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RegisterUncertain time point [NCA / SHAM]
posted by Helmut 
– Vienna, Austria, 2013-05-23 03:35 (3990 d 05:58 ago) – Posting: # 10625
Views: 17,353
Hi Grace!
Duno. But if you treat the value as missing – depending on the algo – you might get a substantially biased AUC (see my conversation with Yung-jin above).
Definitely (as Ohlbe suggested). I once had to assess deficiencies where in two studies the scheduled time points (instead of the actual ones) were used. Impact on the AUC comparison was in the second decimal place. And you have only one (!) value in an entire study…
BTW, scheduled time points were my standard method in hundreds (!) of studies. So what?
Yes, but only if the value is missing. You know the value – only its time point is uncertain.
I would not use an estimate. Use the measured one at the scheduled time point. Report the deviation from the protocol, don’t panic, & sleep well.
Another idea – only if you really have nothing better to do: Most protocols require a justification of a time deviation to be recorded in CRF only if a certain time interval is exceeded (f.i. ±2’ in the very early phase, ±5’ later on, and ±15’ for t ≥24 h). Let’s assume only the actual sampling was not recorded, but still was within the allowed interval (otherwise we have two errors instead of one). Set up two data sets: One assuming the sample was taken at the maximum allowed negative deviation (too early) and the other one with the max. positive deviation (too late). Go ahead with the BE and assess the impact on the outcome.
❝ If we treat it as missing data, don't use it in bioequivalence evaluation, would assessor think we are hiding data?
Duno. But if you treat the value as missing – depending on the algo – you might get a substantially biased AUC (see my conversation with Yung-jin above).
❝ Should we include the data in PK analysis and use schedule time to be the "best guess"?
Definitely (as Ohlbe suggested). I once had to assess deficiencies where in two studies the scheduled time points (instead of the actual ones) were used. Impact on the AUC comparison was in the second decimal place. And you have only one (!) value in an entire study…
BTW, scheduled time points were my standard method in hundreds (!) of studies. So what?
❝ One literature suggest to use log linear interpolation (at elimination phase) to minimize the bias (also as your reply).
Yes, but only if the value is missing. You know the value – only its time point is uncertain.
❝ But someone said the assessor will think you are manipulating data.
I would not use an estimate. Use the measured one at the scheduled time point. Report the deviation from the protocol, don’t panic, & sleep well.
Another idea – only if you really have nothing better to do: Most protocols require a justification of a time deviation to be recorded in CRF only if a certain time interval is exceeded (f.i. ±2’ in the very early phase, ±5’ later on, and ±15’ for t ≥24 h). Let’s assume only the actual sampling was not recorded, but still was within the allowed interval (otherwise we have two errors instead of one). Set up two data sets: One assuming the sample was taken at the maximum allowed negative deviation (too early) and the other one with the max. positive deviation (too late). Go ahead with the BE and assess the impact on the outcome.
—
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Helmut Schütz
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The quality of responses received is directly proportional to the quality of the question asked. 🚮
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Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
- handling of missing data gracehung 2013-05-20 07:35
![[Mix]](https://static.bebac.at/img/mix.png "open in Mix view")
- Lin-up/log-down trapezoidal avoids most trouble Helmut 2013-05-20 14:22
- Lin-up/log-down trapezoidal avoids most trouble yjlee168 2013-05-22 08:25
- Multiple peaks: fallback to linear trapezoidal Helmut 2013-05-22 20:25
- Multiple peaks: fallback to linear trapezoidal yjlee168 2013-05-22 21:57
- No interpolation Helmut 2013-05-22 23:25
- No interpolation yjlee168 2013-05-23 11:43
- Spaghetti & other pasta Helmut 2013-05-23 15:15
- Spaghetti & other pasta yjlee168 2013-05-23 20:47
- Spaghetti & other pasta Helmut 2013-05-23 21:29
- Spaghetti & other pasta yjlee168 2013-05-23 22:46
- Spaghetti & other pasta Helmut 2013-05-24 01:24
- Spaghetti & other pasta yjlee168 2013-05-24 09:17
- Spaghetti & other pasta Helmut 2013-05-24 01:24
- Spaghetti & other pasta yjlee168 2013-05-23 22:46
- Spaghetti & other pasta Helmut 2013-05-23 21:29
- Spaghetti & other pasta yjlee168 2013-05-23 20:47
- Spaghetti & other pasta Helmut 2013-05-23 15:15
- No interpolation Ken Peh 2013-05-30 19:55
- Different algos! Helmut 2013-05-30 22:38
- Different algos! Ken Peh 2013-06-03 17:52
- Calculate what? Helmut 2013-06-03 18:11
- Different algos! Ken Peh 2013-06-03 17:52
- Different algos! Helmut 2013-05-30 22:38
- No interpolation yjlee168 2013-05-23 11:43
- No interpolation Helmut 2013-05-22 23:25
- Multiple peaks: fallback to linear trapezoidal yjlee168 2013-05-22 21:57
- Lin-up/log-down trapezoidal example Helmut 2013-05-25 15:09
- Lin-up/log-down trapezoidal example yjlee168 2013-05-25 19:45
- Multiple peaks: fallback to linear trapezoidal Helmut 2013-05-22 20:25
- Lin-up/log-down trapezoidal avoids most trouble yjlee168 2013-05-22 08:25
- handling of missing data Ohlbe 2013-05-20 21:45
- Lin-up/log-down trapezoidal avoids most trouble Helmut 2013-05-20 14:22
Ing. Helmut Schütz