Sponsorship-related outcome selection bias in published economic studies of triptans: systematic review

Sponsorship bias in oncology cost effectiveness analysis

OBJECTIVES

Cost effectiveness analysis (CEA) has been increasingly used to inform cancer treatment coverage policy making worldwide. The primary objective of this study was to assess the association between industry sponsorship and CEA results in oncology.

STUDY DESIGN AND SETTING

All CEAs in oncology used incremental cost per quality-adjusted life year (QALY) as health effect identified from the Tufts CEA Registry since 1976 was analyzed. Descriptive analyses were performed to present and compare the characteristics of CEA funded by industry and non-industry. Robust logistic regression was performed to assess the relationship between the industry sponsorship and cost effective conclusion over a wide range of threshold values.

RESULTS

A total of 1537 CEAs in oncology published from 1976 to 2021 were included. There were 387 (25.2%) with the industry sponsorship. CEAs sponsored by the industry were more likely to report ICERs below $50,000/QALY (adjusted odds ratio (OR), 1.91, 95% confidence interval (CI), 1.45-2.51, P < 0.001), $100,000/QALY (2.74, 1.98-3.79, P < 0.001), and $150,000/QALY (3.53, 2.37-5.27, P < 0.001) than studies without industry sponsorship.

CONCLUSIONS

Our study suggests that there has been a significant sponsorship bias in CEAs in oncology. This bias could have a profound implication on drug pricing and coverage policy making.

Evaluating the quality of the economic evidence in colorectal cancer genomics studies

The increase in the use of genome-based screening and diagnostic tests adds to the overall costs of oncologic care for colorectal cancer. This, in turn, has resulted in an increase in published economic analyses. Aim: To perform a systematic literature review of the available economic evidence evaluating the value of genomic testing for colorectal cancer and appraise the quality of the economic studies conducted to date. Methods: A systematic review of the literature for economic studies of colorectal cancer genomics from January 2006 through October 2020, and evaluation of study quality using the Quality of Health Economic Studies (QHES) instrument was conducted. The validated QHES was then applied to a final set of articles that met eligibility criteria. Results: Our search of the literature initially yielded 12,859 records. A final set of 49 articles met our inclusion criteria. The QHES score ranged from 24 to 100, with an average score of 82. Most of the studies (n = 40, 82%) scored above 75 and were considered of good quality. Conclusion: Our analysis revealed that most of the economic analyses of colorectal cancer genomic molecular diagnostics in the literature may be of good quality. There is, however, some variation in methodological rigor between the articles.

Industry sponsorship bias in cost effectiveness analysis: registry based analysis

OBJECTIVE

To assess the association between industry sponsorship (drug, medical device, and biotechnology companies) and cost effectiveness results in cost effectiveness analysis (CEA).

DESIGN

Registry based analysis DATA SOURCE: The Tufts Cost-Effectiveness Analysis Registry was used to identify all CEAs published in Medline between 1976 and 2021.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

CEAs that reported incremental cost effectiveness ratio (ICER) using quality adjusted life year and provided sufficient information about the magnitude or location of the ICER.

METHODS

Descriptive analyses were used to describe and compare the characteristics of CEAs with and without industry sponsorship. Logistic regression was used to identify the association between industry sponsorship and the cost effective conclusion using selected threshold values ($50 000 (£40 511; €47 405), $100 000, and $150 000). Robust linear regression was used to assess the association between industry sponsorship and the magnitude of ICER. All regression analyses were adjusted for disease and study design characteristics.

RESULTS

8192 CEAs were eligible and included in the analysis, with 2437 (29.7%) sponsored by industry. Industry sponsored CEAs were more likely to publish ICERs below $50 000 (adjusted odds ratio 2.06, 95% confidence interval 1.82 to 2.33), $100 000 (2.95, 2.52 to 3.44), and $150 000 (3.34, 2.80 to 3.99) than non-industry sponsored studies. Among 5877 CEAs that reported positive incremental costs and quality adjusted life years, ICERs from industry sponsored studies were 33% lower (95% confidence interval -40 to -26) than those from non-industry sponsored studies.

CONCLUSIONS

Sponsorship bias in CEAs is significant, systemic, and present across a range of diseases and study designs. Use of CEAs conducted by independent bodies could provide payers with more ability to negotiate lower prices. This impartiality is especially important for countries that rely on published CEAs to inform policy making for insurance coverage because of limited capacity for independent economic analysis.

