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Objective: Intranasal corticosteroids are recommended as first-line therapy for the treatment of the symptoms of persistent allergic rhinitis (AR). Since the phase-out of chlorofluorocarbon nasal aerosols, intranasal corticosteroids have been available only as aqueous nasal sprays. This study was designed to assess the efficacy, safety, and quality-of-life benefits of beclomethasone dipropionate (BDP) hydrofluoroalkane nasal aerosol in subjects with perennial AR (PAR).
Year: 2012
Source: Allergy and Asthma Proceedings
Link: https://www.ingentaconnect.com/content/ocean/aap/2012/00000033/00000003/art00007%3bjsessionid=71tqtnde4n2nt.x-ic-live-01
Clinical Area: Respiratory
Sample Size Section in Paper/Protocol: |
“Using a standard deviation of 2.0, it was estimated that 235 subjects/treatment group would provide 90% power to detect a difference between the treatment groups of 0.6 in the change from baseline in average A.M. and P.M. subject-reported rTNSS with a two-sided α-level of 0.05.” |
Summary of Necessary Parameter Estimates for Sample Size Calculation:
Parameter | Value |
Significance Level (2-Sided) | 0.05 |
Difference | 0.35 |
Standard Deviation | 0.7 |
Power | 90% |
Step 1:
Select the Two Sample Student’s T-test (equal variances) table from the Select Test Design & Goal window.
This can be done using the radio buttons or alternatively, you can use the search bar at the end of the Select Test Design & Goal window.
Step 2:
Enter the values for sample size calculation taken from the study design statement and survival parameter converter.
Step 3:
Once the relevant Power is entered in the power row, the sample size is calculated automatically.
This gives a sample size of 235, as per the study design |
In the case of the ANCOVA analysis used in the study, the only additional information necessary would be an estimate of R2 between the response and the covariates. For example, using the ANCOVA sample size table available in nQuery Advanced for the above study and assuming a 10% R2 between baseline and the response would have yielded an adjusted sample size of 211 per group.
Step 4:
Once the calculation is completed, nQuery Advanced provides an output statement summarizing the results. It States:
Output Statement: |
A sample size of 235 in each group will have 90% power to detect a difference in means of 0.6 assuming that the common standard deviation is 2 using a two group t-test with a 5% two-sided significance level. |
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