Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
Clin Cancer Res. 2012 Jul 15;18(14):3731-6. doi: 10.1158/1078-0432.CCR-11-2859. Epub 2012 Jun 6.

Cure models as a useful statistical tool for analyzing survival.

Author information

  • 1Fred Hutchinson Cancer Research Center, Seattle, WA 98117, USA. mothus@fhcrc.org

Abstract

Cure models are a popular topic within statistical literature but are not as widely known in the clinical literature. Many patients with cancer can be long-term survivors of their disease, and cure models can be a useful tool to analyze and describe cancer survival data. The goal of this article is to review what a cure model is, explain when cure models can be used, and use cure models to describe multiple myeloma survival trends. Multiple myeloma is generally considered an incurable disease, and this article shows that by using cure models, rather than the standard Cox proportional hazards model, we can evaluate whether there is evidence that therapies at the University of Arkansas for Medical Sciences induce a proportion of patients to be long-term survivors.

PMID:
22675175
[PubMed - indexed for MEDLINE]
PMCID:
PMC3744099
Free PMC Article

Images from this publication.See all images (3)Free text

Figure 1
Figure 2
Figure 3
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for HighWire Icon for PubMed Central
    Loading ...
    Write to the Help Desk