Differences in the Selection of Health State Utility Values by Sponsorship in Published Cost-Effectiveness Analyses

BACKGROUND

Health state utility values (HSUVs) are among the most influential attributes of cost-effectiveness analyses (CEAs). Our objective was to evaluate whether industry-funded studies select systematically different HSUVs as compared with studies without industry funding.

METHODS

Among 10 diseases with high disease burden in the United States, we further identified 31 progressive health states. We then searched the Tufts Medical Center's CEA Registry to identify studies that included HSUVs and were submitted to the registry between 2002 and 2019. Two reviewers mapped the free-text descriptions of health states onto the 31 predefined health states. We analyzed the effect of industry funding on the point estimates of these HSUVs with a beta regression. We also analyzed the difference between related health states within studies by funding source with a linear regression.

RESULTS

After identifying 26,222 HSUVs from 4198 CEAs, we matched 2573 HSUVs to the 31 predefined health states. We observed large variations within each health state: 12 of 31 health states included a range of HSUVs greater than 0.5. The point estimate model showed 1 statistically significant difference of 31 comparisons between studies with any industry funding and those without. The utility difference model found 3 significant differences out of 39 comparisons between CEAs with any industry funding and those without.

LIMITATIONS

Inclusion of unpublished CEAs may have affected our conclusions about the effect of industry funding on selection of HSUVs. We also relied on free-text descriptions of health states available in the CEA Registry and did not include adjustment for multiple comparisons.

CONCLUSION

Limited evidence exists that industry-funded studies select different HSUVs compared to non-industry-funded studies for the health states we considered.

Sponsorship Bias in Base-Case Values and Uncertainty Bounds of Health Economic Evaluations? A Systematic Review of Herpes Zoster Vaccination

BACKGROUND

New health technologies are more likely adopted when they have lower incremental cost-effectiveness ratios (ICERs) and/or when their ICER is presented with more certainty. Industry-funded (IF) health economic evaluations use often more favorable base-case values, leading to more favorable conclusions.

PURPOSE

To study whether IF health economic evaluations of varicella-zoster virus vaccination in the elderly use more favorable base-case values and account for less uncertainty than non-industry-funded (NIF) evaluations.

METHODS

DATA SOURCE

PubMed. Data extracted: funding source; incremental cost per quality-adjusted life year (QALY) gained; vaccine price; study quality score; base-case values, uncertainty ranges, and data sources for influential parameters: duration of vaccine protection, utility loss due to herpes zoster (HZ) disease, percentage of HZ patients developing postherpetic neuralgia (PHN), and duration of PHN.

DATA SYNTHESIS

qualitative comparisons; Fisher exact test for differences in study quality score and 1-sided Mann-Whitney U tests for differences in base-case values and uncertainty ranges.

RESULTS

Despite using the same data sources, IF studies ( n = 10) assume a longer duration of vaccine protection ( U = 56, P = 0.03), have a higher percentage of HZ patients developing PHN ( U = 22/33, P = 0.02/0.03 for ages 60-64/65-69), and tend to use higher HZ utility loss than NIF studies ( n = 11) for their baseline. IF studies show lower ICERs given similar or even higher vaccine prices than NIF studies, consider less uncertainty around the duration of vaccine protection ( U = 8, P < 0.001), and tend to use less uncertainty around the duration of PHN. Yet their quality has been rated equally well, using current standard quality rating tools.

CONCLUSION

Researchers and decision makers should be aware of potential sponsorship bias in health economic evaluations, especially in the way source data are used to specify base-case values and uncertainty ranges.

Industry sponsorship and research outcome

BACKGROUND

Clinical research affecting how doctors practice medicine is increasingly sponsored by companies that make drugs and medical devices. Previous systematic reviews have found that pharmaceutical-industry sponsored studies are more often favorable to the sponsor's product compared with studies with other sources of sponsorship. A similar association between sponsorship and outcomes have been found for device studies, but the body of evidence is not as strong as for sponsorship of drug studies. This review is an update of a previous Cochrane review and includes empirical studies on the association between sponsorship and research outcome.

OBJECTIVES

To investigate whether industry sponsored drug and device studies have more favorable outcomes and differ in risk of bias, compared with studies having other sources of sponsorship.

