Corticosteroid use endpoints in neuro-oncology: Response Assessment in Neuro-Oncology Working Group
Bibliographic record
Abstract
Background: Corticosteroids are the mainstay of treatment for peritumor edema but are often associated with significant side effects. Therapies that can reduce corticosteroid use would potentially be of significant benefit to patients. However, currently there are no standardized endpoints evaluating corticosteroid use in neuro-oncology clinical trials. Methods: The Response Assessment in Neuro-Oncology (RANO) Working Group has developed consensus recommendations for endpoints evaluating corticosteroid use in clinical trials in both adults and children with brain tumors. Results: Responders are defined as patients with a 50% reduction in total daily corticosteroid dose compared with baseline or reduction of the total daily dose to ≤2 mg of dexamethasone (or equivalent dose of other corticosteroid); baseline dose must be at least 4 mg of dexamethasone daily (or equivalent dose of other corticosteroids) for at least one week. Patients must have stable or improved Neurologic Assessment in Neuro-Oncology (NANO) score or Karnofsky performance status score or Eastern Cooperative Oncology Group (ECOG) (Lansky score for children age <16 y), and an improved score on a relevant clinical outcome assessment tool. These criteria must be sustained for at least 4 weeks after baseline assessment to be considered a response, and are confirmed 4 weeks after that (ie, 8 wk after baseline assessment) to be considered a sustained response. Conclusions: This RANO proposal for corticosteroid use endpoints in neuro-oncology clinical trials may need to be refined and will require prospective validation in clinical studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.127 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".