From: Ribbing, Jakob <*Jakob.Ribbing*>

Date: Fri, 21 Aug 2009 14:12:11 +0100

Hi Douglas,

This has been a concern for me as well, although I do not know if this =

ever happens(?). For the automatic (generic scripts) exclusion of etas =

that I use for eta-diagnostics, I tend to exclude a group (e.g. each =

dose or dose-study combination) if all subjects have eta=0 in that =

group. This would for example exclude IOV-eta3 from a study that only =

hade two occasions, or the placebo group(s) for etas on drug effect. I =

feel safe with that exclusion for my diagnostics. If I had to make the =

choice between excluding all etas that are exactly equal to zero or none =

at all, I would more trust diagnostics after exclusion.

Jakob

________________________________

From: Eleveld, DJ [mailto:d.j.eleveld

Sent: 21 August 2009 13:57

To: Ribbing, Jakob; Pyry Välitalo; nmusers

Subject: RE: [NMusers] Calculating shrinkage when some etas are zero

Hi Pyry and Jacob,

If you exclude zero etas then what happens to infomative individuals who =

just happen to have the population typical values?

This approch would exclude these individuals when trying to indicate how =

informative an estimation is about a parameter.

I know this is unlikely, but it is possible.

The etas just tell what value is estimated, its not the whole story =

about how infomative an estimation is. I dont think you can do

this without considering how 'certian' you are of each of those eta =

values.

Douglas Eleveld

________________________________

Van: owner-nmusers

Verzonden: vr 21-8-2009 12:26

Aan: Pyry Välitalo; nmusers

Onderwerp: RE: [NMusers] Calculating shrinkage when some etas are zero

Hi Pyry,

Yes, when calculating shrinkage or looking at eta-diagnostic plots it is =

often better to exclude etas from subjects that has no information on =

that parameter at all. For a PK model we would not include subjects that =

were only administered placebo (if PK is exogenous compound). In the =

same manner placebo subjects are not informative on the drug-effects =

parameters of a (PK-)PD model. These subjects have informative etas for =

the placebo-part of the PD model, but not on the drug-effects (etas on =

Emax, ED50, etc.). For any eta-diagnostics you can removed these etas =

based on design (placebo subject, IV dosing, et c) or the =

empirical-Bayes estimate of eta being zero.

Cheers

Jakob

________________________________

From: owner-nmusers

On Behalf Of Pyry Välitalo

Sent: 21 August 2009 10:45

To: nmusers

Subject: [NMusers] Calculating shrinkage when some etas are zero

Hi all,

I saw this snippet of information on PsN-general mailing list.

Kajsa Harling wrote in PsN-general:

"I talked to the experts here about shrinkage. Apparently, sometimes an

individual's eta may be exactly 0 (no effect, placebo, you probably

understand this better than I do). These zeros should not be included in

the shrinkage calculation, but now they are (erroneously) in PsN."

This led me to wonder about the calculation of shrinkage. I decided to =

post here on nmusers, because my question mainly relates to NONMEM. I =

could not find previous discussions about this topic exactly.

As I understand, if a parameter with BSV is not used by some =

individuals, the etas for these individuals will be set to zero. An =

example would be a dataset with IV and oral dosing data. If oral =

absorption rate constant KA with BSV is estimated for this data, then =

all eta(KA) values for IV dosing group will be zero.

The shrinkage of etas is calculated as

1-sd(etas)/omega

If the etas that equal exactly zero would have to be removed from this =

equation then it would mean that NONMEM estimates the omega based on =

only those individuals who need it for the parameter in question, e.g. =

the omega(KA) would be estimated only based on the oral dosing group. Is =

this a correct interpretation for the rationale to leave out zero etas?

I guess the inclusion of zero etas into shrinkage calculations =

significantly increases the estimate of shrinkage because the zero etas =

always reduce the sd(etas). As a practical example, suppose a dataset of =

20 patients with oral and 20 patients with IV administration. Suppose =

NONMEM estimates an omega of 0.4 for BSV of KA. Suppose the sd(etas) for =

oral group is 0.3 and thus sd(etas) for all patients is 0.3/sqrt(2) =

since the etas in IV group for KA are zero.

Thus, as far as I know, PsN would currently calculate a shrinkage of =

1-(0.3/sqrt(2))/0.4=0.47.

Would it be more appropriate to manually calculate a shrinkage of =

1-0.3/0.4=0.25 instead?

All comments much appreciated.

Kind regards,

Pyry

Kajsa Harling wrote:

Dear Ethan,

I have also been away for a while, thank you for your patience.

I talked to the experts here about shrinkage. Apparently, sometimes an

individual's eta may be exactly 0 (no effect, placebo, you probably

understand this better than I do). These zeros should not be included in

the shrinkage calculation, but now they are (erroneously) in PsN.

Does this explain the discrepancy?

Then, the heading shrinkage_wres is incorrect, it should say

shrinkage_iwres (or eps) they say.

Comments are fine as long as they do not have commas in them. But this

is fixed in the latest release.

Best regards,

Kajsa

________________________________

De inhoud van dit bericht is vertrouwelijk en alleen bestemd voor de =

geadresseerde(n). Anderen dan de geadresseerde(n) mogen geen gebruik =

maken van dit bericht, het niet openbaar maken of op enige wijze =

verspreiden of vermenigvuldigen. Het UMCG kan niet aansprakelijk gesteld =

worden voor een incomplete aankomst of vertraging van dit verzonden =

bericht.

The contents of this message are confidential and only intended for the =

eyes of the addressee(s). Others than the addressee(s) are not allowed =

to use this message, to make it public or to distribute or multiply this =

message in any way. The UMCG cannot be held responsible for incomplete =

reception or delay of this transferred message.

