{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T07:36:19Z","timestamp":1783409779122,"version":"3.54.6"},"reference-count":30,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:00:00Z","timestamp":1779062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Multiparametric MRI (mpMRI) and prostate-specific membrane antigen (PSMA) PET\/CT provide complementary information for prostate cancer diagnosis, but optimal integration strategies remain unclear. We aimed to develop and validate a multivariable model combining clinical and imaging parameters to predict clinically significant prostate cancer (csPCa).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This study included 1305 consecutive patients with suspected prostate cancer who underwent both mpMRI and 18F-PSMA PET\/CT with biopsy at Peking University First Hospital. The development and temporal validation cohorts were temporally divided; the development cohort was split into training (70%) and internal test (30%) sets. csPCa was defined as Gleason Grade Group \u22652. Predictors were selected using LASSO regression (1-standard error criterion) followed by forward stepwise logistic regression (AIC,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.05). Model performance was assessed by AUC, calibration plots, and decision curve analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The final model retained 3 predictors: PRIMARY score, PI-RADS score, and PSAD. The training AUC was 0.916. At the Youden Index cutoff (\u226584%), sensitivity was 79.3% and specificity 76.6%; at the recommended screening cutoff (\u226546%), sensitivity reached 96.0%. The AUC was 0.914 (95% CI: 0.882\u20130.941) in the internal test set and 0.837 (95% CI: 0.778\u20130.891) in temporal validation. The model showed good calibration (Brier score: 0.096) and superior clinical utility over individual imaging parameters.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The multivariable model integrating 18F-PSMA PET\/CT and mpMRI parameters provides accurate risk stratification for csPCa and may help optimize biopsy decisions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fonc.2026.1835850","type":"journal-article","created":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T05:43:07Z","timestamp":1779082987000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["A multivariable prediction model combining 18F-PSMA PET\/CT and mpMRI for clinically significant prostate cancer: development and validation"],"prefix":"10.3389","volume":"16","author":[{"given":"Chaojian","family":"Yu","sequence":"first","affiliation":[{"name":"Department of Urology, Peking University First Hospital","place":["Beijing, China"]},{"name":"Institute of Urology, Peking University","place":["Beijing, China"]},{"name":"National Urological Cancer Center","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zihou","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Urology, Peking University First Hospital","place":["Beijing, China"]},{"name":"Institute of Urology, Peking University","place":["Beijing, China"]},{"name":"National Urological Cancer Center","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peidong","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Urology, Peking University First Hospital","place":["Beijing, China"]},{"name":"Institute of Urology, Peking University","place":["Beijing, China"]},{"name":"National Urological Cancer Center","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingcheng","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Urology, Peking University First Hospital","place":["Beijing, China"]},{"name":"Institute of Urology, Peking University","place":["Beijing, China"]},{"name":"National Urological Cancer Center","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Cai","sequence":"additional","affiliation":[{"name":"Department of Urology, Peking University First Hospital","place":["Beijing, China"]},{"name":"Institute of Urology, Peking University","place":["Beijing, China"]},{"name":"National Urological Cancer Center","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhui","family":"Qiu","sequence":"additional","affiliation":[{"name":"Department of Urology, Peking University First Hospital","place":["Beijing, China"]},{"name":"Institute of Urology, Peking University","place":["Beijing, China"]},{"name":"National Urological Cancer Center","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kan","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Urology, Peking University First Hospital","place":["Beijing, China"]},{"name":"Institute of Urology, Peking University","place":["Beijing, China"]},{"name":"National Urological Cancer Center","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,18]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21871","article-title":"Cancer statistics, 2025","volume":"75","author":"Siegel","year":"2025","journal-title":"Ca"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1056\/nejmoa0810696","article-title":"Mortality results from a randomized prostate-cancer screening trial","volume":"360","author":"Andriole","year":"2009","journal-title":"N Engl J Med"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1097\/pas.0000000000000530","article-title":"The 2014 International Society of Urological Pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma: definition of grading patterns and proposal for a new grading system","volume":"40","author":"Epstein","year":"2016","journal-title":"Am J Surg Pathol"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2013.12.062","article-title":"Overdiagnosis and overtreatment of prostate cancer","volume":"65","author":"Loeb","year":"2014","journal-title":"Eur Urol"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2019.02.033","article-title":"Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2","volume":"76","author":"Turkbey","year":"2019","journal-title":"Eur Urol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1016\/s0140-6736(16)32401-1","article-title":"Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study","volume":"389","author":"Ahmed","year":"2017","journal-title":"Lancet"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1056\/nejmoa1801993","article-title":"MRI-targeted or standard biopsy for prostate-cancer diagnosis","volume":"378","author":"Kasivisvanathan","year":"2018","journal-title":"N Engl J Med"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019182946","article-title":"PI-RADS steering committee: the PI-RADS multiparametric MRI and MRI-directed biopsy