# Presentation: 710849

## Colorectal Cancer Endpoints WorkshopNovember 12, 2003

**A Case for Time to Tumor Progression as a Clinical Benefit Endpoint in the First-line Therapy of Metastatic Colorectal Cancer**

*Langdon L Miller, MD**	**	**Chief Medical Officer*
*PTC Therapeutics*

*Gary L Elfring, MS*
*Statistical Consultant*
*Pfizer Corporation*

**Notes:**
Good morning.  It is a pleasure for me to be here today to make an unabashed case for time to tumor progression as a clinical benefit endpoint in the first-line therapy of metastatic colorectal cancer.   My name is Langdon Miller.  While I am now at PTC Therapeutics, I was formerly with Pharmacia/Pfizer, where I worked closely with Gary Elfring in the design, conduct, and analysis of trials of irinotecan as therapy for metastatic colorectal cancer. 

## Acknowledgements

**Pfizer Corporation**

- Sumant Ramachandra, MDGroup LeaderUS Medical Oncology

- Gabriela Gruia, MD Full-Development Team Leader Camptosar®

**Notes:**
We would like to acknowledge the continued assistance of Pfizer -- in particular, Doctors Sumant Ramachandra and Gabriela Gruia -- in endorsing use of Pfizer data in support of this presentation. 

## Premise (1)

- An objective, non-survival clinical benefit endpoint is needed as the basis for full regulatory approval of new therapies for metastatic colorectal cancer

**Notes:**
The initial premise of our talk is that an objective, non-survival clinical benefit endpoint is needed as the basis for full regulatory approval of new therapies for metastatic colorectal cancer. 

## Why the Need Now?

**Notes:**
A critical question is... Why the need for a new endpoint now?

## An Increasing Number of Treatments Has Added Therapeutic Complexity 

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**Drugs Available**

**Cituximab (Erbitux)***

**Bevacizumab (Avastin)***

**Oxaliplatin (Eloxatin)**

**Capecitabine (Xeloda)**

**Irinotecan/CPT-11 (Camptosar)**

**Leucovorin (Leucovorin)**

**5-fluorouracil (Adrucil)**

***Not yet FDA approved**

**Notes:**
The short answer is that a rapidly increasing number of efficacious therapies has added therapeutic complexity in a disease that had languished for decades with only one treatment, 5-FU. 

## An Increasing Number of TherapiesHas Prolonged Survival 

**An Increasing Number of Therapies****Has Prolonged Survival **

******13 mo**

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**5-FU/LV (capecitabine)**

**5-FU/LV (capecitabine)**

**CPT-11**

**5-FU/LV (capecitabine)**

**CPT-11**

**Oxaliplatin**

**FDA-Approved Therapies**

**Median Survival**

******16 mo**

******19 mo**

**Saltz LB *****et al*****. *****Proc Amer Soc Clin Oncol***** 19:#938, 2000; ****Tournigand C *****et al.  Proc Amer Soc Clin Oncol *****20:#494, 2001****Grothey A***** et al. Proc Amer Soc Clin Oncol *****20:#496, 2001; Goldberg RM *****et al. Proc Amer Soc Clin Oncol *****22:#1009, 2003**

**Notes:**
This success in adding new therapies has prolonged survival from a median of 12-13 months with 5-FU/leucovorin or capecitabine alone, to approximately 16 months with CPT-11/5-FU/LV, to over 19 months with combinations and sequences of 5-FU/leucovorin, CPT-11, and oxaliplatin. 

## Multiple Therapies 

- Confound relationship between early tumor control effects and long-term survival effects

- Disconnect early tumor control effects and long-term survival effects
- Reduce likelihood that survival benefit will be seen

**Notes:**
However, from a clinical trials design perspective, this success with multiple therapies has served to confound the relationship between early tumor control effects and long-term survival effects,  disconnect early tumor control and long-term survival, and  reduce the likelihood that further survival benefit will be seen. 

