Running a Kaplan-Meier analysis with

Dataset to run a Kaplan-Meier analysis
An Excel sheet with both the data and results can be downloaded by clicking The data have been obtained in [Gehan E.A. (1965). A generalized Wilcoxon test for comparing arbitrarily singly-censored samples. Biometrika, 52, pp 203—223] and represent a randomized clinical trial investigating the effect of the drug 6-mercaptopurine on remission times (in weeks) of acute leukemia patients. Goal of this Kaplan-Meier analysis
Our goal is to determine if and how the drug influences the survival time, by comparing the survival curves for two groups of 21 patients, the first being treated, and the second being a control group. All 21 patients of the control group were observed to have a recurrence of their leukemia. Only 9 of the 6-MP patients had an observed recurrence time, while the 12 others were censored. Setting up a Kaplan-Meier analysis
After opening XLSTAT, select the XLSTAT / XLSTAT-Life / Kaplan-Meier analysis
command, or click on the corresponding button of the XLSTAT-Life toolbar (see below).
Once you've clicked on the button, the Kaplan-Meier analysis box will appear. Select the data on the Excel sheet. The Time data corresponds to the durations when the patients either relapsed or were censored.
The Status indicator describes whether a patient relapsed (event code=1) or was censored
(censored code = 0) at a given time.
So that XLSTAT takes into account the information whether the patient belongs to the control or
the treated group, we need to select the groups information, and to activate the compare option
so that the comparison tests are computed.
The computations begin once you have clicked on OK. The results will then be displayed on a
new Excel sheet.
Interpreting the results of a Kaplan-Meier analysis
The results for the first group are displayed first. The first table displays a summary of the data for the "6-MP drug" patients. The next table corresponds to the "Kaplan-Meier table". It contains the results of the Kaplan-Meier analysis with several key indicators. The next tables give the mean and median survival time and the respective confidence intervals. Some values are missing because they could not be computed. Then, we can visualize several curves, including the survival distribution function (SDF, or survivor function, or reliability function), bounded by the confidence intervals. The circles identify the censored data. Next, the same series of results is displayed for the control group. We notice that the median survival time is a lot lower for the control group than for the 6-MP group (8.667 vs 21.943). Then, we can compare the two groups. First, a series of tests is displayed in a table. From the results we can see that the difference between the two survivor functions is very significant. Last the comparison of the two survival curves allows us to conclude to confirm that the drug impacts significantly positively the survival time of patients.



Evolution and Human Behavior 29 (2008) 19 – 25Women's body morphology and preferences forBoguslaw Pawlowskia,b,c,⁎, Grazyna Jasienskad,eaDepartment of Anthropology, University of Wroclaw, 50-138 Wroclaw, PolandbDepartamento de Ecologia Humana CINVESTAV-IPN, Unidad Mérida, 97310 Mérida, MexicocInstitute of Anthropology, Polish Academy of Sciences, 50-951 Wroclaw, PolanddDepartment o


JAVIER ERNESTO SHEFFER TUÑÓN (Resumen ejecutivo) Licenciado en Derecho y Ciencias Políticas egresado de la Universidad de Panamá, con Postgrado en Negociación y Métodos Alternativos para la Solución de Controversias, cursado en la Universidad Tecnológica de Panamá. Posee máster en estas disciplinas alternas al sistema tradicional de justicia ordinaria. Designado por el Mini

Copyright ©2010-2018 Medical Science