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Related Concept Videos

Clinical Trials01:16

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

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,...
Clinical Trials: Overview01:11

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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, controlled...
Cancer Survival Analysis01:21

Cancer Survival Analysis

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...

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Related Experiment Video

Updated: Jul 4, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Analytical approaches to reporting long-term clinical trial data.

Kim A Papp1, Philippe Fonjallaz, Florence Casset-Semanaz

  • 1Probity Medical Research, Waterloo, ON, Canada. kapapp@probitymedical.com

Current Medical Research and Opinion
|June 7, 2008
PubMed
Summary

Long-term clinical studies require robust data analysis. The authors recommend an intent-to-observe approach with multiple methods to handle missing data, ensuring reliable drug safety and effectiveness monitoring.

Related Experiment Videos

Last Updated: Jul 4, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Area of Science:

  • Clinical trial methodology
  • Biostatistics
  • Pharmaceutical research

Background:

  • Long-term clinical studies are crucial for assessing drug safety and efficacy beyond initial approvals.
  • Short-term trial designs (e.g., randomized controlled trials) may not adequately address challenges in long-term studies, such as patient attrition and missing data.
  • Standard analytical strategies like intent-to-treat and per-protocol may introduce bias in long-term data analysis.

Purpose of the Study:

  • To review existing analytical approaches for clinical trial data.
  • To identify and address specific challenges in analyzing data from long-term studies.
  • To propose improved analytical strategies for long-term clinical trial data.

Main Methods:

  • Review of common analytical approaches in clinical trial data assessment.
  • Identification of issues specific to long-term study data analysis.
  • Proposal of an intent-to-observe population and multiple analytical methods for missing data.

Main Results:

  • The study suggests utilizing an intent-to-observe population for long-term studies.
  • It recommends employing at least three different methods for handling missing data.
  • Sensitivity analyses for bias and reporting discrepancies between methods are advised.

Conclusions:

  • Multiple analyses, supported by regulatory guidelines, offer more comprehensive insights than single methods.
  • While not widely adopted, a multiple-analysis approach enhances decision-making by mitigating the limitations of individual methods.
  • Clearly defined analytical methods prevent misleading conclusions in long-term drug studies.