Phase I, open-label, multicentre study of buparlisib in combination with temozolomide or with concomitant radiation therapy and temozolomide in patients with newly diagnosed glioblastoma
Bibliographic record
Abstract
BACKGROUND: Most glioblastoma tumours exhibit intrinsic phosphatidylinositol 3-kinase (PI3K) pathway activation. Preclinical in vitro and in vivo models suggest that buparlisib (an oral pan-PI3K inhibitor) can have an effect on glioblastoma directly and by enhancing the activity of radiation and of temozolomide. METHODS: This was a phase I, two-stage, multicentre, open-label, dose-escalation study of buparlisib in combination with temozolomide and radiotherapy in patients with newly diagnosed glioblastoma. In stage I, patients who completed the concomitant phase of combination of temozolomide and radiation prior to study entry received buparlisib in combination with temozolomide. In stage II, patients received buparlisib in combination with temozolomide and radiotherapy in the concomitant phase and temozolomide in the adjuvant treatment phase. The primary objective was to estimate the maximum tolerated dose (MTD) of buparlisib when combined with the approved first-line treatment of temozolomide and radiotherapy. RESULTS: The MTD of buparlisib in combination with temozolomide at stage I (adjuvant phase only) was 80 mg/day, which was used as the starting dose in stage II. The MTD of buparlisib in combination with temozolomide and radiotherapy in stage II (concomitant + adjuvant phase) was not determined due to the observed dose-limiting toxicities and treatment discontinuations due to adverse events (AEs). In stage I, the most commonly reported AEs were nausea (72.7%) and fatigue (59.1%). In stage II, the most commonly reported AEs were fatigue and nausea (56.3% each). No on-treatment deaths were reported during the study. CONCLUSION: ClinicalTrials.gov identifier: NCT01473901.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".