Proton-pump inhibitors and increased gastric cancer risk: time-related biases
Bibliographic record
Abstract
We read with interest the cohort study by Cheung et al 1 reporting that use of proton-pump inhibitors (PPIs) after Helicobacter pylori eradication is associated with an increased risk of gastric cancer (GC). We believe that the significantly elevated HR of GC with PPI use (HR 2.44; 95% CI 1.42 to 4.20) is a consequence of two time-related biases. Immortal time bias was introduced by misclassifying exposure,2–4 while latency bias was introduced by not incorporating latency in the exposure definition, a major issue for potential carcinogenic drug effects.5 6 Immortal time in a cohort study refers to a period of follow-up time when the outcome could not occur.3 It arises in this study from the definition of frequency of PPI use, ‘calculated by dividing the total treatment duration by the duration of follow-up’, namely the average use over the entire follow-up. Exposure to PPIs was then categorised ‘into non-regular use (<weekly use; reference group) and regular use (at least weekly use)’.1 Thus, the PPI ‘non-users’ included authentic non-users of PPIs and the non-regular PPI users (less than weekly use), together making up the reference group against which the risk …
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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 | 0.010 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.018 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".