Received on Fri Aug 21 2009 - 09:12:11 EDT

Date: Fri, 21 Aug 2009 14:12:11 +0100

Hi Douglas,

This has been a concern for me as well, although I do not know if this =

ever happens(?). For the automatic (generic scripts) exclusion of etas =

that I use for eta-diagnostics, I tend to exclude a group (e.g. each =

dose or dose-study combination) if all subjects have eta=0 in that =

group. This would for example exclude IOV-eta3 from a study that only =

hade two occasions, or the placebo group(s) for etas on drug effect. I =

feel safe with that exclusion for my diagnostics. If I had to make the =

choice between excluding all etas that are exactly equal to zero or none =

at all, I would more trust diagnostics after exclusion.

Jakob

________________________________

From: Eleveld, DJ [mailto:d.j.eleveld

Sent: 21 August 2009 13:57

To: Ribbing, Jakob; Pyry Välitalo; nmusers

Subject: RE: [NMusers] Calculating shrinkage when some etas are zero

Hi Pyry and Jacob,

If you exclude zero etas then what happens to infomative individuals who =

just happen to have the population typical values?

This approch would exclude these individuals when trying to indicate how =

informative an estimation is about a parameter.

I know this is unlikely, but it is possible.

The etas just tell what value is estimated, its not the whole story =

about how infomative an estimation is. I dont think you can do

this without considering how 'certian' you are of each of those eta =

values.

Douglas Eleveld

________________________________

Van: owner-nmusers

Verzonden: vr 21-8-2009 12:26

Aan: Pyry Välitalo; nmusers

Onderwerp: RE: [NMusers] Calculating shrinkage when some etas are zero

Hi Pyry,

Yes, when calculating shrinkage or looking at eta-diagnostic plots it is =

often better to exclude etas from subjects that has no information on =

that parameter at all. For a PK model we would not include subjects that =

were only administered placebo (if PK is exogenous compound). In the =

same manner placebo subjects are not informative on the drug-effects =

parameters of a (PK-)PD model. These subjects have informative etas for =

the placebo-part of the PD model, but not on the drug-effects (etas on =

Emax, ED50, etc.). For any eta-diagnostics you can removed these etas =

based on design (placebo subject, IV dosing, et c) or the =

empirical-Bayes estimate of eta being zero.

Cheers

Jakob

________________________________

From: owner-nmusers

On Behalf Of Pyry Välitalo

Sent: 21 August 2009 10:45

To: nmusers

Subject: [NMusers] Calculating shrinkage when some etas are zero

Hi all,

I saw this snippet of information on PsN-general mailing list.

Kajsa Harling wrote in PsN-general:

"I talked to the experts here about shrinkage. Apparently, sometimes an

individual's eta may be exactly 0 (no effect, placebo, you probably

understand this better than I do). These zeros should not be included in

the shrinkage calculation, but now they are (erroneously) in PsN."

This led me to wonder about the calculation of shrinkage. I decided to =

post here on nmusers, because my question mainly relates to NONMEM. I =

could not find previous discussions about this topic exactly.

As I understand, if a parameter with BSV is not used by some =

individuals, the etas for these individuals will be set to zero. An =

example would be a dataset with IV and oral dosing data. If oral =

absorption rate constant KA with BSV is estimated for this data, then =

all eta(KA) values for IV dosing group will be zero.

The shrinkage of etas is calculated as

1-sd(etas)/omega

If the etas that equal exactly zero would have to be removed from this =

equation then it would mean that NONMEM estimates the omega based on =

only those individuals who need it for the parameter in question, e.g. =

the omega(KA) would be estimated only based on the oral dosing group. Is =

this a correct interpretation for the rationale to leave out zero etas?

I guess the inclusion of zero etas into shrinkage calculations =

significantly increases the estimate of shrinkage because the zero etas =

always reduce the sd(etas). As a practical example, suppose a dataset of =

20 patients with oral and 20 patients with IV administration. Suppose =

NONMEM estimates an omega of 0.4 for BSV of KA. Suppose the sd(etas) for =

oral group is 0.3 and thus sd(etas) for all patients is 0.3/sqrt(2) =

since the etas in IV group for KA are zero.

Thus, as far as I know, PsN would currently calculate a shrinkage of =

1-(0.3/sqrt(2))/0.4=0.47.

Would it be more appropriate to manually calculate a shrinkage of =

1-0.3/0.4=0.25 instead?

All comments much appreciated.

Kind regards,

Pyry

Kajsa Harling wrote:

Dear Ethan,

I have also been away for a while, thank you for your patience.

I talked to the experts here about shrinkage. Apparently, sometimes an

individual's eta may be exactly 0 (no effect, placebo, you probably

understand this better than I do). These zeros should not be included in

the shrinkage calculation, but now they are (erroneously) in PsN.

Does this explain the discrepancy?

Then, the heading shrinkage_wres is incorrect, it should say

shrinkage_iwres (or eps) they say.

Comments are fine as long as they do not have commas in them. But this

is fixed in the latest release.

Best regards,

Kajsa

________________________________

De inhoud van dit bericht is vertrouwelijk en alleen bestemd voor de =

geadresseerde(n). Anderen dan de geadresseerde(n) mogen geen gebruik =

maken van dit bericht, het niet openbaar maken of op enige wijze =

verspreiden of vermenigvuldigen. Het UMCG kan niet aansprakelijk gesteld =

worden voor een incomplete aankomst of vertraging van dit verzonden =

bericht.

The contents of this message are confidential and only intended for the =

eyes of the addressee(s). Others than the addressee(s) are not allowed =

to use this message, to make it public or to distribute or multiply this =

message in any way. The UMCG cannot be held responsible for incomplete =

reception or delay of this transferred message.

Received on Fri Aug 21 2009 - 09:12:11 EDT