P17.15.A ASSOCIATION OF PROTON PUMP INHIBITOR USE WITH OUTCOME OF PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA
Bibliographic record
Abstract
Abstract BACKGROUND Proton pump inhibitors (PPI) are often prescribed to prevent steroid-induced gastritis and peptic ulcer disease in patients with glioblastoma. Yet, these drugs may enhance the activity of aldehyde dehydrogenase 1 A1 (ALDH1A1) which has been linked to protection from oxidative stress, radiotherapy and chemotherapy. MATERIAL AND METHODS We analyzed data from 2981 patients enrolled into 5 randomized clinical trials for newly diagnosed glioblastoma to explore an association of the use of potent ALDH1A1-activating PPI (PA-PPI) and other anti-acid drugs with outcome. We assessed drug use at baseline and at defined landmarks: start of temozolomide maintenance cycles 1 (landmark 1) and 4 (landmark 2), and end of cycle 6 (landmark 3). RESULTS On univariate analysis, we noted inferior progression-free and overall survival for patients treated with PA-PPI at all 4 time points. The multivariate analysis accounting for age, sex, performance status, steroid use, extent of resection, and O6-methylguanine DNA methyltransferase promoter methylation (MGMT) status confirmed a difference for progression-free survival at landmarks 1, 2 and 3, and for overall survival at landmarks 1 and 2. No such effect was seen for the use of other anti-acid drugs. The negative association of PA-PPI use with outcome was observed independently of MGMT promoter methylation and of steroid use. CONCLUSION We conclude that PA-PPI use should be discouraged in patients with glioblastoma since alternative agents are available and since a detrimental effect cannot be excluded. Translational research studies should explore whether PPI-induced activity of ALDH mediates the potential adverse effects of PPI in glioblastoma.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".