Factors Affecting the Treatment Heterogeneity of PPARγ and Pan-PPAR Agonists in Type 2 Diabetes Mellitus: A Systematic Review and Machine Learning-Based Meta-Regression Analysis
Abstract
Background/Objectives: Significant heterogeneity in the treatment response to peroxisome proliferator-activated receptor γ (PPARγ) agonists exists, and predictive factors for their efficacy remain unclear. We aimed to assess the relationships between routinely available clinical features and the efficacy of PPARγ agonists and pan-PPAR agonists by meta-regression analysis. Methods: We searched PubMed, Embase, Cochrane Library, ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) and included randomised controlled trials involving type 2 diabetes patients with 12-week or longer treatment durations with PPARγ agonists or pan-PPAR agonists published before 11 November 2023 (PROSPERO registration number: CRD42024578987). We conducted mixed-effect meta-regression analyses between baseline variables and treatment response. Moreover, we developed a machine learning-based meta-forest model and ranked the relative importance of each variable. Results: In 147 studies involving 29,250 participants, PPARγ and pan-PPAR agonists significantly reduced HbA1c (mean difference(MD) = −0.8876 [95% confidence interval (CI): −0.8999, −0.8754]; p < 0.0001, I2 = 96.0%) and FPG = (MD = −1.7900 [95% CI: −1.9137, −1.6663]; p < 0.0001, I2 = 92.0%). Multivariable association analysis suggested that a greater proportion of female participants (β = 0.0066 [95% CI: 0.0012, 0.0121]; p = 0.017), younger age (β = −0.0314 [95% CI: −0.05, −0.0129]; p = 0.0009) and lower HDL-C…
How strong is the evidence?
Evidence Hub reads this as a systematic review, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 29,250 participants or records.
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