## Subsequent Therapies Confound Relationship Between Early Tumor Control and Overall Survival

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**Time (mo)**

**Alternative Therapy (C)**

**Subsequent Therapies Confound ****Relationship Between Early Tumor Control ****and Overall Survival**

**Treatments**

***Is B inefficacious?***

***Is A+B more ******efficacious than A+C?***

**Notes:**
Let’s examine how subsequent therapies might confound the relationship between early tumor control and overall survival.  
 Consider a standard therapy A to which a new therapy B is added,  inducing a 3-month improvement in time to tumor progression and a  coordinate 3-month improvement in survival.  In the absence of any second-line treatments, a clear change in both tumor control and survival is evident.
 Now consider the same situation but with a forced crossover in the A-only arm to second-line therapy with B.  No survival advantage is now observed.  Based on the survival results, do we conclude that treatment B is inefficacious?
In a third scenarios, consider a situation where a standard combination A+C is compared to a standard combination of A+B.  However, only patients on the A+B arm have access to second-line therapy C.  In this circumstance, prolonged survival is seen in the A+B-followed-by-C arm.  Do we conclude that therapy B is more efficacious than therapy C? While these situations may seem contrived, each has actually happened in the history of recent drug development in metastatic colorectal cancer. 

## Subsequent Therapies Disconnect Early Tumor Control and Long-Term Survival

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**Subsequent Therapies Disconnect Early Tumor Control and Long-Term Survival**

**Notes:**
Let’s also examine how subsequent therapies might disconnect early tumor control effects from long-term survival benefits.  
 Consider our baseline standard therapy A to which a new therapy B is added,  once again inducing the expected 3-month improvement in time to tumor progression.   After a 9-month period with palliative treatment only,  a coordinate 3-month improvement in survival is observed,  resulting in an inverse hazard ratio of 1.23.
 Now consider the same 3-month improvement in early tumor control followed by treatment with multiple sequential second-line therapies in both arms of the study,  extending the median subsequent survival time to 21 and 24 months.  In this case, assuming the first-line tumor control benefit actually extended to a survival increase 18 months later, the inverse hazard ratio is only 1.14.  

## Prolonged Survival

- Increases sample sizes
- Prolongs accrual time
- Delays time until final analysis
- Increases costs

**Notes:**
When planning new trials, these prolonged survivals serve to increase sample sizes, prolong accrual time, delay time until final analysis and increase costs. 

## Sample Size Requirements for a Study Increase

| TherapeuticPlatform |  | Median Survival (mo) |  |  |  | Required Sample Size* |
| --- | --- | --- | --- | --- | --- | --- |
|  |  | PlatformAlone |  | Platform+Investigational  |  |  |
| 5-FU/LV  No therapy |  | 13 |  | 16 |  | 1100 |
| CPT-11/5-FU/LV  No therapy |  | 16 |  | 19 |  | 1600 |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 19 |  | 22 |  | 2200 |
| *Assumes 2-sided =0.05; =0.20; accrual = 100 patients/mo; follow-up = largest hypothesized median + 4 months |  |  |  |  |  |  |

- Superiority Survival Study

**Notes:**
What are the sample size requirements for a superiority survival study?
Lets assume a reasonable statistical design and aggressive patient accrual, and  current baseline therapeutic platforms of 5-FU/LV alone, CPT-11/5-FU/LV, or CPT-11/5-FU/LV followed by second-line oxaliplatin/5-FU/LV.
 Approximate median survivals with the platform therapy alone are either 13, 16, or 19 months.  With the addition of a new investigational therapy, we hope to increase these medians to 16, 19, or 22 months, respectively. 
 As you can see, increases in expected survival times force substantial increases in sample size. 

