# Presentation: 818461

## Clinical Trial Experiences in Early Prostate Cancer

- Kevin Carroll, MSc, FRSS,
- Global Statistical Leader, Oncology, AstraZeneca Pharmaceuticals

**Notes:**
Thank you Mr chairman and good afternoon to you all.   Again, I’d like to thank the FDA, AACR and the panel for providing me with the opportunity to share with you some thoughts and learning points arising out of AZ experience in the design, conduct and analysis of clinical trials in EPC.  

## Contents

- Learnings from the Casodex Early Prostate Cancer (EPC) clinical trial program.
- PSA doubling-free survival (PSA-D) as a surrogate for progression-free survival (PFS).
- Alternative ‘event count’ methods for analysing event-free survival data.

**Notes:**
In terms of contents, I’ll briefly summarise our learning experiences from Casodex EPC program and then move on to talk a little about PSA-D free survival as an endpoint in the adjuvant setting.  I’ll then finish up with a few thoughts on how we might overcome some common issues when using event free survival endpoints.

## Learnings from the Casodex EPC program: Design of, and endpoints in, current and future trials should reflect clinical practice.

- PFS and overall survival cannot sensibly serve as primary trial  endpoints in EPC.
- Hormonal therapies prescribed on or before a PSA rise, prevent observation of objective progression outcomes and complicate survival as an endpoint.
- In future, only trials with endpoints that reflect clinical practice will be feasible.
- Progression-free survival including the initiation of further PCa therapy.
- PSA-D as a surrogate.

**Notes:**
Let me starting by stating quite clearly that, while prolongation of objective PFS and OS are ultimate goals in the management of patients with early PCa, these outcomes cannot sensibly serve as trial endpoints in this setting. 

Quite apart from the long natural history of the disease and the consequent impact on clinical trial size and duration, current world-wide practice means that highly effective hormonal therapies are regularly prescribed on or even before a PSA rise, preventing observation of endpoints such as objective progression – by this I mean progression as evidenced clinically via imaging studies -  and complicating survival as an endpoint.

In light of current practice and patient sensitivity to PSA, as we go forward, only trials with endpoints that reflect clinical practice will be feasible and meaningful.  In practical terms this means that we may have to look to PSA based surrogate endpoints or objective progression, but redefining to include early systemic treatment as an event, if we are to have any prospect of detecting the efficacy of new treatments.  

## 

- Use of effective therapies on progression is calling into question the viability of OS as the primary endpoint in 1st line CRC

- Effective treatments given upon failure dampen the sensitivity of longer term endpoints in clinical trials

- 1st line CRC:

**Notes:**
To appreciate this a little better, I think it is helpful to briefly look at the parallel between CRC and PCa. 

At the endpoint workshop last year and at the follow-up AC held just last month, it was generally recognised that the introduction effective 2nd line treatments  on progression was making it difficult to expect to see treatment effects on OS.

The use of PFS, therefore, as the primary endpoint in this setting was discussed at length, with the AC voting 8 to 4, I think, in favour of it’s use. 

## 

- Longer term endpoints in EPC are nullified by the use of effective therapies on a PSA rise

- In a parallel with CRC, the use of effective hormonal therapies on a PSA rise in early prostate cancer calls into questionthe viability of objective PFS/DFS as a primary endpoint

- Early prostate cancer:

**Notes:**
In early PCA, there is a direct parallel. 

Here, the use of effective therapies prior to objective progression makes it it difficult to expect to see treatment effects on PFS or OS.  Unlike CRC, however, in EPC we will have to re-define what we mean  by ‘progression’, either by accepting biochemical progression as a component of progression or if not, by at least including the initiation of hormonal therapy as a progression event.    

Failure to accept the impact of current practice on traditional endpoints will essentially render early and adjuvant PCa a no-go disease area, as researchers will likely consider the area futile since the required endpoints are unattainable. 

## Casodex EPC Program: A clear objective

- Determine benefit of Casodex 150 mg therapy as an addition to standard care for patients with early-stage disease.
- Surgery or radiation of curative intent.
- Watchful waiting when curative intent is not considered possible or appropriate.

