Systematic review of the association between dietary acid load, alkaline water and cancer
Bibliographic record
Abstract
OBJECTIVES: To evaluate the evidence for a causal relationship between dietary acid/alkaline and alkaline water for the aetiology and treatment of cancer. DESIGN: A systematic review was conducted on published and grey literature separately for randomised intervention and observational studies with either varying acid-base dietary intakes and/or alkaline water with any cancer outcome or for cancer treatment. OUTCOME MEASURES: Incidence of cancer and outcomes of cancer treatment. RESULTS: 8278 citations were identified, and 252 abstracts were reviewed; 1 study met the inclusion criteria and was included in this systematic review. No randomised trials were located. No studies were located that examined dietary acid or alkaline or alkaline water for cancer treatment. The included study was a cohort study with a low risk of bias. This study revealed no association between the diet acid load with bladder cancer (OR=1.15: 95% CI 0.86 to 1.55, p=0.36). No association was found even among long-term smokers (OR=1.72: 95% CI 0.96 to 3.10, p=0.08). CONCLUSIONS: Despite the promotion of the alkaline diet and alkaline water by the media and salespeople, there is almost no actual research to either support or disprove these ideas. This systematic review of the literature revealed a lack of evidence for or against diet acid load and/or alkaline water for the initiation or treatment of cancer. Promotion of alkaline diet and alkaline water to the public for cancer prevention or treatment is not justified.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".