Neoplasm Reports in Food and Drug Administration Adverse Event Reporting System Following Angiotensin Receptor Blocker Recalls
Bibliographic record
Abstract
Background: A worldwide voluntary recall of valsartan in July 2018 due to the potential carcinogen N-nitrosodimethylamine received extensive media and public attention. This was followed by more Food and Drug Administration (FDA) recalls regarding other contaminated ARB (angiotensin receptor blocker) products. Our study investigated the association between the FDA recalls and ARB neoplasm adverse events (AEs) reported to the FDA adverse event reporting system. Methods: In this cross-sectional study, data were retrospectively collected from the FDA adverse event reporting system database from January 2015 to December 2019. Reporting odds ratios (RORs) were estimated to detect signals of association between ARBs (valsartan, irbesartan, and losartan) and reported neoplasm AEs using negative (amoxicillin and sertraline) and positive (omeprazole and ranitidine) control exposures. The χ 2 was used to compare categorical variables. Results: A total of 2 181 524 AEs, including 10 461 nonmetastatic neoplasm AEs were analyzed. Monthly RORs (95% CI) of valsartan-associated neoplasms versus controls (ROR*: valsartan/negative exposures; ROR†: valsartan/omeprazole; and ROR‡: valsartan/ranitidine) showed the highest signals after the recall date in July 2018 (7.64 [4.78–12.19]*; 4.77 [3.36–6.79]†; 4.13 [2.50–6.84]‡) and August 2018 (7.87 [5.19–11.94]*; 5.65 [4.12–7.75]†; and 7.20 [4.46–11.63]‡). In contrast, the highest cancer signals for the irbesartan and losartan recalls detected in March 2019 (4.80*; 4.06†; and 3.38‡) and April 2019 (3.63*; 3.69†; and 2.52‡) respectively, were lower. One-year postrecall reported neoplasm AEs were ≈2-fold higher for valsartan than irbesartan (OR, 1.77 [95% CI, 1.47–2.13], P <0.0001) and losartan (OR, 2.07 [95% CI, 1.85–2.32], P <0.0001). Although all ARBs had the same nitrosamine contamination, we found 1-year postrecall versus prerecall cancer signals for valsartan were 3-fold higher versus control exposures, while the changes in RORs for irbesartan and losartan were only 20-30% higher. Conclusions: Significantly more postrecall neoplasms were reported for valsartan, with higher valsartan-associated cancer signals compared with irbesartan and losartan, although they all contained the same carcinogenic contaminant. Extensive media coverage of the FDA valsartan recall may have alarmed patients and generated these abrupt, biologically infeasible cancer signals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".