SGLT2 Inhibitor Cancer Risk Meta-Analysis: 28 Trials and 98,297 Participants
by Jing Teng·Updated 1mo ago
19.1 KB1files
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Description
A systematic review and meta-analysis of 28 randomized controlled trials involving 98,297 participants, published by Jing Teng in 2026, assesses the long-term safety of SGLT2 inhibitors regarding cancer risk. The analysis found no significant increase in overall cancer risk or in several common cancer types among patients with Type 2 diabetes, heart failure, or chronic kidney disease. The underlying data for this meta-analysis was sourced from PubMed, CENTRAL, Web of Science, and ClinicalTrials.gov up to April 16, 2024.
Use Cases
Conducting a secondary meta-analysis on drug safety based on the pooled risk ratios for cancer outcomes.
Validating the safety of SGLT2 inhibitors in specific patient subgroups (HF, CKD) based on the reported subgroup analyses.
Benchmarking cancer incidence data from clinical trials for Type 2 diabetes treatments.
Strengths
The analysis is based on 28 randomized controlled trials, a substantial number for a meta-analysis.
It includes data from 98,297 participants, providing a large sample size for statistical power.
The study protocol was registered in PROSPERO (CRD42024560310), indicating a structured, pre-defined methodology.
Limitations
The dataset is a 19.1 KB DOCX file, suggesting it contains summary text and tables rather than the raw, row-level clinical trial data.
Column-level documentation for any underlying data tables is absent; field semantics must be inferred after download.
Row count for any potential tabular data within the document is unknown, which may limit suitability assessment.
Provenance
Source
Systematic review of studies from PubMed, CENTRAL, Web of Science, and ClinicalTrials.gov.
Collection Method
Meta-analysis of randomized controlled trials, calculating pooled risk ratios with 95% confidence intervals.
Time Range
Studies published up to April 16, 2024.
Freshness
Last updated 2026-05-08 05:57:10; freshness should be verified.
The primary file is a DOCX document; users seeking raw, analyzable data may need to extract tables from the text.