Intravenous Vitamin C in Cancer Care: Evidence Review and Practical Guidance for Integrative Oncology Practitioners
Bibliographic record
Abstract
Intravenous vitamin C (IVC) is a common therapy used by naturopathic doctors and other licensed integrative practitioners. With several proposed mechanisms of action related to cancer care, it is often used in integrative oncology settings. Despite its common use, there are no published evidence-based resources on the efficacy, safety, and procedural considerations for the use of IVC in practice. The objectives of this review are to summarize the evidence on high-dose IVC in supportive cancer care and to provide a resource of practical clinical guidance for IVC application. In cancer care, IVC is most commonly used at doses high enough to achieve a potential cancer cell cytotoxicity. This review focuses on IVC at doses of ≥15 g which we have defined as high-dose. To date, there are 23 published clinical trials evaluating the use of high-dose IVC in cancer support. Based on data from these clinical studies, IVC used concurrently with oxidative therapies, such as chemotherapy and radiotherapy, seems to produce the greatest likelihood for improvements in quality of life and additive anti-tumour effects compared with IVC as monotherapy or with non-oxidative therapies. IVC has shown promise in improving quality of life in patients with breast cancer and advanced pancreatic and ovarian cancers. Limited evidence suggests survival and/or tumour response may be improved with the inclusion of IVC in patients with advanced pancreatic cancer, non-small cell lung cancer, and RAS-mutated colorectal cancer. IVC does not offer curative potential, and further research is needed to explore its effectiveness relevant to mortality outcomes. Practical guidance including assessment, monitoring, dosing, safety, and communication with other healthcare providers is discussed.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".