A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma

• Published in: BMC gastroenterology Vol. 23; no. 1; p. 54
• Main Authors: Xie, Yangyang, Song, Xue, Du, Danwei, Jin, Haimin, Li, Xiaowen, Ni, Zhongkai, Huang, Hai
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 06.03.2023; BioMed Central; BMC
• Subjects: Adenocarcinoma; Adenocarcinoma - drug therapy; Adjuvant treatment; Analysis; Area Under Curve; Cancer; Cancer therapies; Care and treatment; Chemotherapy; Chemotherapy, Adjuvant; Databases, Factual; Decision making; Diagnosis; Epidemiology; Gastric cancer; Gastroenterology; Gender; Humans; Methods; Nomogram; Nomograms; Nomography (Mathematics); Pathology; Patients; Probability; Regression analysis; SEER Program; Software; Stage IB gastric cancer; Stomach cancer; Survival analysis; Tumor staging; Variables; China; Chemotherapy; SEER Program; Stage IB gastric cancer; Nomogram
• ISSN: 1471-230X; 1471-230X
• DOI: 10.1186/s12876-023-02706-6

The purpose of this research was to construct a novel predictive nomogram to identify specific stage IB gastric adenocarcinoma (GAC) populations who could benefit from postoperative adjuvant chemotherapy (ACT). Between 2004 and 2015, 1889 stage IB GAC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) program database. Then Kaplan-Meier survival analysis, univariate and multivariable Cox analyses, and univariate and multivariable logistic analyses were implemented. Finally, the predictive nomograms were constructed. The methods of area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to validate the clinical effectiveness of the models. Of these patients, 708 cases underwent ACT, while the other 1181 patients didn't receive ACT. After PSM, the patients in the ACT group presented a longer median overall survival (133 vs. 85 months, p = 0.0087). Among the ACT group, 194 (36.0%) patients achieving more prolonged overall survival than 85 months were regarded as the beneficiary population. Then the logistic regression analyses were performed, and age, gender, marital status, primary site, tumor size, and regional nodes examined were included as predicting factors to construct the nomogram. The AUC value was 0.725 in the training cohort and 0.739 in the validation cohort, which demonstrated good discrimination. And calibration curves indicated ideal consistency between the predicted and observed probabilities. Decision curve analysis presented a clinically useful model. Furthermore, the prognostic nomogram predicting 1-, 3-, and 5-year cancer-specific survival presented good predictive ability. The benefit nomogram could guide clinicians in decision-making and selecting optimal candidates for ACT among stage IB GAC patients. And the prognostic nomogram presented great prediction ability for these patients.