Exposure ae dropout analysis in patients treated with pregabalin
Download
1 / 47

Exposure-AE-Dropout Analysis in Patients treated with pregabalin. - PowerPoint PPT Presentation


  • 53 Views
  • Uploaded on

Exposure-AE-Dropout Analysis in Patients treated with pregabalin. Raymond Miller. Pfizer Global Research and Development. Issue. A new  2  ligand ( PD0332334 ) that has anxiolytic properties was in development.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Exposure-AE-Dropout Analysis in Patients treated with pregabalin.' - nina-york


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Exposure ae dropout analysis in patients treated with pregabalin
Exposure-AE-Dropout Analysis in Patients treated with pregabalin.

Raymond Miller

Pfizer Global Research and Development


Issue
Issue pregabalin.

  • A new 2 ligand (PD0332334) that has anxiolytic properties was in development.

  • Little was known about AE’s for this compound, however, extensive knowledge from other 2 ligands (pregabalin) available.

  • It is generally believed that dose titration may reduce AE’s.


Objective
Objective pregabalin.

  • To characterize the relationship between PD0332334 dose, patient characteristics, time, severity and frequency of dizziness and somnolence in patients with GAD.


Questions
Questions pregabalin.

  • Would AE frequency be different if the drug was titrated to the target dose?

  • How long do we need to titrate to minimize AE’s?

  • How many dose steps do we need to minimize AE’s?


Current information
Current Information pregabalin.

  • Multiple phase 3 trials with pregabalin titrated over 3 to 7 days to attain steady state dose in the treatment of GAD.

  • One phase 4 study with three treatment groups: placebo, pregabalin 600 mg/day fixed, 150-600 mg/day titrated..


Phase 3 trials pregabalin.GAD patients treated with Pregabalin

  • 1630 patient’s information (47218 observations) was pooled from 6 clinical studies.

  • All studies consisted of treatment arms with a dose titration phase varying from 3 to 7 days followed by a three or five week maintenance.

  • Dizziness was spontaneously recorded using a daily diary as none=0, mild=1, moderate=2, and severe=3.

  • Dropout was recorded as such up to 3 days before scheduled conclusion of the study.


Objectives
Objectives pregabalin.

  • To describe the exposure-longitudinal AE severity relationship following multiple doses of pregabalin.

  • To describe the relationship between AE and patient dropout

  • To explore the relationship between dose titration of pregabalin and dropout



Exposure-Dizziness-Dropout pregabalin. in GAD patients treated with Pregabalin

  • Models were developed for exposure-AE as well as AE-dropout.

  • For AE separate models were developed for theincidence of adverse event and for the conditional severity of adverse event given that an adverse event has occurred.

  • The unconditional severity probability distribution was obtained by summing the joint probabilities.

  • Dropout was modeled using a discrete time survival model.


Assumption that pregabalin.j ~ Niid(0, 2) is violated.


Incidence model
Incidence Model pregabalin.

  • The probability of incidence of dizziness was modeled using a nonlinear logistic regression model given by the expression:

  • The incidence model does not contain an inter-individual random effect because AEi is observed only once for each patient

  • Sigmoid Emax model best describes the drug effect although γ is not well estimated


Observed vs predicted incidence model
Observed vs. Predicted pregabalin.Incidence Model


Conditional severity model
Conditional Severity Model pregabalin.

  • The probability of each severity (none, mild, moderate, severe) was modeled with a proportional odds model. The conditional severity model given by the expression:

  • Drug exposure was based on the intended daily dose (titrated) of pregabalin.

  • Emax model with time-course placebo effect and a component with an exponential attenuation best describe the AE severity.


Dataset and nonmem control stream

pregabalin.

Dataset and NONMEM control stream

$PRED

B1=THETA(1)

B2=B1+THETA(2)

B3=B2+THETA(3)

;logits for Y>=1, Y>=2, Y.=3

RESP=0

A1 = B1 + RESP + ETA(1)

A2 = B2 + RESP + ETA(1)

A3 = B3 + RESP + ETA(1)

C1=EXP(A1)

C2=EXP(A2)

C3=EXP(A3)

;probabilities for Y>=1, Y>=2, Y>=3

P1=C1/(1+C1)

P2=C2/(1+C2)

P3=C3/(1+C3)

;Probabilities for Y=0 Y=1, Y=2, Y=3

PA=1-P1

PB=P1-P2

PC=P2-P3

PD=P3


Observed vs predicted conditional severity model
Observed vs. Predicted pregabalin.Conditional Severity Model


Markov model
Markov Model pregabalin.

  • Markov elements have been incorporated to account for the correlation between neighboring observations within a subject:

  • The logistic function (proportional odds model) and the same structures obtained with the conditional severity model was used.


Dataset and nonmem control stream1

pregabalin.

Dataset and NONMEM control stream

$PRED

B1=THETA(1)

B2=B1+THETA(2)

B3=B2+THETA(3)

IF(PRE1.EQ.1) THEN

B1=THETA(4)

B2=B1+THETA(5)

B3=B2+THETA(6)

ENDIF

IF(PRE1.EQ.2) THEN

B1=THETA(7)

B2=B1+THETA(8)

B3=B2+THETA(9)

ENDIF

IF(PRE1.EQ.3) THEN

B1=THETA(10)

B2=B1+THETA(11)

B3=B2+THETA(12)

ENDIF

RESP=0

A1 = B1 + RESP + ETA(1)

A2 = B2 + RESP + ETA(1)

A3 = B3 + RESP + ETA(1)

.. ..


