Institute of Hematology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Collaborative Innovation Center of Hematology, Huazhong University of Science and Technology, Wuhan, China.
Front Immunol. 2023 Feb 15;14:1128982. doi: 10.3389/fimmu.2023.1128982. eCollection 2023.
In allogeneic hematopoietic stem cell transplantation (allo-HSCT), prognostic indicators effectively predict survival. The Disease conditions prior to transplantation dramatically affects the outcome of HSCT. Optimization of the pre-transplant risk assessment is critical for enhancing allo-HSCT decision-making. Inflammation and nutritional status play significant roles in cancer genesis and progression. As a combined inflammatory and nutritional status biomarker, the C-reactive protein/albumin ratio (CAR) can accurately forecast the prognosis in various malignancies. This research sought to examine the predictive value of CAR and develop a novel nomogram by combining biomarkers and evaluating their importance following HSCT.
Analyses were conducted retroactively on a cohort of 185 consecutive patients who underwent haploidentical hematopoietic stem cell transplantation (haplo-HSCT) at Wuhan Union Medical College Hospital during the period from February 2017 to January 2019. Of these patients, 129 were randomly assigned to the training cohort, and the remaining 56 patients constituted the internal validation cohort. Univariate and multivariate analyses were carried out to examine the predictive significance of clinicopathological factors in the training cohort. Subsequently, the survival nomogram model was developed and compared with the disease risk comorbidity index (DRCI) using the concordance index (C-index), calibration curve, receiver operating characteristics (ROC) curve, and decision curve analysis (DCA).
Patients were separated into low and high CAR groups using a cutoff of 0.087, which independently predicted overall survival (OS). Based on risk factors, CAR, the Disease Risk Index(DRI), and the Hematopoietic Cell Transplantation-specific Comorbidity Index(HCT-CI), the nomogram was developed to predict OS. The C-index and area under the ROC curve confirmed the improved predictive accuracy of the nomogram. The calibration curves revealed that the observed probabilities agreed well with those predicted by the nomogram in training, validation and entire cohort. It was confirmed by DCA that the nomogram offered greater net benefits than DRCI among all cohorts.
CAR is an independent prognostic indicator for haplo-HSCT outcomes. Higher CAR was related to worse clinicopathologic characteristics and poorer prognoses in patients underwent haplo-HSCT. This research provided an accurate nomogram for predicting the OS of patients following haplo-HSCT, illustrating its potential clinical utility.
在异基因造血干细胞移植(allo-HSCT)中,预后指标可有效预测生存。移植前疾病状况对 HSCT 结果有显著影响。优化移植前风险评估对于增强 allo-HSCT 决策至关重要。炎症和营养状况在癌症发生和发展中起着重要作用。作为一种综合炎症和营养状态的生物标志物,C 反应蛋白/白蛋白比值(CAR)可准确预测各种恶性肿瘤的预后。本研究旨在探讨 CAR 的预测价值,并通过结合生物标志物构建新的列线图,评估其在 HSCT 后的重要性。
回顾性分析了 2017 年 2 月至 2019 年 1 月期间在武汉协和医院接受单倍体造血干细胞移植(haplo-HSCT)的 185 例连续患者的队列。其中 129 例患者被随机分配到训练队列,其余 56 例患者构成内部验证队列。在训练队列中进行单因素和多因素分析,以探讨临床病理因素的预测意义。随后,构建生存列线图模型,并通过一致性指数(C-index)、校准曲线、接收者操作特征(ROC)曲线和决策曲线分析(DCA)与疾病风险合并症指数(DRCI)进行比较。
使用 0.087 作为截断值将患者分为低 CAR 组和高 CAR 组,CAR 独立预测总体生存(OS)。基于风险因素、CAR、疾病风险指数(DRI)和造血细胞移植特异性合并症指数(HCT-CI),构建了预测 OS 的列线图。C-index 和 ROC 曲线下面积验证了列线图预测准确性的提高。校准曲线表明,在训练、验证和整个队列中,观察到的概率与列线图预测的概率吻合良好。DCA 证实,在所有队列中,列线图比 DRCI 提供了更大的净效益。
CAR 是 allo-HSCT 结果的独立预后指标。较高的 CAR 与患者接受 haplo-HSCT 后较差的临床病理特征和预后相关。本研究为预测 haplo-HSCT 后患者的 OS 提供了一个准确的列线图,显示了其潜在的临床应用价值。