Related Experiment Video
Updated: May 18, 2026
04:53
A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
Published on: September 20, 2019
Accommodation of missing data in supportive and palliative care clinical trials
Brenda F Kurland1, Laura L Johnson, Paula H Diehr
1Fred Hutchinson Cancer Research Center, Seattle, Washington 98019, USA. bkurland@fhcrc.org
Current Opinion in Supportive and Palliative Care
|October 9, 2012
Summary
Minimizing missing data in clinical trials is crucial. Strategies include simplifying participation and using advanced statistical methods like multiple imputation for reliable supportive and palliative care research.
Area of Science:
- Clinical Research
- Biostatistics
- Palliative Care
Background:
- Supportive and palliative care clinical trials present unique missing data challenges.
- Addressing missing data is critical for the validity of trial outcomes.
Purpose of the Study:
- To review the literature on missing data concerns specific to supportive and palliative care clinical trials.
- To identify strategies for minimizing and analyzing missing data in these trials.
Main Methods:
- Literature review focusing on missing data in clinical trial design and analysis.
- Examination of statistical approaches for handling missing data, including multiple imputation.
- Discussion of the distinction between missing data and data truncation due to death.
Main Results:
- Preventing missing data through improved study design and conduct is a key focus.
- Simplifying trial participation can minimize missing data.
- Multiple imputation is a viable method for handling nonresponse, provided appropriate models are used.
Conclusions:
- Anticipating missing data patterns during trial planning is essential for effective design modifications.
- Sensitivity analyses are crucial to evaluate the robustness of conclusions to missing data assumptions.
- Distinguishing missing data from death-related truncation is vital in end-of-life care trials.
Related Concept Videos
01:11Clinical 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...
01:15Assumptions of Survival Analysis
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
01:16Clinical 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...
There are four phases in a clinical trial. A phase one...
01:25Continuing Care
Continuing care describes the variety of health, personal, and social services provided over a prolonged period. The need for continuing care is increasing because people are living longer. Many people do not have families or others to care for them. Continuing care is mainly for patients who are disabled, functionally dependent, or suffering from a terminal disease. It is available within institutional settings or in homes. Examples include nursing centers or facilities, assisted living,...
01:24Kaplan-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,...
01:15Bioavailability Study Design: Healthy Subjects Versus Patients
Bioavailability studies are essential for evaluating a drug's therapeutic efficacy and understanding its absorption patterns under various physiological conditions. Conducting such studies on target patient populations provides more relevant data by simulating real-world disease states. However, practical challenges often necessitate the use of young, healthy adult volunteers as study subjects.Patients may exhibit altered drug absorption patterns due to the effects of the disease itself,...