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.
BACKGROUND/AIM: The complexity and cost of treating cancerpatients 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.
Authors: Dayna R Cenin; D James B St John; Melissa J N Ledger; Terry Slevin; Iris Lansdorp-Vogelaar Journal: Med J Aust Date: 2014-10-20 Impact factor: 7.738
Authors: Sujha Subramanian; Florence K L Tangka; Sonja Hoover; Marion Nadel; Robert Smith; Wendy Atkin; Julietta Patnick Journal: J Public Health Manag Pract Date: 2016 Sep-Oct
Authors: Dayna R Cenin; Steffie K Naber; Anne C de Weerdt; Mark A Jenkins; David B Preen; Hooi C Ee; Peter C O'Leary; Iris Lansdorp-Vogelaar Journal: Cancer Epidemiol Biomarkers Prev Date: 2019-11-20 Impact factor: 4.254
Authors: Nishi Kothari; Richard Kim; Robert N Jorissen; Jayesh Desai; Jeanne Tie; Hui-Li Wong; Ian Faragher; Ian Jones; Fiona L Day; Shan Li; Anuratha Sakthinandeswaren; Michelle Palmieri; Lara Lipton; Michael Schell; Jamie K Teer; David Shibata; Timothy Yeatman; Oliver M Sieber; Peter Gibbs; Ben Tran Journal: Acta Oncol Date: 2014-12-31 Impact factor: 4.089
Authors: Mary Dillon; Louisa Flander; Daniel D Buchanan; Finlay A Macrae; Jon D Emery; Ingrid M Winship; Alex Boussioutas; Graham G Giles; John L Hopper; Mark A Jenkins; Driss Ait Ouakrim Journal: PLoS Med Date: 2018-08-16 Impact factor: 11.069
Authors: Michael G Collins; Edward Teo; Stephen R Cole; Choy-Yoke Chan; Stephen P McDonald; Graeme R Russ; Graeme P Young; Peter A Bampton; P Toby Coates Journal: BMJ Date: 2012-07-25