SEARCH METHODS

In this update we searched MEDLINE (2010 to February 2015), Embase (2010 to February 2015), the Cochrane Methodology Register (2015, Issue 2) and Web of Science (June 2015). In addition, we searched reference lists of included papers, previous systematic reviews and author files.

SELECTION CRITERIA

Cross-sectional studies, cohort studies, systematic reviews and meta-analyses that quantitatively compared primary research studies of drugs or medical devices sponsored by industry with studies with other sources of sponsorship. We had no language restrictions.

DATA COLLECTION AND ANALYSIS

Two assessors screened abstracts and identified and included relevant papers. Two assessors extracted data, and we contacted authors of included papers for additional unpublished data. Outcomes included favorable results, favorable conclusions, effect size, risk of bias and whether the conclusions agreed with the study results. Two assessors assessed risk of bias of included papers. We calculated pooled risk ratios (RR) for dichotomous data (with 95% confidence intervals (CIs)).

MAIN RESULTS

Twenty-seven new papers were included in this update and in total the review contains 75 included papers. Industry sponsored studies more often had favorable efficacy results, RR: 1.27 (95% CI: 1.17 to 1.37) (25 papers) (moderate quality evidence), similar harms results RR: 1.37 (95% CI: 0.64 to 2.93) (four papers) (very low quality evidence) and more often favorable conclusions RR: 1.34 (95% CI: 1.19 to 1.51) (29 papers) (low quality evidence) compared with non-industry sponsored studies. Nineteen papers reported on sponsorship and efficacy effect size, but could not be pooled due to differences in their reporting of data and the results were heterogeneous. We did not find a difference between drug and device studies in the association between sponsorship and conclusions (test for interaction, P = 0.98) (four papers). Comparing industry and non-industry sponsored studies, we did not find a difference in risk of bias from sequence generation, allocation concealment, follow-up and selective outcome reporting. However, industry sponsored studies more often had low risk of bias from blinding, RR: 1.25 (95% CI: 1.05 to 1.50) (13 papers), compared with non-industry sponsored studies. In industry sponsored studies, there was less agreement between the results and the conclusions than in non-industry sponsored studies, RR: 0.83 (95% CI: 0.70 to 0.98) (six papers).

AUTHORS' CONCLUSIONS

Sponsorship of drug and device studies by the manufacturing company leads to more favorable efficacy results and conclusions than sponsorship by other sources. Our analyses suggest the existence of an industry bias that cannot be explained by standard 'Risk of bias' assessments.

Cost-effectiveness research in cancer therapy: a systematic review of literature trends, methods and the influence of funding

OBJECTIVE

To perform a first-time analysis of the cost-effectiveness (CE) literature on chemotherapies, of all types, in cancer, in terms of trends and change over time, including the influence of industry funding.

DESIGN

Systematic review.

SETTING

A wide range of cancer-related research settings within healthcare, including health systems, hospitals and medical centres.

PARTICIPANTS

All literature comparative CE research of drug-based cancer therapies in the period 1986 to 2015.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcomes are the literature trends in relation to journal subject category, authorship, research design, data sources, funds and consultation involvement. An additional outcome measure is the association between industry funding and study outcomes.

ANALYSIS

Descriptive statistics and the χ2, Fisher exact or Somer's D tests were used to perform non-parametric statistics, with a p value of <0.05 as the statistical significance measure.

RESULTS

Total 574 publications were analysed. The drug-related CE literature expands over time, with increased publishing in the healthcare sciences and services journal subject category (p<0.001). The retrospective data collection in studies increased over time (p<0.001). The usage of prospective data, however, has been decreasing (p<0.001) in relation to randomised clinical trials (RCTs), but is unchanging for non-RCT studies. The industry-sponsored CE studies have especially been increasing (p<0.001), in contrast to those sponsored by other sources. While paid consultation involvement grew throughout the years, the declaration of funding for this is relatively limited. Importantly, there is evidence that industry funding is associated with favourable result to the sponsor (p<0.001).

CONCLUSIONS

This analysis demonstrates clear trends in how the CE cancer research is presented to the practicing community, including in relation to journals, study designs, authorship and consultation, together with increased financial sponsorship by pharmaceutical industries, which may be more influencing study outcomes than other funding sources.

A systematic review of health economic evaluations of vaccines in Brazil

BACKGROUND

In Brazil, since 2005, the Ministry of Health requires Health Economic Evaluation (HEE) of vaccines for introduction into the National Immunization Program.

