Pan Lanyue, Wu Chunmei, Li Ping, Huang Jiaquan, Wu Yizhi, Li Guo
State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Department and Institute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
PLoS Negl Trop Dis. 2025 May 27;19(5):e0013134. doi: 10.1371/journal.pntd.0013134. eCollection 2025 May.
Advanced schistosomiasis imposed a heavy economic burden on society and had a high rate of mortality and disability. However, methods for assessing its long-term prognosis were currently insufficient, and there was a lack of predictive tools to aid clinical decision-making and personalized follow-up plans for patients. We sought to determine risk factors associated with six-year all-cause mortality in advanced schistosomiasis, deriving and validating a six-year all-cause mortality prediction model through a retrospective cohort study based on a large population-based cohort.
We collected information from 4,136 patients with advanced schistosomiasis who were discharged between December 2014 and January 2015. After excluding 17 patients with the less common subtypes of colonic tumoroid proliferation and dwarfism, as well as 92 patients who were lost to follow-up or had incomplete information, data from 4,027 patients were included in the study. These patients were randomly assigned to the derivation cohort and the external validation cohort in a 7:3 ratio, with 1,400 patients randomly selected from the derivation cohort for internal validation. Sixteen candidate variables were collected: age, gender, nutritional status, splenectomy history, presence of other conditions (such as cardiovascular and digestive diseases), clinical classification, disease duration, ascites occurrence frequency, levels of serum total bilirubin (TBil), direct bilirubin (DBil), aspartate aminotransferase (AST), alanine aminotransferase (ALT), albumin (ALB), alkaline phosphatase (ALP), Hepatitis B surface antigen (HBsAg), and alpha-fetoprotein (AFP). High-risk factors associated with the 6-year mortality outcome were identified through univariate and multivariate Cox proportional hazards regression analyses. The predictive value of different models was evaluated and compared using the receiver operating characteristic (ROC) curves, Akaike information criterion (AIC), net reclassification improvement (NRI), C statistic, and integrated discrimination improvement (IDI).
The derivation cohort comprised 2819 patients and we randomly selected 1400 cases from this cohort for internal validation. The external cohort consisted of 1208 patients. The mortality rate for three groups was around 27%-28%. We identified ten variables associated with increased risk of death, including age, course of disease, frequence of ascites, hepatitis B co-infection, and levels of DBil, ALT, AST, ALP, ALB, and AFP at baseline. Using these variables, we developed a ten-variable model and three simpler models. In the derivation cohort, the ten-variable model showed the highest C statistic (0.759; 95% CI, 0.739-0.778) and the lowest AIC (2834.2). ROC curves indicated an AUC of 0.759 for the ten-variable model, outperforming the simpler models. External validation also demonstrated superior performance of the ten-variable model with a higher C statistic (0.774; 95% CI, 0.749-0.797). This model consistently showed better results in ROC curves, IDI, continuous NRI, and categorical NRI analyses compared to the reduced models in external validation cohort.
This study developed a multivariate model to predict the 6-year all-cause mortality rate in patients with advanced schistosomiasis, which demonstrated good performance. This convenient tool may potentially assist clinicians in formulating patient follow-up plans.
晚期血吸虫病给社会带来了沉重的经济负担,且死亡率和致残率很高。然而,目前评估其长期预后的方法不足,缺乏有助于临床决策和为患者制定个性化随访计划的预测工具。我们试图确定晚期血吸虫病六年全因死亡率的相关危险因素,通过基于大规模人群队列的回顾性队列研究推导并验证一个六年全因死亡率预测模型。
我们收集了2014年12月至2015年1月间出院的4136例晚期血吸虫病患者的信息。排除17例结肠瘤样增殖和侏儒症等较罕见亚型患者,以及92例失访或信息不完整的患者后,4027例患者的数据纳入研究。这些患者按7:3的比例随机分配至推导队列和外部验证队列,从推导队列中随机选取1400例患者进行内部验证。收集了16个候选变量:年龄、性别、营养状况、脾切除史、是否存在其他疾病(如心血管和消化系统疾病)、临床分类、病程、腹水发生频率、血清总胆红素(TBil)、直接胆红素(DBil)、天门冬氨酸氨基转移酶(AST)、丙氨酸氨基转移酶(ALT)、白蛋白(ALB)、碱性磷酸酶(ALP)、乙肝表面抗原(HBsAg)和甲胎蛋白(AFP)。通过单因素和多因素Cox比例风险回归分析确定与6年死亡结局相关的高危因素。使用受试者工作特征(ROC)曲线、赤池信息准则(AIC)、净重新分类改善(NRI)、C统计量和综合判别改善(IDI)评估和比较不同模型的预测价值。
推导队列包括2819例患者,我们从该队列中随机选取1400例进行内部验证。外部队列由1208例患者组成。三组的死亡率约为27%-28%。我们确定了10个与死亡风险增加相关的变量,包括年龄、病程、腹水频率、乙肝合并感染以及基线时的DBil、ALT、AST、ALP、ALB和AFP水平。使用这些变量,我们构建了一个十变量模型和三个更简单的模型。在推导队列中,十变量模型显示出最高的C统计量(0.759;95%CI,0.739-0.778)和最低的AIC(2834.2)。ROC曲线表明十变量模型的AUC为0.759,优于更简单的模型。外部验证也显示十变量模型具有更好的性能,C统计量更高(0.774;95%CI,0.749-0.797)。在外部验证队列中,与简化模型相比,该模型在ROC曲线、IDI、连续NRI和分类NRI分析中始终显示出更好的结果。
本研究构建了一个多变量模型来预测晚期血吸虫病患者的6年全因死亡率,该模型表现良好。这个便捷的工具可能有助于临床医生制定患者随访计划。