kishpokuri ☆ India, 2015-11-24 15:18 (3047 d 20:08 ago) Posting: # 15665 Views: 6,480 |
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Hi all, Can anyone suggest the appropriate sample size for a clinical endpoint bioequivalence study of Brinzolamide 1% ophthalmic suspension in chronic open angle glaucoma patients. OGD guidelines has not mentioned regarding this. Thank you, Regards, Dr. Kishan PV Edit: Category changed. [Helmut] |
ElMaestro ★★★ Denmark, 2015-11-24 17:50 (3047 d 17:36 ago) @ kishpokuri Posting: # 15666 Views: 5,425 |
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Hi Kishpokuri, sample size in BE (regardless of whether we talk BE under the US or EU definition / regardless of whether we discuss PK or PD) will always be depending on your desired level of power, as well as the true (estimated) relative performance of your product (measured as OIP difference) and the variability associated with this similarity measure. So let's hear your thoughts about them. Add to that, please, some thoughts about dropout rates and your statistical model. — Pass or fail! ElMaestro |
d_labes ★★★ Berlin, Germany, 2015-11-25 12:23 (3046 d 23:03 ago) @ kishpokuri Posting: # 15672 Views: 5,426 |
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Dear kishpokuri, ❝ Can anyone suggest the appropriate sample size for a clinical endpoint bioequivalence study of Brinzolamide 1% ophthalmic suspension in chronic open angle glaucoma patients. The FDA guidance on Brinzolamide gives you very specific details on how to establish BE with the clinical endpoint IOP (intra-ocular pressure. Quote: "To establish BE, the limits of each two-sided 95% confidence interval of the treatment difference (test – reference) for mean IOP of both eyes (continuous variable) at all four follow-up points (i.e., at approximately 8:00 a.m. (hour 0; before the morning drop) and 10:00 a.m. (hour 2) at the Day 14 (week 2) and Day 42 (week 6) visits must be within ± 1.5 mm Hg using the PP population for all time points measured and within ± 1.0 mm Hg using the PP population for the majority of time points measured." Now you have:
Then look for a sample size estimation software which covers equivalence studies using the difference between means (f.i. PASS) with parallel group design. You may also 'missuse' PowerTOST , which is intentionally programmed and described for ratios, but works also for differences using the argument logscale=FALSE. Set alpha=0.025, give theta0 as true difference (mm Hg) at which you will be able to accept BE, theta1 and theta2 to the stringenter equivalence margins as -1.0, 1.0 (mm Hg) and set CV to the standard deviation of the IOP (we don't know at moment).Example use with a hypothetical IOP standard deviation and an assumed 'true' difference: library(PowerTOST) theta0 and standard deviation you must of course qualify from data in the literature. The target power is ditto at your choice. Hope this helps — Regards, Detlew |
kishpokuri ☆ India, 2015-11-27 14:46 (3044 d 20:40 ago) @ d_labes Posting: # 15678 Views: 5,145 |
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Thank you guyz |