OBJECTIVES

To describe and analyze the full HEE on vaccines conducted in Brazil from 1980 to 2013.

METHODS

Systematic review of the literature. We searched multiple databases. Two researchers independently selected the studies and extracted the data. The methodological quality of individual studies was evaluated using CHEERS items.

RESULTS

Twenty studies were reviewed. The most evaluated vaccines were pneumococcal (25%) and HPV (15%). The most used types of HEE were cost-effectiveness analysis (45%) and cost-utility analysis (20%). The research question and compared strategies were stated in all 20 studies and the target population was clear in 95%. Nevertheless, many studies did not inform the perspective of analysis or data sources.

CONCLUSIONS

HEE of vaccines in Brazil has increased since 2008. However, the studies still have methodological deficiencies.

Assessing the Quality of Economic Evaluations of FDA Novel Drug Approvals: A Systematic Review

OBJECTIVE

To systematically review and assess the quality of the novel drugs' economic evaluation literature in print during the drugs' early commercial availability following US regulatory approval.

DATA SOURCES

MEDLINE and the United Kingdom National Health Service Economic Evaluation Database were searched from 1946 through December 2011 for economic evaluations of the 50 novel drugs approved by the FDA in 2008 and 2009.

STUDY SELECTION AND DATA EXTRACTION

The inclusion criteria were English-language, peer-reviewed, original economic evaluations (cost-utility, cost-effectiveness, cost-minimization, and cost-benefit analyses). We extracted and analyzed data from 36 articles considering 19 of the 50 drugs. Two reviewers assessed each publication's quality using the Quality of Health Economic Studies (QHES) instrument and summarized study quality on a 100-point scale.

DATA SYNTHESIS

Study quality had a mean of 70.0 ± 16.2 QHES points. The only study characteristics associated with QHES score (with P < 0.05) were having used modeling or advanced statistics, 75.1 versus 61.9 without; using quality-adjusted life years as an outcome, 75.9 versus 64.7 without; and cost-utility versus cost-minimization analysis, 75.9 versus 58.7. Studies most often satisfied quality aspects about stating study design choices and least often satisfied aspects about justifying design choices.

CONCLUSION

The reviewed literature considered a minority of the 2008-2009 novel drugs and had mixed study quality. Cost-effectiveness stakeholders might benefit from efforts to improve the quality and quantity of literature examining novel drugs. Editors and reviewers may support quality improvement by stringently imposing economic evaluation guidelines about justifying study design choices.

Effective but costly: How to tackle difficult trade-offs in evaluating health improving technologies in liver diseases

In the current context of rising health care costs and decreasing sustainability, it is becoming increasingly common to resort to decision analytical modeling and health economics evaluations. Decision analytic models are analytical tools that help decision makers to select the best choice between alternative health care interventions, taking into consideration the complexity of the disease, the socioeconomic context, and the relevant differences in outcomes. We present a brief overview of the use of decision analytical models in health economic evaluations and their applications in the area of liver diseases. The aim is to provide the reader with the basic elements to evaluate health economic analysis reports and to discuss some limitations of the current approaches, as highlighted by the case of the therapy of chronic hepatitis C. To serve its purpose, health economics evaluations must be able to do justice to medical innovation and the market while protecting patients and society and promoting fair access to treatment and its economic sustainability.

CONCLUSION

New approaches and methods able to include variables such as prevalence of the disease, budget impact, and sustainability into the cost-effectiveness analysis are needed to reach this goal. (Hepatology 2016;64:1331-1342).

WHO SHOULD CONDUCT MODELING AND COST-EFFECTIVENESS ANALYSIS?

In some countries, reimbursement of drugs is based on cost-effectiveness analysis (CEA), in others not. In times of ageing populations, increasing number of possible interventions, and limited resources, it seems likely that CEA will be more and more important as a basis for decision making.

When are statins cost-effective in cardiovascular prevention? A systematic review of sponsorship bias and conclusions in economic evaluations of statins

Background

We examined sponsorship of published cost-effectiveness analyses of statin use for cardiovascular (CV) prevention, and determined whether the funding source is associated with study conclusions.

