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Lane JD, Friedberg MW, Bennett CL. Associations Between Industry Sponsorship and Results of Cost-effectiveness Analyses of Drugs Used in Breast Cancer Treatment. JAMA Oncol. 2016;2(2):274–276. doi:10.1001/jamaoncol.2015.3928
A 1999 investigation1 found that industry sponsorship of cost-effectiveness analyses (CEAs) for oncology drugs was associated with lower likelihood of reporting unfavorable conclusions relative to CEAs with other sponsorship. Over the past 15 years, the CEA literature for oncology drugs has expanded dramatically, and oncology now accounts for the largest single pharmaceutical sales area worldwide.2 We sought to determine whether the association between industry sponsorship and CEA results has persisted.
We examined CEAs for breast cancer, the most common target diagnosis among oncology CEAs (36% of studies).3 We obtained data on all such CEAs published between 1991 and 2012 from the Tufts Cost-Effectiveness Analysis Registry, which was created by searching MEDLINE for all English language CEAs using the key words “QALYs” (quality-adjusted life-years), “cost-utility analysis,” and “breast cancer.” From the registry we extracted study characteristics, results (cost per QALY), and registry-assigned quality ratings (which ranged from 2 to 6).4 We considered a study industry-sponsored if a pharmaceutical company provided funding or if 1 or more study authors was a company employee. Study authors provided sponsorship information for 13 studies with unclear funding information in the publication.
We converted each study’s results to 2013 US dollars using purchasing power parity conversion factors, categorized study results based on 3 thresholds ($50 000, $100 000, and $150 000/QALY), and classified studies as “cost-effective” if all results were equal to or more favorable than the chosen threshold, “not cost-effective” if none were, or “mixed” otherwise (note: each study could contain multiple analyses, with varying assumptions). Using JMP Pro statistical software(version 11.0.0, SAS Institute), we tested bivariate associations between industry sponsorship and study characteristics. We then fitted logistic regressions to estimate independent associations between industry sponsorship and study results, adjusting for drug class, cancer stage targeted, and study quality score.
Of 105 CEA studies, 65 were industry funded (Table 1). Study quality ratings were nonsignificantly higher among industry-sponsored studies (mean rating, 4.8 vs 4.4 among studies with other sponsorship; P = .09).
Industry-sponsored studies were statistically significantly more likely than other-sponsored studies to report favorable cost-effectiveness results: 75.4% vs 40.0% at $50 000/QALY (P = .004), 80.0% vs 57.5% at $100 000/QALY (P = .03), and 87.7% vs 67.5% at $150 000/QALY (P = .04) (Table 2). Among the subset of CEAs with high quality ratings (≥4.5), industry-sponsored studies were more likely to report favorable findings (75.5% vs 45.5%, P = .04, at the $50 000/QALY threshold).
Our analysis of breast cancer CEAs suggests that pharmaceutical industry–sponsored studies continue to be more likely to report favorable estimates than studies with other sponsorship. These findings have multiple possible explanations.
First, most CEAs have retrospective designs, which can allow investigators to identify and then conduct, based on early looks at clinical and resource profiles, those trials most likely to yield positive outcomes. Second, potential conflicts of interest exist. Pharmaceutical companies can exert influence through grants, educational funds, or manuscript review requirements. Investigators set the values assigned to quality of life, determine the price and duration of interventions, and make other methodological choices that can affect study findings. Making these choices transparently and before results are known could enhance the credibility of CEAs.5
Our study has limitations. We examined drugs for breast cancer only. Financial relationships between pharmaceutical companies and researchers were considered, but other less readily detectable factors influencing study findings may exist.
Additional studies are needed to determine whether similar associations between industry sponsorship and results exist for CEAs of drugs treating other cancers. Registering CEAs and their methods at inception could help address the conflicts of interest that might underlie these associations.
Corresponding Author: Charles L. Bennett, MD, PhD, MPP, South Carolina College of Pharmacy, University of South Carolina, 715 Sumter St, Coker Life Science, Room 311, Columbia, SC 29208 (firstname.lastname@example.org).
Published Online: December 10, 2015. doi:10.1001/jamaoncol.2015.3928.
Author Contributions: Dr Lane had full access to all of the data in the study and takes responsibility for the integrity of the data and accuracy of data analysis.
Study concept and design: All authors.
Acquisition, analysis, or interpretation of data: Lane, Friedberg.
Drafting of the manuscript: Lane.
Critical revision of the manuscript for important intellectual content: Friedberg, Bennett.
Statistical analysis: Lane, Friedberg.
Administrative, technical, or material support: Bennett.
Supervision: Friedberg, Bennett.
Conflict of Interest Disclosures: None reported.
Funding/Support: This study was supported in part by the National Cancer Institute (1R01CA165609-01A1), the South Carolina SmartState Program, and the Doris Levkoff Meddin Medication Safety Center.
Role of the Funder/Sponsor: These sponsors did not have a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
Additional Contributions: We thank Peter J. Neumann, ScD (Tufts Medical Center) and the Center for the Evaluation of Value and Risk in Health at Tufts Medical Center for establishing, maintaining, and making available the Cost-Effectiveness Analysis Registry. Dr Neumann did not receive compensation for his contribution.