Statins and the risk of idiopathic venous thromboembolism
Bibliographic record
Abstract
The matched case–control study by Yang, Jick and Jick was designed ‘to evaluate the association between current statin use and the risk of idiopathic venous thromboembolism (VTE)’[1]. We feel obligated to address three points that challenge their most tenuous conclusion that ‘current statin use was not associated with a reduced risk of idiopathic VTE’. As shown in the Figure, the authors identified a total of 72 cases with idiopathic VTE, of whom only 37 (51%) had records confirming objectively proven VTE. The remaining 35 cases (49%) (dashed boxes) had ‘probable VTE’, of whom 22 individuals (30%) had no manual records available for review, but an ‘anticoagulant-supported diagnosis’ of idiopathic VTE [1]. Therefore, between 30% and 49% of the 72 cases may have been incorrectly classified as having VTE. Such nondifferential misclassification of disease status always introduces a bias toward the null value for the effect size [2]. Second, out of 72 cases with idiopathic VTE, only three (4.2%) were current or recent statin users, while 18 out of 432 controls (4.2%) were statin users, as listed in Table 2 of their paper [1]. Considering that only 4.2% of cases were exposed to statins, one cannot address the primary study question in a valid manner. At a rate of statin exposure of only 4.2% among the 432 controls, with a 6 : 1 matching of controls to cases, the statistical power was only 8% to demonstrate a statistically significant odds ratio (OR) of 0.5, for example. To show an OR of 0.9, as in their study [1], the corresponding power level was only 5%. Suppose that 8.4% of controls received statins, and there was a 50% reduction in the risk of VTE with statin use (i.e. OR 0.5). Using a case–control study with a 6 : 1 matching ratio, and with α= 0.05 and a conventional power setting of 80%, 373 cases and 2238 controls would be required, a sample size more than five times larger than that used in the current study [1]. Unfortunately, nowhere in their paper do the authors reveal a sample size estimation, or the fact that their study was severely underpowered. Finally, we previously published a retrospective cohort study of statin use and the risk of deep vein thrombosis (DVT) among 125 862 adults aged ≥ 65 years [3]. This study was initiated without knowledge of the findings of the Heart and Estrogen/progestin Replacement Study (HERS) [4]. After adjusting for age, sex, prior hospitalization, newly diagnosed cancer, or prescribed ASA, warfarin or oestrogen, we observed that statin users had an adjusted hazard ratio of 0.78 (95% confidence interval 0.69, 0.87) for DVT relative to those prescribed neutral thyroid replacement agents. This was evident in women but not men [3], supporting the findings of the HERS investigators [4]. Valid evidence is needed to address the hypothesis that statins may be protective against VTE [5]. Yang and colleagues may have arrived at a spuriously negative conclusion based on a suboptimal study design.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".