RE: Time to Event Model

From: [email protected] [mailto:[email protected]] On Behalf Of Friederike Kanefendt Sent: 15 August 2011 09:56 To: [email protected] Subject: [NMusers] Time to Event Model Dear NMusers, I try to model the influence of an intervention on Time-To-Event (disease progression) data with NM7 based on the presentation of Nick Holford (PAGE 2011). One problem might be that I have only data from 21 patients with 11 event data (DV=1) and 10 right censored data (DV=0)... The treatment influences the hazard rate. (h(t)=h0(t)*exp(BETA*X). For X I tested disease progression (DPRG) -affected by ON or OFF treatment-, free drug concentration (C), or the AUC at steady state (AUC_SS). Unfortunately, the estimation aborted with different ERROR messages: 1) for Concentration NUMERICAL DIFFICULTIES WITH INTEGRATION ROUTINE. NO. OF REQUIRED SIGNIFICANT DIGITS IN SOLUTION VECTOR TO DIFFERENTIAL EQUATIONS, 4, MAY BE TOO LARGE. 0PROGRAM TERMINATED BY OBJ --> setting TOL to lower values has no influence 2) for AUC_SS and DPRG CONDITIONAL LIKELIHOOD SET TO NEGATIVE VALUE WITH INDIVIDUAL 1 (IN INDIVIDUAL RECORD ORDERING), DATA RECORD 1 Does someone have experience with that kind of error or have any idea what could be the problem? Attached you find my control file and a part of the structure of the data set Thanks in advance. Best regards, Friederike I have a data set with dosing events and dummy observations for the PK model as well as one row with event/exclusion ID TIME AMT DV MDV CLx Vx ... 1, 0, 50, 0, 1, 30, 2000 1, 23.83, 0, 0, 1, 30, 2000 1, 24, 50, 0, 1, 30, 2000 1, 47.83, 0, 0, 1, 30, 2000 1, 48, 50, 0, 1, 30, 2000 ... 1, 8280, 0, 1, 0, 30, 2000 ; progression (event) 2, 0, 50, 0, 1, 35, 1800 2, 23.83, 0, 0, 1, 35, 1800 2, 24, 50, 0, 1, 35, 1800 2, 47.83, 0, 0, 1, 35, 1800 2, 48, 50, 0, 1, 35, 1800 ... 2, 4236, 0, 0, 0, 35, 1800 ; censored ... $INPUT ID TIME AMT DV MDV CLx Vx ... $DATA data.csv $SUBROUTINE ADVAN6 TOL=4 $MODEL NCOMP=5 COMP=(DEPOT) COMP=(CENTRAL) COMP=(PERI) COMP=(MET) COMP=(HAZ) $THETA (0,0.5) ; 1 TH_BLHAZ - Baseline Hazard $THETA (0.01) ; 2 TH_BETA - Factor $THETA (5) ; 3 TH_EFFECT $THETA (0,5) ; 4 TH_INTRI $THETA (0,0.5) ; 5 TH_SLOPE $OMEGA 0 FIX ; 1 ETA_HAZ $OMEGA 0.1 ; 2 ETA_BETA $OMEGA 0.1 ; 3 ETA_EFFECT $OMEGA 0.1 ; 4 ETA_INTRI $OMEGA 0.1 ; 5 ETA_SLOPE $PK ;HAZARD TVBLHAZ = THETA(1) BLHAZ = TVBLHAZ*EXP(ETA(1)) TVBETA = THETA(2) BETA = TVBETA*EXP(ETA(2)) ;SYMPTOMATIC TREATMENT EFFECT EFFECT = THETA(3)*EXP(ETA(3)) ; TREATMENT EFFECT FACTOR ;DISEASE PROGRESS INTRI = THETA(4)*EXP(ETA(4)) ; INTERCEPT OF DISEASE PROGRESSION SLOPE = THETA(5)*EXP(ETA(5)) ; SLOPE OF DISEASE PROGRESSION ;PHARMACOKINETIC ... ;EXPOSURE OF TOTAL DRUG AT STEADY-STATE AUC_SS = DOSE/CLx+DOSE/CLM A_0(5)=BLHAZ $DES ... C=A(2)/V1+A(4)/VM IF(C.GE.50) THEN ; EFFECTIVE CONCENTRATION TREA = 1 ELSE TREA = 0 ENDIF INTRC = INTRI-EFFECT*TREA DPRG = INTRC+SLOPE*T DADT(5)=BETA*DPRG ; HAZARD RATE ;DADT(5)=BETA*C ;DADT(5)=BETA*AUC_SS $ERROR CUB = A(2)/V1+A(4)/VM CUMHAZ = A(5) ; CUMULATIVE HAZARD ;EFFECTIVE CONCENTRATION IF(CUB.GE.50) THEN ; CONC EFFECTIVE TREAT = 1 ELSE TREAT = 0 ENDIF INTR = INTRI-EFFECT*TREAT ; INTERCEPT OF DISEASE PROGRESSION DISPRG = INTR+SLOPE*TIME SURV = EXP(-CUMHAZ) ; SURVIVAL FUNCTION - probability not to have an event IF(DV.EQ.1) THEN ; EVENT HAZNOW = BLHAZ*EXP(BETA*DISPRG) ; HAZARD RATE AT THAT TIME Y = HAZNOW*SURV ; PDF - PROBABILITY DENSITY FUNCTION ELSE ; CENSORED Y = SURV ENDIF $ESTIMATION SIG=3 SIGL=9 MAXEVAL=9990 METHOD=COND LAPLACE LIKE PRINT=1 $COVARIANCE PRINT=E $TABLE ID TIME BLHAZ SURV HAZNOW CUMHAZ NOPRINT ONEHEADER NOAPPEND FILE=PATAB Friederike Kanefendt - PhD-Student - University of Bonn, Germany -Clinical Pharmacy- Phone: +49 (0)228 73-5781 Fax: +49(0) 228 73-9757 [email protected]