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Updated: Feb 12, 2026

3-D Cell Culture System for Studying Invasion and Evaluating Therapeutics in Bladder Cancer
Published on: September 13, 2018
Modelling cost-effectiveness of a biomarker-based approach to neoadjuvant chemotherapy for muscle-invasive bladder
Yair Lotan1, Solomon L Woldu1, Oner Sanli1,2
1Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Objectives:
To model the cost-effectiveness of a biomarker-based approach to select patients for neoadjuvant chemotherapy (NAC) before radical cystectomy (RC) in muscle-invasive bladder cancer (MIBC).
Patients And Methods:
We obtained data from the most recent clinical studies on patients with locally advanced MIBC treated by RC, including stage distributions, overall survival (OS) estimates, associated costs, and utilisation/response to NAC. Additionally, we estimated the putative efficacy of three biomarkers to select patients for NAC: DNA-repair gene panel [ataxia telangiectasia mutated (ATM), retinoblastoma 1 (RB1), and Fanconi anaemia complementation group C (FANCC)], excision repair cross-complementation group 2 (ERCC2), and ribonucleic acid (RNA) subtypes. A decision analysis model was developed to evaluate the cost-effectiveness of biomarker-based approaches to select patients with MIBC for NAC. Comparison of cost-effectiveness included RC alone, unselected NAC plus RC, and NAC based on the three aforementioned biomarkers.
Results:
The DNA-repair gene panel-based approach to NAC was the most cost-effective strategy (mean OS of 3.14 years, $31 482/life year). Under this approach, 38% would undergo NAC, about twice the number of patients who are currently receiving NAC for MIBC. Such an approach would improve mean OS by 5.2, 1.6, and 4.4 months compared to RC alone, a hypothetical scenario where all patients received NAC, and compared to current estimates of NAC utilisation, respectively.
Conclusions:
A biomarker-based strategy to identify patients with MIBC who should undergo NAC was more cost-effective than unselected use of NAC or RC alone. As further data becomes available, such a model may serve as a basis for incorporating biomarkers into clinical decision making.
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