Lipid biomarkers for the prediction of type 2 diabetes risk, an umbrella review and updated meta-analyses of prospective observational studies.

Publication bias was evident with a highly significant small-study effect in Egger’s test ( P < 0.001) and borderline significance in Begg’s tests ( P = 0.098).

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Egger’s test indicated significant small-study effects ( P = 0.005), whereas Begg’s test showed borderline significance ( P = 0.048). meanwhile, the funnel plot ( Supplementary Figure S18C ) also demonstrated evident asymmetry attributable to publication bias.

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Separately, an excess significance test was conducted using the χ 2 test to investigate whether the observed number of studies with nominally significant results (O;”positive” studies, P < 0.05) differed from the expected number of significant results (E).

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Egger’s test indicated significant small-study effects ( P < 0.001), whereas Begg’s test did not reach statistical significance ( P = 0.444). meanwhile, the funnel plot ( Supplementary Figure S18A ) also demonstrated evident asymmetry attributable to publication bias.

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