NIMG-51T1-HYPERINTENSE LESIONS AS A PREDICTOR OF SURVIVAL IN PATIENTS WITH RECURRENT HIGH GRADE GLIOMA ON BEVACIZUMAB
Bibliographic record
Abstract
BACKGROUND: Recent studies have suggested that the development of T1-hyperintensities early in the course of treatment with bevacizumab may represent a predictive marker for treatment response and survival in patients with recurrent glioblastoma (GBM). These lesions may represent hypoxia-induced calcifications and/or areas of sustained treatment response. This study evaluated the incidence and predictive value of T1-hyperintensities in patients with recurrent high grade glioma (HGG) treated with bevacizumab. METHODS: This retrospective chart review included all patients treated with bevacizumab for recurrent HGG at a large regional cancer centre between 2010 and 2014, and for whom baseline MRI and at least one post-treatment MRI were available. Pre- and post-bevacizumab imaging was evaluated independently by two neuroradiologists for the presence of new or increased hyperintense lesions on precontrast T1-weighted imaging. When available, CT scans were evaluated for the presence of peritumoral calcifications. RESULTS: Sixty-nine patients were eligible for inclusion. Fifty-two patients (75.4%) had pathologically diagnosed GBM, while the remainder had grade III (n = 11), or grade II gliomas with radiological evidence of high grade transformation at recurrence (n = 6). New or increased T1-hyperintense lesions were noted in 45 patients (65.2%) after bevacizumab and were independent of tumor grade. Median time to appearance was 63 days (95% CI 46.7-79.2). Median survival was significantly longer in patients with T1-hyperintense lesions (9.6 v.s. 6.9 mos, p = 0.023), and this effect did not differ by tumor grade. CONCLUSIONS: This study supports previous research demonstrating the predictive value of T1-hyperintense lesions for survival in recurrent GBM. We found that this phenomenon may also occur in patients with grade II-III gliomas treated with bevacizumab. As previously described, these lesions occurred early in the course of therapy and thus may represent an early biomarker of response. These findings may help inform treatment decisions for patients receiving antiangiogenic therapy for recurrent HGG.
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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 | 0.001 | 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) | 0.001 | 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".