This tool uses automated algorithms to extract data from scientific abstracts.
While we strive for accuracy, the extraction process may occasionally misinterpret extraction values,
sample sizes, or study designs.
Always verify the extracted data against the original publication before making any clinical or
research decisions.
This tool is intended for exploratory and educational purposes only.
How It Works
MetaFemina uses large language models to facilitate rapid synthesis of evidence regarding food supplements (nutrition) and breast, ovarian, or uterine cancer. When you enter a nutritional exposure (e.g., "Coffee", "Vitamin
D", "Soy"), the tool:
Searches PubMed for relevant clinical trials and observational studies linking the
exposure to the selected cancer outcome.
Finds Key Studies on PubMed using natural language processing to extract effect sizes (odds ratios, hazard
ratios) and confidence sizes.
Synthesizes Evidence by pooling the results using a Random-Effects Meta-Analysis model.
Visualizes Results in a Forest Plot to show the overall trend.
Source of exposure list: National Institutes of Health, Office of Dietary Supplements (n.d.). Dietary
supplement fact sheets.
Understanding Meta-Analysis in Women's Cancers
A Meta-Analysis is a statistical technique that combines the results of multiple scientific
studies. By pooling data from various sources, we can get a more precise estimate of an effect than any
single study can provide.
Interpreting Heterogeneity (I²)
The I² statistic measures the percentage of variation across studies that is due to heterogeneity (true differences in effects) rather than chance. MetaFemina interprets I² based on standard guidelines:
< 25%: Low heterogeneity (indicating consistent findings across studies)
25% to < 50%: Moderate heterogeneity (suggesting some variability in results)
50% to < 75%: Substantial heterogeneity (reflecting considerable variability)
≥ 75%: Very high heterogeneity (reflecting highly inconsistent results)
If a pooled effect is statistically significant but has substantial or very high heterogeneity (I² ≥ 50%), the results are flagged to be interpreted with caution due to the high variability between the included studies.
Exposure Quantification
To facilitate accurate comparison of findings, MetaFemina categorizes how exposure to food supplements or nutritional factors was measured in each study:
Dietary Intake: The exposure is measured based on self-reported or observed consumption of foods, beverages, or supplements. Common assessment methods include food frequency questionnaires (FFQs), 24-hour dietary recalls, and diet diaries.
Human Biospecimen: The exposure is quantified objectively using biological samples collected from study participants. This involves measuring levels of the nutrient, compound, or its metabolites in biospecimens like blood (serum/plasma), urine, adipose tissue, or other body fluids.
Unclear: If the study abstract does not specify how the exposure was measured or if there is insufficient detail to categorize it, the exposure quantification type is marked as unclear.
JBI Quality Appraisal
Study quality is assessed using the JBI Critical Appraisal Tools, selected automatically
based on the study design identified by the LLM. Cross-Sectional is used as a fallback when the design is
unclear.
JBI Checklist for Randomized Controlled Trials (2023 Revision)
Was true randomization used for assignment of participants to treatment groups?
Was allocation to treatment groups concealed?
Were treatment groups similar at baseline?
Were participants blind to treatment assignment?
Were those delivering the treatment blind to treatment assignment?
Were treatment groups treated identically other than the intervention of interest?
Were outcome assessors blind to treatment assignment?
Were outcomes measured in the same way for treatment groups?
Were outcomes measured in a reliable way?
Was follow-up complete and, if not, were differences between groups in terms of their follow-up adequately described and analyzed?
Were participants analyzed in the groups to which they were randomized?
Was appropriate statistical analysis used?
Was the trial design appropriate, and were any deviations from the standard RCT design (e.g., crossover, cluster) accounted for in the conduct and analysis of the trial?
JBI Checklist for Analytical Cross-Sectional Studies
Were the criteria for inclusion in the sample clearly defined?
Were the study subjects and the setting described in detail?
Was the exposure measured in a valid and reliable way?
Were objective, standard criteria used for measurement of the condition?
Were confounding factors identified?
Were strategies to deal with confounding factors stated?
Were the outcomes measured in a valid and reliable way?
Was appropriate statistical analysis used?
JBI Checklist for Cohort Studies
Were the two groups similar and recruited from the same population?
Were the exposures measured similarly to assign people to both exposed and unexposed groups?
Was the exposure measured in a valid and reliable way?
Were confounding factors identified?
Were strategies to deal with confounding factors stated?
Were the groups/participants free of the outcome at the start of the study (or at the moment of
exposure)?
Were the outcomes measured in a valid and reliable way?
Was the follow up time reported and sufficient to be long enough for outcomes to occur?
Was follow up complete, and if not, were the reasons to loss to follow up described and explored?
Were strategies to address incomplete follow up utilized?
Was appropriate statistical analysis used?
JBI Checklist for Case-Control Studies
Were the groups comparable other than the presence of disease in cases or the absence of disease in
controls?
Were cases and controls matched appropriately?
Were the same criteria used for identification of cases and controls?
Was exposure measured in a standard, valid and reliable way?
Was exposure measured in the same way for cases and controls?
Were confounding factors identified?
Were strategies to deal with confounding factors stated?
Were outcomes assessed in a standard, valid and reliable way for cases and controls?
Was the exposure period of interest long enough to be meaningful?
Was appropriate statistical analysis used?
Scoring Criteria:
Score %: Calculated as the percentage of items rated as "Yes" (items rated "NA" are excluded from the calculation).
Good: > 80% of items rated as "Yes" (i.e., 80.1% or higher).
Moderate: 51% to 80% of items rated as "Yes" (i.e., 51.0% to 80.0% inclusive).
Fair: < 51% of items rated as "Yes" (i.e., 50.9% or lower; this includes exactly 50.0%).
References: • Barker, T. H., Stone, J. C., Sears, K., et al. (2023). The revised JBI critical appraisal tool for the assessment of risk of bias for randomized controlled trials. JBI Evidence Synthesis, 21(3), 494–506.Journal Article Link. • Joanna Briggs Institute. Critical appraisal tools.https://jbi.global/critical-appraisal-tools. Accessed 11 Feb 2026.
Bug Reporting & Feedback
If you encounter any issues, bugs, or discrepancies in the extracted data, please report them to: