Saisudjarit Pattama, Saokaew Surasak, Duangjai Acharaporn, Prasatkhetragarn Anurak, Kanchanasurakit Sukrit, Phisalprapa Pochamana
Department of Applied Science, School of Sciences, University of Phayao, Phayao, Thailand.
Medicine Staff Organization, Thap Khlo Hospital, Phichit, Thailand.
Narra J. 2025 Aug;5(2):e1701. doi: 10.52225/narra.v5i2.1701. Epub 2025 Apr 21.
Tuberculosis (TB) remains a global and national public health concern, with mortality posing a significant challenge in treatment programs. The aim of this study was to develop a simple risk-scoring system to predict mortality among TB patients and assess its applicability in resource-limited settings. Data from TB patient registries in Phichit Province, Thailand, covering from January 1, 2017, to December 31, 2020, were used. Eligible participants were aged ≥18 years, having completed treatment or death. A risk score was developed and internally validated using logistic regression. Coefficients were used to assign weighted points to predictors and applied to a validation cohort to assess diagnostic performance. The performance was evaluated by generating a receiver operating characteristic (ROC) curve. The study included 2,196 participants, randomly allocated into derivation (n=1,600) and validation (n=596) cohorts. The risk score included Charlson Comorbidity Index scores (1-2 points and ≥3 points) and TB meningitis. It showed an area under ROC curve (AuROC) of 74.34% (95%CI: 70.80-77.88%) with good calibration (Hosmer-Lemeshow χ: 0.53; = 0.97). Positive likelihood ratios for low (≤3) and high (≥6) risk were 1.06 (95%CI: 1.03-1.09) and 31.62 (95%CI: 7.23-138.37), respectively. In the validation cohort, AuROC was 79.50% (95%CI: 74.40-84.60%), with 75% and 100% certainty in low- and high-risk groups. In conclusion, this simple risk score, using routine data and two predictors, can predict mortality in TB patients. It may aid clinicians in planning appropriate care strategies. Nevertheless, the tool should undergo external validation before being implemented in clinical practice.
结核病（TB）仍然是一个全球和国家层面的公共卫生问题，死亡率在治疗项目中构成了重大挑战。本研究的目的是开发一种简单的风险评分系统，以预测结核病患者的死亡率，并评估其在资源有限环境中的适用性。使用了泰国披集府2017年1月1日至2020年12月31日期间结核病患者登记处的数据。符合条件的参与者年龄≥18岁，已完成治疗或死亡。使用逻辑回归开发并内部验证了风险评分。系数用于为预测因素分配加权分数，并应用于验证队列以评估诊断性能。通过生成受试者工作特征（ROC）曲线来评估性能。该研究包括2196名参与者，随机分为推导队列（n = 1600）和验证队列（n = 596）。风险评分包括查尔森合并症指数评分（1 - 2分和≥3分）以及结核性脑膜炎。其受试者工作特征曲线下面积（AuROC）为74.34%（95%置信区间：70.80 - 77.88%），校准良好（Hosmer - Lemeshow χ：0.53；P = 0.97）。低风险（≤3）和高风险（≥6）的阳性似然比分别为1.06（95%置信区间：1.03 - 1.09）和31.62（95%置信区间：7.23 - 138.37）。在验证队列中，AuROC为79.50%（95%置信区间：74.40 - 84.60%），低风险和高风险组的确定性分别为75%和100%。总之，这个使用常规数据和两个预测因素的简单风险评分可以预测结核病患者的死亡率。它可能有助于临床医生制定适当的护理策略。然而，该工具在临床实践中实施之前应进行外部验证。
