MTR-13EVALUATION OF p75 EXPRESSION AND PATTERNS OF RECURRENCE IN PATIENTS WITH MALIGNANT GLIOMAS TREATED WITH BEVACIZUMAB
Bibliographic record
Abstract
BACKGROUND: There is no standard treatment for patients with recurrent malignant gliomas (MGs) and after antiangiogenic therapy, 15% recur in a distant location suggesting the development of VEGF independent invasive mechanisms. We hypothesized that p75NTR expression could be associated to the pattern of recurrence/progression in patients with MGs treated with bevacizumab. METHODS: Adult patients with MGs (gliomas Grade III and Glioblastoma) treated with bevacizumab who had given written consent were identified. Clinical data were extracted from the charts. Pathology was centrally reviewed by a neuropathologist (JC) who also evaluated p75NTR by immunohistochemistry using a scoring system (intensity index, prevalence index - % of positive cells- and a combination index - the product of the two). Brain MRIs underwent central neuroradiology review (JS). All researchers were blinded to others' results. RESULTS: Thirty patients were included; 83% were male; 87% had glioblastoma and 84% received bevacizumab as second line therapy. Recurrences were 42% local (n = 10), 21% diffuse (n= 5) and 12% distal (n = 3). Six patients (25%) had radiologic stability despite clinical deterioration. There was no association between p75 expression and pattern of progression. In univariate analysis, progression free survival (PFS) was associated with KPS [HR 0.94 (CI 95% 0.89–0.990; p = 0.046], prevalence index for p75 [HR 1.8 (CI 95% 1.17-1.34); p = 0.007], and combined score for p75 expression [HR 1.18 (CI 95% 1.03-1.34); p = 0.012]. Patients with >50% p75 positive cells had shorter PFS [HR 3.3 (CI 95% 1.12-8.89); p = 0.018]. Tumors with any p75 positive cell had worse PFS than p75 negative tumors [HR 3.64 (CI 95% 1.18-11.22); p = 0.024]. CONCLUSION: The expression of p75 was associated with PFS in recurrent MGs. We were not able to find an association between the pattern of recurrence/progression and the expression of p75 in patients with MGs after treatment with Bevacizumab.
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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 | 0.000 |
| 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".