Guyot-SAS

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Reconstructing individual-level data from published Kaplan-Meier survival curves using the method proposed by Guyot, Patricia et al.

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Code

The code in guyot.sas implements the methods described here.

Inputs

• x is a vector of x coordinates taken from a Kaplan-Meier curve
• y is a vector of y coordinates taken from a Kaplan-Meier curve
• t is a vector of timepoints t where the number at risk is reported
• r is a vector of the number at risk for each timepoint in t
• tot_events is the total number of events reported (optional)

Outputs

The guyot_method module returns a matrix of individual data in rows. The two columns are time and event.

Requirements

Theis code requiers an installation of SAS software with the SAS/STAT (PROC LIFETEST) and SAS/IML (PROC IML) packages, version 14.2 or higher.

If you do not have a SAS license and want to review these methods for educational purposes, check out the free learning offering from SAS here. This free offering includes the required packages.

Method

Guyot, P., Ades, A., Ouwens, M.J. et al. Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves. BMC Med Res Methodol 12, 9 (2012). https://doi.org/10.1186/1471-2288-12-9

Basis for this code

This code follows the R code implementation found here. The sections of this code are marked with comments containing line number ranges, which correspond to the R code implementation, making comparison easy. Several small changes are implemented to provide error catching (for instance, avoiding divide by zero) and taking advantage of SAS/IML language features.

Collaboration and Issues

If you discover bugs, have questions, or have an idea for a feature, then please use the issues tracking part of this repository.

If you have made a change that you would like to share then, please make a PULL request to this repository.

Validation

A series of code checks are currently under construction. The author seeks a third party to assist in an unbiased review of this implementation with validation against the R implementation and the original research. Please reach out if you would like to help with this.

Other Methods

• Tierney, J.F., Stewart, L.A., Ghersi, D. et al. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials 8, 16 (2007). https://doi.org/10.1186/1745-6215-8-16
• Parmar, M. K. B., Torri, V., & Stewart, L. (1998). Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Statistics in Medicine, 17(24), 2815-2834. https://doi.org/10.1002/(SICI)1097-0258(19981230)17:24<2815::AID-SIM110>3.0.CO;2-8
• Hoyle, M.W., Henley, W. Improved curve fits to summary survival data: application to economic evaluation of health technologies. BMC Med Res Methodol 11, 139 (2011). https://doi.org/10.1186/1471-2288-11-139

An excellent review of these methods and the Guyot method is found here.

Example

The following code runs the guyot_method module with created input data. The resulting individual patient data (IPD) is then constructed into a SAS dataset with columns time, event, and treatment. The SAS dataset is used to fit a survival model with PROC LIFETEST (SAS/STAT), and the resulting Kaplan-Meier fit plot is included below.

PROC IML;
    /* Example of Use */
        ipd_curve1 = guyot_method(0:100, exp((-1/50)*(0:100)), {0 10 50}, {1000 800 250});
        ipd_curve2 = guyot_method(0:100, exp((-1/30)*(0:100)), {0 10 50}, {1000 700 100});

        colnames={"time" "event" "treatment"};
            treat1 = j(nrow(ipd_curve1),1,'active');
            treat2 = j(nrow(ipd_curve2),1,'chemo');
        create ipd from ipd_curve1 treat1 [colname=colnames];
            append from ipd_curve1 treat1;
            append from ipd_curve2 treat2;
        close ipd;

        submit;
            ods graphics on;
                proc lifetest data=ipd plots=s(cl nocensor);
                    time time * event(0);
                    strata treatment;
                run;
            ods graphics off;
        endsubmit;
QUIT;