Frequency and predictors of response to outpatient palliative care in patients with moderate to severe cancer pain.
Bibliographic record
Abstract
e19698 Background: Pts with advanced cancer frequently suffer from uncontrolled pain. Response rate is an important clinical and quality of care outcome in most guidelines. The primary aim of this study is to determine frequency and predictors associated with pain response to state of the art palliative care. Methods: Consecutive pts with advanced cancer with moderate to severe pain presenting in the Supportive care clinic with a complete Edmonton symptom assessment scale (ESAS) at initial and subsequent visit were reviewed. All pts received interdisciplinary care led by palliative care specialists (IDT) following common care pathways. A logistic regression model to determine if baseline demographics, primary cancer type, ESAS, Memorial Delirium assessment scale, and CAGE (screening for alcoholism), were associated with response (defined as ≥2 points reduction in pain intensity). Results: 1150 pts (median age 60; male/female ratio 0.98) were included. Median time between initial and follow-up visit 15 days. The mean (SD), median baseline pain was 6.8 (1.9) and 7. Overall 598/1150 patients (52%) had a response. 411/639 (64%) of pts with pain ≥7/10 (severe pain group) at baseline had response compared to 187/511 (37%) of pts with moderate pain (4-6/10), (p<0.0001), however 217/639(34%) of the severe pain group had pain improved to ≤ 3/10 (mild pain) as compared to 170/511(33%) in moderate pain group (p=0.07). Fatigue (r=0.22, p<0.01), depression (r=0.14, <0.01), anxiety (r=0.16, p<0.01), sleep (r=0.15, p<0.01), and feeling of wellbeing (r=0.14, p<0.01), appetite (r=0.14, p<0.01), nausea (r=0.18, p<0.01) are associated with pain at initial consult. Factors associated with response to pain were baseline pain (OR, 1.4 per point; p<0.01), fatigue (OR, 1.01 per point; p=0.014) and ESAS symptom burden (OR, 1.01 per point; p=0.039). However, delirium (p=0.50), alcoholism (p=0.19), depression (p=0.35), anxiety (p=0.25), sleep (p=0.16) did not show significant association with pain response. Conclusions: Current response criteria have more false positive results in severe pain group. Pts with severe pain needs more frequent and aggressive IDT. Further studies are warranted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".