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

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

179
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...
179
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

546
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
546
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

126
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
126
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

135
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
135

You might also read

Related Articles

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

Sort by
Same author

Left and right atrioventricular coupling: state-of-the-art review.

European heart journal. Cardiovascular Imaging·2025
Same author

A streamlined CMR-derived machine-learning model for estimating cardiovascular biological age: development and validation in the UK-biobank and multi-ethnic study of atherosclerosis.

European heart journal. Cardiovascular Imaging·2025
Same author

Association between cardiovascular-kidney-metabolic syndrome, inflammatory biomarkers, and cardiovascular outcomes: Insights from the MESA study.

Atherosclerosis·2025
Same author

Associations between visceral adipose and renal artery calcification: Results from the multi-ethnic study of atherosclerosis.

American journal of preventive cardiology·2025
Same author

More and Less Fear in Serotonin Transporter Knockout Mice.

Genes, brain, and behavior·2025
Same author

Outpatient Palliative Care Program: Impact on Home Death Rate in Brazil.

Cancers·2024

Related Experiment Video

Updated: Jun 28, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.0K

Easy to use tools for retrieving non-published data from clinically relevant subgroups.

Joao Lima1, Alexandre Jacome2

  • 1AC Camargo Cancer Center, São Paulo, Brazil.

Cell Reports. Medicine
|April 17, 2024
PubMed
Summary

Researchers can now extract crucial subgroup data from clinical trials. Two novel methods allow data retrieval for remaining patient groups when only overall and specific subgroup data are published.

More Related Videos

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

31.4K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

Related Experiment Videos

Last Updated: Jun 28, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.0K
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

31.4K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Health Research

Background:

  • Published clinical trials often present data for the total study population and specific subgroups.
  • Data for 'remaining' subgroups (those not explicitly reported) are frequently omitted.
  • This omission can limit comprehensive analysis and understanding of treatment effects across all patient segments.

Purpose of the Study:

  • To introduce and validate methods for extracting data from un-reported subgroups in clinical trials.
  • To enable more complete data utilization from published trial results.
  • To address the common issue of missing data for specific patient populations in trial reports.

Main Methods:

  • The study by Shenoy proposes two distinct mathematical methods.
  • These methods utilize reported overall population data and data from a specified subgroup.
  • The techniques allow for the inference and calculation of data pertaining to the remaining population subgroup.

Main Results:

  • Successful extraction of data for previously unreported subgroups is demonstrated.
  • The methods provide a viable approach to reconstruct missing data points.
  • This enhances the completeness of data available for meta-analysis and further research.

Conclusions:

  • The developed methods offer a valuable tool for researchers working with published clinical trial data.
  • These techniques facilitate a more thorough analysis by including data from all relevant subgroups.
  • Improved data accessibility from published trials can lead to more robust scientific conclusions.