**Notes:**
Now, I’d like to turn to the CASODEX EPC program to illustrate these issues with real data.

As I mentioned earlier, the objective of he program is to..

## Casodex EPC Program: Design

- Three randomized, double-blind, placebo-controlled trials conducted across 23 countries.
- A total of 7,500 patients across trials required to detect at least a 15% improvement in PFS after 2-yr minimum, 3-yr median follow-up.
- Stratified combined analysis prospectively captured in protocols.
- Program is ongoing.

**Notes:**
Again, as covered this morning, the program is the worlds largest prostate cancer treatment trial consisting of three randomized, double-blind, placebo-controlled trials conducted in 23 countries in over 350 sites and 8113 patients.

A total of 7,500 patients were required to detect at least a 15% improvement in PFS after 2-yr minimum, 3-yr median follow-up and a stratified combined analysis was prospectively captured in each of the trial protocols.

A stratified combined analysis at 3 yrs median follow-up was prospectively captured in each of the trial protocols and the program is ongoing.

## Consistent definition of endpoints

**Progression-free survival (PFS) time =** time to first of disease progression or death from any cause.
- Progression confirmed by bone scan, biopsy, CT scan or other imaging technique.
- Changes in PSA not considered an event.
- Addition of further treatment for PCa not considered an event.
**PSA doubling-free survival (PSA-D) time** = time to first of a PSA doubling or PFS event.
- PSA doubling = value no lower than 0.2 ng/ml to a value of at least 0.4 ng/ml.

**Notes:**
PFS was defined consistently across the program as the first of objective disease progression or death from any cause.

Importantly, at the time of writing the protocols back in the early 90’s , changes in PSA were explicitly excluded as an event.  The addition of further treatment for PCA was also not considered an event – the expectation in the protocol was that such treatment would be given post objective progression and so would not be a complicating factor. 

PSA D free-survival was defined as the first of a PSA doubling or a PFS event.

(>3/4 adj pts with a PSA D event were doublings 75% RT, 95% RT!)

## Significant reductions in the risk of a PSA-D event across the program

**0%**

**10%**

**20%**

**30%**

**40%**

**50%**

**60%**

**70%**

**80%**

**% reduction in risk of PDA-D event**

**0023****N. America****(N=3292)**

**0024****Europe, RoW****(N=3603)**

**0025****Scandinavia****(N=1218)**

**All****(N=8113)**

**Reduction in risk associated with bicalutamide**

*****

*****

*****

*****

*** **p<0.0001

**Notes:**
On this next slide, I summarise the outcomes for PFS and PSA-DT in the EPC program.   It’s a little complex so let me take you quickly thru’ it.

Along the bottom you can see the 3 trials highlighted along with the combined data.   The vertical axis gives the % reduction in risk associated with bicaluatmide treatment over placebo.   

The bars represent the results for PSA-DT.  So, as you can see bicalutamide was associated with a significant reduction in the risk of a PSA-D event in all three trials – the reduction in risk was around 35% in the NA and RoW trials and around 70% in the Scandinavian trial which consisted predominantly of pts undergoing WW. 

## Significant reductions in the risk of a PFS event across the program, except in the NA trial

**0%**

**10%**

**20%**

**30%**

**40%**

**50%**

**60%**

**70%**

**80%**

**% reduction in risk of PDA-D event**

**% reduction in risk of PFS event**

**0023****N. America****(N=3292)**

**0024****Europe, RoW****(N=3603)**

**0025****Scandinavia****(N=1218)**

**All****(N=8113)**

**Reduction in risk associated with bicalutamide**

*****

*****

*****

*****

*****

*****

*****

**NS**

*** **p<0.0001

**Notes:**
Now, let’s add in the results for objective PFS, showing here by the purple bars. 

As you can see bicalutamide was associated with a significant reduction in the risk of an objective PFS event in 2 of 3 trials, with the NA trial showing  no difference.

