Examination of real-world data from geriatric assessments in a comprehensive cancer center to explore predominant and cancer-specific domains for intervention.
Bibliographic record
Abstract
e24027 Background: Older adults (OA) with cancer have a higher risk of harm with cancer treatment. Geriatric Assessment (GA) based treatment modifications can help mitigate toxicity and functional impairment. The Geriatric Oncology Assessment and Plan (GOAL) Clinic was established with the aim of providing age-friendly care to OA with cancer at Huntsman Cancer Institute. This retrospective study presents the needs identified using GA in the real-world setting. Methods: Patients (pts) aged ≥65 years are referred to the GOAL clinic by their oncologists/hematologists for age-related concerns. A geriatrics nurse practitioner administers a GA upon initial visit, communicates specific age-related concerns with the referring provider, and subsequently manages any geriatric syndromes that may interfere with their treatment tolerance or outcomes. We analyzed GA data to identify the specific needs of OA with cancer referred to the GOAL clinic. Results: We evaluated 222 pts in the GOAL clinic between September 2020 and January 2023. The median age was 77 years, 52% were female. The most common cancer diagnosis was prostate, followed by breast, colorectal, pancreatic, and bladder. Of the pts assessed, the median Eastern Cooperative Oncology Group (ECOG) was 1, and the median body mass index (BMI) was 26.4 kg/m 2 . 12% of pts had a moderate to high risk for malnutrition. A Patient Health Questionnaire-9 (PHQ-9) showed minimal, mild, moderate, moderately severe, and severe depression in 35%, 20%, 14%, 7%, and 3% of pts, respectively. The Generalized Anxiety Disorder scale-7 (GAD-7) showed minimal, mild, moderate, and severe anxiety symptoms in 35%, 19%, 9%, and 7% of pts respectively. The median Mini-cog score was 4, and those who reflexed to testing with Montreal Cognitive Assessment (MOCA) had a median score of 22 out of 30 suggesting mild cognitive impairment (MCI). A greater proportion of pts with prostate cancer (PC) were overweight and had MCI by MOCA (Table 1). Multidisciplinary interventions were implemented, and GA was used to determine the appropriateness of cancer treatment. Conclusions: Cognitive dysfunction and depression were this population's most common geriatric syndromes. PC pts had a higher median BMI and greater proportion of patients with MCI than pts with other cancers. Dysmetabolic syndrome associated with elevated BMI is not a domain of GA but is pertinent to treatment toxicity in PC. MCI is not apparent on a routine oncology evaluation. Interventions are needed to prevent, screen, and treat MCI in OA with cancer, especially PC, and dysmetabolic syndrome in OA with PC.[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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.001 | 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".