ArticleBMC cancer2023
Risk model and factors for prediction of response to neoadjuvant chemotherapy in patients with advanced gastric cancer-a two-center cohort study.
Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Factors influencing pathological response after neoadjuvant therapy for advanced gastric cancer.American journal of translational research · 2025Article
- Predictive factors for histological response to neoadjuvant therapy in gastric adenocarcinomas.Arquivos brasileiros de cirurgia digestiva : ABCD = Brazilian archives of digestive surgery · 2025Article
- Novel computed tomography-based nomograms for the pretherapeutic prediction of response to neoadjuvant chemotherapy with S-1 and oxaliplatin with or without the addition of docetaxel in patients with advanced gastric cancer.Quantitative imaging in medicine and surgery · 2024Article
- HIST1H2BK predicts neoadjuvant-chemotherapy response and mediates 5-fluorouracil resistance of gastric cancer cells.Translational oncology · 2024Article
- Systemic immunoinflammatory index and prognostic nutrition index for predicting pathologic responses of patients with advanced gastric cancer after neoadjuvant therapy for advanced gastric cancer.American journal of cancer research · 2024Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveDue to inconsistency in neoadjuvant chemotherapy (NACT) response in advanced gastric cancer (GC), the indications remain the source of controversy. This study focused on identifying factors related to NACT chemosensitivity and providing the best treatment for GC cases.
methodsClinical data in 867 GC cases treated with neoadjuvant chemotherapy were downloaded from two medical centers between January 2014 and December 2020, and analyzed by logistic regression and the least absolute shrinkage and selection operator (LASSO) for identifying potential factors that predicted NACT response and might be incorporated in constructing the prediction nomogram.
resultsAfter the inclusion and exclusion criteria were applied, totally 460 cases were enrolled, among which, 307 were males (66.74%) whereas 153 were females (33.26%), with the age of 24-77 (average, 59.37 ± 10.60) years. Consistent with RECIST standard, 242 patients were classified into effective group (PR or CR) while 218 were into ineffective group (PD or SD), with the effective rate of 52.61%. In training set, LASSO and logistic regression analysis showed that five risk factors were significantly associated with NACT effectiveness, including tumor location, Smoking history, T and N stages, and differentiation. In terms of our prediction model, its C-index was 0.842. Moreover, calibration curve showed that the model-predicted results were in good consistence with actual results. Validation based on internal and external validation sets exhibited consistency between training set results and ours.
conclusionsThis study identified five risk factors which were significantly associated with NACT response, including smoking history, clinical T stage, clinical N stage, tumor location and differentiation. The prediction model that exhibited satisfying ability to predict NACT effectiveness was constructed, which may be adopted for identifying the best therapeutic strategy for advanced GC by gastrointestinal surgeons.
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