Curbside Consults Podcast
Published November 27, 2019
Survival data are central to the analysis of clinical trials, with many journal club discussions anchored around the tables and graphs used to display these outcomes. In this episode of Curbside Consults, we are joined once again by Dr. David Harrington, statistical editor at the NEJM, for a discussion on how survival is defined and how the data are interpreted and used.
0:00 – Introduction
1:36 – Stats content introduction
2:37 – Paper to be discussed: Perl et al. Gilteritinib or Chemotherapy for Relapsed or Refractory FLT3-Mutated AML.
3:21 – How is survival defined?
4:18 – What kind of information do survival analyses give?
5:21 – How does one account for staggered entry when calculating and comparing survival data?
5:49 – Dealing with the data from patients who are lost to follow-up
6:18 – What about patients who make it all the way through the study without the event occurring?
6:46 – How do you determine length of time for follow-up?
7:45 – Can survival analyses be applied to retrospective data?
9:31 – What is the Kaplan-Meier method?
10:58 – What other methods are used with survival data?
12:12 – How do we account for recurrent events?
12:31 – Can we use survival curves to extrapolate a clinical prognosis?
13:22 – What are some of the biases and limitations to be aware of in a survival analysis?
14:29 – Takeaways and Conclusion
Resources and articles discussed in this episode:
1. Perl AE et al. Gilteritinib or Chemotherapy for Relapsed or Refractory FLT3-Mutated AML. N Engl J Med 2019.
The Curbside Consults series complements the foundational information in Rotation Prep by taking a deep dive into key clinical topics with expert clinicians and educators. These podcasts explore and critique the evidence behind clinical practice and break down statistical concepts for the busy clinical trainee.