Patient-physician agreement on function and pain is associated with long-term outcomes in sarcoma: findings from a longitudinal study
Bibliographic record
Abstract
PURPOSE: We aimed to describe the level of agreement between patients and physicians on the ratings of daily functioning and pain in a cohort of sarcoma patients and assess how (dis)agreement and its change over time predicted patient-reported outcomes in survivorship. METHOD: We performed secondary analysis of longitudinal data from a sarcoma-specialty clinic in Montreal, Canada. Demographics, clinical characteristics and patient-physician agreement were summarized descriptively. Linear mixed models were used to assess the effects of time, baseline agreement, change in agreement over time, interaction of time and change in agreement and 12-month daily functioning, quality of life, and fatigue. RESULTS: Data were available for 806 patients (57.7% male, x̄ = 53.3 years) who completed at least one questionnaire. Patient-physician disagreement was common on the level of function (43.4%) and pain (45.7%). Baseline physician-patient agreement was associated with better 12-month outcomes. Improvement in agreement on function over time was significantly associated with daily functioning (F(2, 212) = 3.18, p = 0.043) and quality of life (F(2, 212) = 3.17, p < 0.044). The pattern was similar though less pronounced for the agreement on pain. CONCLUSIONS: Our study offers novel insights into the importance of patient-physician agreement and communication's role in long-term patient-reported outcomes in sarcoma. IMPLICATIONS FOR CANCER SURVIVORS: The results emphasize the importance of mutual understanding of symptoms and patients' needs and suggest that further consultation in cases of discordance of ratings and opinions might be beneficial for optimal survivorship.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".