Prognostic significance of symptoms of advanced cancer patients
Bibliographic record
Abstract
8150 Background: Advanced cancer Palliative care patients have a variety of distressing symptoms. Their prognostic significance with regard to survival has not been systematically studied. Methods: Symptoms (type and severity) were assessed during an in-depth interview by a clinical nurse specialist with 166 cancer patients (46% male, 54% female) referred to a university hospital palliative care teamnurse specialist. WHO performance status: 2% 1, 27% 2, 50% 3, 21% 4. Diagnosis: 14% breast, 11% gynaecological, 19% gastrointestinal, 11% head and neck, 11% lung, 8% prostate and 26% other types of cancer. For 90 patients scores were available from the Edmonton Symptom Assessment Schedule (ESAS). Medical data and survival were recorded. The prognostic significance of the most frequent symptoms was analysed using Kaplan-Meier and multivariate linear and logistic regression analyses. Results: We recorded 29 different physical and psychological symptoms occurring in ≥10% of patients. 96% of the patients has have died. Survival at two months was 51%. In univariate analysis, headache, abdominal pain, pain in an extremity, anorexia, nausea, vomiting, dysphagia, dyspnea, drowsiness, confusion and depression were predictive of survival. The ESAS-scores for anorexia, nausea, dysphagia, dyspnea and drowsiness were significantly correlated with survival. After correcting for diagnosis, dyspnea, dysphagia, vomiting, confusion and nausea vomiting, confusion and nausea (occurring in 31%, 11%, 25%, 17% and 39%, 25%, 17% and 39% of patients, respectively) were independent predictive factors of survival. Patients with confusion, dyspnea, dysphagia or vomiting had an increased chance of dying within two months of 9.4, 7.3, 4.3, and 4.,3, respectively, compared to patients without these symptoms. Conclusion: Patients with confusion, dyspnea, dysphagia, vomiting or nausea have a significantly worse prognosis, regardless of diagnosis. A comprehensive assessment of symptoms is useful to determine prognosis in advanced cancer patients. No significant financial relationships to disclose.
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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 | 0.003 |
| 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) | 0.002 | 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".