# Presentation: 572635

## Non-inferiority designs for relapse prevention of schizophrenia

- Gene Laska Ph.D.
- Department of Psychiatry
- NYU School of Medicine
- Nathan Kline Institute for Psychiatric Research

## The problem of relapse in schizophrenia

- Montero’s review of the literature estimated that 42 percent of patients with schizophrenia relapsed over the course of a year1
- For patients who discontinued antipsychotic therapy, relapse was an almost certain at one year2
- 	1.  Montero, I., Pérez, I. Ruiz, & Gómez-Beneyto, M. (1998). Social adjustment in schizophrenia: Factors predictive of short-term social adjustment in a sample of schizophrenic patients. Acta Psychiatrica Scandinavica, 97, 116-121
- 	2. Weiden, P.J., and Olfson, M. (1995). Cost of relapse in schizophrenia. Schizophrenia Bulletin, 24, 419-429.

## Framing the issue

- Comparisons to placebo in a RCT provide  the most persuasive evidence
- It may be unethical to use placebo when better treatments exist
- Are active controlled trials using non-inferiority designs a valid alternative?

## Logic of non-inferiority trials

- If a standard S is consistently superior to  placebo, then
- To show that a test treatment T is superior to placebo...
- It suffices to show that the test treatment is as good as (not inferior) to the standard

## The formal concept of non-inferiority: definition

- If T’s effect is not worse than C’s effect by more than δ, it is said to be *non-inferior *
* *δ is a pre-specified *non-inferiority margin*

## Equivalence, non-inferiority  and superiority: graphically

- Control better

- Test better

- - 

- 0

- 

- equivalent

- non-inferior

- test superior

- control superior

- uninformative

- Test - Control

## Setting the non-inferiority margin

- Subjective – often contentious
- If too large: inferior treatments may be called non-inferior
- If too small:  huge sample sizes are required
- Usually a fraction of the historical difference between control and placebo

## Assay sensitivity

- The ability of a RCT to find a difference between treatments if there truly is a difference- a property of one trial
- Sensitivity is a property for a class of RCTs
- Statisticians call this “power” – the probability of detecting a true difference of size 

## Assay sensitivity in a three armed RCT with T,C and P

- If T>P or S>P then the trial has demonstrated assay sensitivity
- If T=S=P then the trial is a failure
- 	It has no assay sensitivity because it is known that S>P
- 	No inference regarding the equivalence of S and T is possible

## Assay sensitivity in a  two armed RCT with T and S

- A trial that finds T>S or S>T has *ipso facto* demonstrated assay sensitivity
*Problem:* A two armed trial that does not distinguish treatments (S=T) has *not* demonstrated assay sensitivity
- Differentiating a failed trial from a trial that correctly finds no difference is not possible

## Therefore

- The conclusion that a test drug is non inferior to a standard *is only valid* if the standard *would have been superior to placebo had one been included in the trial*
- This possibility can only be appraised* by comparing the results with historical RCTs*

## Randomized controlled relapse prevention studies in the literature

- Leucht *et al *- *AJP 2003 *
- 			numerous studies*
- Schooler *et al* - *AJP 2005*
-           risperidone/haloperidol
- Pigott *et al* *J - Clin Psych 2003*
-           aripiprazole /placebo
- *Trials needed to have estimated relapse rates using Kaplan Meier
-   and have reasonable sample sizes

## Probability of relapsing in 6 months based on KM Estimates-Aty vs Pl

- atypical

- placebo

## Probability of relapsing in 6 months based on KM Estimates-Aty vs Conv

*Probability of relapsing in 6 months **based on KM Estimates-Aty vs Conv*

- atypical

- conventional

## Six month relapse rates for eleven prevention studies

- placebo

- atypical

- atypical

- conventional

## Implications of the historical RCTs

-                       **Six-month relapse rates**
- 	_	__	__	__Range__	__	__Mean__	__  vs P   vs Con_
- Atypicals  	 3  - 39		19.1	   21.6    17.0
- Conventionals 	 3 -  47	 	26.6
- Placebo   	53 – 63	56.0	_                                         _
- There is no overlap of active vs placebo
- Reasonable to set  = 10 -15% test vs a conventional
- 				        15 - 20% test vs an atypical

## Powering the trial: example 

- Assume PC = PT is about .35
- Suppose  = .15
- Let the two groups have equal sample sizes
- What sample size will reject H0 with  	80% power?
- Approximate sample size is 183 per group
-             (based on Fisher’s exact test)

## Conclusion

*Regulatory Concern:* Just as in an acute trial, the major concern is concluding that an ineffective drug works
- The historical record suggests that in active controlled relapse preventions studies in schizophrenia this risk is small