Critical Appraisal of Decision Models Used for the Economic Evaluation of Bladder Cancer Screening and Diagnosis: A Systematic Review

Background and Objective Bladder cancer is common among current and former smokers. High bladder cancer mortality may be decreased through early diagnosis and screening. The aim of this study was to appraise decision models used for the economic evaluation of bladder cancer screening and diagnosis, and to summarise the main outcomes of these models. Methods MEDLINE via PubMed, Embase, EconLit and Web of Science databases was systematically searched from January 2006 to May 2022 for modelling studies that assessed the cost effectiveness of bladder cancer screening and diagnostic interventions. Articles were appraised according to Patient, Intervention, Comparator and Outcome (PICO) characteristics, modelling methods, model structures and data sources. The quality of the studies was also appraised using the Philips checklist by two independent reviewers. Results Searches identified 3082 potentially relevant studies, which resulted in 18 articles that met our inclusion criteria. Four of these articles were on bladder cancer screening, and the remaining 14 were diagnostic or surveillance interventions. Two of the four screening models were individual-level simulations. All screening models (n = 4, with three on a high-risk population and one on a general population) concluded that screening is either cost saving or cost effective with cost-effectiveness ratios lower than $53,000/life-years saved. Disease prevalence was a strong determinant of cost effectiveness. Diagnostic models (n = 14) assessed multiple interventions; white light cystoscopy was the most common intervention and was considered cost effective in all studies (n = 4). Screening models relied largely on published evidence generalised from other countries and did not report the validation of their predictions to external data. Almost all diagnostic models (n = 13 out of 14) had a time horizon of 5 years or less and most of the models (n = 11) did not incorporate health-related utilities. In both screening and diagnostic models, epidemiological inputs were based on expert elicitation, assumptions or international evidence of uncertain generalisability. In modelling disease, seven models did not use a standard classification system to define cancer states, others used risk-based, numerical or a Tumour, Node, Metastasis classification. Despite including certain components of disease onset or progression, no models included a complete and coherent model of the natural history of bladder cancer (i.e. simulating the progression of asymptomatic primary bladder cancer from cancer onset, i.e. in the absence of treatment). Conclusions The variation in natural history model structures and the lack of data for model parameterisation suggest that research in bladder cancer early detection and screening is at an early stage of development. Appropriate characterisation and analysis of uncertainty in bladder cancer models should be considered a priority.