Integration and feasibility of symptom burden assessment and early palliative care into an adolescent and young adult leukemia clinic.
Bibliographic record
Abstract
10052 Background: Patients (pts) diagnosed with hematologic malignancies during adolescence & young adulthood (AYA) are a uniquely challenging population who are understood to have robust supportive care needs. Here, we describe their symptom burdens and the feasibility of integrating palliative care into an outpatient, multi-disciplinary AYA leukemia clinic at an academic medical center. Methods: Palliative care was introduced into the AYA clinic in 8/2020 to provide symptom-focused care. Pre-existing clinic services included psychologists, pharmacists, and social workers. All established pts receiving routine follow up were referred by the oncology team to the Supportive Care team, which provided same-day palliative care consultation in the same clinic space with a telehealth option and as needed follow-up. To describe baseline symptom burdens, a random cross-sectional sample of pts completed a multi-domain symptom assessment (SA) using validated self-report instruments including physical (Edmonton Symptom Assessment Scale [ESAS]); emotional (Brief Symptom Inventory-18 [BSI-18]); financial (FACIT-COST); cognitive (Childhood Cancer Survivor Study – Neurocognitive Questionnaire); spiritual (FACIT -Spiritual Well-being Scale); and quality of life (QOL) (FACT-General) measures. All pts have a diagnosis of acute or chronic leukemia and were on active treatment or in survivorship. Results: Over 6 months, 30 pts (median age 29 years at assessment, range 18-45 years) received symptom-focused palliative care over 16 combined clinics with 81 total encounters averaging 5 pts (range 1-8) per clinic. 47% were female. No pts declined palliative care. Pts received on average 2.7 follow up visits (range 1-6), with 50% of encounters resulting in adjustments to medical management. Common issues addressed included pain, muscle cramps, neuropathy, anxiety, insomnia, depression, nausea, and non-pharmacological symptom control remedies. Of 46 pts, 31 (67%) completed the SA (median age 30 years at assessment, range 18-43 years); 48% were female; 84% were on treatment. 100% of pts reported fatigue, and 48% reported > = 1 severe symptom (range 0-7) based on the ESAS with “poor feeling of well-being” as the most common (23%). 45% met criteria for BSI-18 emotional distress, and 45% reported some neurocognitive impairment. Emotional distress (p < 0.01), financial toxicity (p = 0.03), low spiritual well-being (p < 0.01), and presence of pain, nausea, or depression (p < 0.05) were all associated with lower QOL. Conclusions: AYA pts with leukemia undergoing treatment and in survivorship experience high symptom burden with poor QOL. It is feasible to both assess symptom burden and provide early palliative care focused on symptom management in an outpatient, multi-disciplinary clinic setting.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".