Industry-sponsored cost-effectiveness analyses (CEAs) are more likely to conclude that a new drug, treatment, or medical device is more effective, compared with studies supported by independent funding, according to a new report.
Significant sponsorship bias occurs particularly often in analyses for drug interventions, as well as studies that involved cancer, the circulatory system, infectious diseases, metabolic diseases, and mental disorders.
“CEAs are widely used to support drug pricing and insurance coverage decision-making,” Feng Xie, PhD, the lead study author and a professor of health economics at McMaster University in Hamilton, Ontario, Canada, told Medscape Medical News.
“Industry could use the sponsorship to influence the conduct of the CEA to produce favorable results, which could bring in significant profits for them,” he said.
The study was published in BMJ on June 22.
Three Threshold Values
Xie and postdoctoral fellow Ting Zhou analyzed data from the Tufts Cost-Effectiveness Analysis Registry for studies published in Medline between 1976 and 2021.
The research team compared the characteristics of the cost-effectiveness analyses with and without industry sponsorship, where “nonindustry” represented studies with funding from governments, nonprofit organizations, healthcare organizations, professional membership organizations, or no listed sponsorship.
The researchers included analyses that reported incremental cost-effectiveness ratios using incremental cost per quality adjusted life year, which is a variable that allows for comparisons across studies, as well as sufficient information about the magnitude of the cost-effectiveness ratio.
After adjusting the ratios to 2021 US dollars, the research team used the common threshold values of $50,000, $100,000, and $150,000 to look at the association between industry sponsorship and the study conclusion.
Among the 8192 cost-effectiveness analyses included, 2437 were sponsored by industry, or 29.7%. Overall, 5877 cost-effectiveness analyses, or 71.7%, reported that the intervention was more effective and more expensive than the comparator, and about 21% reported that the intervention was better and cheaper.
Industry-sponsored analyses were more likely than nonindustry analyses to conclude that the intervention was more cost effective than the comparator at all thresholds. Industry-sponsored analyses were twice as likely to make that conclusion at $50,000, nearly three times as likely at $100,000, and 3.3 times as likely at $150,000.
Among the 5877 analyses that reported positive incremental costs, the incremental cost-effectiveness ratios from industry-sponsored studies were 33% lower than those from studies without industry funding.
Consequence: Higher Prices
“We were not surprised by the results, as previous research has consistently shown the sponsorship bias in CEAs,” Xie said. “We are surprised that we have not done much to improve that over two decades.”
In addition, industry-sponsored analyses conducted outside of North America were more likely to report that the intervention was cost effective at the $50,000 threshold. Analyses in Europe and central Asia were more than twice as likely to report favorable results, and other regions were 2.5 times more likely.
“The consequence is that eventually all of us, as payers and users of healthcare systems, pay higher prices for drugs or medical devices,” Xie said. “This affects high-, middle-, and low-income countries, but it could be worse for low- and middle-income countries where there is no capacity for independent CEA.”
Xie and colleagues are now focusing on specific disease areas where the sponsorship bias is among the worst. For instance, in this study, industry-sponsored analyses were more likely to report that the intervention was cost effective at the $50,000 threshold for cancer, mental disorders, and infectious and parasitic diseases, as well as those involving the circulatory, endocrine, and metabolic systems.
In addition, cost-effectiveness analyses on drugs accounted for nearly three-quarters of industry-sponsored studies, as compared with just over a third among nonindustry-sponsored studies. Some of the largest sponsorship biases occurred among the drug analyses, the study authors write, which could have major implications.
“Need for Transparency”
“CEA can be a very useful component to decision-making in healthcare. However, for it to be useful, decision-makers need to trust the results of the analyses. Biased results can lead to the adoption of therapies that do not benefit patients or health systems,” Adam Raymakers, PhD, a senior health economist at British Columbia Cancer Control Research in Vancouver, told Medscape Medical News.
Raymakers, who wasn’t involved with the study, cowrote an accompanying editorial in BMJ that calls for high-quality analyses and greater confidence in accurate conclusions.
“The sustainable delivery of healthcare requires good evidence to inform decision-making,” he said. “From drug development through to clinical trials and eventual patient access, there is a need for transparency and rigor in evidence generation. The rapid pace of drug development, and the associated high costs of new drugs, means that these features of evidence generation will be increasingly important.”
The study received no funding support. Xie and Raymakers have disclosed no relevant financial relationships.