Search research articles

Related Concept Videos

Clinical Trials

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...

Clinical Trials: Overview

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...

Truncation in Survival Analysis

Truncation in Survival Analysis

Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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,...

Blinding

Blinding

Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

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...

You might also read

Related Articles

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

Sort by

Same author

Targeted statin and antiplatelet therapy in women with high-risk cardiovascular disease: how can we overcome sex-based differences?

Expert review of cardiovascular therapy·2026

Same author

Aspirin vs clopidogrel in chronic coronary syndromes: a meta-analysis of ethnic differences.

European heart journal·2026

Same author

The Effect of Zalunfiban on High Sensitivity Cardiac Troponin and the Association with Clinical Outcomes in Patients with STEMI.

medRxiv : the preprint server for health sciences·2026

Same author

Cardiovascular adverse effects of common non-oncologic medications: from mechanisms to clinical management.

European heart journal. Cardiovascular pharmacotherapy·2026

Same author

Residual cardiovascular risk in coronary artery disease: from pathophysiology to established and novel therapies.

Nature reviews. Cardiology·2026

Same author

Sex Differences in Spontaneous Coronary Artery Dissection: A Report of the iSCAD Registry.

Journal of the American Heart Association·2026

Same journal

A Bundle to Frame Guidelines and American Heart Association Statements.

Circulation·2026

Same journal

<i>Circulation</i> Editors and Editorial Board.

Circulation·2026

Same journal

A New <i>Circulation</i>, For You.

Circulation·2026

Same journal

Cardiovascular Risk Reduction With GLP-1 RA Drugs.

Circulation·2026

Same journal

Obesity, Severe Obesity, and Abdominal Obesity in US Youth and Adults From 1999 to 2023.

Circulation·2026

Same journal

Lipid Profile Testing and Interpretation.

Circulation·2026

See all related articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jan 11, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Minimizing Missing Data in Clinical Trials.

C Michael Gibson^1,2, Sojaita Jenny Mears³, M Cecilia Bahit^1,2,4

¹Baim Institute for Clinical Research, Boston, MA (C.M.G., M.C.B.).

|November 17, 2025

Summary

This summary is machine-generated.

Minimizing missing data in clinical trials is crucial for reliable results. Proactive strategies during trial design and execution, alongside understanding data missingness, ensure data integrity and accurate conclusions.

Keywords:

clinical trials missing data

More Related Videos

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

Published on: September 20, 2019

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Related Experiment Videos

Last Updated: Jan 11, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

Published on: September 20, 2019

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Area of Science:

Clinical Trials
Data Management
Biostatistics

Background:

Missing data is a persistent challenge in clinical trials, increasingly influenced by data privacy regulations.
The reasons for missing data (random vs. not at random) significantly impact trial integrity and can lead to biased results, such as differential censoring.

Purpose of the Study:

To provide a comprehensive roadmap for minimizing missing data in clinical trials.
To address the evolving landscape of missing data due to enhanced data privacy.
To outline strategies for proactive data missingness management and interpretation.

Main Methods:

Implementing proactive strategies from trial outset, including informed consent detailing outcome tracking.
Continuously minimizing missing data during the trial via flexible visit schedules and alternative follow-up methods.
Characterizing the reasons for data missingness to accurately assess its impact on trial interpretation.

Main Results:

Proactive minimization strategies can significantly reduce the occurrence of missing data.
Understanding the basis of data missingness is critical for robust interpretation of trial outcomes.
The proposed roadmap offers a structured approach to enhance data quality in clinical trials.

Conclusions:

Minimizing missing data requires a multi-faceted approach, integrating trial design, ongoing management, and careful analysis.
Addressing data missingness proactively is essential for maintaining the validity and reliability of clinical trial findings.
Effective data missingness management ensures unbiased assessment of drug safety and efficacy.