{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T20:03:26Z","timestamp":1793217806403,"version":"4.5.0"},"reference-count":34,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T00:00:00Z","timestamp":1772582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background: Individuals with type 2 diabetes mellitus (T2DM) are at markedly increased risk of developing coronary heart disease (CHD); however, the generalizability and transportability of existing prediction models remain uncertain. Objective: To identify and evaluate multivariable prognostic models developed to predict CHD in adults with T2DM. Methods: We conducted a PRISMA-guided systematic review and meta-analysis of multivariable prognostic models predicting CHD in T2DM populations. Model characteristics and performance metrics were extracted following the CHARMS and TRIPOD-SRMA frameworks, and pooled discrimination was estimated on the logit-transformed AUC scale using a random-effects model (REML, Hartung\u2013Knapp adjustment). Between-study heterogeneity and 95% prediction intervals were quantified, while risk of bias and applicability were assessed using the PROBAST tool. Results: Thirteen studies encompassing clinical, imaging-based, and omics-augmented models met the inclusion criteria. The pooled AUC was 0.69 (95% CI: 0.66\u20130.71), with high heterogeneity (I2 = 97.4%; \u03c42 = 0.0979) and a wide 95% prediction interval (0.54\u20130.81). Classical regression-based models demonstrated modest discrimination, whereas machine learning, imaging, and proteomic approaches achieved higher AUC estimates but were frequently constrained by small sample sizes, internal-only validation, and poor calibration reporting. The analysis domain emerged as the principal source of bias in PROBAST evaluations, and applicability issues were most frequent in models requiring advanced imaging or molecular platforms. Conclusions: Prognostic models for CHD in T2DM demonstrate moderate-to-good discrimination but substantial heterogeneity and frequent miscalibration across studies. Their clinical utility depends on rigorous external validation and local recalibration, particularly when incorporating imaging or molecular predictors. Future research should prioritize standardized CHD outcomes, consistent calibration reporting, decision-analytic assessments, and the development of transportable multimodal prediction models across diverse populations.<\/jats:p>","DOI":"10.3390\/diagnostics16050765","type":"journal-article","created":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T08:51:33Z","timestamp":1772614293000},"page":"765","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Prognostic Models for Predicting Coronary Heart Disease Risk in Patients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0934-702X","authenticated-orcid":false,"given":"Maicol","family":"Cortez-Sandoval","sequence":"first","affiliation":[{"name":"Escuela de Medicina Humana, Universidad Cient\u00edfica del Sur, Lima 15067, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5433-4044","authenticated-orcid":false,"given":"C\u00e9sar J.","family":"Eras L\u00e9vano","sequence":"additional","affiliation":[{"name":"Escuela de Posgrado, Universidad Privada \u201cSan Juan Bautista\u201d, Lima 15067, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joaqu\u00edn Fern\u00e1ndez","family":"\u00c1lvarez","sequence":"additional","affiliation":[{"name":"NeumoVigo I+i Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312 Vigo, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6342-6733","authenticated-orcid":false,"given":"Jorge","family":"L\u00f3pez-Leal","sequence":"additional","affiliation":[{"name":"Instituto Mexicano del Seguro Social, \u00d3rgano de Operaci\u00f3n Administrativa Desconcentrada Estatal en Chihuahua, Chihuahua 31000, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0835-0454","authenticated-orcid":false,"given":"Lady","family":"Mor\u00e1n Valenzuela","sequence":"additional","affiliation":[{"name":"Escuela de Medicina, Universidad Cat\u00f3lica Santiago de Guayaquil, Guayaquil 090615, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raul H.","family":"Sandoval-Ato","sequence":"additional","affiliation":[{"name":"Escuela de Medicina, Universidad Privada Antenor Orrego, Trujillo 13008, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9168-8995","authenticated-orcid":false,"given":"Hady","family":"Keita","sequence":"additional","affiliation":[{"name":"Universidad de la Sierra Sur, Oaxaca 70800, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Gomez-Lujan","sequence":"additional","affiliation":[{"name":"Escuela de Medicina, Universidad Nacional Federico Villarreal, Lima 15001, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5700-4372","authenticated-orcid":false,"given":"Fernando M.","family":"Quevedo Candela","sequence":"additional","affiliation":[{"name":"Instituto Nacional Cardiovascular, INCOR, Lima 15076, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4571-328X","authenticated-orcid":false,"given":"Jes\u00fas I. Parra","family":"Prado","sequence":"additional","affiliation":[{"name":"Escuela de Medicina, Universidad Aut\u00f3noma de Chihuahua, Chihuahua 31125, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9403-1566","authenticated-orcid":false,"given":"Jos\u00e9 Luis","family":"Mu\u00f1oz-Carrillo","sequence":"additional","affiliation":[{"name":"Laboratorio de Inmunolog\u00eda, Centro Universitario de los Lagos, Universidad de Guadalajara, Lagos de Moreno 47460, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6546-3570","authenticated-orcid":false,"given":"Oriana","family":"Rivera-Lozada","sequence":"additional","affiliation":[{"name":"Vicerrectorado de Investigaci\u00f3n, Universidad Se\u00f1or de Sip\u00e1n, Chiclayo 14001, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2896-1407","authenticated-orcid":false,"given":"Joshuan J.","family":"Barboza","sequence":"additional","affiliation":[{"name":"Vicerrectorado de Investigaci\u00f3n, Universidad Se\u00f1or de Sip\u00e1n, Chiclayo 14001, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7003","DOI":"10.1038\/s41598-025-85692-x","article-title":"Construction of a Prediction Model for Coronary Heart Disease in Type 2 Diabetes Mellitus: A Cross-Sectional Study","volume":"15","author":"Zhang","year":"2025","journal-title":"Sci. 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