[Prognostic Value of Geriatric Screening Tools in Elderly Cancer Patients].
Bibliographic record
Abstract
The elderly population is heterogeneous. Chronological age alone does not reflect heterogeneity in the aging process. It is recommended that elderly cancer patients should be evaluated for some form of geriatric assessment(GA)to detect problems, to predict treatment-related toxicities, to predict functional decline, to predict prognosis, and to assist in cancer treatment decisions. It was reported that functional status, nutritional status, mental status, polypharmacy, and comorbidity were independent prognostic factors for survival in elderly cancer patients. Although a full GA is valuable, it is time-consuming. Therefore, in a busy practice, geriatric screening tools are useful to identify patients in need of further evaluation using a full GA. Assessment for screening tools takes a few minutes. Some screening tools such as Geriatric 8(G8), Vulnerable Elders Survey-13(VES-13), Groningen Frailty Indicator(GFI), and Flemish version of the Triage Risk Screening Tool(fTRST)have prognostic value for survival. These screening tools may help physicians make informed treatment decisions in daily practice.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".