The Incidence of Alcoholism in Patients with Advanced Cancer Receiving Active Treatment in Two Tertiary Care Centers in Italy
Bibliographic record
Abstract
INTRODUCTION: Substance abuse is frequently under-diagnosed among cancer patients. Alcoholism is a problem afflicting about 18% of the general population. This percentage is higher in hospitalized patients. Previous studies conducted on advanced cancer patients admitted in palliative care units have highlighted this problem only for a small percentage of cases. The objective of the study was to evaluate the incidence of alcoholism in patients with advanced cancer admitted to two Italian Oncology Units for active cancer treatment, using a recognized and validated assessment tool. SHORT SUMMARY: To evaluate the incidence of alcoholism in cancer patients and its impact on symptoms, the CAGE questionnaire was completed by 117 patients in active anticancer treatment. The percentage of CAGE-positive patients was higher than previously detected in palliative settings and was associated to male sex and lower ESAS score. METHODS: All eligible patients were enrolled consecutively during a 12-month recruitment period. Clinical and demographic data were collected. Each enrolled patient completed the Cut down, Annoyed, Guilty, Eye-opener (CAGE) questionnaire. RESULTS: Hundred and seventeen consecutive patients were surveyed in the 12-month period. The mean age was 63.3 (SD 12.0) years and 66 were males. The mean Karnofsky level was 68.3 (SD 16.0). Twelve patients were CAGE positive (10.3%). Males (P = 0.05) and patients with low Edmonton Symptom Assessment System score (P = 0.03) proved to be CAGE positive. CONCLUSIONS: Alcoholism is widespread and under-diagnosed among patients undergoing active cancer treatment. Compared with other experience in palliative settings among European population, percentage of CAGE-positive patients was double. CAGE-positive patients were more likely to be male, with lower ESAS score. It is possible to hypothesize an effect of alcohol consumption on patients' perception of symptoms. This data has never been reported in the literature and will certainly need confirmation studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".