Evaluation of aspartame cancer epidemiology studies based on quality appraisal criteria
Bibliographic record
Abstract
Given the widespread use of the low-calorie sweetener aspartame over the last 30 years, the current work was undertaken to evaluate aspartame epidemiology studies looking at cancer endpoints against quality appraisal criteria. The quality appraisal tool used was from the National Heart, Lung and Blood Institute (NHLBI) of the National Institute of Health. Studies identified included nine case-control studies and five prospective cohort studies. Most studies assessed low-calorie or diet beverages rather than aspartame intake specifically; however, common use of aspartame in diet sodas does allow for some general extrapolation of results. Following consideration of study quality, two case-control and five prospective studies were considered to meet the majority of the NHLBI criteria. The primary limitation of the other case-control studies was an inadequate sample size. Overall, the results of the studies do not support that exposures to low and no-calorie sweeteners and beverages, and by extension aspartame, are associated with an increased risk of cancer in humans. • Aspartame epidemiology studies evaluated according to quality appraisal criteria. • Two case-control studies and five prospective studies were of reasonable quality. • Highest quality epidemiology studies do not support an increased risk of cancer.
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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 | 0.271 | 0.391 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.022 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".