Methods for frailty screening and geriatric assessment in older adults with cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review highlights the latest development in the use of geriatric assessment(GA) and frailty assessment for older adults with cancer. RECENT FINDINGS: From 2019, there were six large randomized controlled trials (RCTs) completed of GA for older adults with cancer, as well as several studies of frailty screening tools. SUMMARY: The findings in this review highlight the benefits of implementing GA, followed by interventions to address the identified issues (GA -guided interventions). Four of six RCTs that implemented GA for older adults with cancer showed positive impact on various outcomes, including treatment toxicity and quality of life. GA implementation varied significantly between studies, from oncologist acting on GA summary, geriatrician comanagement, to full GA by a multidisciplinary team. However, there were several barriers reported to implementing GA for all older adults with cancer, such as access to geriatrics and resource issues. Future research needs to elucidate how to best operationalize GA in various cancer settings. The authors also reviewed frailty screening tools and latest evidence on their use and impact.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".