The National Cancer Institute clinical trials planning meeting to address gaps in observational and intervention trials for cancer-related cognitive impairment
Bibliographic record
Abstract
Cancer-related cognitive impairment is a broad term encompassing subtle cognitive problems to more severe impairment. The severity of this impairment is influenced by host, disease, and treatment factors, and the impairment affects patients before, during, and following cancer treatment. The National Cancer Institute (NCI) Symptom Management and Health-Related Quality of Life Steering Committee (SxQoL SC) convened a clinical trial planning meeting to review the state of the science on cancer-related cognitive impairment and develop phase II/III intervention trials aimed at improving cognitive function in cancer survivors with non-central nervous system disease and longitudinal studies to understand the trajectory of cognitive impairment and contributing factors. Participants included experts in the field of cancer-related cognitive impairment, members of the SxQoL SC, patient advocates, representatives from all 7 NCI Community Oncology Research Program research bases, and the NCI. Presentations focused on the following topics: measurement, lessons learned from pediatric and geriatric oncology, biomarker and mechanism endpoints, longitudinal study designs, and pharmacological and behavioral intervention trials. Panel discussions provided guidance on priority cognitive assessments, considerations for remote assessments, inclusion of relevant biomarkers, and strategies for ensuring broad inclusion criteria. Three clinical trial planning meeting working groups (longitudinal studies as well as pharmacological and behavioral intervention trials) convened for 1 year to discuss and report on top priorities and to design studies. The meeting experts concluded that sufficient data exist to advance phase II/III trials using selected pharmacological and behavioral interventions for the treatment of cancer-related cognitive impairment in the non-central nervous system setting, with recommendations included herein.
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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 | 0.475 | 0.444 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.012 | 0.013 |
| Research integrity | 0.031 | 0.041 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".