Methodology used to develop the AANS/CNS management of brain metastases evidence-based clinical practice parameter guidelines
Bibliographic record
Abstract
Brain metastases, which occur in approximately 20–40% of individuals with systemic cancer, represent a significant cause of morbidity and mortality and overwhelm all other types of brain tumors in terms of incidence and public health impact [1]. Considerable research has focused on improving survival and quality of life for this patient population. Given the expanding knowledge base and the rapid emergence of new therapies, the American Association of Neurological Surgeons (AANS), the Congress of Neurological Surgeons (CNS), and the AANS/CNS Joint Tumor Section jointly funded an initiative to produce methodologically rigorous evidence-linked clinical practice parameter guidelines on this topic. The overall objective of this series of guideline papers is to provide the latest up-to-date evidence-based recommendations for the management of patients with brain metastases centering on eight questions related to commonly encountered clinical scenarios (Tables 1, 2, 3). Accomplishment of this goal required undertaking a systematic review of the literature. The McMaster University Evidence-based Practice Center (EPC), which is an academic research unit partially funded by an EPC grant from the Agency for Healthcare Research and Quality (AHRQ), with specialized expertise in evidence-based medicine and the development of systematic reviews, was contracted to performed the systematic review in consultation with the guideline panel assembled for the initiative. The McMaster EPC also served as facilitators during the guideline development, consensus and writing processes. The Joint Tumor Section of the AANS/CNS recruited representatives from surgical neuro-oncology (including microsurgical, stereotactic radiosurgery and experimental therapies), radiation oncology (fractionated radiotherapy, stereotactic radiosurgery and brachytherapy) and medical neuro-oncology (chemotherapy and experimental therapies) to form a multi-disciplinary panel of 17 clinical experts who developed the evidence-based practice guidelines from the systematic review results (Table 4). These seventeen experts across several disciplines were all nominated and selected by the Executive Committee of the AANS/CNS Tumor Section based on their clinical expertise and recognized contributions to the field of neurooncology in general and brain metastases in particular. The Tumor Section Executive Committee then selected a chairperson for this endeavor to organize and lead the effort, serving also to encourage and manage debate on the various topics involved.
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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 | 0.114 | 0.339 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".