Development and analysis of a nomogram for predicting pathological response to neoadjuvant immunochemotherapy in locally advanced gastric cancer.
[BACKGROUND] Neoadjuvant immunochemotherapy (NICT) has demonstrated potential to enhance tumor regression in patients with locally advanced gastric cancer (LAGC).
- 95% CI 0.773-0.923
- OR 0.22
APA
Yu H, Pu Y, et al. (2026). Development and analysis of a nomogram for predicting pathological response to neoadjuvant immunochemotherapy in locally advanced gastric cancer.. Frontiers in oncology, 16, 1737833. https://doi.org/10.3389/fonc.2026.1737833
MLA
Yu H, et al.. "Development and analysis of a nomogram for predicting pathological response to neoadjuvant immunochemotherapy in locally advanced gastric cancer.." Frontiers in oncology, vol. 16, 2026, pp. 1737833.
PMID
41883960
Abstract
[BACKGROUND] Neoadjuvant immunochemotherapy (NICT) has demonstrated potential to enhance tumor regression in patients with locally advanced gastric cancer (LAGC). However, the benefits for some patients are limited. Existing biological markers have only restricted ability to predict pathological response. New biomarkers and predictive models are essential for identifying patients optimally responsive to immunotherapy.
[METHODS] In our retrospective analysis, we included LAGC patients who underwent surgical treatment following NICT at our center between January 2021 and March 2025. Classification was done according to the pathological response rates observed in the excised tumor samples, categorizing patients into major pathological response (MPR) and non-MPR groups. Least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression models were used to pinpoint risk factors linked to MPR. A nomogram was subsequently constructed using the significant predictors.
[RESULTS] In total, 113 LAGC patients fitting the criteria were enrolled, with 46 in the MPR cohort and 67 in the non-MPR cohort, yielding an overall MPR incidence of 40.7%. Independent predictors of MPR following NICT were identified through multivariate logistic regression. These include pre-treatment tumor bed diameter 3.75 cm (OR = 0.22), CEA 1.765 ng/mL (OR = 0.26), CA19-9 18.390 U/mL (OR = 0.148), NLR 2.422 (OR = 0.265), and SII 597.483 (OR = 0.194). We constructed a nomogram model with an area under the curve of 0.848 (95% CI:0.773-0.923) based on these five predictors. The calibration curve indicated a robust agreement between forecasted probabilities and real MPR occurrences (Hosmer-Lemeshow test: = 4.705, 23 P = 0.789).
[CONCLUSION] Tumor bed diameter, CEA, CA19-9, NLR, and SII were determined to be independent predictors of MPR in LAGC patients undergoing NICT. The constructed nomogram demonstrated good accuracy and clinical utility in predicting MPR after NICT, and may help guide the implementation of personalized treatment strategies.
[METHODS] In our retrospective analysis, we included LAGC patients who underwent surgical treatment following NICT at our center between January 2021 and March 2025. Classification was done according to the pathological response rates observed in the excised tumor samples, categorizing patients into major pathological response (MPR) and non-MPR groups. Least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression models were used to pinpoint risk factors linked to MPR. A nomogram was subsequently constructed using the significant predictors.
[RESULTS] In total, 113 LAGC patients fitting the criteria were enrolled, with 46 in the MPR cohort and 67 in the non-MPR cohort, yielding an overall MPR incidence of 40.7%. Independent predictors of MPR following NICT were identified through multivariate logistic regression. These include pre-treatment tumor bed diameter 3.75 cm (OR = 0.22), CEA 1.765 ng/mL (OR = 0.26), CA19-9 18.390 U/mL (OR = 0.148), NLR 2.422 (OR = 0.265), and SII 597.483 (OR = 0.194). We constructed a nomogram model with an area under the curve of 0.848 (95% CI:0.773-0.923) based on these five predictors. The calibration curve indicated a robust agreement between forecasted probabilities and real MPR occurrences (Hosmer-Lemeshow test: = 4.705, 23 P = 0.789).
[CONCLUSION] Tumor bed diameter, CEA, CA19-9, NLR, and SII were determined to be independent predictors of MPR in LAGC patients undergoing NICT. The constructed nomogram demonstrated good accuracy and clinical utility in predicting MPR after NICT, and may help guide the implementation of personalized treatment strategies.
같은 제1저자의 인용 많은 논문 (5)
- Recent advances of metal-organic frameworks (MOFs) for drug delivery, cancer imaging and theranostics.
- miR-193a-5p carried by ferric oxide nanoparticles interferes with the TGF-β1/Smad signaling pathway and promotes pyroptosis in gastric cancer cells.
- Exosome encapsulated albumin nanoparticles target delivery of DBET6 as a treatment for triple-negative breast cancer.
- MicroRNA-150 deficiency promotes progesterone synthesis and apoptosis in goat luteal cells by targeting nuclear receptor NR4A1.
- The predictive value of multiparametric magnetic resonance imaging in enhancing prostate-specific antigen assessment for prostate cancer: a cross-sectional study.