Letter by Azoulay and Suissa Regarding Article, “Statins and the Risk of Cancer After Heart Transplantation”
Bibliographic record
Abstract
person-years of follow-up (using median follow-up times provided in Table 2).However, the latter included immortal person-time (ie, time between cohort entry and the first statin prescription where no cancer could have occurred).Assuming an average 3-year gap between cohort entry and the first statin prescription, a total of 453 immortal person-years would have been misclassified as exposed.By correctly reclassifying this person-time, the rate of cancer in the unexposed group would become 54/(650+453)=4.9per 100 personyears instead of 8.3 per 100 person-years, whereas the rate in the statin-exposed group would become 54/(1570-453)=4.8per 100 person-years instead of 3.4 per 100 person-years, resulting in a corrected crude rate ratio of 0.98.Although this illustration shows the potential impact of immortal time bias in cohort studies, it would be constructive if the authors redid their analyses by defining statin exposure in a time-dependent fashion, while also considering issues of latency and the impact of reverse causality.
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.036 | 0.029 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".