Discrepancy Among Observational Studies: Example of Naproxen- Associated Adverse Events
Bibliographic record
Abstract
BACKGROUND: Observational studies assessing the cardiovascular adverse effect of naproxen have had conflicting results. It is not clear whether variation in population characteristics between studies may explain some of this discrepancy. OBJECTIVE: To determine whether changes in patient characteristics of naproxen users occurred between 1999 and 2004 in Québec, Canada and to examine whether these temporal changes were accompanied by changes in estimates of naproxen-related hospitalizations for gastrointestinal (GI) ulcers and myocardial infarction, using provincial health services administrative databases. METHODS: Demographic, pharmaceutical and physician billing records of patients 65 years and older, who received naproxen or acetaminophen prescriptions between 1999 and 2004 were used. Two identical cohort studies, labeled Study 1 and Study 2 were conducted and their results were compared. One study was confined to the time period 1999-2001 and the other to 2002-2004. Patient characteristics at index date (the date of the first naproxen or acetaminophen prescription during the corresponding period) were compared between the study cohorts in naproxen and acetaminophen users, respectively, and within each study cohort between naproxen and acetaminophen users, using logistic regression models. Cox regression models with time dependent exposure were used to assess the association between naproxen vs acetaminophen and hospitalizations for GI events or AMI, respectively within each study. Results were then compared between the two studies. RESULTS: Study 1 (1999-2001) cohort included 240,568 patients (205,238 acetaminophen and 35,330 naproxen) and Study 2 (2002-2004) cohort included 213,802 patients (193,918 acetaminophen and 19,884 naproxen). Patient characteristics of naproxen and acetaminophen users differed between the two studies. Naproxen users in Study 2 vs Study 1 were slightly younger, less likely to be females, less likely to have concomitant GI disease, less likely to have osteoarthritis and other co-morbidities and more likely to have used proton pump inhibitors, antihypertensive agents, anticoagulants, clopidogrel and aspirin. In general, similar changes in patient characteristics were observed in acetaminophen users between the two study cohorts. Compared to acetaminophen (without aspirin), the estimates of the GI risks with naproxen whether, used with or without aspirin, were significantly higher in Study 2 vs Study 1 [Hazard Ratio (HR) (95% CI): 4.94 (3.48, 7.02)] vs [2.22 (1.62, 3.06)], naproxen with aspirin [4.94 (2.93, 8.33) vs 2.47 (1.48, 4.12)], and acetaminophen and aspirin: [2.31 (1.89, 2.82) vs 1.46 (1.20, 1.77)]. The estimate of the AMI risk with naproxen also seemed to be higher in Study 2 vs Study 1, however the increase was not statistically significant [HR (95% CI) in the naproxen group: 1.18 (0.83, 1.67) in Study 1 vs 0.94 (0.70, 1.25) in Study 2], naproxen with aspirin. [1.44 (0.95, 2.18) vs 1.05 (0.68, 1.61)]; and acetaminophen and aspirin. 1.15 (1.01, 1.30) vs 1.10 (0.97, 1.26). CONCLUSION: Variation in patient characteristics in naproxen users was observed between 1999 and 2004. This variation was likely to be accompanied by a variation in patient pre-disposition to GI events that may explain the increase in estimates of naproxen-related GI adverse events observed during this period.
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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 | 0.179 | 0.453 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".