Causal Estimation of Long-term Intervention Cost-effectiveness Using Genetic Instrumental Variables: An Application to Cancer.
Padraig DixonRichard M MartinSean HarrisonPublished in: Medical decision making : an international journal of the Society for Medical Decision Making (2024)
The article demonstrates a novel method of assessing long-term intervention cost-effectiveness without relying on randomized controlled trials or cohort simulations.Mendelian randomization was used to estimate the causal effects of certain cancers on health care costs and quality-adjusted life-years (QALYs) using data from the UK Biobank cohort.Given causal data on the association of different cancer exposures on costs and QALYs, it was possible to simulate the cost-effectiveness of an anticancer intervention.Genetic liability to prostate cancer and breast cancer significantly affected health care costs and QALYs, but the hypothetical intervention using SGLT2 inhibitors for prostate cancer may not be cost-effective, depending on the drug's price for the new anticancer indication. The methods we propose and implement can be used to efficiently estimate intervention cost-effectiveness and to inform decision making in all manner of preventative and therapeutic contexts.
Keyphrases
- randomized controlled trial
- prostate cancer
- healthcare
- papillary thyroid
- radical prostatectomy
- electronic health record
- study protocol
- big data
- genome wide
- systematic review
- machine learning
- clinical trial
- gene expression
- squamous cell
- air pollution
- copy number
- cross sectional
- molecular dynamics
- lymph node metastasis
- childhood cancer