Describing Omega that includes both BSV and IOV

3 messages 3 people Latest: Sep 04, 2015

Describing Omega that includes both BSV and IOV

From: 이소정 Date: September 04, 2015 technical
Dear all, Currently I’m summarizing the NONMEM estimates of population PK for writing a manuscript. However, I wonder how to describe the omega which includes both between-subject variability and inter-occasional variability. The code of ‘variability’ is followed below, $PK IF(OCC.EQ.1) IOV = ETA(8) IF(OCC.EQ.2) IOV = ETA(9) IF(OCC.EQ.3) IOV = ETA(10) …. KA = THETA(9) * EXP(IOV) (à In final model, PK parameter was estimated like this) ; KA = THETA(9) * EXP(ETA(4)+IOV) (à When I used this code, there were some problems (boundary error, large RSE (>80%), very small estimate of BSV and so on) ) ; KA = THETA(9) * EXP(ETA(4)) (à when I used BSV only, the OFV is quite higher than upper two cases, so I thought that IOV should be considered. ) $OMEGA BLOCK(1) SAME $OMEGA BLOCK(1) SAME $OMEGA BLOCK(1) 0.3 In this case, the individual eta was re-calculated in one subject according to occasion, isn’t it? Then, how should I describe this ‘variability’ and estimate of omega in a manuscript? (i.e., between subject variability containing inter-occasional variability? Or any other appropriate term?) I will appreciate if someone give any advice. Thanks in advance. Best regards, SoJeong Yi SoJeong Yi, Ph.D Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea Tel: 82-2-740-8291 Fax: 82-2-742-9252 C.P: 82-10-3178-4133 E-mail: <mailto:[email protected]> [email protected]

RE: Describing Omega that includes both BSV and IOV

From: Hyeong-Seok Lim Date: September 04, 2015 technical
Dear SoJeong Yi, Sometime we cannot estimate the variances for IIV and IOV separately, although we have multiple dosing data within each subject. At that time, the alternative could be to combine the IIV and IOV to a single random effect parameter, which is the way you have done. In this case, the random effect parameter can be described as “random effect parameter reflecting both IIV and IOV”, and so on. Best regards, ============================================================================================= Hyeong-Seok Lim MD PhD Associate Professor Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan 88, Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Republic of Korea Tel: +82-2-3010-4613 Fax: +82-2-3010-4623 LinkedIn: http://kr.linkedin.com/pub/hyeong-seok-lim/28/926/848 Email: [email protected] <mailto:[email protected]> , [email protected] <mailto:[email protected]> =============================================================================================
Quoted reply history
From: [email protected] [mailto:[email protected]] On Behalf Of 이소정 Sent: Friday, September 4, 2015 11:13 AM To: [email protected] Subject: [NMusers] Describing Omega that includes both BSV and IOV Dear all, Currently I’m summarizing the NONMEM estimates of population PK for writing a manuscript. However, I wonder how to describe the omega which includes both between-subject variability and inter-occasional variability. The code of ‘variability’ is followed below, $PK IF(OCC.EQ.1) IOV = ETA(8) IF(OCC.EQ.2) IOV = ETA(9) IF(OCC.EQ.3) IOV = ETA(10) …. KA = THETA(9) * EXP(IOV) (--> In final model, PK parameter was estimated like this) ; KA = THETA(9) * EXP(ETA(4)+IOV) (--> When I used this code, there were some problems (boundary error, large RSE (>80%), very small estimate of BSV and so on) ) ; KA = THETA(9) * EXP(ETA(4)) (--> when I used BSV only, the OFV is quite higher than upper two cases, so I thought that IOV should be considered. ) $OMEGA BLOCK(1) SAME $OMEGA BLOCK(1) SAME $OMEGA BLOCK(1) 0.3 In this case, the individual eta was re-calculated in one subject according to occasion, isn’t it? Then, how should I describe this ‘variability’ and estimate of omega in a manuscript? (i.e., between subject variability containing inter-occasional variability? Or any other appropriate term?) I will appreciate if someone give any advice. Thanks in advance. Best regards, SoJeong Yi SoJeong Yi, Ph.D Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea Tel: 82-2-740-8291 Fax: 82-2-742-9252 C.P: 82-10-3178-4133 E-mail: <mailto:[email protected]> [email protected]

