort study, 40 adults aged ≥65 with myeloma completed the Cancer and Aging Research Group geriatric assessment within three months of initial diagnosis. Geriatric assessment data was used to categorize patients’ frailty status according to three indices: The International Myeloma Working Group (IMWG) Frailty Index, the Revised Myeloma Comorbidity Index (R-MCI), and the Carolina Frailty Index (CFI). Agreement between the indices was examined using Cohen’s kappa. Twenty-eight patients were classified as frail by at least one of the models. However, only slight agreement exists on the classification of frailty among the indices, with little concordance among the models (Kappa 0.03-0.12). Only three patients were categorized as frail by all three models. In a cohort of 40 older adults with newly diagnosed multiple myeloma, three frailty indices have differing approaches to operationalizing frailty resulting, in different patients being categorized as frail. Little agreement existed between the models. Further studies are needed to explore the utility of these models in predicting treatment toxicity and prognosis.
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影响因子：
10.1
作者：
Engelhardt, Monika;Domm, Anne-Saskia;Waesch, Ralph
通讯作者：
Waesch, Ralph
DOI：
10.1111/j.1525-1438.2003.13603.x
发表时间：
2003-11-01
影响因子：
4.8
作者：
Calhoun, EA;Welshman, EE;Cella, D
通讯作者：
Cella, D
影响因子：
3.8
作者：
McCarthy, A. L.;Peel, N. M.;Hubbard, R. E.
通讯作者：
Hubbard, R. E.
DOI：
10.1111/j.1532-5415.1991.tb01616.x
发表时间：
1991-02-01
影响因子：
6.3
作者：
PODSIADLO, D;RICHARDSON, S
通讯作者：
RICHARDSON, S
影响因子：
6.5
作者：
Lenhoff, S;Hjorth, M;Turesson, I
通讯作者：
Turesson, I