051 EDMONTON FRAIL SCALE AS A PREDICTOR OF ADVERSE EVENTS IN OLDER PATIENTS UNDERGOING SYSTEMIC CANCER THERAPY IN IRELAND
Bibliographic record
Abstract
Background The Edmonton Frail Scale (EFS) is a geriatric assessment tool. It covers: Cognition, Health, Independence, Performance, Social, Medications, Nutrition, Mood, and Continence. We prospectively examined the EFS as a predictor of adverse outcomes in older patients undergoing systemic cancer therapy. Methods With ethics approval, patients aged ≥ 65 years, who were prescribed a new systemic treatment by their Consultant Medical Oncologist were approached for participation. All patients gave written informed consent and were assessed using the EFS. Patient demographics, cancer diagnosis and ECOG performance status (PS) were collected. Adverse events were assessed using the NCI CTCAE v4. The association between EFS and toxicity during systemic treatment was examined. Results Over six months, 48 patients (25 men, 23 women) of median age 72 years (range 66-92) were included. Patients had the following primary cancer diagnoses; lower gastrointestinal 25 (31%), breast 8 (17%), lung 7 (15%), upper gastrointestinal 6 (12%), and others 12 (25%). Patients were categorised as; no frailty 25 (52%), apparently vulnerable 12 (25%), mild frailty 8 (10%), moderate frailty 2 (4%) and severe frailty 1 (2%). Only 6 (12%) patients had an ECOG PS of 2 or above. A positive correlation between EFS and PS was identified. A positive association between EFS and number of toxicity events was seen (r = 0.26). During systemic treatment, 8 (16%) patients had treatments held, of whom 1 (12%) of patients had a baseline high frailty score (EFS>11). Overall, no statistically significant association was seen between EFS and dose delay (r = −0.04) or between EFS and hospitalisation (r = 0.19). Conclusion In this prospective study, frailty, as evidenced by EFS score, was associated with toxicity from systemic therapy. However, EFS did not predict for dose delay or hospitalisation. Definitive conclusions are limited by relatively small numbers and heterogeneous patient population.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".