Predictive role of Vulnerable Elders Survey-13 screen tool for elder cancer patients in final oncology treatment plan.
Bibliographic record
Abstract
e24020 Background: The Vulnerable Elders Survey (VES-13) is one of several tools that can identify older patients who are vulnerable (if the score is ≥ 3 out of 10) and more likely to benefit from Comprehensive Geriatric Assessment (CGA) prior to cancer treatment. The optimal cutpoint of the VES-13 to identify those whose final oncologic treatment plan would change after CGA is unclear. We hypothesized that patients with high positive scores (7-10) will have a higher likelihood of a change in the final oncologic treatment plan compared to low positive patients (score 3-6). Methods: Retrospective review of a customized database of all patients seen for pre-treatment assessment (solid tumor and lymphoma) in the geriatric oncology clinic at the Princess Margaret Cancer Centre from June 2015 to June 2019. Various VES-13 score cutpoints were compared with the final treatment plan to identify those individuals whose treatment was modified after CGA. Area under the curve was calculated and subgroups of patients treated locally or systemically were also examined to determine if performance varied by type of patient. Results: 386 patients with mean age 81, 58% males were included. Gastrointestinal cancer was the most common site 31% and 60% were planned to receive curative treatment. The final treatment plan was modified in 50% with VES-13 scores 7-10, 46.7% with scores 3-6 and 26.8 % for scores < 3 (P = 0.002; Table). The optimal VES-13 cutoff was between 3-6 (C-statistics 0.57-0.59).The VES-13 performed similarly in those considering local treatment (surgery with/without radiation) vs. chemotherapy. Modified final treatment for local therapy with VES-13 scores < 3 was 11.4 % compared to 42.9% with scores ≥ 3 was 42.9% (p-value < 0.001), whereas for systemic therapy it was 32.4% and 62.5%, respectively (p-value = 0.002). Conclusions: Although high positive VES-13 scores (7-10) had slightly higher likelihood of having the final oncologic treatment plan modified, there was no strong advantage compared to the conventional cutpoint of 3 or higher. The VES-13 performed similarly in predicting treatment change after CGA for local and systemic treatment plans. Further studies are required to identify the optimal frailty screening tool and cutpoint. [Table: see text]
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".