## Early intervention with PCa therapies may nullify objective PFS as an endpoint  

**(Rx=561)**

**0023****N. America**
**(Rx=270)**

**0025****Scandinavia**
**(Rx=303)**

**All**
**(Rx=1134)**

**% patients receiving PCa therapy**

- Early intervention with PCa therapies may nullify objective PFS as an endpoint

**Notes:**
It is clearly of interest to ask why there is no difference in objective progression in the NA trial in spite of there being a large effect on PSA DT.

An answer, perhaps, and an important learning point for future trials in EPC, lies in the early use of additional therapies for PCa as shown on this slide.  

As you can see, of those pts in the NA trial who received additional therapy (the vast majority of which was hormonal) 3⁄4 did so in the absence of an objective progression event.  There was some early treatment given in the other two trials also, but to a lesser extent.   It is at least a hypothesis, therefore,  that early treatment on small PSA rise in the NA trial, being consistent with current practice, has blunted objective progression as an endpoint in that trial.  

It is interesting to note that more pts (205 I think) received early hormonal therapy in the NA trial than actually reached the protocolled progression endpoint.  It is conceivable, therefore that this trial will always remain equivocal. 

## Analyses reflective of clinical practice reveals significant effects in all 3 trials

**0023****N. America****(N=3292)**

**0024****Europe, RoW****(N=3603)**

**0025****Scandinavia****(N=1218)**

**All****(N=8113)**

**Reduction in risk associated with bicalutamide**

- p=0.0143

- p<0.0001

- p<0.0001

- p<0.0001

**Notes:**
If we look at PFS but now include early hormonal therapy as an event, then all 3 trials yield a significant outcome.

The importance of this observation to the discussion here today is very clear: future trials in EPC need to focus on clinically relevant endpoints that reflect clinical practice.  

We cannot ignore the impact of a decision to treat a pt with an elevated PSA and hope somehow to capture the effect of treatment on a later endpoint.   

## Even if we ignored the impact of early hormonal therapies, trials focusing on PFS will take many years to complete

- 90% of RP patients without a PFS event at 3yrs.
- 1800 patients recruited over 2 years followed for minimum of 10 yrs for 90% power to detect a 33% improvement.
- 78% of RP patients without a PSA-D event at 3yrs.
- 1500 patients recruited over same period followed for minimum of 5 yrs for 90% power to detect same relative effect.

**Notes:**
Even if we were to ignore the confounding of early PCa therapies in EPC, trials focussing on PFS may be prohibitively large and lengthy to contemplate.

For example,

That’s a 10 yr trial.

Contrast that with a trial looking at PSA-D free survival – the trial is 1⁄2 as long with 60% fewer patients and thus is more feasible proposition to contemplate. 

## PSA doubling-free survival (PSA-D) as a surrogate for progression-free survival (PFS).

**Notes:**
So that’s all I wanted to say on the learning points arising out of the EPC program.  

Given that traditional endpoints like PFS and OS cannot sensibly and feasibly be employed as primary endpoints EPC trials conducted today and in the future, what other endpoints might we consider?  

As we have heard from Dr D’Amico, PDA-DT may be a useful endpoint an this has consequently been explored in the Casodex EPC program. 

## Delaying disease progression in EPC is a benefit in and of itself

- Disease progression is a necessary and irreversible step between cancer growth, patient morbidity and death.
- Delaying disease in EPC therefore represents a direct benefit to the patient.
- However, current clinical practice makes objective PFS an unattainable endpoint in clinical trials.
- There is a need, therefore, to explore the surrogacy of early endpoints, like PSA-D, for progression outcome.

**Notes:**
However, before I look at the Casodex EPC data, I think it is important to consider the inherent value of delaying disease progression in EPC.

As a statistician, this is not something I am qualified to comment upon directly, but perhaps I can highlight that others have noted previously that disease progression is a necessary step between cancer growth, patient morbidity and death and, hence, it would seem axiomatic that delaying the progression of disease in EPC represents a direct benefit to the patient.
However, as I have just illustrated, current clinical practice makes objective PFS an unattainable endpoint in trials in EPC. 
There is a need, therefore, to explore the surrogacy of a treatment effect on early endpoints, like PSA-DT, for the treatment effect on progression outcome in EPC.

