How reliable are randomised controlled trials for studying the relationship between diet and disease? A narrative review
Bibliographic record
Abstract
Large numbers of randomised controlled trials (RCT) have been carried out in order to investigate diet-disease relationships. This article examines eight sets of studies and compares the findings with those from epidemiological studies (cohort studies in seven of the cases). The studies cover the role of dietary factors in blood pressure, body weight, cancer and heart disease. In some cases, the findings from the two types of study are consistent, whereas in other cases the findings appear to be in conflict. A critical evaluation of this evidence suggests factors that may account for conflicting findings. Very often RCT recruit subjects with a history of the disease under study (or at high risk of it) and have a follow-up of only a few weeks or months. Cohort studies, in contrast, typically recruit healthy subjects and have a follow-up of 5-15 years. Owing to these differences, findings from RCT are not necessarily more reliable than those from well-designed prospective cohort studies. We cannot assume that the results of RCT can be freely applied beyond the specific features of the studies.
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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 | 0.072 | 0.321 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.005 |
| 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".