Clinical utility of targeted next-generation sequencing assay in IDH-wildtype glioblastoma for therapy decision-making
Bibliographic record
Abstract
BACKGROUND: Targeted gene NGS testing is available through many academic institutions and commercial entities and is increasingly incorporated in practice guidelines for glioblastoma (GBM). This single-center retrospective study aimed to evaluate the clinical utility of incorporating NGS results in the management of GBM patients at a clinical trials-focused academic center. METHODS: We identified 1011 consecutive adult patients with pathologically confirmed GBM (IDHwt or IDHmut) who had somatic tumor sequencing (Oncopanel, ~500 cancer gene panel) at DFCI from 2013-2019. Clinical records of all IDHwt GBM patients were reviewed to capture clinical trial enrollment and off-label targeted therapy use based on NGS results. RESULTS: Of the 557 IDHwt GBM patients with sequencing, 182 entered clinical trials at diagnosis (32.7%) and 213 (38.2%) entered after recurrence. Sequencing results for 130 patients (23.3%) were utilized for clinical trial enrollment for either targeted therapy indications (6.9 % upfront and 27.7% at recurrent clinical trials and 3.1% for off-label targeted therapy) or exploratory studies (55.4% upfront and 6.9% recurrent clinical trials). Median overall survival was 20.1 months with no survival difference seen between patients enrolled in clinical trials compared to those who were not, in a posthoc analysis. CONCLUSIONS: While NGS testing has become essential for improved molecular diagnostics, our study illustrates that targeted gene panels remain underutilized for selecting therapy in GBM-IDHwt. Targeted therapy and clinical trial design remain to be improved to help leverage the potential of NGS in clinical care.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".