{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T10:07:38Z","timestamp":1772273258544,"version":"3.50.1"},"posted":{"date-parts":[[2026,2,2]]},"group-title":"Urology","reference-count":32,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T00:00:00Z","timestamp":1769990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.medrxiv.org\/about\/FAQ#license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,2,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                <jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>Bladder cancer is associated with significant morbidity and mortality in the US, with 85,000 new cases and 17,400 deaths expected in 2025. Black patients are more likely than White patients to be diagnosed with bladder cancer at advanced stages, as are female patients compared with male patients. We examine whether differences in cancer diagnosis rates by race and sex can explain the observed variability using a simulation model and project outcomes of potential improvement in diagnosis.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We developed a state transition model for bladder cancer to simulate four cohorts based on sex (males, females) and race (Blacks, Whites) from birth through various health states, including disease-free, preclinical stages (0a\/0is - IV), clinical stages (0a\/0is - IV), and death (bladder cancer or other cause death). Parameters related to disease onset, progression, and diagnosis were estimated by calibrating the model to race- and sex-specific incidence rates by age, and stage distribution at diagnosis for cases diagnosed between 2015 and 2019 in SEER 17 registry areas. We conducted a scenario analysis to examine the impact of differences in diagnosis rates on stage distribution and life expectancy, assuming that Black males (or females) and White females had diagnosis rates similar to those of White males.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The calibrated model attributes the differences in stage distribution to lower diagnosis rates in White females (hazard ratio, [HR] = 0.95, 95% credible interval [CI]: 0.92 - 0.96), Black males (0.80, 95% CI: 0.75 - 0.81) and Black females (0.56, 95% CI: 0.53 - 0.58), relative to White males. If diagnosis rates for all demographic groups were similar to White males, the expected life span of a 65-year-old bladder cancer patient would increase by 0.2 years for White females (from 13.8 to 13.9 years), 0.6 years for Black males (from 10.6 to 11.1 years), and 1.9 years for Black females (from 10.5 to 12.4 years).<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Differences in diagnosis rates of bladder cancer by race and sex explain the observed differences in stage distribution at diagnosis. Targeted interventions aimed at improving diagnosis rates have the potential to substantially improve survival for patients with bladder cancer.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.01.30.26344972","type":"posted-content","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T19:45:22Z","timestamp":1770061522000},"source":"Crossref","is-referenced-by-count":1,"title":["Differences in Bladder Cancer Diagnosis by Demographic Factors: A Simulation Modeling Analysis"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4948-968X","authenticated-orcid":false,"given":"Praveen","family":"Kumar","sequence":"first","affiliation":[{"name":"Department of Health Policy and Management, School of Public Health, University of Pittsburgh"},{"name":"Public Health Dynamics Laboratory, School of Public Health, University of Pittsburgh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5076-1172","authenticated-orcid":false,"given":"Fernando","family":"Alarid-Escudero","sequence":"additional","affiliation":[{"name":"Department of Health Policy, School of Medicine, Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tanvi V","family":"Chiddarwar","sequence":"additional","affiliation":[{"name":"Division of Health Policy and Management, School of Public Health, University of Minnesota"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0459-1579","authenticated-orcid":false,"given":"David Ulises","family":"Garibay-Trevi\u00f1o","sequence":"additional","affiliation":[{"name":"School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Krishna Roy","family":"Chowdhury","sequence":"additional","affiliation":[{"name":"School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prince","family":"Peprah","sequence":"additional","affiliation":[{"name":"School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruce L","family":"Jacobs","sequence":"additional","affiliation":[{"name":"Department of Urology, Division of Health Services Research, University of Pittsburgh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karen M","family":"Kuntz","sequence":"additional","affiliation":[{"name":"Division of Health Policy and Management, School of Public Health, University of Minnesota"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stella K.","family":"Kang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Columbia University Irving Medical Center"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3990-1848","authenticated-orcid":false,"given":"Thomas A.","family":"Trikalinos","sequence":"additional","affiliation":[{"name":"Department of Health Services, Policy, and Practice and Center for Evidence Synthesis in Health, School of Public Health, Brown University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hawre","family":"Jalal","sequence":"additional","affiliation":[{"name":"School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2026020410450712000_2026.01.30.26344972v1.1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21871"},{"key":"2026020410450712000_2026.01.30.26344972v1.2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2022.11.023"},{"key":"2026020410450712000_2026.01.30.26344972v1.3","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.23986"},{"key":"2026020410450712000_2026.01.30.26344972v1.4","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0142(20000915)"},{"key":"2026020410450712000_2026.01.30.26344972v1.5","doi-asserted-by":"publisher","DOI":"10.1016\/j.juro.2006.04.074"},{"key":"2026020410450712000_2026.01.30.26344972v1.6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jamcollsurg.2005.09.009"},{"key":"2026020410450712000_2026.01.30.26344972v1.7","doi-asserted-by":"publisher","DOI":"10.1002\/cam4.4917"},{"key":"2026020410450712000_2026.01.30.26344972v1.8","doi-asserted-by":"publisher","DOI":"10.1016\/j.urolonc.2017.12.015"},{"key":"2026020410450712000_2026.01.30.26344972v1.9","unstructured":"Surveillance , Epidemiology and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database: Incidence - SEER Research Plus Data (Specialized Staging Over Time Fields), 12 Registries, Nov 2021 Sub (1992-2019) - Linked To County Attributes - Total U.S., 1969-2020 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2022, based on the November 2021 submission. 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