The potential of cannabinoids in managing cancer-related anorexia in older adults: a systematic review of the literature
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Anorexia of aging (AoA) is a prevalent geriatric syndrome characterized by a multifactorial decline in appetite and reduced food intake associated with the aging process. This systematic review aims to investigate the use and outcomes of cannabinoids in addressing AoA, with the goal of providing a comprehensive understanding and discussing their potential integration into daily clinical practice. METHODS: A thorough search of databases (Embase Ovid, Scopus, PubMed, Cochrane Library, and Web of Science) identified 6100 studies. After eliminating duplicates and screening titles and abstracts, 25 studies underwent full appraisal. Two reviewers assessed inclusion suitability, and study methodologies were evaluated using the Newcastle-Ottawa Scale (NOS) for observational studies and the modified Jadad Scoring Scale for randomized controlled trials. Ultimately, six studies published between 2002 and 2019, involving 869 participants, were included in the review. RESULTS: Out of the 6 fin. l papers selected, 5 were randomized trials, and 1 was a prospective study. Megestrol acetate (800 mg/d) proved to be more effective than dronabinol 2.5 mg twice a day in increasing appetite. Nabilone (at a dosage of 0.5 mg per day) did not show superiority over placebo in alleviating symptoms such as pain, nausea, loss of appetite, and weight. However, with a double dosage followed by 1.0 mg/6 weeks, after eight weeks of treatment, patients recorded a significant increase in calorie intake and carbohydrate consumption compared to the placebo group, with some patients also experiencing substantial weight gain. Regarding delta-9-tetrahydrocannabinol (THC), a weight increase of ≥10% was observed in 17.6% of patients with doses of 5 mg or 10 mg capsules daily, without significant side effects. Additionally, patients treated with THC 2.5 mg reported improved chemosensory perception and increased appetite before meals compared to placebo. No significant side effects were reported in older adults taking cannabinoids. CONCLUSIONS: Cannabinoids offer promise in enhancing the quality of life for older individuals with active neoplastic disease. However, to establish comprehensive guidelines, further research with larger sample sizes is essential. Only through this approach can we fully grasp the potential and application of cannabinoids in addressing the nutritional concerns associated with neoplastic diseases.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".