Factors Associated with Early Referral to Palliative Care in Outpatients with Advanced Cancer
Bibliographic record
Abstract
BACKGROUND: Although timely palliative care is recommended for patients with advanced cancer, referrals to palliative care services are often late. OBJECTIVES: To identify factors associated with early referral to an oncology palliative care clinic and to describe symptom severity according to timing of referral. DESIGN: We conducted a retrospective review of 337 patients with advanced cancer referred to outpatient palliative care at a comprehensive cancer center. We gathered data related to patient demographics, diagnosis, and referral. Timing of referral was categorized as early (>12 months before death), intermediate (6-12 months before death), or late (<6 months before death). Ordinal logistic regression was used to determine factors related to referral timing, and the Kruskal-Wallis test to determine symptom severity in each referral timing category. RESULTS: Of the 337 patients, 232 (69%) referrals were late, 60 (18%) intermediate, and 45 (13%) early. On multivariable analysis, earlier referral was associated with earlier primary cancer diagnosis (p = 0.004), and referral for pain and symptom management (p = 0.001). Patients who were referred late had worse overall Edmonton Symptom Assessment System distress scores, as well as worse tiredness, nausea, drowsiness, appetite, and wellbeing (all p ≤ 0.001). Severity of pain, shortness of breath, anxiety, and depression did not differ based on time of referral. CONCLUSIONS: A longer disease course and referral for symptom management were associated with earlier referral, whereas overall symptom burden was higher for late referrals. Further research is required on combining symptom screening with timely referral to improve symptom management in advanced cancer.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".