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Kaplan-Meier survival analysis

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Biostatistics and epidemiology

Biostatistics

Introduction to biostatistics
Introduction to biostatistics
Types of data
Probability
Statistical probability distributions
Mean, median, and mode
Range, variance, and standard deviation
Standard error of the mean (Central limit theorem)
Normal distribution and z-scores
Parametric tests
Paired t-test
Two-sample t-test
Hypothesis testing: One-tailed and two-tailed tests
One-way ANOVA
Two-way ANOVA
Repeated measures ANOVA
Correlation
Methods of regression analysis
Linear regression
Logistic regression
Non-parametric tests
Spearman's rank correlation coefficient
Mann-Whitney U test
Kappa coefficient
Chi-squared test
Fisher's exact test
Kaplan-Meier survival analysis
Outcomes of statistical hypothesis testing
Type I and type II errors

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Kaplan-Meier survival analysis

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Kaplan-Meier survival analysis

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USMLE® Step 1 style questions USMLE

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USMLE® Step 2 style questions USMLE

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Preview

A researcher is studying the prognosis of patients diagnosed with pancreatic adenocarcinoma. Data points from 45 patients are obtained and used to generate the following Kaplan-Meier curve. The red line represents the survival curve, and the dashed lines represent the 95% confidence limits. Which of the following conclusions can be drawn from this figure?  

Summary

Kaplan-Meier survival analysis is a statistical technique used to estimate the chance of survival (or failure) for a group of patients (or other objects) over time. It does this by partitioning the total time into intervals and computing the proportion of subjects who are still alive or still in the study at the end of each interval.