## Sample Size Requirements for a Study Increase

| TherapeuticPlatform |  | Median Survival (mo) |  |  |  | Required Sample Size* |
| --- | --- | --- | --- | --- | --- | --- |
|  |  | Existing |  | Investigational  |  |  |
| 5-FU/LV  No therapy |  | 13 |  | 11.5 |  | 2600 |
| CPT-11/5-FU/LV  No therapy |  | 16 |  | 14.5 |  | 4000 |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 19 |  | 17.5 |  | 5700 |
| *Assumes retention of 50% of survival benefit relative to prior therapy,1-sided =0.025; =0.20; accrual = 100 patients/mo; follow-up = longest hypothesized median + 4 months |  |  |  |  |  |  |

- Non-inferiority Survival Study

**Notes:**
For a non-inferiority survival study using the same therapeutic platforms, the situation becomes even more extreme.  In this example, we assume a desire to retain 50% of the survival benefit associated with the prior therapy. 
 Sample sizes in these circumstances become absolutely extraordinary, with populations that are bigger than almost any single study every conducted in colorectal cancer.  

## Time to Accrue Sufficient Number of Patients Increases

| TherapeuticPlatform |  | Sample Size |  |  |  | Time to Accrue (mo) |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
|  |  | Superiority |  | Non-inferiority  |  | Superiority |  | Non-inferiority  |
| 5-FU/LV  No therapy |  | 1100 |  | 2600 |  | 11 |  | 26 |
| CPT-11/5-FU/LV  No therapy |  | 1600 |  | 4000 |  | 16 |  | 40 |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 2100 |  | 5700 |  | 21 |  | 57 |
| *Assumes accrual = 100 patients/mo |  |  |  |  |  |  |  |  |

- Survival Study

**Notes:**
When considering these same sample sizes for superiority and non-inferiority studies side-by-side,  accrual times become substantial... 

## Time to Acquisition of Mature Data is Prolonged

| ExistingTherapy |  | Number of Events* |  |  |  | Time to Analysis (mo) |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
|  |  | Superiority |  | Non-inferiority  |  | Superiority |  | Non-inferiority  |
| 5-FU/LV  No therapy |  | 728 |  | 2062 |  | 31 |  | 43 |
| CPT-11/5-FU/LV  No therapy |  | 1076 |  | 3212 |  | 39 |  | 60 |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 1448 |  | 4726 |  | 47 |  | 80 |
| *Based on assumptions from prior slides |  |  |  |  |  |  |  |  |

- Survival Study

**Notes:**
... and time to analysis  becomes even more protracted,  with superiority studies extending to almost 4 years and  non-inferiority studies going out to an incredible length of more than 6 years. 

## Cost to Conduct A Study Increases

| ExistingTherapy |  | Sample Size |  |  |  | Trial Cost* |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
|  |  | Superiority |  | Non-inferiority  |  | Superiority |  | Non-inferiority  |
| 5-FU/LV  No therapy |  | 1100 |  | 2600 |  | $44M |  | $104M |
| CPT-11/5-FU/LV  No therapy |  | 1600 |  | 4000 |  | $64M |  | $160M |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 2200 |  | 5700 |  | $88M |  | $228M |
| *Assumes fully loaded internal and external costs of  $40,000/patient |  |  |  |  |  |  |  |  |

- Survival Study

**Notes:**
Based on fairly standard expenses of $40,000 per patient, total costs for future survival studies could reach stratospheric heights. 

## Implications for Evaluation of Survival as the Primary Measure of Clinical Benefit

- Value of survival as an endpoint is reduced

- Development in colorectal cancer takes on added risk, time, and expense
- Conduct of noninferiority studies or multiple studies becomes impractical
- NDA submissions are delayed
- Antitumor therapies may not be studied

**Notes:**
What are the implications of evaluation of survival as the primary measure of clinical benefit in the first-line therapy of metastatic colorectal cancer?
 Clearly, the value of survival as an endpoint is reduced;  development in colorectal cancer takes on added risk, time, and expense; the conduct of noninferiority studies or multiple studies becomes impractical; regulatory submissions are delayed;  and there is the prospect that active antitumor therapies are not definitively studied. 

