Industry funding of patient and health consumer organisations: systematic review with meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To investigate pharmaceutical or medical device industry funding of patient groups. DESIGN: Systematic review with meta-analysis. DATA SOURCES: Ovid Medline, Embase, Web of Science, Scopus, and Google Scholar from inception to January 2018; reference lists of eligible studies and experts in the field. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Observational studies including cross sectional, cohort, case-control, interrupted time series, and before-after studies of patient groups reporting at least one of the following outcomes: prevalence of industry funding; proportion of industry funded patient groups that disclosed information about this funding; and association between industry funding and organisational positions on health and policy issues. Studies were included irrespective of language or publication type. REVIEW METHODS: Reviewers carried out duplicate independent data extraction and assessment of study quality. An amended version of the checklist for prevalence studies developed by the Joanna Briggs Institute was used to assess study quality. A DerSimonian-Laird estimate of single proportions with Freeman-Tukey arcsine transformation was used for meta-analyses of prevalence. GRADE (Grading of Recommendations Assessment, Development, and Evaluation) was used to assess the quality of the evidence for each outcome. RESULTS: 26 cross sectional studies met the inclusion criteria. Of these, 15 studies estimated the prevalence of industry funding, which ranged from 20% (12/61) to 83% (86/104). Among patient organisations that received industry funding, 27% (175/642; 95% confidence interval 24% to 31%) disclosed this information on their websites. In submissions to consultations, two studies showed very different disclosure rates (0% and 91%), which appeared to reflect differences in the relevant government agency's disclosure requirements. Prevalence estimates of organisational policies that govern corporate sponsorship ranged from 2% (2/125) to 64% (175/274). Four studies analysed the relationship between industry funding and organisational positions on a range of highly controversial issues. Industry funded groups generally supported sponsors' interests. CONCLUSION: In general, industry funding of patient groups seems to be common, with prevalence estimates ranging from 20% to 83%. Few patient groups have policies that govern corporate sponsorship. Transparency about corporate funding is also inadequate. Among the few studies that examined associations between industry funding and organisational positions, industry funded groups tended to have positions favourable to the sponsor. Patient groups have an important role in advocacy, education, and research, therefore strategies are needed to prevent biases that could favour the interests of sponsors above those of the public. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017079265.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.059 | 0.172 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".