Gong Wei-Jing, Cao Peng, Huang Yi-Fei, Liu Ya-Ni, Yang Yu, Zhang Rui, Li Qiang, Wu San-Lan, Zhang Yu
Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan 430022, China.
Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan 430022, China.
Curr Probl Cancer. 2024 Feb;48:101058. doi: 10.1016/j.currproblcancer.2023.101058. Epub 2023 Dec 15.
Pemetrexed plus platinum chemotherapy is the first-line treatment option for lung adenocarcinoma. However, hematological toxicity is major dose-limiting and even life-threatening. The ability to anticipate hematological toxicity is of great value for identifying potential chemotherapy beneficiaries with minimal toxicity and optimizing treatment. The study aimed to develop and validate a prediction model for hematologic toxicity based on real-world data.
Data from 1754 lung adenocarcinoma patients with pemetrexed plus platinum chemotherapy regimen as first-line therapy were used to establish and calibrate a risk model for hematological toxicity using multivariate and stepwise logistic regression analysis based on real-world data. The predictive performance of the model was tested in a validation cohort of 753 patients. An area under the curve (AUC) of the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis were used to assess the prediction model.
5 independent factors (platinum, pre-use vitamin B12, cycle of chemotherapy before hematological toxicity, Hb before first chemotherapy, and PLT before first chemotherapy) identified from multivariate and stepwise logistic regression analysis were included in the prediction model. The hematological toxicity prediction model achieved a sensitivity of 0.840 and a specificity of 0.822. The model showed good discrimination in both cohorts (an AUC of 0.904 and 0.902 for the derivation and validation cohort ROC) at the cut-off value of 0.591. The calibration curve showed good agreement between the actual observations and the predicted results.
We developed a prediction model for hematologic toxicity with good discrimination and calibration capability in lung adenocarcinoma patients receiving a pemetrexed plus platinum chemotherapy regimen based on real-world data.
培美曲塞联合铂类化疗是肺腺癌的一线治疗方案。然而，血液学毒性是主要的剂量限制因素，甚至危及生命。预测血液学毒性的能力对于识别潜在的化疗受益患者、使毒性最小化以及优化治疗具有重要价值。本研究旨在基于真实世界数据开发并验证血液学毒性预测模型。
使用1754例接受培美曲塞联合铂类化疗方案作为一线治疗的肺腺癌患者的数据，基于真实世界数据，采用多因素逐步逻辑回归分析建立并校准血液学毒性风险模型。在753例患者的验证队列中测试该模型的预测性能。采用受试者操作特征（ROC）曲线下面积（AUC）、校准曲线和决策曲线分析来评估预测模型。
多因素逐步逻辑回归分析确定的5个独立因素（铂类、使用前维生素B12、血液学毒性前化疗周期、首次化疗前血红蛋白、首次化疗前血小板）纳入预测模型。血液学毒性预测模型的灵敏度为0.840，特异度为0.822。在截断值为0.591时，该模型在两个队列中均显示出良好的区分度（推导队列和验证队列ROC的AUC分别为0.904和0.902）。校准曲线显示实际观察结果与预测结果之间具有良好的一致性。
我们基于真实世界数据开发了一种血液学毒性预测模型，该模型在接受培美曲塞联合铂类化疗方案的肺腺癌患者中具有良好的区分度和校准能力。
