RE: Aspirin, Ibuprofen, and the Risk for Colorectal Cancer in Lynch Syndrome
Bibliographic record
Abstract
We read with interest the study by Ait Ouakrim et al. (1) that appeared in a recent issue of the Journal. In this study, conducted in a cohort of patients with Lynch syndrome, ever use of aspirin and ever use of ibuprofen were both associated with a strong overall decreased risk of colorectal cancer (hazard ratio [HR] = 0.48, 95% confidence interval [CI] = 0.33 to 0.71, and HR = 0.33, 95% CI = 0.20 to 0.55, respectively). We believe these effect estimates may have been exaggerated by immortal time bias (2). In this study, exposure to aspirin and ibuprofen was retrospectively assessed via questionnaires administered at the time of recruitment. Patients were asked whether they had “taken aspirin or ibuprofen at least twice a week for a month or longer.” Based on the response, patients were classified into one of two exposure groups: ever vs never use. These exposure groups were then followed from birth until their age at the time of colorectal cancer diagnosis or censoring because of the end of follow-up. However, this time-fixed exposure definition ignores the age at which exposure to the drug of interest was initiated and thus introduces immortal time bias. Specifically, based on this exposure definition, all ever users were considered to have been exposed during the entire follow-up period, that is, from birth until the event or end of follow-up. This introduces two methodological issues. First, the time between birth and the age at first exposure is incorrectly classified as exposed person-time. Second, by design, it is impossible for patients to have an event during this misclassified time period as an event would result in their reclassification as never users (Figure 1). The inclusion of this misclassified immortal time in the denominator of the rate for the exposure group can lead to spurious “protective” effects (3). The time-fixed approach introduces immortal time bias by defining exposure at cohort entry (in this case, birth). To be classified as exposed, patients must survive without colorectal cancer up to the age of first exposure to aspirin. This period of immortal time is classified as exposed even though the drug was not actually taken. This misclassified immortal person-time inflates the denominator of the incidence rate of the exposed, thus resulting in a rate ratio that is biased away from the null. In the correct, time-dependent approach, each patient may contribute person-time to both the exposed and the unexposed groups. While the authors did not provide information regarding the mean age at first exposure, it is likely that the majority of patients became regular users of aspirin and ibuprofen later in life. In this context, this would represent thousands of unexposed person-years of follow-up misclassified as exposed. It would thus be informative if the authors repeated their analyses with exposure to aspirin and ibuprofen defined using a time-dependent approach (2), which would correctly classify the unexposed and exposed person-time for all patients included in the cohort. We believe that such an approach would provide a more valid estimate of the potential chemopreventive effects of aspirin and ibuprofen on the incidence of colorectal cancer.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.025 | 0.021 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".