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Journal of the National Cancer Institute Advance Access published online on January 8, 2008

JNCI Journal of the National Cancer Institute, doi:10.1093/jnci/djm265
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© The Author 2008. Published by Oxford University Press.

COMMENTARY

Visualizing Length of Survival in Time-to-Event Studies: A Complement to Kaplan–Meier Plots

Patrick Royston, Mahesh K. B. Parmar, Douglas G. Altman

Affiliations of authors: Cancer Group, Medical Research Council Clinical Trials Unit, London, UK (PR, MKBP); Centre for Statistics in Medicine, University of Oxford, Oxford, UK (DGA)

Correspondence to: Patrick Royston, DSc, Cancer Group, MRC Clinical Trials Unit, 222 Euston Rd, London NW1 2DA, UK (e-mail: pr{at}ctu.mrc.ac.uk).

Because of censoring, standard methods of plotting individual survival times are invalid. Therefore, graphic display of time-to-event data usually takes the form of a Kaplan–Meier survival plot. Kaplan–Meier plots, however, make differences between groups seem larger than they really are. To overcome these limitations, we developed a technique for producing scatter plots with survival data and applied it to data from a randomized trial of patients with renal cancer. As of June 21, 2001, 25 of the 347 patients with kidney cancer in the Medical Research Council RE01 randomized treatment trial for whom data were available had been censored, and the remainder had died. Values of the censored survival times were imputed by assuming a log-normal distribution in survival times and by drawing a random sample given that that each patient with censored data survived at least to the point of censoring. The combined original and imputed data were then examined by use of dot plots and scatter plots. In the RE01 trial, median survival of patients treated with interferon was 3.0 months (95% confidence interval = 0.3 to 5.5 months) longer than that in patients treated with medroxyprogesterone acetate. The Kaplan–Meier analysis showed clear separation between treatment groups and between prognostic groups. In contrast, comparisons of individual observed and imputed survival times between groups of patients showed considerable overlap and gave a more realistic idea of the modest between-group differences than Kaplan–Meier comparisons. These graphs of the distribution of survival times for individuals in each study group, which are simple to produce, may usefully complement Kaplan–Meier plots.



The authors take full responsibility for the design of the study, the collection of the data, the analysis and interpretation of the data, the decision to submit the manuscript for publication, and the writing of the manuscript.

None of the authors has any conflict of interests with respect to the material of this article. No specific funding was required.

Manuscript received December 11, 2006; revised October 1, 2007; accepted November 7, 2007.


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Correspondence about this Article

Re: Visualizing Length of Survival in Time-to-Event Studies: A Complement to Kaplan–Meier Plots
Nicola Lama and Ciro Gallo
J Natl Cancer Inst 2008 100: 1188. [Extract] [Full Text] [PDF]

Editorial about this Article

Times to Event: Why Are They Hard to Visualize?
Janet Wittes
J Natl Cancer Inst 2008 100: 80-81. [Extract] [Full Text] [PDF]

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Re: Visualizing Length of Survival in Time-to-Event Studies: A Complement to Kaplan-Meier Plots
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