使用达拉单抗治疗方案的多发性骨髓瘤患者严重感染并发症的预测因素和概况:肺炎风险的机器学习模型。

IF 4.5 2区 医学 Q1 ONCOLOGY Cancers Pub Date : 2024-11-03 DOI:10.3390/cancers16213709
Damian Mikulski, Marcin Kamil Kędzior, Grzegorz Mirocha, Katarzyna Jerzmanowska-Piechota, Żaneta Witas, Łukasz Woźniak, Magdalena Pawlak, Kacper Kościelny, Michał Kośny, Paweł Robak, Aleksandra Gołos, Tadeusz Robak, Wojciech Fendler, Joanna Góra-Tybor
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引用次数: 0

摘要

背景:达拉单抗(Daratumumab,Dara)是首个用于临床实践治疗多发性骨髓瘤(MM)的单克隆抗体。目前,它是新诊断(ND)和复发/难治(RR)患者治疗方案的主要药物。然而,之前的报告显示,在以达拉为基础的治疗过程中,感染性并发症(ICs)的风险增加。在这项研究中,我们旨在确定接受达拉方案治疗的 MM 患者的感染并发症概况,并确定其发生的预测因素:这项回顾性的真实研究纳入了2019年7月至2024年3月期间在我院接受达拉治疗的MM患者。感染事件采用《不良事件术语标准》(CTCAE)5.0版进行评估:研究组共有 139 名患者,包括 49 名 NDMM 和 90 名 RRMM。在 RR 环境中,大多数患者(60.0%)接受达拉、硼替佐米和地塞米松(DVd)方案治疗,而 ND 患者主要(98%)接受达拉、硼替佐米、沙利度胺和地塞米松(DVTd)方案治疗。总体而言,55 名患者(39.6%)出现了 IC。最常见的 IC 是肺炎(37.5%),其次是上呼吸道感染(26.8%)。最后,25 名患者出现了严重的 IC(≥ 3 级),需要住院治疗,8 名患者因 IC 而死亡。在调整了环境(ND/RR)和年龄的最终多变量模型中,血红蛋白水平(OR 0.77,95% CI:0.61-0.96,p = 0.0037)和东部合作肿瘤学组(ECOG)>1(OR 4.46,95% CI:1.63-12.26,p = 0.0037)是影响严重 IC 发生的重要因素。此外,我们还使用 J48 决策树、梯度提升和随机森林算法建立了预测模型。在进行10倍交叉验证后,这些模型在预测达拉单抗方案治疗期间肺炎的发生方面表现出很强的性能:结论:简单的临床和实验室评估,包括血红蛋白水平和ECOG评分,对识别达拉单抗治疗期间易受感染的患者很有价值,有助于制定个性化的预防策略。
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Predictors and Profile of Severe Infectious Complications in Multiple Myeloma Patients Treated with Daratumumab-Based Regimens: A Machine Learning Model for Pneumonia Risk.

Background: Daratumumab (Dara) is the first monoclonal antibody introduced into clinical practice to treat multiple myeloma (MM). It currently forms the backbone of therapy regimens in both newly diagnosed (ND) and relapsed/refractory (RR) patients. However, previous reports indicated an increased risk of infectious complications (ICs) during Dara-based treatment. In this study, we aimed to determine the profile of ICs in MM patients treated with Dara-based regimens and establish predictors of their occurrence.

Methods: This retrospective, real-life study included MM patients treated with Dara-based regimens between July 2019 and March 2024 at our institution. Infectious events were evaluated using the Terminology Criteria for Adverse Events (CTCAE) version 5.0.

Results: The study group consisted of a total of 139 patients, including 49 NDMM and 90 RRMM. In the RR setting, the majority (60.0%) of patients received the Dara, bortezomib, and dexamethasone (DVd) regimen, whereas ND patients were predominantly (98%) treated with the Dara, bortezomib, thalidomide, and dexamethasone (DVTd) regimen. Overall, 55 patients (39.6%) experienced ICs. The most common IC was pneumonia (37.5%), followed by upper respiratory tract infections (26.8%). Finally, twenty-five patients had severe ICs (grade ≥ 3) and required hospitalization, and eight patients died due to ICs. In the final multivariable model adjusted for setting (ND/RR) and age, hemoglobin level (OR 0.77, 95% CI: 0.61-0.96, p = 0.0037), and Eastern Cooperative Oncology Group (ECOG) >1 (OR 4.46, 95% CI: 1.63-12.26, p = 0.0037) were significant factors influencing severe IC occurrence. Additionally, we developed predictive models using the J48 decision tree, gradient boosting, and random forest algorithms. After conducting 10-fold cross-validation, these models demonstrated strong performance in predicting the occurrence of pneumonia during treatment with daratumumab-based regimens.

Conclusions: Simple clinical and laboratory assessments, including hemoglobin level and ECOG scale, can be valuable in identifying patients vulnerable to infections during Dara-based regimens, facilitating personalized prophylactic strategies.

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来源期刊
Cancers
Cancers Medicine-Oncology
CiteScore
8.00
自引率
9.60%
发文量
5371
审稿时长
18.07 days
期刊介绍: Cancers (ISSN 2072-6694) is an international, peer-reviewed open access journal on oncology. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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