BMC cancer · 2025
Analysis of the predictive effect of gut microbiota changes on the occurrence of chemotherapy resistance in pancreatic cancer patients based on nomogram prediction models.
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Li Ying, Liu Shini, Lai Xiaorong, Yang Dongyang
Аннотация
OBJECTIVE: Investigate gut microbiota's role in chemotherapy resistance development among pancreatic cancer patients and evaluate a nomogram prediction model.
METHODS: 510 pancreatic cancer patients who received chemotherapy in our hospital from January 2023 to December 2024 were randomly divided into training set (n = 357) and validation set (n = 153). Risk factors for chemotherapy resistance in pancreatic cancer were screened through multiple logistic regression analysis, and a Nomogram model was constructed. The predictive efficacy of the model was evaluated by drawing the receiver operating characteristic curve and calibration curve, and was verified in the validation set. The clinical application value of the model was evaluated using decision curve analysis.
RESULTS: The incidence of resistance in the training set was 64.99% (232/357), and that in the validation set was 65.36% (100/153). Multiple logistic regression analysis showed that Escherichia coli, Enterococcus faecalis, and Fusobacterium nucleatum were independent risk factors affecting the occurrence of chemotherapy resistance in pancreatic cancer patients (P < 0.05), while Akkermansia and Bifidobacterium were independent protective factors affecting the occurrence of chemotherapy resistance in pancreatic cancer patients (all P < 0.05). The C-indexes of the constructed Nomogram model in the training set and the validation set were 0.767 and 0.762 respectively. The areas under the curve (AUC) were 0.767 (95% CI: 0.708-0.827) and 0.762 (95% CI: 0.669-0.854) respectively. The sensitivity and specificity were 0.455, 0.865 and 0.511, 0.873 respectively.
CONCLUSION: The Nomogram prediction model constructed based on gut microbiota change indicators has a high predictive efficacy for the occurrence of chemotherapy resistance in pancreatic cancer patients, providing a basis for clinical early screening and intervention.
METHODS: 510 pancreatic cancer patients who received chemotherapy in our hospital from January 2023 to December 2024 were randomly divided into training set (n = 357) and validation set (n = 153). Risk factors for chemotherapy resistance in pancreatic cancer were screened through multiple logistic regression analysis, and a Nomogram model was constructed. The predictive efficacy of the model was evaluated by drawing the receiver operating characteristic curve and calibration curve, and was verified in the validation set. The clinical application value of the model was evaluated using decision curve analysis.
RESULTS: The incidence of resistance in the training set was 64.99% (232/357), and that in the validation set was 65.36% (100/153). Multiple logistic regression analysis showed that Escherichia coli, Enterococcus faecalis, and Fusobacterium nucleatum were independent risk factors affecting the occurrence of chemotherapy resistance in pancreatic cancer patients (P < 0.05), while Akkermansia and Bifidobacterium were independent protective factors affecting the occurrence of chemotherapy resistance in pancreatic cancer patients (all P < 0.05). The C-indexes of the constructed Nomogram model in the training set and the validation set were 0.767 and 0.762 respectively. The areas under the curve (AUC) were 0.767 (95% CI: 0.708-0.827) and 0.762 (95% CI: 0.669-0.854) respectively. The sensitivity and specificity were 0.455, 0.865 and 0.511, 0.873 respectively.
CONCLUSION: The Nomogram prediction model constructed based on gut microbiota change indicators has a high predictive efficacy for the occurrence of chemotherapy resistance in pancreatic cancer patients, providing a basis for clinical early screening and intervention.