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不适合移植的多发性骨髓瘤患者早期发生 ≥ 3 级感染风险的预测模型:FIRST 试验分析。

A predictive model for risk of early grade ≥ 3 infection in patients with multiple myeloma not eligible for transplant: analysis of the FIRST trial.

机构信息

Hospices Civils de Lyon, Lyon, France.

CHU Bordeaux, Bordeaux, France.

出版信息

Leukemia. 2018 Jun;32(6):1404-1413. doi: 10.1038/s41375-018-0133-x. Epub 2018 Apr 26.

Abstract

Infections are a major cause of death in patients with multiple myeloma. A post hoc analysis of the phase 3 FIRST trial was conducted to characterize treatment-emergent (TE) infections and study risk factors for TE grade ≥ 3 infection. The number of TE infections/month was highest during the first 4 months of treatment (defined as early infection). Of 1613 treated patients, 340 (21.1%) experienced TE grade ≥ 3 infections in the first 18 months and 56.2% of these patients experienced their first grade ≥ 3 infection in the first 4 months. Risk of early infection was similar regardless of treatment. Based on the analyses of data in 1378 patients through multivariate logistic regression, a predictive model of first TE grade ≥ 3 infection in the first 4 months retained Eastern Cooperative Oncology Group performance status and serum β-microglobulin, lactate dehydrogenase, and hemoglobin levels to define high- and low-risk groups showing significantly different rates of infection (24.0% vs. 7.0%, respectively; P < 0.0001). The predictive model was validated with data from three clinical trials. This predictive model of early TE grade ≥ 3 infection may be applied in the clinical setting to guide infection monitoring and strategies for infection prevention.

摘要

感染是多发性骨髓瘤患者死亡的主要原因。对 3 期 FIRST 试验的事后分析旨在描述治疗后出现的(TE)感染,并研究 TE 分级≥3 感染的危险因素。在治疗的前 4 个月(定义为早期感染),每月 TE 感染的数量最高。在 1613 例接受治疗的患者中,有 340 例(21.1%)在头 18 个月内发生了 TE 分级≥3 的感染,其中 56.2%的患者在头 4 个月内发生了首次 TE 分级≥3 的感染。无论治疗如何,早期感染的风险相似。根据对 1378 例患者的数据进行多变量逻辑回归分析,在头 4 个月内首次发生 TE 分级≥3 感染的预测模型保留了东部合作肿瘤学组(ECOG)表现状态以及血清β-微球蛋白、乳酸脱氢酶和血红蛋白水平,以定义高风险和低风险组,两组的感染率有显著差异(分别为 24.0%和 7.0%;P<0.0001)。该预测模型还在三项临床试验的数据中得到了验证。这种早期 TE 分级≥3 感染的预测模型可在临床环境中应用,以指导感染监测和预防感染策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/494d/5990520/ec52dc838210/41375_2018_133_Fig1_HTML.jpg

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