Department of Hematology, Shandong Provincial Hospital, Shandong University, Jinan, China.
Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Cancer Med. 2023 Apr;12(8):9570-9582. doi: 10.1002/cam4.5733. Epub 2023 Mar 3.
This study aimed to evaluate the predictive value of systemic inflammation response index (SIRI) in primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL) patients and establish a highly discriminating risk prediction model.
This retrospective analysis included 153 PGI-DCBCL patients diagnosed between 2011 and 2021. These patients were divided into a training set (n = 102) and a validation set (n = 51). Univariate and multivariate Cox regression analyses were conducted to examine the significance of variables on overall survival (OS) and progression-free survival (PFS). An inflammation-covered score system was established according to the multivariate results.
The presence of high pretreatment SIRI (≥1.34, p < 0.001) was significantly associated with poorer survival and identified as an independent prognostic factor. Compared with NCCN-IPI, the prognostic and discriminatory capability of the novel model SIRI-PI showed a more precise high-risk assessment with a higher area under the curve (AUC) (0.916 vs 0.835) and C-index (0.912 vs 0.836) for OS in the training cohort, and similar results were obtained in the validation cohort. Moreover, SIRI-PI also showed good discriminative power for efficacy assessment. This new model identified patients at risk of developing severe gastrointestinal complications following chemotherapy.
The results of this analysis suggested that the pretreatment SIRI may be a potential candidate for identifying patients with a poor prognosis. And we established and validated a better-performing clinical model, which facilitated the prognostic stratification of PGI-DLBCL patients and can serve as a reference for clinical decision-making.
本研究旨在评估全身炎症反应指数(SIRI)在原发性胃肠弥漫大 B 细胞淋巴瘤(PGI-DLBCL)患者中的预测价值,并建立一个具有高度区分能力的风险预测模型。
本回顾性分析纳入了 2011 年至 2021 年间诊断的 153 例 PGI-DCBCL 患者。这些患者被分为训练集(n=102)和验证集(n=51)。采用单因素和多因素 Cox 回归分析来评估变量对总生存(OS)和无进展生存(PFS)的显著性。根据多因素结果建立了一个炎症评分系统。
高预处理 SIRI(≥1.34,p<0.001)的存在与较差的生存显著相关,并被确定为独立的预后因素。与 NCCN-IPI 相比,新型模型 SIRI-PI 的预后和区分能力具有更高的 AUC(训练队列 0.916 比 0.835)和 C 指数(0.912 比 0.836),在验证队列中也得到了类似的结果。此外,SIRI-PI 还显示出对疗效评估的良好区分能力。该新模型可识别出化疗后发生严重胃肠道并发症的风险患者。
该分析结果表明,预处理 SIRI 可能是识别预后不良患者的潜在候选指标。并且我们建立并验证了一个性能更好的临床模型,该模型有助于对 PGI-DLBCL 患者进行预后分层,可为临床决策提供参考。