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.

Download Manual

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

Set Parameter

1. Probabilities

2. beta init:

3. Label for x-axis

4. Label for y-axis

5. Choose SROC type

SROC

HSROC

1. Functionalities

2. The format of your data

Case Example

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

Summary of Prognostic Studies

Step 1. Data preparation

Step 1. Data preparation

Choose delimiter that separates the values

Step 2. Sheets selection

Step 3. Data preparation

Select Data

Editor

Data Preview