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 Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

458
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
458
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

553
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
553
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

303
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
303

You might also read

Related Articles

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

Sort by
Same author

Undiagnosed dementia and mortality among older adults in the United States and Brazil: A cross-national cohort study.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Mortality and Generalizability of the National Lung Screening Trial.

JAMA network open·2026
Same author

Frequent in dementia, deadliest without it: delirium and mortality in hospitalised older adults.

Age and ageing·2026
Same author

Patterns of Daily Administration of Psychoactive Drug Classes for Distress Behavior in Dementia.

Journal of the American Medical Directors Association·2026
Same author

Using Natural Language Processing to Improve Fall Documentation in VA Nursing Home Residents.

Journal of the American Medical Directors Association·2026
Same author

End-of-Life Loneliness, Social Isolation, and Symptom Burden: A Nationally-Representative Study.

Journal of the American Geriatrics Society·2026

Related Experiment Video

Updated: Sep 19, 2025

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
07:59

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer

Published on: September 8, 2023

1.3K

Time to Benefit for Lung Cancer Screening: A Systematic Review and Survival Meta-Analysis.

Eliana E Kim1, Irena Cenzer1, Francis J Graham2

  • 1Division of Geriatrics, Department of Medicine, University of California San Francisco, San Francisco, California.

American Journal of Preventive Medicine
|May 30, 2025
PubMed
Summary

Lung cancer screening with low-dose computed tomography (LDCT) prevents one death after 2.2 to 5.2 years, depending on the number of people screened. This indicates LDCT is most beneficial for high-risk individuals with a life expectancy over 3.4 years.

More Related Videos

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening
08:14

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening

Published on: October 26, 2017

15.8K
Endobronchial Ultrasound-guided Intratumoral Injection of Cisplatin for the Treatment of Isolated Mediastinal Recurrence of Lung Cancer
04:04

Endobronchial Ultrasound-guided Intratumoral Injection of Cisplatin for the Treatment of Isolated Mediastinal Recurrence of Lung Cancer

Published on: February 12, 2017

10.6K

Related Experiment Videos

Last Updated: Sep 19, 2025

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
07:59

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer

Published on: September 8, 2023

1.3K
MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening
08:14

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening

Published on: October 26, 2017

15.8K
Endobronchial Ultrasound-guided Intratumoral Injection of Cisplatin for the Treatment of Isolated Mediastinal Recurrence of Lung Cancer
04:04

Endobronchial Ultrasound-guided Intratumoral Injection of Cisplatin for the Treatment of Isolated Mediastinal Recurrence of Lung Cancer

Published on: February 12, 2017

10.6K

Area of Science:

  • Medical Screening
  • Pulmonology
  • Oncology

Background:

  • Lung cancer screening with low-dose computed tomography (LDCT) offers long-term mortality reduction but involves immediate risks.
  • Current guidelines recommend screening for individuals with a life expectancy exceeding the time to benefit.
  • Estimating this time to benefit is crucial for optimizing screening protocols.

Purpose of the Study:

  • To estimate the time to benefit for lung cancer screening in terms of preventing lung cancer mortality.
  • To inform clinical guidelines regarding the appropriate duration of screening for individuals.

Main Methods:

  • Systematic review and meta-analysis of eight randomized controlled trials (N=88,526) on LDCT for lung cancer screening.
  • Weibull survival curve fitting and Markov chain Monte Carlo simulations to estimate absolute risk reduction (ARR) over time.
  • Time to benefit defined as time to reach ARR thresholds of 0.0005, 0.001, and 0.002.

Main Results:

  • For every 1,000 individuals screened, one lung cancer death was prevented after 3.4 years (ARR=0.001).
  • Preventing one death per 2,000 screened (ARR=0.0005) required 2.2 years; preventing one death per 500 screened (ARR=0.002) required 5.2 years.
  • Screening effectiveness varied based on the number of participants and time to benefit.

Conclusions:

  • Lung cancer screening is most appropriate for high-risk older adults with a life expectancy exceeding 3.4 years.
  • The estimated time to benefit supports the long-term nature of LDCT screening for lung cancer.
  • Individualized assessment of life expectancy is essential for determining screening eligibility.