Costs of cancer care for use in economic evaluation: a UK analysis of patient-level routine health system data
Menée au Royaume-Uni à partir de données de patients atteints d'un cancer de la prostate (104 cas), du côlon-rectum (145 cas) et du sein (223 cas), cette étude présente une évaluation des coûts associés aux soins et analyse la possibilité d'utiliser les données collectées en routine pour produire des estimations économiques
Background: The rising financial burden of cancer on health-care systems worldwide has led to the increased demand for evidence-based research on which to base reimbursement decisions. Economic evaluations are an integral component of this necessary research. Ascertainment of reliable health-care cost and quality-of-life estimates to inform such studies has historically been challenging, but recent advances in informatics in the United Kingdom provide new opportunities. Methods: The costs of hospital care for breast, colorectal and prostate cancer disease-free survivors were calculated over 15 months from initial diagnosis of cancer using routinely collected data within a UK National Health Service (NHS) Hospital Trust. Costs were linked at patient level to patient-reported outcomes and registry-derived sociodemographic factors. Predictors of cost and the relationship between costs and patient-reported utility were examined. Results: The study population included 223 breast cancer patients, 145 colorectal and 104 prostate cancer patients. The mean 15-month cumulative health-care costs were £12 595 (95% CI £11 517–£13 722), £12 643 (£11 282–£14 102) and £3722 (£3263–£4208), per-patient respectively. The majority of costs occurred within the first 6 months from diagnosis. Clinical stage was the most important predictor of costs for all cancer types. EQ-5D score was predictive of costs in colorectal cancer but not in breast or prostate cancer. Conclusion: It is now possible to evaluate health-care cost using routine NHS data sets. Such methods can be utilised in future retrospective and prospective studies to efficiently collect economic data.