Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

[Statistical analysis of a prognostic study].

A Laplanche1, C Mahé

  • 1Département de santé publique, Institut Gustave-Roussy, rue Camille-Desmoulins, 94805 Villejuif Cedex.

Bulletin Du Cancer
|October 2, 2001
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The countryside or the city: Which environment is better for the honeybee?

Environmental research·2021
Same author

Exploring uncertainty and risk in the accelerated response to a COVID-19 vaccine: Perspective from the pharmaceutical industry.

Vaccine·2020
Same author

Risk factors for Clostridioides difficile infection in hospitalized patients and associated mortality in Japan: a multi-centre prospective cohort study.

The Journal of hospital infection·2019
Same author

Differential time to positivity of central and peripheral blood cultures is inaccurate for the diagnosis of Staphylococcus aureus long-term catheter-related sepsis.

The Journal of hospital infection·2018
Same author

Patterns of relapse in poor-prognosis germ-cell tumours in the GETUG 13 trial: Implications for assessment of brain metastases.

European journal of cancer (Oxford, England : 1990)·2017
Same author

[Not Available].

Progres en urologie : journal de l'Association francaise d'urologie et de la Societe francaise d'urologie·2015

This study provides guidance on analyzing prognostic research, particularly those using Cox models with censored data in oncology. It addresses the unreliability and lack of consensus in current prognostic study methods.

Area of Science:

  • Clinical epidemiology
  • Biostatistics
  • Medical research

Context:

  • Prognostic studies are crucial for understanding disease progression and patient outcomes.
  • Challenges exist in the reliability and standardization of prognostic study methodologies.
  • Censored endpoints are common in clinical research, necessitating specific statistical approaches.

Purpose:

  • To offer methodological directions for analyzing prognostic studies.
  • To provide a framework for reliable prognostic research, especially with censored data.
  • To illustrate analytical approaches using a case study in oncology.

Summary:

  • This paper focuses on the statistical analysis of prognostic studies, frequently employing Cox proportional hazards models for censored data.

Related Experiment Videos

  • It highlights the need for improved consensus and reliability in conducting and analyzing such studies.
  • Commented results from an oncology study serve as a practical illustration.

    • Impact:

    • Aims to enhance the rigor and consistency of prognostic research in clinical and epidemiological settings.
    • Provides practical guidance for researchers dealing with censored data and Cox models.
    • Contributes to more reliable predictions of illness evolution based on individual characteristics.