# Presentation: 789135

## Assessing the Relationship between Success on the Investigator Global Evaluation and Acne Lesion Counts

- Biostatistics Team Leader
-  DBIII, OB, CDER, FDA

## Outline

- 1.  Background
- 2.  Modeling IGE Success
- 3.  Interpretation and Assessment of Fit
- 4.  Final Comments

## Background

- Measures used for efficacy evaluation
- Lesion counts, change or relative change from baseline (Count Data)
- Investigator’s Global Evaluation (IGE) (Ordinal Data)
- Expect two evaluations to be related
- Goal: Investigate the relationship between the      	 dichotomized IGE and lesion counts

## 	Use empirical modeling to address the following points:

1.  Impact of lesion counts (or changes) on    success on the IGE

2. Whether a certain type of lesion has more impact on the IGE success

3.  Utility of adding baseline counts to model

- 1.  Impact of lesion counts (or changes) on    success on the IGE
- 2. Whether a certain type of lesion has more impact on the IGE success
- 3.  Utility of adding baseline counts to model

## 	Where 
p = probability of success on IGE
Xj = lesion counts (infl or non-infl; baseline or final) or change from baseline (infl or non-infl)
j = the change in the log odds of success on the IGE due to an increase of 1 unit in the corresponding count or change

*p* = probability of success on IGE
*X**j** = *lesion counts (infl or non-infl; baseline or final) or change from baseline (infl or non-infl)
***j** = *the change in the log odds of success on the IGE due to an increase of 1 unit in the corresponding count or change

- Logistic Regression Model for Success on IGE

## Data Set Analyzed

- 400 subjects
- 12 week duration (Evaluations at baseline, Weeks 4, 8, and 12)
- IGE: 0=none, 1=minimal, 2=mild, 3=moderate, 4=severe, 5=very severe
- Success on IGE = none or minimal

## Model 1 - Final Lesion Counts

- Where
- X1=Week 12 inflammatory lesions
- X2 =Week 12 non-inflammatory lesions
- (Analysis excludes 1 outlier with influence on Hosmer-Lemeshow test.)

- Consider a stepwise approach for including covariates.

## Comments

- 1 unit increase in inflammatory lesions at Week 12 implies decrease of  *e**-0.413** = *0.662 in odds for success on IGE
- 1 unit increase in non-inflammatory lesions at Week 12 implies decrease of  *e**-0.090** = *0.914 in odds for success on IGE

## Comments (Cont’d)

- The coefficient for infl. lesions is over 4 times that for non-infl. lesions
- may be due to appearance, color, size, surrounding halo of erythema, etc. of infl. lesions
- Note that when final lesion counts are given, baseline values provide no additional information for explaining IGE success

## Assessing the Fit of the Model

## Model 2 - Change from Baseline

- Where
- X1 = change in infl		X2 = change in non-infl
- X3 = baseline infl		X4 = baseline non-infl
- (Analysis excludes 1 outlier with influence on Hosmer-Lemeshow test.)

- 	Fitted model:

## Comments

- Change in lesion counts (infl. or non-infl.) do not fully explain IGE (baseline still important)
- Larger reductions in infl. and non-infl. lesions increase the odds of IGE success
- Increases in baseline infl. and non-infl. lesions reduce the odds of IGE success
- Infl again has about 4 times the impact as non-infl

## Table 2: Obs. and exp. frequencies of IGE Success based on change from baseline (Model 2) for the Hosmer-Lemeshow test

## Final Comments

- Inflammatory lesions have more impact on IGE success than non-inflammatory lesions
- Absolute changes in lesion counts alone do not fully explain variability in IGE success (baseline counts still important)
- Fitted model useful for checking consistency of study findings based on IGE success and lesion counts