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Preliminary analysis of the cost-effectiveness of the National Bowel Cancer Screening Program: demonstrating the potential value of comprehensive real world data


  • Funding: BioGrid Australia Pty Ltd supported the study.

  • Conflict of interest: None.

Ben Tran, The Royal Melbourne Hospital, Grattan Street, Parkville, Vic. 3050, Australia. Email:


Background/Aim:  The complexity and cost of treating cancer patients is escalating rapidly and increasingly difficult decisions are being made regarding which interventions provide value for money. BioGrid Australia supports collection and analysis of comprehensive treatment and outcome data across multiple sites. Here, we use preliminary data regarding the National Bowel Cancer Screening Program (NBCSP) and stage-specific treatment costs for colorectal cancer (CRC) to demonstrate the potential value of real world data for cost-effectiveness analyses (CEA).

Methods:  Data regarding the impact of NBCSP on stage at diagnosis were combined with stage-specific CRC treatment costs and existing literature. An incremental CEA was undertaken from a government healthcare perspective, comparing NBCSP with no screening. The 2008 invited population (n= 681 915) was modelled in both scenarios. Effectiveness was expressed as CRC-related life years saved (LYS). Costs and benefits were discounted at 3% per annum.

Results:  Over the lifetime and relative to no screening, NBCSP was predicted to save 1265 life years, prevent 225 CRC cases and cost an additional $48.3 million, equivalent to a cost-effectiveness ratio of $38 217 per LYS. A scenario analysis assuming full participation improved this to $23 395.

Conclusions:  This preliminary CEA based largely on contemporary real world data suggests population-based faecal occult blood test screening for CRC is attractive. Planned ongoing data collection will enable repeated analyses over time, using the same methodology in the same patient populations, permitting an accurate analysis of the impact of new therapies and changing practice. Similar CEA using real world data related to other disease types and interventions appears desirable.