Bias from depletion of susceptibles: the example of hormone replacement therapy and the risk of venous thromboembolism
Bibliographic record
Abstract
PURPOSE: The data on the association between hormone replacement therapy and the increased risk of venous thromboembolism (VTE) in postmenopausal women are conflicting. The observed differences between oral estrogen and oral estrogen-progestogen combination formulations may be the result of bias from depletion of susceptibles. METHODS: We used United Kingdom's Clinical Practice Research Datalink to identify the cohort of all women aged 50 to 79 during 1987-2008, with all incident cases of VTE occurring during the study period identified. Using a nested case-control approach, the rate ratios (RRs) of VTE with current use of oral estrogen and oral estrogen-progestogen combinations were estimated as a function of duration of use using conditional logistic regression with cubic splines. RESULTS: The cohort of 955 582 postmenopausal women included 23 505 cases of VTE matched to 231 562 controls. The risk of VTE was increased with current use of oral estrogen (RR 1.49; 95% confidence interval: 1.37 to 1.63) and oral estrogen-progestogen (RR 1.54; 95% confidence interval: 1.44 to 1.65), relative to non-use. When assessed by duration of use, the risks with oral formulations were particularly elevated during the first year of use and were reduced subsequently. CONCLUSION: The phenomenon of depletion of susceptibles should be considered in cohort studies evaluating acute side effects of medications. This can be achieved by estimating the risk as a function not only of current use but also of duration of use. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.135 | 0.346 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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, 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".