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Record W4367316328 · doi:10.1016/j.gloepi.2023.100110

The role of study quality in aspartame and cancer epidemiology study reviews

2023· article· en· W4367316328 on OpenAlexaboutno aff
Julie E. Goodman, Elyssa G. Anneser, Alahi Khandaker, Denali N. Boon

Bibliographic record

VenueGlobal Epidemiology · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsnot available
FundersAmerican Beverage Association
KeywordsAspartameEpidemiologyCancerQuality (philosophy)Environmental healthMedicineFood scienceBiologyInternal medicinePhysics

Abstract

fetched live from OpenAlex

Toews et al. [1] and the World Health Organization (WHO) [2] reviewed observational epidemiology studies of non-sugar sweeteners (NSSs) and various health effects. The former used the Risk of Bias in Non-randomised Studies - of Interventions (ROBINS-I) tool and the latter used both the ROBINS-I tool and the Newcastle-Ottawa Scale to evaluate study quality. Both reviews concluded that there were no associations between NSS or aspartame consumption and cancer (except possibly between saccharin and bladder cancer) but indicated that the certainty of the evidence for all cancer types was "very low." While we agree with this conclusion, the support for the confidence in the evidence generally was not transparently documented, as the results of the study quality assessment were only provided in scores or ratings. An examination of illustrative case studies shows that some important aspects of study quality domains specific for NSSs generally or aspartame specifically (i.e., issues with the exposure and outcome assessments, the consideration of confounding/covariates, and selection bias) may have been overlooked or not given appropriate consideration, while other aspects that were less likely to have a large impact on overall study quality dominated the results in the two assessments. Our review of other studies published after the WHO [2] review further demonstrates this point. While this may not seem important given the overall lack of associations, it impacts the degree to which evidence supports a lack of effects as opposed to not being adequate to evaluate associations. In the future, aspartame and cancer outcome reviews should focus on those study quality domains that are most likely to impact the interpretation of results and discuss them in a transparent, systematic manner. If there is very low certainty in the evidence as a result of low study quality, reviewers should conclude the evidence is inadequate for making a causal determination.

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 imitation

Not 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.

metaresearch head score (Codex)0.640
metaresearch head score (Gemma)0.890
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.444

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6400.890
Meta-epidemiology (narrow)0.0020.004
Meta-epidemiology (broad)0.0120.010
Bibliometrics0.0210.027
Science and technology studies0.0040.011
Scholarly communication0.0160.014
Open science0.0090.009
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.205
GPT teacher head0.517
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designSystematic review
DomainMethods
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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