Conflicts of Interest in “Throwaway” Dermatology Publications: Analysis of the Open Payments Database
Bibliographic record
Abstract
BACKGROUND: Dermatology journals, periodicals, editorials, and news magazines are influential resources that are not uniformly regulated and subject to influence from the pharmaceutical industry. This study evaluates industry payments to physician editorial board members of common dermatology publications, including "throwaway" publications. OBJECTIVE: The aim of this study was to characterize the extent and nature of industry payments to editorial board members of different dermatologic publications in order to ascertain differences in payments between different types of publications. METHODS: A list of editorial board members was compiled from a collection of clinical dermatology publications received over a 3-month period. Data from the Open Payments database from 2013 to 2019 were collected, and analysis of payments data was performed. RESULTS: Ten publications were evaluated, and payments data for 466 physicians were analyzed. The total compensation across all years was US $75,622,369.64. Consulting, services other than consulting, and travel or lodging payments constituted most of the payments. A fraction of dermatologists received the majority of payments. The top payers were manufacturers of biologic medications. Payment amounts were higher for throwaway publications compared to peer-reviewed journals. CONCLUSIONS: Editorial board members of dermatology publications received substantial payments from the pharmaceutical industry. A minority of physicians receive the lion's share of payments from industry. "Throwaway" publications have more financial conflict of interest than do peer-reviewed journals. The impact of these conflicts of interest on patient care, physicians' practice patterns, and patient perception of physicians is noteworthy.
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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 | 0.017 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.023 | 0.031 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".