Observed vs predicted conditional severity model with markov
Observed vs. Predicted pregabalin.Conditional Severity Model with Markov


Simulation step example time course of incidence
Simulation Step pregabalin.(example: Time-course of incidence)

ID=1

Probability of Incidence

“Mean of trial”

ID=2

N times simulations

ID=3

“Summary of Mean”

……..

ID=1630

Original Dataset


Posterior predictive check distributions of the number of the different transitions
Posterior Predictive Check pregabalin.Distributions of the Number of the Different Transitions

with Markov

without Markov

The vertical line in each plot represents the observed number of transition in the original dataset


Simulation mild severity model with markov
Simulation ( pregabalin.≥mild)Severity Model withMarkov

Simulated Probabilities Are Presented By Means (lines) with 95% CI (dash lines) and 80 %CI (shades) from 100 Simulations.


Simulation moderate severity model with markov
Simulation ( pregabalin.≥ moderate)Severity Model with Markov

Simulated Probabilities Are Presented By Means (lines) with 95% CI (dash lines) and 80 %CI (shades) from 100 Simulations.


Simulation severe severity model with markov
Simulation ( pregabalin.≥severe)Severity Model with Markov

Simulated Probabilities Are Presented By Means (lines) with 95% CI (dash lines) and 80 %CI (shades) from 100 Simulations.


Conclusion pregabalin.

  • The probability of experiencing dizziness during any day increases with pregabalin daily dose.

  • The predicted mean incidence of dizziness was around 35 % at daily dose of 200 mg/day or greater, which was at least 2 fold higher compared to those of at daily doses <150 mg/day.

  • The most frequently reported severity was mild to moderate. The risk of experience dizziness with any severity increases within 1 week, but decline to over the next 3 to 4 weeks. The risk of mild or moderate dizziness increases up to 25 % within 1 week, and declines to around 7 % over 3 to 4 weeks.

  • The proportional odds model including a Markov element could describe the time-course of probability of dizziness well.


Dropout model
Dropout Model pregabalin.



Dropout model1
Dropout Model pregabalin.

  • Dropout was modeled using a discrete time survival model (Gompertz).

  • Dizziness severity was included in the model as a covariate.

g(w,Yt-1) represents the hazard function


Simulations of dropout probabilities based on simulated severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)


GOF 5th – 95th prediction interval severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line) constructed from 200 simulations using the original dataset structure as well as median model predicted dropout (grey line) and Kaplan-Meier estimates of in study-survival (black line).


External Validation severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line):Pregabalin BID Add-On Titration Trial: A Randomized, Double-Blind,Placebo-Controlled, Parallel-Group, Multicenter Study in Patients With Partial Seizures (1008-157)


Time to withdrawal
TIME TO WITHDRAWAL severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)


External Validation severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line):Observed (Kaplan Meier) dropout from an independent 12 week GAD trial (red line) with either placebo or 600 mg daily pregabalin treatment and its corresponding 5th-95th nonparametric confidence intervals at weekly increments. Gray polygon outlines a prediction interval of 5th and 95th quantiles of 1000 trial simulation using the described GAD dropout model


Titration scenario s 300 mg daily itt
Titration Scenario’s severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)300 mg daily ITT

# Scenario 1 (1week): 50x2, 100, 150, 200, 250, 300

# Scenario 2 (2week): 50x3, 100x3, 150x2, 200x2, 250x2, 300...

# Scenario 3 (3week): 50x4, 100x4, 150x4, 200x4, 250x3, 300...

# Scenario 4 (4week): 50x6, 100x5, 150x5, 200x5, 250x5, 300...

# Scenario 5 (6week): 50x8, 100x8, 150x8, 200x8, 250x8, 300...


>=mild severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)


Moderate
>=moderate severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)


Severe
>=severe severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)

Note: y-axis scale is adjusted to enlarge the AE profile


S severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)imulated GADsurvival probabilities from the combined Dizziness-dropout model. Two dosing schemes (blue) within a weeklong titration regimen differ only over 3 initial days of dosing.


Next steps
Next Steps severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)

  • Clinical Trial Simulations using different titration scenarios.

    • Titration over different times

    • Variations in the first week.

    • Scaling to drugs in same class


Acknowledgements
Acknowledgements severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)

  • Kaori Ito

  • Bojan Lalovic

  • Matt Hutmacher


Backup
Backup severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)


>=mild severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)


Moderate1
>=moderate severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)


Severe1
>=severe severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)

Note: y-axis scale is adjusted to enlarge the AE profile


Simulation of dropout
Simulation of dropout severity of dizziness stratified by representative unique dose titration profiles over time. Observed (red line)


Graphical data exploration nonparametric kaplan meier analysis poolability of placebo cohorts gad
Graphical Data Exploration- Nonparametric/Kaplan Meier AnalysisPoolability of Placebo Cohorts GAD

number of events

number at risk

  • At ti there are di events (dropouts) and ni individuals (“at risk”).

In Splus (survfit) only accommodates categorical time-invariant covariates (strata)!


Comparison of dropout across titration schemes gad
Comparison of Dropout Across Titration Schemes GAD Analysis

[email protected] Day 6 +100 mg/day

[email protected] Day 7 +150 mg/day

600 mg

400 mg

Longer titration (time-to-attainment of randomized dose) ->lower dropout

Study 87- an outlier?


ad