Prescription ranitidine use and population exposure in 6 Canadian provinces, 1996 to 2019: a serial cross-sectional analysis
Bibliographic record
Abstract
BACKGROUND: RA) in Canada when recalled in 2019 because of potential carcinogenicity. We sought to compare geographic and temporal patterns in use of prescription ranitidine and 3 other HRAs and estimated population exposure to ranitidine in 6 provinces between 1996 and 2019. METHODS: RAs dispensed from community pharmacies in Nova Scotia, Ontario, Manitoba, Saskatchewan, Alberta and British Columbia. We estimated the period prevalence of ranitidine use per 100 population by province, age category and sex. We estimated exposure to ranitidine between 2015 and 2019 using defined daily doses (DDDs). RESULTS: Overall, 2.4 million ranitidine prescriptions were dispensed to patients aged 65 years and older, and 1.7 million were dispensed to younger adults. Among older adults, the median period prevalence of ranitidine use among females was 16% (interquartile range [IQR] 13%-27%) higher than among males. Among younger adults, the median prevalence was 50% (IQR 37%-70%) higher among females. Among older adults, between 1996 and 1999, use was highest in Nova Scotia (33%) and Ontario (30%), lower in the prairies (Manitoba [18%], Saskatchewan [26%], Alberta [17%]) and lowest in BC (11%). By 2015-2019, use of ranitidine among older adults dropped by at least 50% in all provinces except BC. We estimate that at least 142 million DDDs of prescribed ranitidine were consumed annually in 6 provinces (2015-2019). INTERPRETATION: Over the 24-year period in 6 provinces, patients aged 65 years and older were dispensed 2.4 million prescriptions of ranitidine and younger adults were dispensed 1.7 million prescriptions of ranitidine. These estimates of ranitidine exposure can be used for planning studies of cancer risk and identifying target populations for cancer surveillance.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".