Best Way to Learn Network Meta Analysis With Example Dataset & Free Software| Easy Tutorial on NMA|
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- Опубликовано: 22 авг 2024
- #network #metaanalysis #data #freesoftware
Network meta-analysis (NMA) is an advanced statistical technique used in evidence synthesis to compare and analyze multiple treatment options simultaneously. It extends the traditional pairwise meta-analysis, which compares two treatments at a time, by allowing the comparison of several treatments, even if some have not been directly compared in head-to-head clinical trials.
Here are the key aspects and benefits of network meta-analysis:
1. **Simultaneous Comparison**:
- NMA enables the comparison of multiple treatments by synthesizing direct and indirect evidence. Direct evidence comes from head-to-head clinical trials, while indirect evidence is inferred from trials that have a common comparator.
2. **Network of Evidence**:
- The method creates a network of studies where nodes represent different treatments, and edges (connections) represent the available direct comparisons from clinical trials.
3. **Transitivity Assumption**:
- For valid indirect comparisons, NMA relies on the assumption of transitivity. This means that the populations, interventions, and outcomes are sufficiently similar across the studies to allow meaningful indirect comparisons.
4. **Increased Precision**:
- By integrating both direct and indirect evidence, NMA often provides more precise estimates of treatment effects than traditional pairwise meta-analyses.
5. **Ranking of Treatments**:
- NMA can rank treatments according to their effectiveness and safety, which is particularly useful in guiding clinical decision-making and policy development.
6. **Assessment of Consistency**:
- It includes methods to check for consistency between direct and indirect evidence. Inconsistencies might indicate potential biases or differences in study populations or methodologies.
7. **Applicability**:
- NMA is widely applicable in fields like medicine, pharmacology, and health technology assessments, where multiple treatment options are common.
Example
Suppose there are three treatments for a condition: A, B, and C. Clinical trials have compared A vs. B and B vs. C, but not A vs. C. NMA can use the results from the A vs. B and B vs. C trials to infer the comparative effectiveness of A vs. C, combining all available evidence into a single analysis.
Steps in Network Meta-Analysis
1. **Define the Scope**:
- Identify the treatments and outcomes of interest.
2. **Systematic Literature Review**:
- Conduct a comprehensive search for all relevant studies.
3. **Data Extraction**:
- Extract data on study characteristics, treatment comparisons, and outcomes.
4. **Modeling**:
- Use statistical models to combine direct and indirect evidence.
5. **Consistency and Sensitivity Analyses**:
- Assess the consistency of the network and perform sensitivity analyses to check the robustness of results.
6. **Interpretation**:
- Interpret the results, focusing on the relative effectiveness and ranking of treatments.
Network meta-analysis is a powerful tool that enhances the ability to make informed decisions in clinical practice and policy-making by providing a comprehensive comparison of multiple treatment options.
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Hello sir... I am a new subscriber ...loving your videos. Please explain network meta analysis using an example from management specifically hrm types.. please
I will. I am working on it. Thanks dear
@@Dr.Munshi-Naser Well explained for new comers like me Doctor, i will also wait for the video... warm message from indonesia
Sir, what is TE, VMD, seTE, and how to calculate them??
TE treat effect which can be calculated using mean difference. But you Don't need to calculate. This is done by software.
@@Dr.Munshi-Naser can you tell us software to fnd out Te, vmd and seTE
Sir, is it used in management also.
Yes