ACTR-27. COMPLIANCE AND TREATMENT DURATION PREDICT SURVIVAL IN A PHASE 3 EF-14 TRIAL OF TUMOR TREATING FIELDS WITH TEMOZOLOMIDE IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA
Bibliographic record
Abstract
Tumor treating fields (TTFields) are a physical anti-mitotic treatment modality characterized by their immediate mode of action and lack of a half-life. It has been shown previously that average monthly compliance with TTFields is correlated with overall survival in recurrent glioblastoma. A ≥75% compliance, i.e. an average daily use of at least 18h/d, has been suggested as a target for patients with recurrent glioblastoma when receiving TTFields as monotherapy. In the EF-14 phase 3 trial in newly diagnosed glioblastoma, TTFields were applied together with temozolomide (TTFields/TMZ) and led to superior progression free (PFS) and overall survival (OS) compared to TMZ alone. Patients in the TTFields/TMZ arm received TTFields for a median of 8.2 months (95%CI 7.9–9.3), with 13%, 3%, 1% and <1% of patients on therapy at 2, 3, 4 and 5 years, respectively. We looked at different TTFields compliance bins and correlated them with PFS and OS compared to TMZ alone. The results show a threshold value of 50% average monthly compliance with TTFields is needed in order to obtain extension of both PFS (HR 0.70 95%CI 0.47–1.05) and OS (HR 0.67 95%CI 0.45–0.99) versus TMZ alone. A trend in favor of longer PFS and OS was seen with higher compliance bins (>90% compliance: PFS HR 0.54 95%CI 0.37–0.79; OS HR 0.52 95%CI 0.35–0.79). A Cox model controlling for gender, extent of resection, MGMT methylation status, age, region and performance status indicated compliance is independent of these factors (HR 0.78; p=0.031; for OS at compliance ≥75% vs <75%). In conclusion, in the EF-14 trial a compliance threshold of 50% with TTFields treatment was correlated with significantly improved outcomes. The results clearly show that the higher patients’ compliance with TTFields, the better their outcomes. This effect was independent of other prognostic factors such as performance status, age and MGMT methylation.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".