Application of Novel Response/Progression Measures for Surgically Delivered Therapies for Gliomas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The Response Assessment in Neuro-Oncology (RANO) Working Group is an international, multidisciplinary effort to develop new standardized response criteria for clinical trials in brain tumors. The RANO group identified knowledge gaps relating to the definitions of tumor response and progression after the use of surgical or surgically based treatments. OBJECTIVE: To outline a proposal for new response and progression criteria for the assessment of the effects of surgery and surgically delivered therapies for patients with gliomas. METHODS: The Surgery Working Group of RANO identified surgically related end-point evaluation problems that were not addressed in the original Macdonald criteria, performed an extensive literature review, and used a consensus-building process to develop recommendations for how to address these issues in the setting of clinical trials. RESULTS: Recommendations were formulated for surgically related issues, including imaging changes associated with surgical resection or surgically mediated adjuvant local therapies, the determination of progression in the setting where all enhancing tumor has been removed, and how new enhancement should be interpreted in the setting where local therapies that are known to produce nonspecific enhancement have been used. Additionally, the terminology used to describe the completeness of surgical resections has been recognized to be inconsistently applied to enhancing vs nonenhancing tumors, and a new set of descriptors is proposed. CONCLUSION: The RANO process is intended to produce end-point criteria for clinical trials that take into account the effects of prior and ongoing therapies. The RANO criteria will continue to evolve as new therapies and technologies are introduced into clinical trial and/or practice.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 it