Methods and Findings

We searched PubMed/MEDLINE (up to June 2011) to identify cost-effectiveness analyses of statin use for CV prevention reporting outcomes as incremental costs per quality-adjusted life years (QALY) and/or life years gained (LYG). We examined relationships between the funding source and the study conclusions by means of tests of differences between proportions. Seventy-five studies were included. Forty-eight studies (64.0%) were industry-sponsored. Fifty-two (69.3%) articles compared statins versus non-active alternatives. Secondary CV prevention represented 42.7% of articles, followed by primary CV prevention (38.7%) and both (18.7%). Overall, industry-sponsored studies were much less likely to report unfavourable or neutral conclusions (0% versus 37.1%; p<0.001). For primary CV prevention, the proportion with unfavourable or neutral conclusions was 0% for industry-sponsored studies versus 57.9% for non-sponsored studies (p<0.001). Conversely, no statistically significant differences were identified for studies evaluating secondary CV prevention (0% versus 12.5%; p=0.222). Incremental costs per QALY/LYG estimates reported in industry-sponsored studies were generally more likely to fall below a hypothetical willingness-to-pay threshold of US $50,000.

Conclusions

Our systematic analysis suggests that pharmaceutical industry sponsored economic evaluations of statins have generally favored the cost-effectiveness profile of their products particularly in primary CV prevention.

COST-EFFECTIVENESS OF ORAL TRIPTANS FOR ACUTE MIGRAINE: MIXED TREATMENT COMPARISON

Background: The cost-effectiveness of triptans in the treatment of migraine has not been assessed since generic sumatriptan entered the Finnish market in 2008.

Methods: Using systematic review and mixed treatment comparison, the effectiveness of triptans was estimated with regard to 2-hour response, 2-hour pain-free, recurrence, and any adverse event, using published clinical data. Direct and indirect costs (2010 EUR, societal perspective) and quality-adjusted life-years (QALYs) were evaluated over one acute migraine attack using a decision-tree model.

Results: The meta-analysis combined data from fifty-six publications. The highest probability of achieving the primary outcome, “sustained pain-free, no adverse event” (SNAE), was estimated for eletriptan 40 mg (20.9 percent). Sumatriptan 100 mg was the treatment with lowest estimated costs (€20.86), and the incremental cost-effectiveness ratio of eletriptan 40 mg compared with sumatriptan 100 mg was €43.65 per SNAE gained (€19,659 per QALY gained).

Conclusion: Depending on the decision-maker's willingness-to-pay threshold, either sumatriptan 100 mg or eletriptan 40 mg is likely to be cost-effective.

Coauthorship and institutional collaborations on cost-effectiveness analyses: a systematic network analysis

Background

Cost-Effectiveness Analysis (CEA) has been promoted as an important research methodology for determining the efficiency of healthcare technology and guiding medical decision-making. Our aim was to characterize the collaborative patterns of CEA conducted over the past two decades in Spain.

Methods and Findings

A systematic analysis was carried out with the information obtained through an updated comprehensive literature review and from reports of health technology assessment agencies. We identified CEAs with outcomes expressed as a time-based summary measure of population health (e.g. quality-adjusted life-years or disability-adjusted life-years), conducted in Spain and published between 1989 and 2011. Networks of coauthorship and institutional collaboration were produced using PAJEK software. One-hundred and thirty-one papers were analyzed, in which 526 authors and 230 institutions participated. The overall signatures per paper index was 5.4. Six major groups (one with 14 members, three with 7 members and two with 6 members) were identified. The most prolific authors were generally affiliated with the private-for-profit sector (e.g. consulting firms and the pharmaceutical industry). The private-for-profit sector mantains profuse collaborative networks including public hospitals and academia. Collaboration within the public sector (e.g. healthcare administration and primary care) was weak and fragmented.

Conclusions

This empirical analysis reflects critical practices among collaborative networks that contributed substantially to the production of CEA, raises challenges for redesigning future policies and provides a framework for similar analyses in other regions.

Cost-effectiveness analysis for clinicians

In a climate of economic uncertainty, cost effectiveness analysis is a potentially important tool for making choices about health care interventions. Methods for such analyses are well established, but the results need to be interpreted carefully and are subject to bias. Making decisions based on results of cost-effectiveness analyses can involve setting thresholds, but for individual patients, there needs to be disaggregation of benefits and harms included in a quality adjusted life year to ensure appropriate consideration of benefits and harms as well as personal preferences and circumstances.