What if… [General Statistics]
❝ […] I would suggest to do two studies:
❝ Fasting: two way cross-over study
❝ Fed: replicate study
Right (that’s a ‘need to know’).* But EMA is interested in the comparison of Tfed vs. Tfasted and Rfed vs. Rfasted as well (that’s the ‘nice to know’ part).
*
If you run two 2×2 studies you can perform such a comparison only between these studies - which is lacking power.Therefore EMA stated in the draft GL:
In cases where information is required in both the fed and fasted states, it is preferable to conduct a four-period single dose crossover design study (both products fed and fasted) rather than conducting two separate bioequivalence studies in fed and fasted state, respectively. In a four-period crossover design study, the food effect on test and reference product can be evaluated which is not the case when conducting two separate two-period, two-sequence single dose crossover design studies under fasting and fed conditions, respectively. In addition to the bioequivalence evaluation of test/reference in fasting and in fed state, the food effect can be presented for test and reference, i.e. the ratio food/fasting and 90% confidence interval for test and reference, respectively.
(my emphases) Of course the text in red in nonsense – such a comparison is just based on a parallel design. If the usual precautions (polymorphism, etc.) are followed in designing these studies, unbiased estimates and CIs may be obtained.Following comments (p. 78-83) on the draft this paragraph was simplified; the final GL states only:
In cases where information is required in both the fed and fasted states, it is acceptable to conduct either two separate two-way cross-over studies or a four-way cross-over study.
(my emphases)- These terms where extensively discussed at the BioInternational Conference 1994 in Munich and are used ever since in that context.
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Helmut Schütz
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Science Quotes
Complete thread:
- 4-period BE study fed/fasting: statistical issues Amandine 2009-06-04 12:31 [General Statistics]
- Confounded effects; common variance Helmut 2009-06-04 12:55
- Neglecting period effects? d_labes 2009-06-10 10:10
- Assumptions... Helmut 2009-06-23 14:38
- What if... Ohlbe 2010-03-10 14:27
- What if... Dr_Dan 2010-03-11 15:50
- What if…Helmut 2010-03-11 16:39
- What if… Dr_Dan 2010-03-12 08:49
- Need-to-know / nice-to-know Helmut 2010-03-12 11:35
- many ANOVA but only one trial boonchai_l 2010-05-24 11:53
- many ANOVA but only one trial GSTATS 2010-06-08 21:52
- many ANOVA but only one trial boonchai_l 2010-05-24 11:53
- Need-to-know / nice-to-know Helmut 2010-03-12 11:35
- What if… Dr_Dan 2010-03-12 08:49
- What if…Helmut 2010-03-11 16:39
- What if... Dr_Dan 2010-03-11 15:50
- Neglecting period effects? d_labes 2009-06-10 10:10
- Confounded effects; common variance Helmut 2009-06-04 12:55