Department of Hematology, Aalborg University Hospital, Aalborg, Denmark.
Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
Cancer Med. 2018 Jan;7(1):114-122. doi: 10.1002/cam4.1271. Epub 2017 Dec 13.
The international prognostic index (IPI) and similar models form the cornerstone of clinical assessment in newly diagnosed diffuse large B-cell lymphoma (DLBCL). While being simple and convenient to use, their inadequate use of the available clinical data is a major weakness. In this study, we compared performance of the International Prognostic Index (IPI) and its variations (R-IPI and NCCN-IPI) to a Cox proportional hazards (CPH) model using the same covariates in nondichotomized form. All models were tested in 4863 newly diagnosed DLBCL patients from population-based Nordic registers. The CPH model led to a substantial increase in predictive accuracy as compared to conventional prognostic scores when evaluated by the area under the curve and other relevant tests. Furthermore, the generation of patient-specific survival curves rather than assigning patients to one of few predefined risk groups is a relevant step toward personalized management and treatment. A test-version is available on lymphomapredictor.org.
国际预后指数(IPI)和类似模型是新诊断弥漫性大 B 细胞淋巴瘤(DLBCL)临床评估的基石。虽然使用简单方便,但它们对现有临床数据的利用不足是一个主要弱点。在这项研究中,我们比较了国际预后指数(IPI)及其变体(R-IPI 和 NCCN-IPI)与 Cox 比例风险(CPH)模型的性能,这些模型使用了相同的非二项形式的协变量。所有模型均在来自基于人群的北欧登记处的 4863 例新诊断的 DLBCL 患者中进行了测试。通过曲线下面积和其他相关测试评估,CPH 模型与传统预后评分相比,显著提高了预测准确性。此外,生成患者特异性生存曲线而不是将患者分配到少数几个预设风险组之一,是实现个性化管理和治疗的重要步骤。一个测试版本可在 lymphomapredictor.org 上获得。