{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T22:24:36Z","timestamp":1793917476419,"version":"4.8.0"},"reference-count":37,"publisher":"Baishideng Publishing Group Inc.","issue":"46","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["World J Gastroenterol"],"abstract":"BACKGROUND<\/jats:p>\n Gastric cancer (GC) is one of the most prevalent malignant tumors worldwide and poses a significant threat to human health. Helicobacter pylori (H. pylori )- negative early GC (HpN-EGC) often remains undetected because of its asymptomatic progression.<\/jats:p>\n AIM<\/jats:p>\n To accurately and efficiently identify high-risk HpN-EGC individuals and guide clinical diagnosis and treatment, we developed a clinical prediction model for HpN-EGC.<\/jats:p>\n METHODS<\/jats:p>\n This retrospective case-control study evaluated 593 confirmed H. pylori -negative cases at a hospital. Eligible patients were randomized into training (n = 416) and internal validation (n = 177) groups. Multivariate logistic regression analysis identified significant predictors, which were incorporated into the nomogram. Patients from a different hospital were included in the external validation group (n = 109). Subgroup analyses explored H. pylori eradication (> 1 year) in H. pylori -naive populations.<\/jats:p>\n RESULTS<\/jats:p>\n Risk factors for HpN-EGC were advanced age [odds ratio (OR): 1.13], digestive comorbidities (OR: 17.55), and frequent consumption of smoked and hot foods (OR: 19.00; OR: 4.19). Regular legume and nut intake had protective effects (OR: 0.30; OR: 0.14). The nomogram showed excellent discrimination [training area under the curve (AUC) = 0.904; internal validation AUC = 0.865; external validation AUC = 0.794], stable calibration, and predictive accuracy, with a C-index of 0.904 (95% confidence interval: 0.876-0.931). Good model fit was supported by a non-significant Hosmer-Lemeshow test result (\u03c7 2 = 7.57, P = 0.477). Subgroup analysis revealed that smoking and alcohol consumption specifically increased the risk in H. pylori -naive patients, whereas legume and nut consumption consistently reduced the risk across subgroups.<\/jats:p>\n CONCLUSION<\/jats:p>\n The HpN-EGC risk prediction tool effectively identifies high-risk individuals based on age, digestive comorbidities, consumption of smoked and hot foods, and legume and nut intake.<\/jats:p>","DOI":"10.3748\/wjg.v31.i46.112791","type":"journal-article","created":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T01:35:41Z","timestamp":1765330541000},"source":"Crossref","is-referenced-by-count":1,"title":["Development and validation of a nomogram incorporating dietary factors for predicting\n Helicobacter pylori<\/i>\n -negative early gastric cancer risk"],"prefix":"10.3748","volume":"31","author":[{"given":"Xin-Yuan","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan-Qi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu-Tian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiu-Jing","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2060","published-online":{"date-parts":[[2025,12,14]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21834"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1007\/s10120-015-0581-1"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1007\/s00464-023-10125-7"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1007\/s10120-017-0716-7"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.3238\/arztebl.2018.0429"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(08)61159-9"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1111\/den.12471"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1097\/00042737-199806000-00007"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1111\/j.1523-5378.2011.00859.x"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.5009\/gnl14416"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1111\/j.1523-5378.2011.00889.x"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1080\/17474124.2021.1845140"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1002\/cac2.12067"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(14)71116-7"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1080\/00365521.2021.2023626"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.1007176"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2021.103631"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1007\/s10120-015-0479-y"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.3390\/nu13082739"},{"key":"B20","unstructured":"Gao J, Fei JQ, Jiang LJ, Yao WQ, Lin B, and Guo HW. 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