Exposure to valsartan products containing nitrosamine impurities in the US, Canada, and Denmark
Bibliographic record
Abstract
ABSTRACT Background Following the mass recall of valsartan products with nitrosamine impurities in July 2018, the number of patients exposed to these valsartan products, the duration of exposure, and the potential for cancer remains unknown. Therefore, we assessed the extent and duration of use of valsartan products with a nitrosamine impurity in the US, Canada, and Denmark. Methods We conducted a retrospective cohort study using administrative healthcare data from the US FDA Sentinel System, four Canadian provinces that contribute to the Canadian Network for Observational Drug Effect Studies (CNODES), and the Danish National Prescription Registry. Patients, 18 years and older between May 2012 and December 2020 with a valsartan dispensing were identified in each database. Patients were followed from the date of valsartan dispensing until discontinuation. We defined four valsartan exposure categories based on nitrosamine impurity status; recalled generic products with confirmed NDMA/NDEA levels (recalled-tested); recalled generic products that were not tested (recalled); non-recalled generic and non-recalled branded products. In Denmark, recalled-tested category was not included due to absence of testing data. The proportion and duration of use of valsartan episodes stratified by nitrosamine-impurity status. Results We identified 3.3 and 2.8 million (US) and 51.3 and 229 thousand (Canada) recalled-tested and recalled valsartan exposures. In Denmark, where valsartan exposure was generally low, there were 10,747 recalled exposures. Immediately after the recall notices were issued, there was increased rates of switching to a non-valsartan ARB. The mean duration of use of the recalled-tested products was 167(±223.1) and 146(±255.8) days in the US and Canada respectively. For the recalled products, mean cumulative duration of use was 178(±249.6), 269(±397.3) and 166(±251.0) days in the US, Canada, and Denmark, respectively. Conclusion In this cohort study, despite widespread use of recalled generic valsartan between 2012 and 2018, the duration of use was relatively short and likely did not pose an elevated risk of nitrosamine-induced cancer. However, since products with nitrosamine impurity could have been on the market over a six-year period, patients potentially exposed to these products for longer duration could have a different risk of cancer.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".