Bevacizumab Combined with Corticosteroids Does Not Improve the Clinical Outcome of Nasopharyngeal Carcinoma Patients With Radiation-Induced Brain Necrosis
Bibliographic record
Abstract
Objective Our aim was to compare the clinical outcomes of patients treated with bevacizumab combined with corticosteroids and those with bevacizumab monotherapy from a radiation-induced brain necrosis (RN) registry cohort (NCT03908502). Methods We utilized clinical data from a prospective RN registry cohort (NCT03908502) from July 2017 to June 2020. Patients were considered eligible if they had symptomatic RN after radiotherapy for nasopharyngeal carcinoma (NPC) and received bevacizumab (5 mg/kg, two to four cycles) with a minimum follow-up time of 3 months. The primary outcome was a 2-month response rate determined by MRI and clinical symptoms. Secondary outcomes included quality of life [evaluated by the abbreviated World Health Organization Quality of Life (WHOQOL-BREF) questionnaire] and cognitive function (evaluated by the Montreal Cognitive Assessment scale) at 2 months, RN recurrence during follow-up, and adverse events. Results A total of 123 patients (34 in the combined therapy group and 89 in the monotherapy group) were enrolled in our study with a median follow-up time of 0.97 year [interquartile range (IQR) = 0.35–2.60 years]. The clinical efficacy of RN did not differ significantly between patients in these two groups [odds ratio (OR) = 1.642, 95%CI = 0.584–4.614, p = 0.347]. Furthermore, bevacizumab combined with corticosteroids did not reduce recurrence compared with bevacizumab monotherapy [hazard ratio (HR) = 1.329, 95%CI = 0.849–2.079, p = 0.213]. The most common adverse events of bevacizumab were hypertension (17.89%), followed by nosebleed (8.13%) and fatigue (8.13%). There was no difference in grade 2 or more severe adverse events between the two groups (p = 0.811). Interpretation Our results showed that the treatment strategy of combining bevacizumab with corticosteroids did not lead to better clinical outcomes for RN patients with a background of radiotherapy for nasopharyngeal carcinoma.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".