Vitamin C for the Treatment of Depression in Cancer Patients: A Literature Review
Bibliographic record
Abstract
Introduction: One in two Canadians will be diagnosed with cancer in their lifetime and one in four will experience depression during their diagnosis. The cause of depression during cancer could be related to psychological, social, inflammatory, or immunological factors. Vitamin C can exert an effect on oxidative stress levels, adrenal function, and immune function and may have a role in the treatment of both cancer and depression. Vitamin C levels can affect neurotransmitter levels and its ability to increase quality of life in cancer patients, as well as relieve other cancer-related symptoms such as pain, has been documented. Methods: A systematic literature search was completed to identify all studies that assessed changes in depression symptom severity in patients receiving intravenous vitamin C treatment. The databases utilized include PubMed, Medline Complete, CINAHL Plus, Web of Science, Cochrane, and PMC. The inclusion criteria were: human participants with confirmed cancer of any type and stage, intravenous vitamin C treatment, with or without conventional treatment and with or without additional oral vitamin C dosing, and assessment of depression. Results: Out of 152 unique articles analyzed, four observational studies evaluate depression symptoms as part of an assessment of quality of life in cancer patients undergoing intravenous vitamin C treatment. All four studies reported improvement in mood. Discussion: The four included studies assessed the role of intravenous vitamin C in the treatment of depression in cancer patients. These studies confirmed previous research reporting improved quality of life and other cancer-related benefits (i.e. decreasing fatigue and pain). All four studies noted a decrease of depression in cancer patients which are summarized in Table 1. The included studies all evaluated safety and reported no significant adverse effects associated with the treatment. Conclusion: The current literature suggests that intravenous vitamin C could potentially have a beneficial effect on levels of depression in patients with cancer; however, more research is needed. Prospective clinical trials using validated assessment tools to capture changes in depression and control groups are needed to further study the potential role of this therapy in the treatment of depression in cancer patients.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".