Estimation of time‐dependent rate ratios in case‐control studies: comparison of two approaches for exposure assessment
Bibliographic record
Abstract
PURPOSE: In pharmacoepidemiology, it is well recognized that the rate of adverse events may vary as a function of the cumulative duration of the drug exposure and/or the time since the end of the exposure. In case-control studies, two different approaches have been used to estimate temporal effects of drug exposure: the time-windows (T-Ws) approach and the duration-specific (D-S) approach. We decided to conduct a simulation study to compare the two approaches when the rate ratios (RRs) vary as a function of the cumulative duration of exposure and/or the time since the end of exposure. METHODS: We generated three cohorts of 500,000 individuals in which the rate of the event was varying as a function of the cumulative duration of exposure and the time since the end of exposure. For each cohort, a nested case-control analysis was performed using both the D-S and the T-Ws approaches. In the T-Ws approach, a RR is estimated within specific periods of time prior to the outcome, while a RR is estimated within periods of cumulative duration of exposure and time since the end of exposure in the D-S approach. RESULTS: We found that the RRs obtained from the D-S approach exactly corresponded to the RRs obtained from the cohort analyses, while the RRs obtained from the T-Ws approach generally not. RRs obtained from the T-Ws approach were difficult to interpret in terms of the effect of the duration and timing of the exposure. CONCLUSION: The D-S approach should be used to investigate the duration-related effects of exposure in case-control studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".