Related Experiment Video
Updated: Feb 5, 2026

06:41
In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
Published on: August 20, 2019
14.4K
Statistical Considerations for an Adaptive Design for a Serious Rare Disease
Kaushik Patra1, Bruce A C Cree2, Eliezer Katz1
11 MedImmune, Gaithersburg, MD, USA.
Therapeutic Innovation & Regulatory Science
|September 19, 2018
Summary
The N-MOmentum trial evaluated MEDI-551 for neuromyelitis optica spectrum disorder (NMOSD), using innovative statistical methods to balance patient safety and research integrity in this rare autoimmune disease.
Area of Science:
- Neurology
- Clinical Trials
- Immunology
Background:
- Neuromyelitis optica spectrum disorder (NMOSD) is a rare, debilitating autoimmune disease affecting the central nervous system.
- Clinical trials for NMOSD face significant design and statistical hurdles in accurately assessing treatment efficacy and patient risk.
Purpose of the Study:
- To evaluate the efficacy and safety of MEDI-551, an anti-CD19 B-cell depleting monoclonal antibody, in patients diagnosed with NMOSD.
- To implement novel statistical methodologies within a clinical trial setting for NMOSD research.
Main Methods:
- The N-MOmentum trial randomized patients with NMOSD to receive MEDI-551 or placebo in a 3:1 ratio for up to 197 days.
- Key design features include investigator-assessed NMOSD attacks confirmed by an independent adjudication committee, with time to first relapse as the primary endpoint.
- Interim analyses for sample size re-estimation and futility, alongside novel multiplicity adjustment methods and inter/intrarater reliability assessments, were incorporated.
Main Results:
- The study design aims to minimize placebo exposure for individual participants.
- Novel statistical approaches were applied to maintain scientific rigor while prioritizing patient safety.
Conclusions:
- The N-MOmentum trial introduces innovative statistical methods to the field of NMOSD research.
- These methods seek to optimize the balance between minimizing patient risk and ensuring the scientific validity of the study findings.
Related Concept Videos
Design Consideration
580
Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
The factor of safety is another key...
580
Transmission Line Design Considerations
631
Aluminum has become the material of choice for overhead transmission lines, surpassing copper due to its abundance and cost-effectiveness. The most prevalent type is the aluminum conductor, steel-reinforced (ACSR), which combines aluminum strands around a steel core. Other variants include all-aluminum conductors (AAC), all-aluminum alloy conductors (AAAC), aluminum conductor alloy-reinforced (ACAR), and aluminum-clad steel conductors. Advanced designs, such as aluminum conductors with steel...
631
Study Design in Statistics
10.0K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
10.0K
Statistical Significance
21.9K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
21.9K
Factorial Design
13.8K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.8K
Probability in Statistics
23.4K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
23.4K

