Geriatric assessment with management for older patients with cancer receiving radiotherapy. Protocol of a Norwegian cluster-randomised controlled pilot study
Bibliographic record
Abstract
About 50% of patients with cancer are expected to need radiotherapy (RT), and the majority of these are older. To improve outcomes for older patients with cancer, geriatric assessment (GA) with management (GAM) is highly recommended. Evidence for its benefits is still scarce, in particular for patients receiving RT. We report the protocol of a cluster-randomised pilot study designed to test the effect, feasibility and health economic impact of a GAM intervention for patients ≥65 years, referred for palliative or curative RT. The randomising units are municipalities and city districts. The intervention is municipality-based and carried out in collaboration between hospital and municipal health services from the start of RT to eight weeks after the end of RT. Its main constituents are an initial GA followed by measures adapted to individual patients' impairments and needs, systematic symptom assessments and regular follow-up by municipal cancer nurses, appointed to coordinate the patient's care. Follow-up includes at least one weekly phone call, and a house call four weeks after the end of RT. All patients receive an individually adapted physical exercise program and nutritional counselling. Detailed guidelines for management of patients' impairments are provided. Patients allocated to the intervention group will be compared to controls receiving standard care. The primary outcome is physical function assessed by the European Organisation of Research and Treatment of Cancer Quality of Life Questionnaire C-30. Secondary outcomes are global quality of life, objectively tested physical performance and use of health care services. Economic evaluation will be based on a comparison of costs and effects (measured by the main outcome measures). Feasibility will be assessed with mixed methodology, based on log notes and questionnaires filled in by the municipal nurses and interviews with patients and nurses. The study is carried out at two Norwegian RT centres. It was opened in May 2019. Follow-up will proceed until June 2022. Statistical analyses will start by the end of 2021. We expect the trial to provide important new knowledge about the effect, feasibility and costs of a GAM intervention for older patients receiving RT. Trial registration: ClinTrials.gov, ID NCT03881137, initial release 13th of March 2019.
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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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".