{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T19:21:50Z","timestamp":1781896910942,"version":"3.54.5"},"reference-count":31,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"2","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Glob Oncol"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:sec>\n                    <jats:title>PURPOSE<\/jats:title>\n                    <jats:p>To characterize gastric cancer epidemiology in Latin America and the Caribbean, identify country-level predictors of the mortality-to-incidence ratio (MIR), and describe the clinical research landscape with emphasis on precision oncology (PO).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>We conducted a retrospective, country-level study integrating GLOBOCAN 2022 incidence and mortality data, ClinicalTrials.gov records (2004-2025), and socioeconomic indicators (United Nations Development Program Human Development Index [HDI] 2023 and current health expenditure). MIR was calculated per country. Precision-oncology studies were flagged by a curated drug dictionary applied to the Interventions field; country involvement was measured as country-study participations. Analyses included geospatial mapping, Spearman correlation, ordinary least squares regression, K-Means clustering (k = 3), and a Random Forest classifier for feature ranking and discrimination.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>\n                      Across 24 countries, incidence ranged from 3.97 to 14.31 per 100,000 and mortality from 2.98 to 11.06 per 100,000. MIR was highest in Honduras (0.93), Belize (0.89), and Guatemala (0.88) and lowest in Cuba (0.65), Uruguay (0.66), and Costa Rica (0.68). The HDI correlated inversely with MIR (\u03c1 = \u20130.71,\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; .001); the association with number of trials was weak (\u03c1 = \u20130.09). Three regional archetypes were identified. The Random Forest model achieved an AUC of 0.94 and ranked HDI as the top predictor. Of the 105 studies, 81 were interventional; phase III accounted for 40.7% and phase II for 30.9%. Country-study participations were concentrated in Brazil (23.4%), Chile (19.1%), and Argentina (15.2%). In PO, participation was dominated by Brazil, Chile, Argentina, and Mexico (72.2% of 140 participations), mostly involving trastuzumab, pembrolizumab, ramucirumab, and nivolumab.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>Socioeconomic context was more associated with outcomes than research volume. Regional research remains concentrated and drug-limited, supporting policies to strengthen diagnostics, access, and equitable clinical investigation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1200\/go-25-00531","type":"journal-article","created":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T20:58:11Z","timestamp":1770238691000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":2,"title":["Gastric Cancer Mortality-to-Incidence Ratios in Latin America and the Caribbean: A Machine Learning Analysis of Socioeconomic and Clinical Research Predictors"],"prefix":"10.1200","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3640-0498","authenticated-orcid":true,"given":"Daniel F.","family":"Pilco-Janeta","sequence":"first","affiliation":[{"name":"Latin American Institute of Precision Oncology (CancerLat), Quito, Ecuador"},{"name":"Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8878-0974","authenticated-orcid":true,"given":"Myriam","family":"De la Cruz-Puebla","sequence":"additional","affiliation":[{"name":"Latin American Institute of Precision Oncology (CancerLat), Quito, Ecuador"},{"name":"Department of Internal Medicine, Health Sciences Faculty, Technical University of Ambato, Tungurahua, Ecuador"},{"name":"Atlantic Fellows for Equity in Brain Health, University of California, San Francisco (UCSF), San Francisco, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9212-0872","authenticated-orcid":true,"given":"Daisy R.","family":"Guam\u00e1n-Pilco","sequence":"additional","affiliation":[{"name":"Latin American Institute of Precision Oncology (CancerLat), Quito, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anthony D.","family":"Moyolema-Pilco","sequence":"additional","affiliation":[{"name":"Latin American Institute of Precision Oncology (CancerLat), Quito, Ecuador"},{"name":"Andean University Sim\u00f3n Bol\u00edvar, Quito, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diego","family":"Montenegro","sequence":"additional","affiliation":[{"name":"Latin American Institute of Precision Oncology (CancerLat), Quito, Ecuador"},{"name":"Department of Oncology, Oncology Institute of Eastern Bolivia, Santa Cruz, Bolivia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5342-4235","authenticated-orcid":true,"given":"William","family":"Miranda","sequence":"additional","affiliation":[{"name":"Department of Health Services, Ministry of Public Health, Managua, Nicaragua"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"233","reference":[{"key":"e_1_3_7_2_2","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21834"},{"key":"e_1_3_7_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.canep.2016.03.008"},{"key":"e_1_3_7_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.canep.2023.102392"},{"key":"e_1_3_7_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.canep.2019.04.003"},{"key":"e_1_3_7_6_2","volume-title":"Population-Based Helicobacter pylori Screen-and-Treat Strategies for Gastric Cancer Prevention: Guidance on Implementation","author":"Park JY","year":"2025","unstructured":"Park JY: Population-Based Helicobacter pylori Screen-and-Treat Strategies for Gastric Cancer Prevention: Guidance on Implementation. 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