Question

The below is for a hypothetical study demonstrating the application of the concepts for superiority and non-inferiority testing.

A study investigated a new agent for the treatment of arthritis. Participants were randomized to receive either the current widely used (and effective) treatment or to the new experimental treatment. After 3 weeks they recorded if, based on a clinical assessment, there were improvements in symptoms (recorded as yes/no). Because of the potential large impact of age the investigators used a multiple regression model to test for differences adjusting for age. (Technically since the outcome is binary they used what is called a logistic regression model, but the analytic approach is the same.)

Investigators want to test if the new treatment is non-inferior to the current treatment.

Treatment is coded as 0=usual treatment and 1=new treatment so that a positive coefficient represents greater improvement with the new treatment. The study was done on a large sample and you may use the normal distribution for testing coefficients.

Prior to testing the investigators selected (±) 0.40 for the non-inferiority parameter (d).

Parameter	Estimate	Standard Error
Intercept	-2.57	1.11
Treat (b1)	0.52	0.46
age	0.03	0.02

1. [1] Based on the above table, what is the 95% confidence interval for the coefficient for the treatment effect (b₁)?

2. [1] Is the p-value for testing the superiority of the new treatment greater than or less than 0.05?

3. [1] What can you conclude from the above analyses concerning the superiority of the new treatment?

4. [2] Using the above non-inferiority parameter, what can the investigators conclude about the non-inferiority of the new treatment? Justify your response.

Answer 1