Hong Zhong, Zhang Shiqing, Li Lu, Li Yinlong, Liu Ting, Guo Suying, Xu Xiaojuan, Yang Zhaoming, Zhang Haoyi, Xu Jing
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China.
Department of Schistosomiasis Control and Prevention, Anhui Institute of Parasitic Diseases, Hefei 230061, China.
Trop Med Infect Dis. 2023 Jan 3;8(1):33. doi: 10.3390/tropicalmed8010033.
Advanced schistosomiasis is the late stage of schistosomiasis, seriously jeopardizing the quality of life or lifetime of infected people. This study aimed to develop a nomogram for predicting mortality of patients with advanced schistosomiasis japonica, taking Dongzhi County of China as a case study.
Data of patients with advanced schistosomiasis japonica were collected from Dongzhi Schistosomiasis Hospital from January 2019 to July 2022. Data of patients were randomly divided into a training set and validation set with a ratio of 7:3. Candidate variables, including survival outcomes, demographics, clinical features, laboratory examinations, and ultrasound examinations, were analyzed and selected by LASSO logistic regression for the nomogram. The performance of the nomogram was assessed by concordance index (C-index), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). The calibration of the nomogram was evaluated by the calibration plots, while clinical benefit was evaluated by decision curve and clinical impact curve analysis.
A total of 628 patients were included in the final analysis. Atrophy of the right liver, creatinine, ascites level III, N-terminal procollagen III peptide, and high-density lipoprotein were selected as parameters for the nomogram model. The C-index, sensitivity, specificity, PPV, and NPV of the nomogram were 0.97 (95% [CI]: [0.95-0.99]), 0.78 (95% [CI]: [0.64-0.87]), 0.97 (95% [CI]: [0.94-0.98]), 0.78 (95% [CI]: [0.64-0.87]), 0.97 (95% [CI]: [0.94-0.98]) in the training set; and 0.98 (95% [CI]: [0.94-0.99]), 0.86 (95% [CI]: [0.64-0.96]), 0.97 (95% [CI]: [0.93-0.99]), 0.79 (95% [CI]: [0.57-0.92]), 0.98 (95% [CI]: [0.94-0.99]) in the validation set, respectively. The calibration curves showed that the model fitted well between the prediction and actual observation in both the training set and validation set. The decision and the clinical impact curves showed that the nomogram had good clinical use for discriminating patients with high risk of death.
A nomogram was developed to predict prognosis of advanced schistosomiasis. It could guide clinical staff or policy makers to formulate intervention strategies or efficiently allocate resources against advanced schistosomiasis.
晚期血吸虫病是血吸虫病的晚期阶段,严重危及感染者的生活质量或寿命。本研究旨在以中国东至县为例,开发一种预测日本血吸虫病晚期患者死亡率的列线图。
收集2019年1月至2022年7月东至血吸虫病医院日本血吸虫病晚期患者的数据。患者数据按7:3的比例随机分为训练集和验证集。通过LASSO逻辑回归分析和选择包括生存结局、人口统计学、临床特征、实验室检查和超声检查在内的候选变量用于列线图。通过一致性指数(C指数)、敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)评估列线图的性能。通过校准图评估列线图的校准情况,同时通过决策曲线和临床影响曲线分析评估临床获益情况。
最终分析共纳入628例患者。右肝萎缩、肌酐、腹水Ⅲ级、Ⅲ型前胶原氨基端肽和高密度脂蛋白被选为列线图模型的参数。训练集中列线图的C指数、敏感性、特异性、PPV和NPV分别为0.97(95%[CI]:[0.95 - 0.99])、0.78(95%[CI]:[0.64 - 0.87])、0.97(95%[CI]:[0.94 - 0.98])、0.78(95%[CI]:[0.64 - 0.87])、0.97(95%[CI]:[0.94 - 0.98]);验证集中分别为0.98(95%[CI]:[0.94 - 0.99])、0.86(95%[CI]:[0.64 - 0.96])、0.97(95%[CI]:[0.93 - 0.99])、0.79(95%[CI]:[0.57 - 0.92])、0.98(95%[CI]:[0.94 - 0.99])。校准曲线显示,该模型在训练集和验证集的预测与实际观察之间拟合良好。决策曲线和临床影响曲线显示,列线图在鉴别死亡高风险患者方面具有良好的临床应用价值。
开发了一种预测晚期血吸虫病预后的列线图。它可以指导临床工作人员或政策制定者制定干预策略或有效分配针对晚期血吸虫病的资源。