Suppr超能文献

用于预测弥漫性大 B 细胞淋巴瘤治疗前结局的肿瘤体积和体能状态模型。

A tumor volume and performance status model to predict outcome before treatment in diffuse large B-cell lymphoma.

机构信息

Hémato-oncologie, Université de Paris, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France.

Statistique, Lymphoma Academic Research Organisation, Piérre-Benite, France.

出版信息

Blood Adv. 2022 Dec 13;6(23):5995-6004. doi: 10.1182/bloodadvances.2021006923.

Abstract

Aggressive large B-cell lymphoma (LBCL) has variable outcomes. Current prognostic tools use factors for risk stratification that inadequately identify patients at high risk of refractory disease or relapse before initial treatment. A model associating 2 risk factors, total metabolic tumor volume (TMTV) >220 cm3 (determined by fluorine-18 fluorodeoxyglucose positron emission tomography coupled with computed tomography) and performance status (PS) ≥2, identified as prognostic in 301 older patients in the REMARC trial (#NCT01122472), was validated in 2174 patients of all ages treated in 2 clinical trials, PETAL (Positron Emission Tomography-Guided Therapy of Aggressive Non-Hodgkin Lymphomas; N = 510) and GOYA (N = 1315), and in real-world clinics (N = 349) across Europe and the United States. Three risk categories, low (no factors), intermediate (1 risk factor), and high (2 risk factors), significantly discriminated outcome in most of the series. Patients with 2 risk factors had worse outcomes than patients with no risk factors in the PETAL, GOYA, and real-world series. Patients with intermediate risk also had significantly worse outcomes than patients with no risk factors. The TMTV/Eastern Cooperative Oncology Group-PS combination outperformed the International Prognostic Index with a positive C-index for progression-free survival and overall survival in most series. The combination of high TMTV > 220 cm3 and ECOG-PS ≥ 2 is a simple clinical model to identify aggressive LBCL risk categories before treatment. This combination addresses the unmet need to better predict before treatment initiation for aggressive LBCL the patients likely to benefit the most or not at all from therapy.

摘要

侵袭性大 B 细胞淋巴瘤(LBCL)的预后存在差异。目前的预后工具使用风险分层因素,但这些因素不能充分识别初始治疗前疾病难治或复发风险较高的患者。在 REMARC 试验(#NCT01122472)中,联合 2 个风险因素(氟-18 氟代脱氧葡萄糖正电子发射断层扫描与计算机断层扫描测定的总代谢肿瘤体积[TMTV]>220 cm3 和表现状态[PS]≥2)的模型被鉴定为具有预后意义,随后在 2 项临床试验(PETAL [正电子发射断层扫描指导侵袭性非霍奇金淋巴瘤治疗;N=510]和 GOYA [N=1315])和欧洲和美国的真实世界临床实践(N=349)中对 2174 例所有年龄段的患者进行了验证。低危(无风险因素)、中危(1 个风险因素)和高危(2 个风险因素)这 3 个风险类别在大多数系列中显著区分了结局。在 PETAL、GOYA 和真实世界系列中,具有 2 个风险因素的患者比无风险因素的患者结局更差。具有中危因素的患者比无风险因素的患者结局也显著更差。TMTV/东部肿瘤协作组-PS 联合模型在大多数系列中对无进展生存期和总生存期的进展具有更高的 C 指数,优于国际预后指数。高 TMTV>220 cm3 和 ECOG-PS≥2 的联合是一种简单的临床模型,可以在治疗前识别侵袭性 LBCL 的风险类别。这种联合可以在治疗前更准确地预测侵袭性 LBCL 患者,从而更好地满足那些可能从治疗中受益最多或完全无益的患者的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f3/9691911/9f4573a34f5d/BLOODA_ADV-2021-006923-fx1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验