Comprehensive geriatric assessment and management for Canadian elders with Cancer: The 5C study.
Bibliographic record
Abstract
12011 Background: Comprehensive Geriatric Assessment (CGA) is recommended by ASCO for older adults with cancer undergoing chemotherapy to identify issues that can interfere with treatment delivery and optimize functional status and quality of life. However, few randomized controlled trials have been completed so far. Our objective is to evaluate the effectiveness of CGA on improving quality of life for older adults receiving cancer treatment. Methods: Eligible patients were aged 70+, diagnosed with a solid tumour, lymphoma or myeloma, referred for first/second line chemotherapy, speaking English/French, and with an Eastern Collaborative Oncology Group Performance Status 0–2. The CGA was done by a nurse and geriatrician followed by monthly phone calls by the study nurse for 6 months. Patients were randomly assigned (1:1) to receive either the intervention (CGA plus follow-up by geriatric trained team in addition to usual oncology care) or usual care alone. All participants received a monthly healthy aging booklet for attention control. Randomization was stratified by center and treatment intent (curative/adjuvant versus palliative). Our primary outcome was health-related quality of life (HRQOL) assessed with the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 global health scale (items 29 and 30). Secondary outcomes include functional status (Instrumental Activities of Daily Living). Outcome data collection was completed monthly for the first 6 months, then at 9 and 12 months. For the primary outcome we used a pattern mixture model using an intent-to-treat approach (at 0, 3, and 6 months). The last data collection took place March 8 2021. Results: From May 2017 to March 2020, 351 participants from 8 hospitals across Canada were enrolled. All patients were seen on or after day 1 of treatment for the intervention per patient request. Patient characteristics at baseline were similar in both arms. The average age was 75.7 (SD = 4.8), 60.4% was male and 54.3% had treatment with palliative intent. Change in HRQOL scores did not differ by arm (p =.80). Neither group exceeded the MCID of 10 points. There was also no difference in IADL between the groups (p = 0.82). Conclusion: CGA was not effective in improving quality of life for older adults receiving cancer treatment in this study. CGA may need to be performed prior to treatment initiation to achieve benefits. Clinical trial information: NCT03154671.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".