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JNCI Journal of the National Cancer Institute 2003 95(19):1434-1439; doi:10.1093/jnci/djg052
© 2003 by Oxford University Press
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© 2003 Oxford University Press

COMMENTARY

Comparing Survival of a Sample to That of a Standard Population

Dianne M. Finkelstein, Alona Muzikansky, David A. Schoenfeld

Affiliation of authors: Biostatistics Center, Massachusetts General Hospital, Boston, MA.

Correspondence to: Dianne M. Finkelstein, PhD, Biostatistics Center, Massachusetts General Hospital, 50 Staniford St., Suite 560, Boston, MA 02114 (e-mail: finkel@biostat.harvard.edu).

The first 150 words of the full text of this article appear below.

Comparing groups on the basis of survival is common in medical research. Survival time data require methods that properly account for the situation when the time of death is not observed because some subjects are still alive at the end of the study (censoring). In addition, methods are required that make no assumptions about the shape of the survival time distribution (nonparametric). There are widely used methods for statistical comparison and graphic display of survival of two samples. The log-rank test (1) provides a comparison of the observed number of deaths in each group versus the number that would be expected if the total mortality were distributed according to the proportion in each group. These statistical comparisons are often accompanied by Kaplan–Meier curves that provide a graphic display of the distribution of survivorship over time (2). This estimator, calculated from samples that are partially censored, is . . . [Full Text of this Article]

ONE-SAMPLE LOG-RANK TEST

RELATIONSHIP TO THE STANDARDIZED MORTALITY RATIO

ESTIMATION OF EXPECTED SURVIVAL DISTRIBUTION

POWER AND CONFIDENCE INTERVALS

ILLUSTRATION: COMPARING PATIENTS TREATED FOR EXTRA-MAMMARY PAGET’S DISEASE TO THE STANDARD POPULATION

DISCUSSION

APPENDIX

Derivation of One-Sample Log-Rank Test

Confidence Interval for Standardized Mortality Ratio


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