pathway","volume":"292","author":"Padhani","year":"2019","journal-title":"Radiology"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1016\/s0022-5347(17)37393-7","article-title":"Prostate specific antigen density: a means of distinguishing benign prostatic hypertrophy and prostate cancer","volume":"147","author":"Benson","year":"1992","journal-title":"J Urol"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-017-3670-z","article-title":"68Ga-PSMA PET\/CT: joint EANM and SNMMI procedure guideline for prostate cancer imaging: version 1.0","volume":"44","author":"Fendler","year":"2017","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-016-3573-4","article-title":"F-18 labelled PSMA-1007: biodistribution, radiation dosimetry and histopathological validation of tumor lesions in prostate cancer patients","volume":"44","author":"Giesel","year":"2017","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2022.1030187","article-title":"Preclinical evaluation and first in human study of Al18F radiolabeled ODAP-urea-based PSMA targeting ligand for PET imaging of prostate cancer","volume":"12","author":"Ren","year":"2022","journal-title":"Front Oncol"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.121.263448","article-title":"The PRIMARY score: using intraprostatic 68Ga-PSMA PET\/CT patterns to optimize prostate cancer diagnosis","volume":"63","author":"Emmett","year":"2022","journal-title":"J Nucl Med"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2024.03.027","article-title":"EAU-EANM-ESTRO-ESUR-ISUP-SIOG guidelines on prostate cancer\u20142024 update. Part I: screening, diagnosis, and local treatment with curative intent","volume":"86","author":"Cornford","year":"2024","journal-title":"Eur Urol"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"J R Stat Soc Ser B Stat Method"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1016\/s0001-2998(78)80014-2","article-title":"Basic principles of ROC analysis","volume":"8","author":"Metz","year":"1978","journal-title":"Semin Nucl Med"},{"key":"B17","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1186\/s12916-019-1466-7","article-title":"Calibration: the Achilles heel of predictive analytics","volume":"17","author":"Van Calster","year":"2019","journal-title":"BMC Med"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1177\/0272989x06295361","article-title":"Decision curve analysis: a novel method for evaluating prediction models","volume":"26","author":"Vickers","year":"2006","journal-title":"Med Decision Making"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.25080\/majora-92bf1922-00a","article-title":"Data structures for statistical computing in Python","volume":"445","author":"McKinney","year":"2010","journal-title":"Scipy"},{"key":"B20","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.21037\/tau-22-832","article-title":"Prediction of clinically significant prostate cancer using a novel 68Ga-PSMA PET-CT and multiparametric MRI-based model","volume":"12","author":"Cheng","year":"2023","journal-title":"Trans Andrology Urol"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.117.198119","article-title":"Prostate cancer molecular imaging standardized evaluation (PROMISE): proposed miTNM classification for the interpretation of PSMA-ligand PET\/CT","volume":"59","author":"Eiber","year":"2018","journal-title":"J Nucl Med"},{"key":"B22","doi-asserted-by":"publisher","first-page":"501921","DOI":"10.1016\/j.acuroe.2026.501921","article-title":"Radical prostatectomy without prior biopsy in patients with positive PSMA PET and\/or mpMRI: A practiced but poorly documented approach. Retrospective multicenter cohort study","author":"Rodr\u00edguez","year":"2026","journal-title":"Actas Urol\u00f3gicas Espa\u00f1olas (English Edition)"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2014.17942","article-title":"Comparison of MR\/ultrasound fusion\u2013guided biopsy with ultrasound-guided biopsy for the diagnosis of prostate cancer","volume":"313","author":"Siddiqui","year":"2015","journal-title":"Jama"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2015.04.005","article-title":"Prediction models need appropriate internal, internal-external, and external validation","volume":"69","author":"Steyerberg","year":"2015","journal-title":"J Clin Epidemiol"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djj131","article-title":"Assessing prostate cancer risk: results from the Prostate Cancer Prevention Trial","volume":"98","author":"Thompson","year":"2006","journal-title":"J Natl Cancer Institute"},{"key":"B26","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.eururo.2009.08.025","article-title":"A risk-based strategy improves prostate-specific antigen\u2013driven detection of prostate cancer","volume":"57","author":"Roobol","year":"2010","journal-title":"Eur Urol"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(15)00361-7","article-title":"Prostate cancer screening in men aged 50\u201369 years (STHLM3): a prospective population-based diagnostic study","volume":"16","author":"Gr\u00f6nberg","year":"2015","journal-title":"Lancet Oncol"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1056\/nejmoa1910038","article-title":"MRI-targeted, systematic, and combined biopsy for prostate cancer diagnosis","volume":"382","author":"Ahdoot","year":"2020","journal-title":"N Engl J Med"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1111\/bju.16452","article-title":"Perspectives on technology: Prostate Imaging\u2010Reporting and Data System (PI\u2010RADS) interobserver variability","volume":"134","author":"Taya","year":"2024","journal-title":"BJU Int"},{"key":"B30","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1111\/bju.14858","article-title":"Detection and localisation of primary prostate cancer using 68gallium prostate\u2010specific membrane antigen positron emission tomography\/computed tomography compared with multiparametric magnetic resonance imaging and radical prostatectomy specimen pathology","volume":"126","author":"Kalapara","year":"2020","journal-title":"BJU Int"}],"container-title":["Frontiers in Oncology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2026.1835850\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T05:43:09Z","timestamp":1779082989000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2026.1835850\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,18]]},"references-count":30,"alternative-id":["10.3389\/fonc.2026.1835850"],"URL":"https:\/\/doi.org\/10.3389\/fonc.2026.1835850","relation":{},"ISSN":["2234-943X"],"issn-type":[{"value":"2234-943X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,18]]},"article-number":"1835850"}}