Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones

• Published in: Frontiers in oncology Vol. 13; p. 1037194
• Main Authors: Zhu, Zhencheng, Luo, Kunlun, Zhang, Bo, Wang, Gang, Guo, Ke, Huang, Pin, Liu, Qiuhua
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 27-02-2023
• Subjects: clinical prediction model; gallbladder neoplasms; logistic (logit) regression; nomogram; Oncology; risk factors; risk factors; nomogram; logistic (logit) regression; clinical prediction model; gallbladder neoplasms
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2023.1037194

Gallbladder carcinoma (GBC) is a biliary tract tumor with a high mortality rate. The objectives of this study were to explore the risk factors of GBC in patients with gallstones and to establish effective screening indicators.
A total of 588 patients from medical centers in two different regions of China were included in this study and defined as the internal test samples and the external validation samples, respectively. We retrospectively reviewed the differences in clinicopathologic data of the internal test samples to find the independent risk factors that affect the occurrence of GBC. Then, we constructed three different combined predictive factors (CPFs) through the weighting method, integral system, and nomogram, respectively, and named them CPF-A, CPF-B, and CPF-C sequentially. Furthermore, we evaluated these indicators through calibration and DCA curves. The ROC curve was used to analyze their diagnostic efficiency. Finally, their diagnostic capabilities were validated in the external validation samples.
In the internal test samples, the results showed that five factors, namely, age (RR = 3.077, 95% CI: 1.731-5.496), size of gallstones (RR = 13.732, 95% CI: 5.937-31.762), course of gallstones (RR = 2.438, 95% CI: 1.350-4.403), CEA (RR = 9.464, 95% CI: 3.394-26.392), and CA199 (RR = 9.605, 95% CI: 4.512-20.446), were independent risk factors for GBC in patients with gallstones. Then, we established three predictive indicators: CPF-A, CPF-B, and CPF-C. These models were further validated using bootstrapping with 1,000 repetitions. Calibration and decision curve analysis showed that the three models fit well. Meanwhile, multivariate analysis showed that CPF-B and CPF-C were independent risk factors for GBC in patients with gallstones. In addition, the validation results of the external validation samples are essentially consistent with the internal test samples.
Age (≤58.5
. >58.5 years), size of gallstones (≤1.95
. >1.95cm), course of gallstones (≤10
. >10 years), CEA (≤5
. >5 ng/ml), and CA199 (≤37
. >37 U/ml) are independent risk factors for GBC in patients with gallstones. When positive indicators were ≥2 among the five independent risk factors or the score of the nomogram was >82.64, the risk of GBC was high in gallstone patients.