## Surrogacy and Surrogate Endpoints

- “A lab measurement or a physical sign used as a substitute for a clinically meaningful endpoint that measures directly how a patient feels, functions or survives.   Changes induced by a therapy on a surrogate endpoint are expected to reflect changes in a clinically meaningful endpoint.”Dr Robert Temple, Director of Medical Policy, CDER, FDA (1995).
- Correlation is necessary but not sufficient to establish an endpoint as a surrogate.

**Notes:**
Surrogacy and surrogate endpoints is a concept that is often discussed in the context of clinical trials, but frequently and unfortunately confused with correlation.  

As captured here, surrogacy is all about whether the effect of treatment on some earlier endpoint predicts for an effect of treatment on a long term clinical endpoint.  

Thus, correlation whilst necessary for surrogacy, in of itself, is insufficient, to prove it.

## PSA-D free survival as a surrogate for PFS in early prostate cancer

- Buyse and Molenbergs1 provide a contemporary method to estimate the effect of treatment on a later endpoint given the effect of treatment on an earlier endpoint.
- Casodex EPC data indicates that a hormonal therapy inducing a large effect on PSA-D free survival induces a significant effect on PFS.
- PSA-D free survival can therefore be employed as the primary endpoint in early prostate cancer treatment trials.

- 1Buyse and Molenbergs (2000).

**Notes:**
Given sufficient data from randomised controlled trials, Buyse and Molenbergs describe how one can predict the effect of treatment on a clinical outcome endpoint given its effect on some earlier, intermediate endpoint. 

When their approach is applied to the EPC data, the data suggest that a hormonal therapy that induces a large effect on PSA-D free survival is likely to also induce a significant effect on objective PFS, suggesting that PSA-D free survival could be used as the primary endpoint in early PCa trials.

## Overall positive association between treatment effects on PFS and PSA-D free-survival

- Log HR for PSA-D free survival

- Log HR for PFS

- r=0.69, p=0.001

-  = region

**Notes:**
The significant association between the effect of treatment on PDA-D and the effect of treatment on PFS in the EPC program is shown on this slide.

Here the circles represent distinct regions – countries in fact – that participated in the trial program.   As you can see there was a significant association between treatment effects on PSAD and treatment effects on PFS  which supports PSAD as a surrogate for survival in this setting.

If we add 95% CI around the line we can then determine the minimum impact on PSAD that would be needed to be confident of a significant impact on PFS.   I’ll say more about this in a moment.

## Positive association between treatment effects on PFS and PSA-D free-survival in RP patients

- Log HR for PSA-D free survival

- Log HR for PFS

- r=0.46, p=0.037

-  = region

- Positive association between treatment effects on PFS and PSA-D free-survival in _RP patients_

**Notes:**
This slide is of a similar format, but looks only at patients who underwent RP. 

Again, we see a significant association between treatment effects on PSAD and treatment effects on PFS.  

## Positive association between treatment effects on PFS and PSA-D free-survival in RT patients

- Log HR for PSA-D free survival

- Log HR for PFS

- r=0.65, p=0.01

-  = region

- Positive association between treatment effects on PFS and PSA-D free-survival in _RT patients_

**Notes:**
And this slide looks at patients who underwent RT

And, again, we see a significant association between treatment effects on PSAD and treatment effects on PFS.

## Large effects on PSA-D free survival can predict for positive effects on PFS 

- Minimum reduction in the risk of a PSA-D event to yield a significant reduction (p<0.05) in the risk of a PFS event:
- 20% in All patients
- 30% in RP patients
- 50% in RT patients
- PSA-D free survival can be used as the primary endpoint in early prostate cancer trials.

**Notes:**
So what does all this mean?

Well, based on all the data, it tells us that if a hormonal treatment has a 20% effect on PSA-DT, then it will likely have a significant effect on PFS.  

In terms of  pts undergoing RP or RT, a treatment having a 30-50% effect on PSA-DT will likely have a significant impact on PFS.

These data, together with the data offered earlier by Dr D’Amico, further support the use of PSA-D free survival as the primary endpoint in early PCa trials.   

