## Expected deviation of test from reference; actual content [Power / Sample Size]

Dear Nirali!

» What is the importance of Null ratio (=test/reference) in sample size calculations?

Since power curves become very steep if moving the test/reference ratio away from 1 (for examples see this post) it's quite important to use reasonable estimates (of both the expected deviation of test from reference and CV

» I gone through many guidelines but none has mentioned clearly about null ratio. ANVISA says take difference 0%

» Is it appropriate to consider actual variability as a null ratio

The

Specifications for batch release commonly are set to ±5% of the declared content. If both products show identical BA, you may expect in your study a deviation of ±5% (let’s say, test’s content -2.5% and reference’s content +2.5% of nominal).

... report from 1411 studies submitted to the FDA deviations of 3.13% (±2.71) for AUC

A more recent metaanalysis of 1636 BE studies submitted to the FDA within 1996-2005 showed deviations of 3.19% (±2.72) for AUC

If you have no clue, expect the true ratio to be 1

Power curves are not symmetrical; if you want to go with a 5% deviation of test from reference and have no clue about which direction the deviation will point to, it's wise to use a ratio of 0.95 instead of 1.05. Power is lower for ratios <1 than for ratios >1; therefore you should apply the most conservative approach.

At least

Canada calls for a sample size estimation based on the expected deviation, but wants to see two evaluations - one with original data and one with data corrected for actual content of study batches.

The European guideline calls for a sample size estimation based on the

The WHO’s guideline also suggests the expected deviation; a dose correction (which was suggested in earlier versions) is currently not recommended.

As guidelines are ambiguous in their recommendations about potency correction, some people opt for this procedure:

» What is the importance of Null ratio (=test/reference) in sample size calculations?

Since power curves become very steep if moving the test/reference ratio away from 1 (for examples see this post) it's quite important to use reasonable estimates (of both the expected deviation of test from reference and CV

_{intra}).» I gone through many guidelines but none has mentioned clearly about null ratio. ANVISA says take difference 0%

**or**5%. USFDA**suggested**to consider 5% variability. pls guide what is appropriate?» Is it appropriate to consider actual variability as a null ratio

The

**magical**number ±5% has its origin in the following reasoning:Specifications for batch release commonly are set to ±5% of the declared content. If both products show identical BA, you may expect in your study a deviation of ±5% (let’s say, test’s content -2.5% and reference’s content +2.5% of nominal).

Nwakama P, Haidar S, Yang Y, Davit B, Conner D, Yu L. *Generic Drug Products Demonstrate Small Differences in Bioavailability Relative to the Brand Name Counterparts: A Review of ANDAs Approved 1996 – 2004.* AAPS J. 2005;7/S2:Abstract M1262. online abstract

... report from 1411 studies submitted to the FDA deviations of 3.13% (±2.71) for AUC

_{t}, 3.05% (±2.62) for AUC_{inf}, and 4.52% (±3.57) for C_{max}.A more recent metaanalysis of 1636 BE studies submitted to the FDA within 1996-2005 showed deviations of 3.19% (±2.72) for AUC

_{t}, 3.12% (±2.66) for AUC_{inf}, and 4.50% (±3.57) for C_{max}.If you have no clue, expect the true ratio to be 1

**and**want to be*very conservative*you may even go with an expected deviation of ±10%.Power curves are not symmetrical; if you want to go with a 5% deviation of test from reference and have no clue about which direction the deviation will point to, it's wise to use a ratio of 0.95 instead of 1.05. Power is lower for ratios <1 than for ratios >1; therefore you should apply the most conservative approach.

At least

*some*guidelines are specific:Canada calls for a sample size estimation based on the expected deviation, but wants to see two evaluations - one with original data and one with data corrected for actual content of study batches.

The European guideline calls for a sample size estimation based on the

*expected*deviation; a potency correction is currently under discussion for the next revision.The WHO’s guideline also suggests the expected deviation; a dose correction (which was suggested in earlier versions) is currently not recommended.

As guidelines are ambiguous in their recommendations about potency correction, some people opt for this procedure:

- No potency correction if deviation of actual contents ≤5%,

- Potency corrected analysis primary if deviation >5%; original data supportive only.

—

Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

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*Dif-tor heh smusma*🖖Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

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### Complete thread:

- Importance of Null Ratio in Sample size calculation Nirali 2007-10-24 08:21 [Power / Sample Size]
- Expected deviation of test from reference; actual contentHelmut 2007-11-02 17:05