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SAS Global Forum 2011 Posters Paper 2282011 MatchingAdjusted Indirect Comparison Analysis Using Common SAS 9.2 PROCEDURES Elisabeth Malone, Analytica International, New York, NY, USA Steven Sherman,
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How to fill out matching-adjusted indirect comparison analysis:

01
Start by clearly defining the research question or objective of the analysis. This will help guide the entire process.
02
Identify the available evidence and studies that are relevant to the research question. This may include randomized controlled trials, observational studies, or other types of research.
03
Assess the validity and quality of the studies identified. Consider factors such as study design, sample size, bias, and reliability of the data.
04
Determine the clinical and methodological characteristics of the studies that will be included in the analysis. This may involve selecting specific endpoints or outcomes, population characteristics, or other relevant factors.
05
Conduct a statistical analysis to compare the data from the different studies. This may involve techniques such as indirect treatment comparison or network meta-analysis.
06
Adjust the results of the analysis to account for any differences in patient characteristics, treatment effects, or other factors that may influence the outcomes being studied. This is the matching-adjusted step of the analysis.
07
Interpret the findings of the analysis and draw conclusions based on the results. Consider factors such as the strength of the evidence, potential biases, and the implications for clinical practice or decision-making.

Who needs matching-adjusted indirect comparison analysis:

01
Pharmaceutical companies and drug developers may use matching-adjusted indirect comparison analysis to assess the relative efficacy or safety of their products compared to competing treatments.
02
Health technology assessment agencies and regulatory bodies may utilize these analyses to evaluate the cost-effectiveness and comparative effectiveness of different treatment options.
03
Researchers and academics may conduct matching-adjusted indirect comparison analysis as part of their studies or systematic reviews to gain insights into the effectiveness of different interventions or therapies.
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Matching-adjusted indirect comparison analysis is a statistical method used in health economics and outcomes research to compare the effectiveness of interventions.
Pharmaceutical companies and researchers conducting clinical trials are typically required to file matching-adjusted indirect comparison analysis.
To fill out matching-adjusted indirect comparison analysis, one must gather clinical trial data, perform statistical analysis, and report the results in a structured format.
The purpose of matching-adjusted indirect comparison analysis is to provide valuable insights into the effectiveness of healthcare interventions by comparing different treatments in a systematic way.
Information such as baseline characteristics of study populations, treatment effect estimates, confidence intervals, and statistical methods used must be reported on matching-adjusted indirect comparison analysis.
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Relevant keywords

2011 2010 New_York SAS comparator PROC CI distributions dataset bootstrapped Malangone 95CI percentiles MSKCC DATAAll PHREG DATAin DATAODS SURVEYSELECT Analytica JMEN ISPOR 13th LIFETEST ESMO mRCC SAMPSI

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