Extending Synthesis Analysis to Survival Outcome

Music City Center 

Meta-analysis is a statistical technique to combine and summarize prior quantitative studies to assess the impact of a specific subject or intervention. Synthesizing these meta-analyses can determine the consistency and robustness of findings across different populations and settings. Synthesis analysis is one such application, which is a multivariable meta-analysis that estimates the relationship between multiple predictors and an outcome variable. However, this method has only been applied to linear and logistic models. Survival analysis, which focuses on time-to-event data, offers critical insights into the timing of events such as disease progression or treatment efficacy. Extending synthesis analysis to survival data is a novel meta-analytic approach that allows for a more comprehensive synthesis of public health studies. The extension aims to improve risk estimation, statistical power and reduce biases while optimizing temporal, labor, and financial efficiencies, focusing on non-communicable diseases like cardiovascular disease, diabetes, and cancer. This paper provides a comprehensive review of existing synthesis analyses, guiding their application to survival outcomes.

Meta-analysis

Synthesis analysis

Prediction model

Multivariable analysis

Survival outcome

Non-communicable disease 

Biometrics Section