New study assesses cost-effectiveness of Transpara as part of national screening protocol

As mammography screening programs around the world seek to adopt artificial intelligence to help them detect cancer more effectively and more efficiently, a key question emerges: given the cost of such tools and technology, are these strategies effective at delivering a return on investment in both monetary and human terms?

New research published in European Radiology seeks to explore that question by evaluating the cost-effectiveness of AI-assisted digital mammography (AI-DM) compared to conventional Swedish biennial breast cancer digital mammography screening (cDM in a double reader setting), and to investigate the change in cost-effectiveness based on sub-strategies of AI-DM. 

Using ScreenPoint Medical’s Transpara Detection solution as part of the AI-DM protocol, researchers modeled outcomes for AI-DM across biennial breast cancer screening in a Swedish population of women aged 40-74 years. Highlights from the study include: 

• Cost savings: The total costs, including both screening-related costs and breast cancer-related costs, were €3,468,967 and €3,528,288 per 1000 women for AI-DM and cDM, respectively. AI-DM resulted in a cost saving of €59,320 compared to cDM

• QALYs: Per 1000 individuals, AI-DM gained 10.8 quality-adjusted life years (QALYs) compared to cDM. Gaining QALYs at a lower cost means that the AI-DM screening strategy was dominant compared to cDM.
  
  
• Notably, break-even occurred at the second screening at age 42 years, leading researchers to conclude that “implementation of [Transpara] is clearly cost-effective as it reduces the total cost for the healthcare system and simultaneously results in a gain in QALYs.”

• Original research in European Radiology
• Link to MASAI study in The Lancet Digital Health