SCOUT (NYU) Columbia University Irving Medical Center

Purpose

Simulate the natural history of bladder cancer, incorporating broad-ranging risk for urinary system cancers, to evaluate screening and management strategies in both average- and high-risk populations.

Summary

Simulation of Cancers of the Urinary Tract Model (SCOUT) is a discrete-time non-homogenous Markov microsimulation model.sup.fw-bold¹ The model simulates a hypothetical U.S. cohort with broad-ranging risk for bladder cancers and competing mortality risks. The incorporated risk factors include sex, tobacco smoking status, diabetes mellitus, hypertension, and chronic kidney disease (CKD). SCOUT was developed to assess the comparative effectiveness of screening and management strategies for bladder cancers in general population and subpopulations with elevated risk of bladder cancer.

As CKD is a well-established risk factor for urothelial cancers and prevalent in U.S. adults, SCOUT simulates the development and progression of CKD.^{2, 3} It models seven stages of CKD (no CKD, stage 1, stage 2, stage 3a, stage 3b, stage 4, stage 5), which is defined by glomerular filtration rate (GFR) and albuminuria levels, and incorporates risk factors of CKD: hypertension and diabetes.⁴ Using an annual cycle, a simulated person may develop hypertension and/or diabetes, experience a decline in GFR, develop micro- or macro-albuminuria. The annual rates of GFR decline and the annual transition probability among albuminuria levels depends on age, sex, and presence/absence of hypertension and diabetes. Those with CKD progress in increasing severity of stages, where elevated CKD stage is associated with higher risk of bladder cancer and cardiovascular disease (CVD) morality risk. In addition to CKD, SCOUT assigns static smoking status of never, former, and current based on the estimated distribution of smoking from the National Health and Nutrition Examination Survey (NHANES).

SCOUT simulates the natural history of bladder with four main health states: disease-free, non-muscle invasive bladder cancers or NMIBC (Ta, Tis, T1), muscle invasive bladder cancers or MIBC (T2, T3, T4 excluding metastatic disease), and metastasis using a monthly cycle. At each cycle, a simulated person may experience one of the following: remain disease-free, develop low-grade Ta or high-grade Ta that is initially undetectable, transition from undetectable to detectable state for those with NMIBC, transition from detectable to detected stage (for those with NMIBC), transition from low to high grade (for those with NMIBC), and experience an increase in T stage. Once a person reaches the metastatic state, they are at risk for metastatic blader cancer death in addition to other causes of death including non-CVD and CVD. Undetectable states are defined as the presence of tumor without detectable clinical signs or symptoms. Detectable states are defined as having symptoms of either gross or macro hematuria, which is a common symptom of bladder cancer. Proportion of gross and macrohematuria depends on the stage of bladder cancer. As CKD itself can result in hematuria, SCOUT allows a small proportion of CKD patients to develop asymptomatic hematuria as well. The monthly probability of developing tumors depends on age, sex, smoking status, and CKD stage. The monthly transition probability among bladder cancer states from Ta to T4 depends on age and sex. SCOUT is calibrated to bladder cancer incidence according to SEER Cancer registry.

Public health impact

By incorporating major risk factors of bladder cancer and comorbidities, SCOUT can be used for assessing the comparative effectiveness of potential screening and management strategies in individuals with differential levels of risks. Based on the risk-based urinary bladder screening approaches, our model could potentially inform new clinical guidelines according to urinary system cancer risks, identify the elevated risk groups who benefit tremendously from programmatic early-stage detection and curative treatment, and inform trial designs for a common chronic systemic condition.

References

1. Jalal H, Kang SK, Alarid-Escudero F, Chrysanthopoulou SA, Garibay-Trevino DU, Kuntz KM, Praveen K, Popp JH, Sereda Y, Siriruchatanon M, Wong JB, Trikalinos TA. Comparative Modeling of the Burden of Bladder Cancer in the United States. 2025.
2. United States Renal Data System. 2023 USRDS Annual Data Report: Epidemiology of kidney disease in the United States. 2023.
3. Brooks ER, Siriruchatanon M, Prabhu V, Charytan DM, Huang WC, Chen Y, Kang SK. Chronic kidney disease and risk of kidney or urothelial malignancy: systematic review and meta-analysis. Nephrol Dial Transplant. 2024;39(6):1023-33. doi: 10.1093/ndt/gfad249.
4. Levin A, Stevens PE. Summary of KDIGO 2012 CKD Guideline: behind the scenes, need for guidance, and a framework for moving forward. Kidney Int. 2014;85(1):49-61. Epub 20131127. doi: 10.1038/ki.2013.444.