Dairy product consumption and development of cancer: an overview of reviews
Bibliographic record
Abstract
OBJECTIVES: To provide a comprehensive systematic overview of current evidence from pooled analyses/meta-analyses and systematic reviews (PMASRs) pertaining to dairy consumption and incident cancer and/or all-cause or cancer-specific mortality. DESIGN: Overview of reviews. SETTING: Community setting. PARTICIPANTS: The unit of analysis is PMASRs. A total of 42 PMASRs was included in this overview of reviews. INTERVENTIONS/EXPOSURES: Any dairy product consumption (eg, milk, yogurt, etc). PRIMARY AND SECONDARY OUTCOMES MEASURES: Primary outcome measure is development of any type of cancer. Secondary outcome measures are all-cause mortality and cancer-specific mortality. RESULTS: From 9693 citations identified, we included 42 PMASRs (52 study reports) published between 1991 and 2017. Thirty-one (74%) of these was pooled analyses/meta analyses, and only 11 (26%) were systematic reviews and meta-analyses. There was a wide variability in the type of study designs included within the other PMASRs, thus contributing to variable and, in instances, divergent estimates of cancer risk for several cancer subtypes. For example, only one systematic review and meta-analysis exclusively included prospective study designs. Most PMASRs were of low to moderate quality based on the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) scores. The median AMSTAR score was 5 (IQR 2-7). Our overview identified conflicting evidence from PMASRs on association between dairy consumption and incident cancers or mortality. Heterogeneity in summary estimates reflected the inclusion of variable study designs and overall low methodological quality of individual PMASRs. CONCLUSIONS: The association between dairy consumption and cancer risk has been explored in PMASRs with a variety of study designs and of low to moderate quality. To fully characterise valid associations between dairy consumption and risk of cancer and/or mortality rigorously conducted, PMASRs including only high-quality prospective study designs are required. TRIAL REGISTRATION NUMBER: CRD42017078463.
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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 | 0.014 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.012 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".