Xie Yanni, Yang Gaohui, Pan Lin, Gan Zhaoping, Huang Yumei, Lai Yongrong, Liu Rongrong
Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning 530021, China.
Ther Adv Hematol. 2024 May 9;15:20406207241245190. doi: 10.1177/20406207241245190. eCollection 2024.
Secondary failure of platelet recovery (SFPR) is a common complication that influences survival and quality of life of patients with β-thalassemia major (β-TM) after hematopoietic stem cell transplantation (HSCT).
A model to predict the risk of SFPR in β-TM patients after HSCT was developed.
A retrospective study was used to develop the prediction model.
The clinical data for 218 β-TM patients who received HSCT comprised the training set, and those for another 89 patients represented the validation set. The least absolute shrinkage and selection operator regression algorithm was used to identify the critical clinical factors with nonzero coefficients for constructing the nomogram. Calibration curve, C-index, and receiver operating characteristic curve assessments and decision curve analysis (DCA) were used to evaluate the calibration, discrimination, accuracy, and clinical usefulness of the nomogram. Internal and external validation were used to test and verify the predictive model.
The nomogram based on pretransplant serum ferritin, hepatomegaly, mycophenolate mofetil use, and posttransplant serum albumin could be conveniently used to predict the SFPR risk of thalassemia patients after HSCT. The calibration curve of the nomogram revealed good concordance between the training and validation sets. The nomogram showed good discrimination with a C-index of 0.780 (95% CI: 70.3-85.7) and 0.868 (95% CI: 78.5-95.1) and AUCs of 0.780 and 0.868 in the training and validation sets, respectively. A high C-index value of 0.766 was reached in the interval validation assessment. DCA confirmed that the nomogram was clinically useful when intervention was decided at the possibility threshold ranging from 3% to 83%.
We constructed a nomogram model to predict the risk of SFPR in patients with β-TM after HSCT. The nomogram has a good predictive ability and may be used by clinicians to identify SFPR patients early and recommend effective preventive measures.
血小板恢复继发失败(SFPR)是一种常见并发症,会影响重型β地中海贫血(β-TM)患者造血干细胞移植(HSCT)后的生存及生活质量。
建立一种预测β-TM患者HSCT后发生SFPR风险的模型。
采用回顾性研究来建立预测模型。
218例接受HSCT的β-TM患者的临床数据构成训练集,另外89例患者的数据作为验证集。使用最小绝对收缩和选择算子回归算法来识别具有非零系数的关键临床因素,以构建列线图。采用校准曲线、C指数、受试者工作特征曲线评估和决策曲线分析(DCA)来评估列线图的校准、区分度、准确性和临床实用性。采用内部和外部验证来测试和验证预测模型。
基于移植前血清铁蛋白、肝肿大、霉酚酸酯的使用情况及移植后血清白蛋白的列线图,可方便地用于预测地中海贫血患者HSCT后的SFPR风险。列线图的校准曲线显示训练集和验证集之间具有良好的一致性。列线图在训练集和验证集中的区分度良好,C指数分别为0.780(95%CI:70.3 - 85.7)和0.868(95%CI:78.5 - 95.1),AUC分别为0.780和0.868。在区间验证评估中达到了较高的C指数值0.766。DCA证实,当干预可能性阈值在3%至83%范围内时,列线图具有临床实用性。
我们构建了一种列线图模型来预测β-TM患者HSCT后发生SFPR的风险。该列线图具有良好的预测能力,临床医生可使用它早期识别SFPR患者并推荐有效的预防措施。