ArticleHealth economics2015
Parameter Heterogeneity In Breast Cancer Cost Regressions - Evidence From Five European Countries.
Article in Health economics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Trends and drivers of pharmaceutical expenditures from systemic anti-cancer therapy.The European journal of health economics : HEPAC : health economics in prevention and care · 2023Article
- Heterogeneity in the costs of medical care among people living with HIV/AIDS in the United States.AIDS (London, England) · 2019Article
- Parameter Heterogeneity In Breast Cancer Cost Regressions - Evidence From Five European Countries.Health economics · 2015Article
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We investigate parameter heterogeneity in breast cancer 1-year cumulative hospital costs across five European countries as part of the EuroHOPE project. The paper aims to explore whether conditional mean effects provide a suitable representation of the national variation in hospital costs. A cohort of patients with a primary diagnosis of invasive breast cancer (ICD-9 codes 174 and ICD-10 C50 codes) is derived using routinely collected individual breast cancer data from Finland, the metropolitan area of Turin (Italy), Norway, Scotland and Sweden. Conditional mean effects are estimated by ordinary least squares for each country, and quantile regressions are used to explore heterogeneity across the conditional quantile distribution. Point estimates based on conditional mean effects provide a good approximation of treatment response for some key demographic and diagnostic specific variables (e.g. age and ICD-10 diagnosis) across the conditional quantile distribution. For many policy variables of interest, however, there is considerable evidence of parameter heterogeneity that is concealed if decisions are based solely on conditional mean results. The use of quantile regression methods reinforce the need to consider beyond an average effect given the greater recognition that breast cancer is a complex disease reflecting patient heterogeneity.
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