Role of Cyproheptadine as Appetite Stimulant in Cancer Associated Anorexia
Bibliographic record
Abstract
Objectives: to assess the role of anti-histaminic serotonin antagonist cyproheptadine in treatment of cancer related appetite loss. Background: Patients with cancer often report changes in their appetite. Optimized nutritional intake together with pharmacological factors can be considered to improve food intake. Methods: One hundred thirty-eight patients with anorexia were randomized into two groups. Either to receive nutritional support only (control group) or to receive nutritional support with cyproheptadine. We used Edmonton symptom Assessment system (ESAS) and functional assessment of anorexia/cachexia therapy-anorexia cachexia scale (FAACT-ACS) scores for assessment of appetite and FAACT total scores for assessment of quality of life. Anthropometric measures, hemoglobin level and albumin were obtained at baseline. both the scores and measures were repeated every 3 months. Results: There was significant improvement in both FACCT- ACS and ESAS scores in both drug and control arms compared to baseline. The appetite scores were better in drug arm however, the difference was not statistically significant. The total FACCT quality of life scores were significantly lower than baseline scores in control arm (P value: Conclusion: Both Cyproheptadine with nutritional support improved appetite scores among the studied group of patients, however cyproheptadine helped patients in drug arm to retain body weight, BMI, albumin, and hemoglobin levels throughout the treatment period.
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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 | 0.000 |
| 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) | 0.001 | 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".