Does screening for frailty with the vulnerable elders survey (VES-13) identify older adults with GU malignancy who benefit most from a consultation in a geriatric oncology clinic?
Bibliographic record
Abstract
209 Background: The VES-13 is a well-studied brief frailty screening tool for ≥ 65 older adults (OAs) in the oncology setting. Vulnerable patients (scoring ≥ 3) are at higher risk for adverse outcomes and will benefit from a Comprehensive Geriatric assessment (CGA) and cancer treatment decision optimization. Whether the VES-13 is effective specifically in patients with Genitourinary (GU) malignancies remains to be established. Primary objective: to determine if the VES-13 can predict which OAs with GU cancer (Bladder, Prostate, Kidney) had subsequent treatment modification after CGA. Secondary objective: to investigate if there is any association between VES-13 score with comorbidity and chemotherapy toxicity prediction tool (CARG). Methods: The VES-13 was administered to consecutive patients referred to the geriatric oncology (GO) clinic from GU site at the Princess Margaret Cancer Centre, Canada. All patients underwent CGA. CGA assess 8 domains including cognition, comorbidities, function, falls risk. Among patients referred for pre-treatment assessment, we examined whether the VES-13 predicted changes in the final treatment plan after CGA. Descriptive statistics were used to describe the VES-13 scores and final treatment impact. Results: From July 2015-October 2019, 77 were included in this analysis. The VES-13 ≥ 3 group were 52/77 (67.5%), and significantly associated with higher comorbidities (P = 0.003) and worse CARG scores (P = 0.005). The final treatment plan was modified in 36/77 (47%). In univariate analysis, the odds ratio (OR) for VES-13 ≥3 was 1.92 (95% CI 0.72-5.12) for change in final treatment, which was not statistically significant likely due to modest sample size. Interestingly in the same univariate analysis, there was a strong association between final treatment plan with falls risk (OR 2.63, 95% CI 1.03-6.72), physical performance (OR 2.51, 95% CI 0.98-6.45) and cognition (OR 3.95, 95% CI 1.19-13.19). Conclusions: The VES-13 identified vulnerable GU patients who will benefit from CGA and may predict treatment optimization by identifying patients at higher risk of chemotherapy toxicity and higher comorbidity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".