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Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones
BACKGROUND: 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. METHODS: A total of 588 patients from medical centers in two...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009222/ https://www.ncbi.nlm.nih.gov/pubmed/36923422 http://dx.doi.org/10.3389/fonc.2023.1037194 |
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author | Zhu, Zhencheng Luo, Kunlun Zhang, Bo Wang, Gang Guo, Ke Huang, Pin Liu, Qiuhua |
author_facet | Zhu, Zhencheng Luo, Kunlun Zhang, Bo Wang, Gang Guo, Ke Huang, Pin Liu, Qiuhua |
author_sort | Zhu, Zhencheng |
collection | PubMed |
description | BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: Age (≤58.5 vs. >58.5 years), size of gallstones (≤1.95 vs. >1.95cm), course of gallstones (≤10 vs. >10 years), CEA (≤5 vs. >5 ng/ml), and CA199 (≤37 vs. >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. |
format | Online Article Text |
id | pubmed-10009222 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100092222023-03-14 Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones Zhu, Zhencheng Luo, Kunlun Zhang, Bo Wang, Gang Guo, Ke Huang, Pin Liu, Qiuhua Front Oncol Oncology BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: Age (≤58.5 vs. >58.5 years), size of gallstones (≤1.95 vs. >1.95cm), course of gallstones (≤10 vs. >10 years), CEA (≤5 vs. >5 ng/ml), and CA199 (≤37 vs. >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. Frontiers Media S.A. 2023-02-27 /pmc/articles/PMC10009222/ /pubmed/36923422 http://dx.doi.org/10.3389/fonc.2023.1037194 Text en Copyright © 2023 Zhu, Luo, Zhang, Wang, Guo, Huang and Liu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Zhu, Zhencheng Luo, Kunlun Zhang, Bo Wang, Gang Guo, Ke Huang, Pin Liu, Qiuhua Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones |
title | Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones |
title_full | Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones |
title_fullStr | Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones |
title_full_unstemmed | Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones |
title_short | Risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones |
title_sort | risk factor analysis and construction of prediction models of gallbladder carcinoma in patients with gallstones |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009222/ https://www.ncbi.nlm.nih.gov/pubmed/36923422 http://dx.doi.org/10.3389/fonc.2023.1037194 |
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