## Alternative ‘event count’ methods for analysing event-free survival data.

**Notes:**
That’s all I wanted to offer to the workshop in terms of  the learning from the EPC program and relationship between PSA-D free survival and PFS. 

If we are to use an event free survival endpoints like PSA-D free survival, there are a number of technical issues that give some cause for concern.  

I therefore wanted to take a few moments to discuss the use of alternative methods  for the analysis of event-free survival analyses that might serve to address these concerns and, thus, provide greater confidence that treatment comparisons based on event free–survival data are robust and unbiased. 

## Actual event times are often unknown in clinical trials1,2

- Visit 1

- Visit 2

- Randomization

- = Date of Death or actual tumor progression

- Survival Event Date

- Visit 1

- Visit 2

- Randomization

- Event Date

- Survival Time

- Event time

- Actual event times are often unknown in clinical trials1,2

- 1 Slide adapted from Dr G Williams, web link; 2 Williams et al, Proc ASCO, 2002.

**Notes:**
I think some of you will have seen this slide before, being taken from Dr William’s presentation at the NSCLC endpoint workshop in April last year.

As you are all well aware, survival is determined exactly in trials, whereas the ‘event’ in an event free survival analysis, such as progression of PSA-D is not, leading to over estimation of PFS time.  

As reported by Dr Williams et al, this can result in bias when comparing treatments.

## Benefits in using an overall ‘event count’ to compare treatments in trials1,2,3

- As an alternative to event-free survival time, treatments could be compared on the overall event count over the trial follow-up period:

- 1 Cuzick, Biometrics, 1982; 2 Gail, Cont Clinical Trials, 1985; 3 Carroll, Clinical Trials, submitted 2004.

- free from concerns and potential biases associated with the timing of the event.
- treatment effect described in terms of the relative risk (RR) of an event between treatments.
- offers the opportunity to simplify clinical trial design.
- is more powerful if treatment effect is delayed.

**Notes:**
There are numerous ways to try to tackle this issue, many of which involve complex algorithms with respect to censoring mechanisms.

One simple approach might be to compare treatments on the basis of an overall event count over the follow-up period. This is akin to the ‘single time point’ idea that has been raised previously to this committee.  In my next slide I’ll be comparing this approach with the regular analysis of PFS time in  two prostate cancer trials.    

Before I do that, we might briefly consider what might be gained if we took this approach.   Firstly, treatments would be compared free from concerns about the timing of progression and any biases that might introduced and the  treatment effect described in terms of the relative risk of an event over the follow-up period.   

Use of an overall event count approach also offers the opportunity to greatly simplify clinical trial design in terms of, conduct and data collection and subsequent data review and auditing. 
It can further be shown that an overall event count analysis is more powerful if the effect of treatment is delayed i.e. if the usual KM curves fail to separate at time zero. 

Of course, it is important to note that as with the regular log rank approach, one would require treatments to be followed equally with no serious imbalance in censoring between treatment arms. 

Overall therefore, this approach offers at least a supporting analysis to provide reassurance that comparisons made on event free survival time were robust and may be particularly useful in situations where differential visit structures may arise, as might be the case when comparing a novel oral agent with chemotherapy.  

## Bicalutamide 50mg+LHRHa vs. flutamide+LHRHa in 1st line PCa (trial US0001)

- Time to progression (yrs)

- Proportion progression-free

- Bicalutamide 50mg+LHRHa vs. flutamide+LHRHa in 1st line PCa (trial US0001)

- +++  = bicalutamide 50mg+LHRHa+++  = flutamide+LHRHa

- Schellhammer PF, Sharifi R, Block NL et al. Br J Urol 1997; 80 (Suppl 2): 278.

**Notes:**
As I promised, here are the KM curves for PFS of Casodex 50mg in combination with LHRHa  vs. flutamide+LHRHA in the treatment of D2 disease.  

As you can see the regular analyses of PFS time by the log rank gave a HR of 0.87 with CI which met the protocol criteria for NI. 

