Saelue Pirun, Penthinapong Thitichaya
Hematology Unit, Division of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Pharmaceutical Care Training Center, Department of Pharmaceutical Care, Faculty of Pharmacy, Chiang Mai University, Mueang, Chiang Mai, Thailand.
Infect Chemother. 2024 Dec;56(4):483-491. doi: 10.3947/ic.2024.0045. Epub 2024 Aug 30.
In patients with aplastic anemia (AA), infection-related complications are the leading cause of mortality. However, limited knowledge about the predictive factors for infection in these patients exists. Thus, this study aimed to evaluate risk factors for infection and develop a risk prediction model for the occurrence of infection in patients with AA.
Between January 2004 and December 2020, 206 patients with AA ≥15 years of age were included in this study. Survival analysis using recurrent event methodologies was conducted to identify predictive factors associated with infection, including the Anderson and Gill model; Prentice, Williams, and Peterson (PWP) Total Time model; PWP Gap Time model; marginal model; and frailty models. The best model was determined using backward stepwise regression, and internal validation was performed using the bootstrapping method with 500 re-samplings.
With a median follow-up of 2.95 years, the incidence rate of infection among patients with AA was 32.8 events per 100 person-years. The PWP Total Time model revealed that cirrhosis comorbidity, lymphocytes ≥80%, and previous infection increased the risk of infection, while bone marrow cellularity ≥20% offered protection. The bone marrow cellularity, lymphocyte percentage, previous infection, cirrhosis, and hematocrit (BLICH) model was generated to predict the risk of infection. The internal validation showed a good calibration of this model.
Cirrhosis, lymphocytes ≥80%, previous infection, and bone marrow cellularity <20% are risk factors for infection in patients with AA. The BLICH model can predict the risk of infection in these patients.
在再生障碍性贫血（AA）患者中，感染相关并发症是主要死亡原因。然而，对于这些患者感染的预测因素了解有限。因此，本研究旨在评估感染的危险因素，并建立AA患者感染发生的风险预测模型。
2004年1月至2020年12月期间，本研究纳入了206例年龄≥15岁的AA患者。采用复发事件方法进行生存分析，以确定与感染相关的预测因素，包括安德森和吉尔模型；普伦蒂斯、威廉姆斯和彼得森（PWP）总时间模型；PWP间隔时间模型；边际模型；以及脆弱模型。使用向后逐步回归确定最佳模型，并采用500次重抽样的自举法进行内部验证。
中位随访2.95年，AA患者的感染发生率为每100人年32.8次事件。PWP总时间模型显示，肝硬化合并症、淋巴细胞≥80%以及既往感染会增加感染风险，而骨髓细胞计数≥20%则具有保护作用。生成了骨髓细胞计数、淋巴细胞百分比、既往感染、肝硬化和血细胞比容（BLICH）模型来预测感染风险。内部验证显示该模型具有良好的校准。
肝硬化、淋巴细胞≥80%、既往感染以及骨髓细胞计数<20%是AA患者感染的危险因素。BLICH模型可以预测这些患者的感染风险。
