Hi Sameer,
Several comments:
--------------------
You did not provide the entire code, but if BL is the observed baseline,
it should not be included in the dataset. If you have
BL=THETA(*)*EXP(ETA(*)) then the data are fine
--------------------
Additive error is assumed. I would rather use combined error (my guess
is that assay STD at DV=65 is larger than STD at DV < LLOQ).
---------------------
M2 method can be implemented using YLO option (BQL observations are
included with MDV=1). PRB will give you a model-based probability of
DV > YLO (see YLO EXAMPLE in help).
$ERROR
YLO = LOG1
IF(ASSY.EQ.2) YLO=LOG2
PRB = PR_Y
$EST METH=1 LAPLACIAN SLOW NOABORT
--------------------
I would increase TOL to 9 (if possible). It does not look like a stiff
system, so ADVAN6 can be tried
------------------
You have not described the problem: how well these M3 - M4 methods
describe your data? If you are not satisfied, could you describe the
deficiencies if there are any; these can help to resolve them.
Thanks
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
Doshi, Sameer wrote:
Hello,
We are attempting to model suppression of a biomarker, where a number of
samples (40-60%) are below the quantification limit of the assay and
where 2 different assays (with different quantification limits) were
used. We are trying to model these BQL data using the M3 and M4 methods
proposed by Ahn et al (2008).
I would like to know if anyone has any comments or experience
implementing the M3 or M4 methods for biomarker data, where levels are
observed at baseline, are supressed below the LOQ for a given duration,
and then return to baseline.
Also please advise if there are other methods to try and incorporate
these BQL data into the model.
I have included the relevant pieces of the control file (for both M3 and
M4) and data from a single subject.
Thanks for your review/suggestions.
Sameer
DATA:
#ID TIME AMT DV CMT EVID TYPE ASSY
1 0 0 65.71 0 0 0 1
1 0 120 0 3 1 0 1
1 168 0 10 0 0 1 1
1 336 0 10 0 0 1 1
1 336 120 0 3 1 0 1
1 504 0 12.21 0 0 0 1
1 672 120 0 3 1 0 1
1 1008 0 10 0 0 1 1
1 1008 120 0 3 1 0 1
1 1344 0 10 0 0 1 1
1 1344 120 0 3 1 0 1
1 1680 0 10 0 0 1 1
1 1680 120 0 3 1 0 1
1 2016 0 10 0 0 0 1
1 2352 0 25.64 0 0 0 1
1 2688 0 59.48 0 0 0 1
MODEL M3:
$DATA data.csv IGNORE=#
$SUB ADVAN8 TRANS1 TOL=6
$MODEL
COMP(central)
COMP(peri)
COMP(depot,DEFDOSE)
COMP(effect)
$DES
DADT(1) = KA*A(3) - K10*A(1) - K12*A(1) + K21*A(2)
DADT(2) = K12*A(1) - K21*A(2)
DADT(3) = -KA*A(3)
CONC = A(1)/V1
DADT(4) = KEO*(CONC-A(4))
$ERROR
CALLFL = 0
LOQ1=10
LOQ2=20
EFF = BL* (1 - IMAX*A(4)**HILL/ (IC50**HILL+A(4)**HILL))
IPRED=EFF
SIGA=THETA(7)
STD=SIGA
IF(TYPE.EQ.0) THEN ; GREATER THAN LOQ
F_FLAG=0
Y=IPRED+SIGA*EPS(1)
IRES =DV-IPRED
IWRES=IRES/STD
ENDIF
IF(TYPE.EQ.1.AND.ASSY.EQ.1) THEN ; BELOW LOQ1
DUM1=(LOQ1-IPRED)/STD
CUM1=PHI(DUM1)
F_FLAG=1
Y=CUM1
IRES = 0
IWRES=0
ENDIF
IF(TYPE.EQ.1.AND.ASSY.EQ.2) THEN ; BELOW LOQ2
DUM2=(LOQ2-IPRED)/STD
CUM2=PHI(DUM2)
F_FLAG=1
Y=CUM2
IRES = 0
IWRES=0
ENDIF
$SIGMA 1 FIX
$ESTIMATION MAXEVAL=9990 NOABORT SIGDIG=3 METHOD=1 INTER LAPLACIAN
POSTHOC PRINT=2 SLOW NUMERICAL
$COVARIANCE PRINT=E SLOW
MODEL M4:
$DATA data.csv IGNORE=#
$SUB ADVAN8 TRANS1 TOL=6
$MODEL
COMP(central)
COMP(peri)
COMP(depot,DEFDOSE)
COMP(effect)
$DES
DADT(1) = KA*A(3) - K10*A(1) - K12*A(1) + K21*A(2)
DADT(2) = K12*A(1) - K21*A(2)
DADT(3) = -KA*A(3)
CONC = A(1)/V1DADT(4) = KEO*(CONC-A(4))
$ERROR
CALLFL = 0
LOQ1=10
LOQ2=20
EFF = BL* (1 - IMX*A(4)**HILL/ (IC50**HILL+A(4)**HILL))
IPRED=EFF
SIGA=THETA(7)
STD=SIGA
IF(TYPE.EQ.0) THEN ; GREATER THAN LOQ
F_FLAG=0
YLO=0
Y=IPRED+SIGA*EPS(1)
IRES =DV-IPRED
IWRES=IRES/STD
ENDIF
IF(TYPE.EQ.1.AND.ASSY.EQ.1) THEN
DUM1=(LOQ1-IPRED)/STD
CUM1=PHI(DUM1)
DUM0=-IPRED/STD
CUMD0=PHI(DUM0)
CCUMD1=(CUM1-CUMD0)/(1-CUMD0)
F_FLAG=1
Y=CCUMD1
IRES = 0
IWRES=0
ENDIF
IF(TYPE.EQ.1.AND.ASSY.EQ.2) THEN
DUM2=(LOQ2-IPRED)/STD
CUM2=PHI(DUM2)
DUM0=-IPRED/STD
CUMD0=PHI(DUM0)
CCUMD2=(CUM2-CUMD0)/(1-CUMD0)
F_FLAG=1
Y=CCUMD2
IRES = 0
IWRES=0
ENDIF
$SIGMA 1 FIX
$ESTIMATION MAXEVAL=9990 NOABORT SIGDIG=3 METHOD=1 INTER LAPLACIAN
POSTHOC PRINT=2 SLOW NUMERICAL
$COVARIANCE PRINT=E SLOW
Sameer Doshi
Pharmacokinetics and Drug Metabolism, Amgen Inc.
(805) 447-6941