Re: Describing Omega that includes both BSV and IOV

From: Paolo Denti Date: September 04, 2015 technical
Dear SoJeong Yi, Hyeong-Seok Lim is right, and indeed that ETA in your model is probably accounting for both BOV and BSV. On the other hand, if your best OFV is obtained with BOV alone (as opposed to BSV alone or both BOV+BSV), this is telling you that the BOV differences are more important than the BSV differences. In my experience, this is very common for absorption, whose large variability is often driven by accidental factors (food intake, pH in the stomach, stomach emptying time, co-medications, moon phase :) ), rather than real differences between the patients. I would say that in this case modellers simply report in the paper that the OMEGA was BOV, without any need for further explanation. I hope this reassures you. Paolo
Quoted reply history
On 2015/09/04 04:49, Hyeong-Seok Lim wrote: Dear SoJeong Yi, Sometime we cannot estimate the variances for IIV and IOV separately, although we have multiple dosing data within each subject. At that time, the alternative could be to combine the IIV and IOV to a single random effect parameter, which is the way you have done. In this case, the random effect parameter can be described as “random effect parameter reflecting both IIV and IOV”, and so on. Best regards, ============================================================================================= Hyeong-Seok Lim MD PhD Associate Professor Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan 88, Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Republic of Korea Tel: +82-2-3010-4613 Fax: +82-2-3010-4623 LinkedIn: http://kr.linkedin.com/pub/hyeong-seok-lim/28/926/848 http://kr.linkedin.com/pub/hyeong-seok-lim/28/926/848 Email: <mailto:[email protected]> [email protected]<mailto:[email protected]>, [email protected]<mailto:[email protected]> ============================================================================================= From: [email protected]<mailto:[email protected]> [mailto:[email protected]] On Behalf Of 이소정 Sent: Friday, September 4, 2015 11:13 AM To: [email protected]<mailto:[email protected]> Subject: [NMusers] Describing Omega that includes both BSV and IOV Dear all, Currently I’m summarizing the NONMEM estimates of population PK for writing a manuscript. However, I wonder how to describe the omega which includes both between-subject variability and inter-occasional variability. The code of ‘variability’ is followed below, $PK IF(OCC.EQ.1) IOV = ETA(8) IF(OCC.EQ.2) IOV = ETA(9) IF(OCC.EQ.3) IOV = ETA(10) …. KA = THETA(9) * EXP(IOV) (--> In final model, PK parameter was estimated like this) ; KA = THETA(9) * EXP(ETA(4)+IOV) (--> When I used this code, there were some problems (boundary error, large RSE (>80%), very small estimate of BSV and so on) ) ; KA = THETA(9) * EXP(ETA(4)) (--> when I used BSV only, the OFV is quite higher than upper two cases, so I thought that IOV should be considered. ) $OMEGA BLOCK(1) SAME $OMEGA BLOCK(1) SAME $OMEGA BLOCK(1) 0.3 In this case, the individual eta was re-calculated in one subject according to occasion, isn’t it? Then, how should I describe this ‘variability’ and estimate of omega in a manuscript? (i.e., between subject variability containing inter-occasional variability? Or any other appropriate term?) I will appreciate if someone give any advice. Thanks in advance. Best regards, SoJeong Yi SoJeong Yi, Ph.D Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea Tel: 82-2-740-8291 Fax: 82-2-742-9252 C.P: 82-10-3178-4133 E-mail: <mailto:[email protected]> [email protected]<mailto:[email protected]> -- ------------------------------------------------ Paolo Denti, PhD Pharmacometrics Group Division of Clinical Pharmacology Department of Medicine University of Cape Town K45 Old Main Building Groote Schuur Hospital Observatory, Cape Town 7925 South Africa phone: +27 21 404 7719 fax: +27 21 448 1989 email: [email protected]<mailto:[email protected]> ------------------------------------------------ ________________________________ UNIVERSITY OF CAPE TOWN This e-mail is subject to the UCT ICT policies and e-mail disclaimer published on our website at http://www.uct.ac.za/about/policies/emaildisclaimer/ or obtainable from +27 21 650 9111. This e-mail is intended only for the person(s) to whom it is addressed. If the e-mail has reached you in error, please notify the author. If you are not the intended recipient of the e-mail you may not use, disclose, copy, redirect or print the content. If this e-mail is not related to the business of UCT it is sent by the sender in the sender's individual capacity.