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Abstract：
Objective This study aims to identify factors predictive of mortality in patients with gallbladder adenocarcinoma and to develop a risk score to predict poor outcomes using data from the Using Healthcare Cost and Utilization Project National Inpatient Database (HCUP-NIS) database between 2016 and 2020. Methods We conducted a retrospective cohort study analyzing 8596 patients diagnosed with gallbladder adenocarcinoma. Data were extracted using the International Classification of Diseases (ICD) 10th Edition Clinical Modification (CM) code C23. Variables analyzed included age, gender, hospital division, race, income quartile, and APRDRG mortality risk. Logistic regression was utilized to determine the predictors of mortality and develop a risk-scoring system. Descriptive statistics and Chi-squared tests assessed the relationship between variables and mortality, with p-values indicating significance. Results The study population had a mean age of 68.3 years, with 66.6% female patients. The overall mortality rate was 7.2%. Key predictors of mortality included higher All Patients Refined Diagnosis Related Groups (APR DRG) risk of mortality (p<0.001), age (p=0.04), and female gender (p=0.033). Race and hospital division were significantly associated with mortality (p<0.001 and p=0.015, respectively). A logistic regression model incorporating these variables yielded an area under the receiver operating characteristics curve of 0.82, indicating good discriminative ability. The developed risk score categorized patients into low, medium, and high-risk groups, with corresponding mortality rates of 0.88%, 5.28%, and 17.78%. Conclusion This study identified critical predictors of mortality in gallbladder adenocarcinoma patients, with APR DRG risk of mortality and age being the most significant. The developed risk score effectively stratifies patients by risk, potentially guiding clinical decision-making and improving patient outcomes.
摘要：
目的本研究旨在确定预测胆囊腺癌患者死亡率的因素，并使用2016年至2020年间使用医疗保健成本和利用项目国家住院数据库（HCUP-NIS）数据库的数据开发风险评分来预测不良结局。方法对8596例胆囊腺癌患者进行回顾性队列研究。使用国际疾病分类(ICD)第10版临床修改(CM)代码C23提取数据。分析的变量包括年龄，性别,医院部门,种族,收入四分位数，和APRDRG死亡风险。使用Logistic回归来确定死亡率的预测因子并开发风险评分系统。描述性统计和卡方检验评估了变量与死亡率之间的关系，p值表示显著性。结果研究人群平均年龄为68.3岁,66.6%为女性患者。总死亡率为7.2%。死亡率的主要预测因素包括所有患者精细诊断相关组（APRDRG）死亡风险较高（p<0.001），年龄（p=0.04），和女性（p=0.033）。种族和医院划分与死亡率显着相关（分别为p<0.001和p=0.015）。包含这些变量的逻辑回归模型在受试者工作特征曲线下的面积为0.82，表明具有良好的判别能力。开发的风险评分将患者分类为低，中等,和高危人群，相应的死亡率为0.88%，5.28%,17.78%。结论本研究确定了胆囊腺癌患者死亡率的关键预测因子。APRDRG的死亡风险和年龄最为显著。开发的风险评分有效地按风险对患者进行分层，潜在的指导临床决策和改善患者预后。
