Evidence map›Paper›PMID 41439159›Full record

ArticleEuropean urology open science2026

Bladder Cancer Burden in the USA: Population Scenarios for 2040.

Hawre Jalal, Stella K Kang, Fernando Alarid-Escudero, Stavroula A Chrysanthopoulou, David Ulises Garibay-Trevino, Bruce L Jacobs, Karen M Kuntz, Praveen Kumar, Jonah H Popp, Yuliia Sereda and 4 more

Abstract read
In one paragraph

Article in European urology open science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Hawre JalalSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.
Stella K KangDepartment of Radiology, Columbia University Irving Medical Center, New York, NY, USA.
Fernando Alarid-EscuderoDepartment of Health Policy, Stanford School of Medicine, Stanford, CA, USA.
Stavroula A ChrysanthopoulouDepartment of Biostatistics and Center for Biostatistics and Health Data Science, School of Public Health, Brown University, Providence, RI, USA.
David Ulises Garibay-TrevinoSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.
Bruce L JacobsDivision of Health Services Research, Department of Urology, University of Pittsburgh, Pittsburgh, PA, USA.
Karen M KuntzDivision of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, MN, USA.
Praveen KumarDepartment of Health Policy and Management, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Jonah H PoppDepartment of Health Services, Policy, and Practice and Center for Evidence Synthesis in Health, School of Public Health, Brown University, Providence, RI, USA.
Yuliia SeredaDepartment of Health Services, Policy, and Practice and Center for Evidence Synthesis in Health, School of Public Health, Brown University, Providence, RI, USA.
Mutita SiriruchatanonDepartment of Radiology, Columbia University Irving Medical Center, New York, NY, USA.
John B WongDepartment of Medicine, Division of Clinical Decision Making, Tufts Medical Center, Tufts University School of Medicine, Boston, MA, USA.
Thomas A TrikalinosSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.
CISNET Bladder Cancer Modeling Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objective: Bladder cancer is the sixth most common cancer among men and is expensive to manage. We independently developed three microsimulation models that describe its natural history and explain epidemiological trends. We projected bladder cancer burden in the USA through 2040 to inform workforce planning. Methods: We calibrated the models to the Surveillance, Epidemiology and End Results (SEER) program incidence data and standardized key inputs. For White men, the highest-incidence subgroup, the models inferred unobservable epidemiological metrics, including lifetime risks by birth cohort and ages of the key events in the natural history. We simulated individual life histories under calibrated parameter sets and summarized the outcomes as yearly rates and counts. Key findings and limitations: Each model's predictions reproduced SEER age- and stage-specific incidence data. Across models, the lifetime risk of bladder cancer grew from approximately 1.5-2.4% in the 1910 to 3.1-4.4% in the 2010 birth cohorts, consistent with longevity and smoking exposure patterns. Of the cancer cases, 75% instantiate after ages 61-64 yr. The median model durations from when a cancer is screen detectable to its clinical manifestation were 2.1-3.3 yr, with a wide range across individuals. Through 2040, the incidence standardized to the 2000 US population declined by 0.4-0.6%/yr (consistent with the declining smoking rates, the most important environmental risk factor), but the annual incidence and new cases increased by 1.5-1.8%/yr (because the baby boomer population is living longer). Modeling supplements incomplete data with assumptions, but similar findings across independent models suggest some robustness to assumptions. Conclusions and clinical implications: Projected cohort longevity and smoking patterns imply an increased disease burden in the future, which may benefit from commensurate increased research and resources. From the inferred natural history, we speculate a theoretical opportunity for screening, which should be investigated with dedicated modeling and empirical studies. Patient summary: Three computer simulation models predicted the future incidence of bladder cancer burden in White men, in whom this cancer is most common. The models found that although the future incidence of bladder cancer would decrease slightly over time (consistent with the declining smoking rates, the most important environmental risk factor), the overall disease burden increased because the baby boomer population is living longer.

Indexed as

Bladder cancerComparative modelingEarly detectionEpidemiological projectionsSimulation

Identifiers

PMID41439159
PMCPMC12721285

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.