Sulley Saanie, Zhou Yan
Pathology and Laboratory Medicine, Boston University, Boston, USA.
Cureus. 2024 Jun 29;16(6):e63457. doi: 10.7759/cureus.63457. eCollection 2024 Jun.
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.
目的 本研究旨在确定胆囊腺癌患者死亡率的预测因素，并利用2016年至2020年医疗保健成本和利用项目国家住院数据库（HCUP-NIS）的数据开发一个风险评分系统，以预测不良预后。方法 我们进行了一项回顾性队列研究，分析了8596例诊断为胆囊腺癌的患者。使用国际疾病分类（ICD）第10版临床修订本（CM）编码C23提取数据。分析的变量包括年龄、性别、科室、种族、收入四分位数和APRDRG死亡风险。采用逻辑回归确定死亡率的预测因素并开发风险评分系统。描述性统计和卡方检验评估变量与死亡率之间的关系，p值表示显著性。结果 研究人群的平均年龄为68.3岁，女性患者占66.6%。总死亡率为7.2%。死亡率的关键预测因素包括较高的所有患者精细诊断相关组（APR DRG）死亡风险（p<0.001）、年龄（p=0.04）和女性性别（p=0.033）。种族和科室与死亡率显著相关（分别为p<0.001和p=0.015）。纳入这些变量的逻辑回归模型的受试者工作特征曲线下面积为0.82，表明具有良好的区分能力。开发的风险评分将患者分为低风险、中风险和高风险组，相应的死亡率分别为0.88%、5.28%和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素，其中APR DRG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，可能指导临床决策并改善患者预后。
