Prostate cancer (PCa) screening is still a controversial topic in the scientific community, this is mostly related to the low specificity of PSA value that has been the cause of overdiagnosis of clinically insignificant PCa, with lack of survival improvement. Imaging plays a valuable role in the non-invasive diagnosis of PCa. MRI has been recognized as "state of the art" management tool and the most cost-effective exam for PCa detection in patient at risk. In the screening setting, instead, the role of MRI is still under investigation. At the same time, Health technology Assessment (HTA) is a well-known approach that has as focus to appraise technologies for the provision of health care to assess not just their safety and efficacy but also whether the outcomes they achieve justify their costs.
With this background, the primary aim of the project is to evaluate the cost-effectiveness of non-contrast MRI in adjunct to an artificial intelligence (AI) tool, as secondary screening test for early PCa detection, in males aged between 49-69 years. The project will be conducted in adjunct to the ongoing randomized controlled trial PROSA (ClinicalTrials Ident: NCT04803188), on a cohort of 710 patients, employees of the AOU Policlinico Umberto I and Sapienza University, enrolled by the Occupational Medicine Division.
The HTA will cover an evaluation of the epidemiology of PCa, of the efficacy and safety of non-contrast MRI and AI using the PRISMA statement methodology, and of the economic analysis including cost-effectiveness, cost-utility, cost-benefit and budget impact assessments. Also, the organizational aspects related to the mode of delivery of MRI, patient preferences from the perspective of patient-reported outcome (defined as any outcome concerning the state of health reported directly by the patient), and of the ethical aspects of introducing non-contrast MRI and AI to maximize the benefits and minimize the harms of research, will be analyzed.
PCa screening, as already mentioned, is still a controversial topic in the scientific community, this is mostly related to the low specificity of PSA value that has been the cause of overdiagnosis of ciPCa for many years (1). Recently, Van Poppel et al. (2) proposed a novel early detection algorithm for PCa that sees risk stratification for prostate biopsy with multivariable risk prediction models and/or contrast MRI mandatory for an individualized assessment of the potential risk of having a csPCa detection, defining annual PSA testing as redundant. In research settings the role of MRI without contrast medium is investigated to push toward a more personalized, less invasive, and highly cost-effective diagnostic workup. Indeed, in the diagnostics of prostate cancer, due to the steady increase in MRI demand, there are growing concerns about the lack of availability of qualified radiologist and radiographers, that would allow to face the upcoming large demand of prostate MRI. In addition, Porter et al. (3) modeled the potential cost of bpMRI to determine cost savings and predicted that performing short protocol non-contrast MRI would lead to an increase in gross profit of $10,710.98 in a 9 hours business day. Recently, the PI-RADS steering committee released a position statement on the role of non-contrast MRI in biopsy naïve patients with clinical suspicion of PCa (4). The authors detailed possible approaches to the growing demand for prostate MRI, proposing solutions that should increase operational benefits without compromising diagnostic performance, quality, and service delivery. Also, they recommended the use of risk grouping for the risk assessment of biopsy naïve men for whom contrast medium injection is advisable and to guide biopsy and/or focal treatment. The proposed risk stratification consisted of grouping men into low-, intermediate-, and high-risk categories, using proven clinical risk assessment calculators and nomograms. In detail, the Committee suggested to screen low-risk patients to rule out csPCa using bpMRI and lower the diagnosis of ciPCa; instead, for intermediate- and high-risk patients contrast-enhanced MRI is recommended in order to rule out/in and rule in csPCa, respectively (discriminating PI-RADS 3 foci and confirming the disease); for patients at very high-risk of PCa, non-contrast MRI is recommended to rule in csPCa, to confirm the diagnosis, for biopsy/therapy planning and for local staging.
At the same time, the rapid technological innovation in radiology has led to continuous advances causing a strong transformation in the specialty. Soon, the highest impact on medical imaging will likely derive from artificial intelligence (AI) technology developments. Indeed, in the age of the Big Data, AI and its application, have been the object of many investigations, including the diagnosis of PCa with non-contrast MRI showing promising results. However, AI systems should ensure that the main benefits of biopsy avoidance are delivered while maintaining consistent high specificities, at a range of disease prevalence, and this will be assessed in the project. AI-based, robust, standard operating procedures will increase the confidence of patients and payers, thus enabling the wider adoption of the MRI-directed approach for prostate cancer diagnosis (5).
Our approach will further improve the early detection of PCa, since it is performed in the screening setting, lowering the worldwide burden of over diagnosis and overtreatment.
An optimal economic assessment on ¿real-world¿ secondary screening using MRI would certainly promote the use of MRI with or without AI that would allow to improve accessibility to MRI. This becomes even truer when looking at the health and economic benefits of scaling up imaging modalities for prostate cancer, especially for low-income countries, to enable the developments of affordable imaging technologies and solutions.
Regarding the implementation of new preventive pathways, the HTA approach can highlight the characteristic elements to fully evaluate new disease screening, through the assessment of epidemiological dimensions, burden of disease, mathematical modeling, economic evaluation, organizational change and ELSI aspects, including the Patient-preferred outcomes.
References
1. Pinsky P, et al. Prostate Cancer Screening. A Perspective on the Current State of the Evidence. NEJM. 2017
2. Van Poppel H, et al. Early Detection of Prostate Cancer in 2020 and Beyond: Facts and Recommendations for the European Union and the European Commission. Eur Urol. 2021
3. Porter, et al. Financial implications of biparametric prostate MRI. Prostate Cancer Prostatic Dis. 2020
4. Schoots, et al. PI-RADS Committee Position on MRI Without Contrast Medium in Biopsy Naive Men with Suspected Prostate Cancer: A Narrative Review. AJR. 2020
5. Bonekamp et al. Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values. Radiology. 2018