Factors associated with the severity and improvement of fatigue in patients with advanced cancer presenting to an outpatient palliative care clinic
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to determine factors associated with the severity of cancer related fatigue (CRF) and predictors of improvement of CRF at the first follow-up visit in patients with advanced cancer referred to outpatient palliative care clinic (OPC). METHODS: We reviewed the records of consecutive patients with advanced cancer presenting to OPC. Edmonton Symptom Assessment System (ESAS) scores were obtained at the initial and subsequent visits between January 2003 and December 2008. All patients received interdisciplinary care led by palliative medicine specialists following an institutional protocol. Fatigue improvement was defined as a reduction of ≥2 points in ESAS score relative to the baseline. Descriptive statistics were used to summarize patient characterstics. Univariate analyses were performed and only significant variables were included in multivariate regression analysis to determine factors associated with severity and improvement in CRF. RESULTS: A total of 1778 evaluable patients were analyzed (median age, 59 years; 52% male). The median time between visits was 15 days. Median fatigue scores on the ESAS were 6 at baseline and 5 at follow-up. Severity of all ESAS items and low serum albumin were associated with fatigue at baseline (p < 0.0001). The improvement of fatigue was observed in 586 patients (33%). The hierarchical model showed that fatigue improved over time (b = -0.009; p = 0.0009). low appetite (odds ratio [OR] = 1.09 per point; p = 0.0113) and genitourinary cancer (OR = 1.74 per point; p = 0.0458) were significantly associated with improvement of fatigue. CONCLUSIONS: CRF is strongly associated with physical and emotional symptoms. Genitourinary cancer and low appetite at baseline were associated with successful improvement of fatigue.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".