RE: Strange PRED prediction in SAEM with M3 BQL handling

________________________________________ From: [email protected] [[email protected]] on behalf of Smit, Cornelis (Klinische Farmacie) [[email protected]] Sent: 22 February 2019 10:11 To: [email protected] Subject: RE: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling Hi Andrew, When your observation is <BLQ, M3 gives you a likelihood of this value being < BLQ in the PRED column. So this value will be close to 1 when the model is fairly sure that the concentration should be BLQ. This might explain why the PREDs might be relatively high in your diagnostics here. I usually exlude the <BLQ values in my GOF diagnostics, and check for model misspecification with a VPC showing BLQ data (as described in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691472/ ). You can do this with the old xpose package. I don’t think there is any way to visualize the BLQ prediction in the ‘usual’ GOF but I’m very curious if someone else has some ideas regarding this. Kind regards, Cornelis Smit Hospital Pharmacist / PhD candidate Dept. of Clinical Pharmacy St. Antonius Hospital Dept. of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands VRIJWARING: Dit e-mail bericht is uitsluitend bestemd voor de geadresseerde(n). Verstrekking aan en gebruik door anderen is niet toegestaan. Als u niet de geadresseerde bent, stel dan de verzender hiervan op de hoogte en verwijder het bericht. Aan de inhoud van dit bericht kunnen geen rechten worden ontleend. Van: [email protected] [mailto:[email protected]] Namens Andrew Tse Verzonden: vrijdag 22 februari 2019 10:23 Aan: [email protected] Onderwerp: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling Dear all, I am running SAEM with M3 BQL handling method via PsN but having some strange PRED values in mytab table if someone can shed some light: I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both have normal looking fitting with data in individual plots. Once I have coded SAEM with M3 codes and include BQL data it showed very strange PRED vs time plots (eg. 100 times over prediction at BQL time point). IPRED had normal results. Here are the control stream that I have used: $PK TVCL=THETA(1) MU_1=LOG(TVCL) CL=EXP(MU_1+ETA(1)) TVV2=THETA(2) MU_2=LOG(TVV2) V2=EXP(MU_2+ETA(2)) TVQ=THETA(3) MU_3=LOG(TVQ) Q=EXP(MU_3+ETA(3)) TVV3=THETA(4) MU_4=LOG(TVV3) V3=EXP(MU_4+ETA(4)) K23=Q/V2 ;Distribution rate constant K32=Q/V3 ;Distribution rate constant KA=0 A_0(1)=0 A_0(2)=0 A_0(3)=0 $DES DADT(1)= -KA*A(1) DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3) DADT(3)= K23*A(2)-K32*A(3) $ERROR IPRED=A(2)/V2 W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2)) IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1 IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2 IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3 IF(BQL.EQ.0) THEN F_FLAG=0 Y=IPRED+W*ERR(1) ELSE F_FLAG=1 ;BQL so Y is likelihood Y=PHI((LIM-IPRED)/W) ENDIF IWRES=(DV-IPRED)/W IRES=DV-IPRED My question is that whether there is error in my M3 $ERROR model? or whether PRED values for BQL means something else other than prediction for BQL data? Thanks a lot. Kind regards, Andrew Tse Research Pharmacist ******************************************************************************************************************** This message may contain confidential information. If you are not the intended recipient please inform the sender that you have received the message in error before deleting it. Please do not disclose, copy or distribute information in this e-mail or take any action in relation to its contents. To do so is strictly prohibited and may be unlawful. Thank you for your co-operation. NHSmail is the secure email and directory service available for all NHS staff in England and Scotland. NHSmail is approved for exchanging patient data and other sensitive information with NHSmail and other accredited email services. For more information and to find out how you can switch, https://portal.nhs.net/help/joiningnhsmail