##  Overall event count analysis provides similar results compared to conventional PFS time, log rank analysis

- Follow-up time (months)

- Treatment effect and 95% CI

-  = Hazard ratio = Relative risk

-  Overall event count analysis provides similar results compared to conventional PFS time, log rank analysis

- Bicalutamide 50mg+LHRHa vs. flutamide+LHRHa in 1st line PCa

- Close match between approachesthroughout the follow-up period

**Notes:**
On this slide I compare an event count analyses with regular log rank analyses of these data.

Again, this slide is a little complex, so I’ll just take you through it: 

The open blue circles show the HR and 95% CI for the analysis of PFS times for increasing lengths of follow-up.   The solid red circles show the corresponding analysis, based on just the event count over the same follow-up period. 

So, for example, if we were to compare treatments over the first 9 months of follow-up, we can see that both the regular log rank analysis of PFS time and the simpler event count analysis based on just the number of events occurring over the first 9 months yield virtually identical results.

As you can see, and as you would predict mathematically, there is a close match between the two approach in this trial throughout the follow-up period. 

This, I think, is reassuring as it illustrates that analyses based on PFS time in this trial were robust and further suggests that a simplified approach to collection and analysis of event-free survival data may be possible in PCa trials

## Bicalutamide 150mg vs. placebo in early, 

- Time to progression (yrs)

- Proportion progression-free

- Wirth M, Tyrrell C, Wallace M et al. Urology 2001**58:**146-151

- +++  = bicalutamide 150mg+++  = placebo

- Bicalutamide 150mg vs. placebo in early,
- non-metastatic PCa (trial 0024)

**Notes:**
In terms of an example in EPC, here are the KM curves for PFS in the EU Casodex EPC trial.

##  Overall event count analysis provides similar results compared to conventional PFS time, log rank analysis

- Treatment effect and 95% CI

-  = Hazard ratio = Relative risk

-  Overall event count analysis provides similar results compared to conventional PFS time, log rank analysis

- Bicalutamide 150mg vs. placebo in early, non-metastatic PCa

**Notes:**
As you can see, and as you would expect, there is again a close match between the regular log rank approach and the event count approach in this trial also. 

So, that’s all I wanted to say on approaches to the analysis of event –free survival data.

Turning finally now to summary and conclusions,...

## Summary and Conclusions

- PFS and overall survival therefore can no longer serve as primary trial endpoints in EPC trials.
- Hormonal therapies prescribed on or before a PSA rise, prevent observation of objective progression outcomes and complicate survival as an endpoint.
- Today, only trials with endpoints that reflect clinical practice are feasible.
- Disease progression survival including the initiation of further PCa therapy.
- PSA-D as a surrogate.
- PSA-D free survival can be used as the primary endpoint in early prostate cancer trials.

**Notes:**
.... the experience we have gained in the EPC program  indicates that objective progression, in terms of progression as evidence on imaging, and also OS cannot sensibly serve as trial endpoints in trials of early PCa. 

As highlighted by Keloff and co-workers in clinical cancer research just this month, quite apart from the long natural history of the disease and the consequent impact on clinical trial size and duration, current world-wide practice means that highly effective hormonal therapies are regularly prescribed on a PSA rise, preventing observation of endpoints such as objective progression and, thus, complicating survival.

Therefore, in light of current practice and patient sensitivity to PSA, as we go forward from here, only trials with endpoints that reflect clinical practice will be feasible and meaningful.  

Fortunately, data from the EPC program support the ideas offered by Dr D’Amico and suggest that PSA-D free-survival can be employed as a surrogate endpoint in early PCa, with a large treatment effect on PSA-D free-survival predicting for a positive treatment effect on objective PFS.

I’d like to finish by noting that failure to embrace alternative endpoints and recognise the consequences of current practice on traditional endpoints will, I fear, essentially render early PCa a no-go disease area, as researchers will likely consider the area futile since the required endpoints will be unattainable and trials that pursue them will lack the sensitivity to detect beneficial therapeutic advances in patient care. 

That concludes my presentation – I’d like to thank you for your time and attention. I’d be happy to take any questions at this time.