Meta-analysis of prognosis studies is used to summaries prognostic accuracy at different time points using multiple prognosis studies

1. Functionalities

  • To upload data files, preview data set, and check the correctness of data input
  • The model for meta-analysis is bivariate normal model (Hattori & Zhou. 2016)
  • To produce time-dependent summary ROC (SROC) curves and summary AUC (SAUC)
  • To detect the publication bias in the results
  • To do sensitivity analysis for the publication bias

2. The format of your data

  • Data of log hazard ratio and standard errors or confidence intervals
  • Data of survival probabilities at different time points
  • Data of median survival probabilities

Case Example

We used the meta-analysis for Ki67. (de Azambuja et al. 2007)

Please follow the Steps, and Outputs will give the analytical results.

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Summary of Prognostic Studies

Data Preview

Bivariate Normal Model for Meta-Analysis


Summary ROC (SROC) Plot

Forest Plot for lnHR
Forest Plot for Sensitivity
Forest Plot for Specificity

Likelihood-based Sensitivity Analysis for Publication Bias

Estimates of sensitivity analysis