Letter: comparative safety and efficacy of infliximab vs. adalimumab in Crohn's disease – should one consider disease location? Authors’ reply
Bibliographic record
Abstract
We appreciate the interest in our manuscript analysing outcomes of anti-tumour necrosis factor (TNF)-α naive patients with active Crohn's disease (CD) who were treated with infliximab (IFX) or adalimumab (ADA).1, 2 We agree with Dr Srinivas that it is interesting to observe the subgroup analyses from our study, and note that a significant difference in maintenance of clinical remission was reported in our study among patients with ileal CD who were treated with ADA compared to IFX. However, it is important to remember that this was a prospective cohort study, and not a randomised clinical trial, which suggests that there may be differences between the two cohorts that are potentially unmitigated by the lack of randomisation. For instance, patients with ileal disease receiving ADA may not have been similar to those receiving IFX in terms of disease duration or the presence of fibrostenotic disease. These potential differences between the two groups could influence their likelihood of responding to treatment. It is also worthwhile mentioning the utility of subgroup analyses. It is natural to examine for differences in the effect of therapy in clinical subgroups, particularly when there does not appear to be any difference between the two groups in overall outcomes. We must remember, however, that this is a post hoc analysis, which was not postulated before the study, for which the difference is not very large, and which has not been shown in other observational experiences comparing these two drugs. When several subgroup analyses are performed, probability suggests some will demonstrate significant benefit due to chance alone. There have been many examples of misleading findings from subgroup results in otherwise well-done randomised, controlled trials likely on account of chance alone,3 such as beta-blockers being found ineffective for inferior myocardial infarctions,4 only to be refuted by subsequent research. For this reason, subgroup analysis should be mainly used to generate hypotheses for future trials. It will be interesting to see if other investigators report similar experiences in using ADA and IFX for ileal CD, but there is little reason to think one anti-TNFα agent would have significantly better impact in the ileum than another. The authors’ declarations of personal and financial interests are unchanged from those in the original article.2
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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 | 0.009 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.028 | 0.028 |
| 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".