Second- and Third-generation BCR-ABL Tyrosine-Kinase Inhibitors and the Risk of Pulmonary Arterial Hypertension: A Prevalent new-user Population-based Cohort Study
Bibliographic record
Abstract
BCR-ABL tyrosine kinase inhibitors (TKI) have been increasingly linked to pulmonary arterial hypertension (PAH) since 2009, although supporting evidence is limited. Objective was to evaluate the risk of PAH associated with second- and third-generations BCR-ABL TKI, compared with imatinib in adults. We conducted a prevalent new-user study within the French national healthcare database from 2008 to 2022. Hazard ratios (HR) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models, stratified by exposure-set to account for time effect. Incidence rates (IR) and corresponding 95% CIs were calculated using the Poisson distribution. Primary outcome was new onset of PAH, previously validated in the French Healthcare database. In total, 5,644 dasatinib, 4,668 nilotinib, 1,756 bosutinib and 1,019 ponatinib new-users were each matched with up to 15 imatinib users on time conditional propensity score and on duration of prior imatinib use (prevalent users). Dasatinib was associated with a 10-fold increased risk of PAH compared with imatinib (331 versus 9 events per million persons per year; HR 10.16, 95%CI 2.61–39.55). Two PAH cases were identified after bosutinib exposure, corresponding to an IR of 490 (95%CI 59–1,771), versus none in the matched imatinib group. Both cases occurred on patients previously exposed to dasatinib. No cases of PAH were observed with nilotinib and ponatinib. This study suggests that dasatinib associated with an elevated risk of PAH, while bosutinib exposure may aggravate or trigger a recurrence of PAH in patients with prior dasatinib use.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".