## Why Not Evaluate Symptom Control Instead?

**Notes:**
So..., why not evaluate symptom control instead? 

## Issues with Symptom Control

- Symptom severity is subjective

- Disparate types of symptoms in metastatic colorectal cancer complicate interpretation
- Fatigue vs pain vs anorexia vs dyspnea vs ascites
- Symptoms are not uniformly present at diagnosis and are often not severe
- Treatment and disease may induce the same symptoms (eg, nausea, diarrhea)
- Relevant symptoms may be missed

**Notes:**
As we are all aware, there are many issues with symptom control as an endpoint.  
 Obviously, symptom severity is subjective.  Moreover, disparate types of symptoms in metastatic colorectal cancer complicate interpretation; what are the relative detriments associated with symptoms such as fatigue, pain, anorexia, dyspnea, or ascites?
Of course, symptoms are not uniformly present at diagnosis and are often not severe,  treatment and disease may induce the same symptoms, and  relevant symptoms may be missed. 

## Baseline Symptoms in Patients with Untreated Metastatic Colorectal Cancer

| Baseline Symptom* |  | % of Patients(N=849) | AverageSymptom Score(Max 100) |
| --- | --- | --- | --- |
| Fatigue  |  | 86 | 35 |
| Physical dysfunction |  | 64 | 31 |
| Pain |  | 54 | 20 |
| Appetite Loss |  | 38 | 18 |
| Dyspnea |  | 34 | 15 |
| Nausea/Vomiting |  | 28 | 9 |
| Diarrhea |  | 37 | 15 |
| Abdominal swelling |  | Not collected | Not collected |
|  |  |  |  |

**Baseline Symptoms in Patients with Untreated Metastatic Colorectal Cancer**

**Notes:**
These issues are exemplified by the baseline symptoms recorded on the EORTC QLQ C-30 quality-of-life instrument in the Saltz and Douillard registration studies.  Disparate symptoms are seen.  Specific symptoms are observed in varying proportions of patients.  Complaints are generally not severe.  Certain symptoms can be induced by therapy as well as disease, and,  in the case of abdominal swelling due to ascites -- are not collected by use of this particular quality-of-life instrument at all. 

## Issues with Symptom Control

- Instruments may be insensitive to important changes in tumor size

**Notes:**
A further concern is that symptom collection instruments may not be sensitive to important changes in tumor size. 

## Subjective Measures of Quality of Life May Not Change Despite Objective Tumor Shrinkage

**Notes:**
In the Saltz and Douillard studies, highly significant improvements in objective response rate resulted from the addition of CPT-11 to 5-FU/LV.  However, in both studies, treatment and control patients had only minor non-significant patterns of change in global quality of life. 

## Issues with Symptom Control

- Symptom progression analyses are often not useful because symptom progression usually occurs after tumor progression (when patient is off study)

**Notes:**
The remaining prospect, to look at time to symptom progression, is often not useful since symptom progression usually occurs after tumor progression. 

## Weight Loss Most Often Occurs after Tumor Progression

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**Weight Loss ********5%**

**Time to Tumor Progression**

**Weight Loss Most Often Occurs ****after Tumor Progression**

***Definitive weight loss (last time weight was <5% from baseline)****Data from Saltz *****et al*****. *****N Engl J Med *****343:905, 2000 and Douillard *****et al*****. *****Lancet *****355:1041, 2000**

- N=1015

**Notes:**
If it it observed at all, time to weight loss >5% occurs substantially later than tumor progression in most patients. 

## Declines in Functional Scores Most Often Occur After Tumor Progression

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**Physical Functioning**

**Emotional Functioning**

**Time to Tumor Progression**

***Definitive EORTC QLQ C-30 score worsening (last time score was no worse than baseline)****Data from Saltz *****et al*****. *****N Engl J Med *****343:905, 2000 and Douillard *****et al*****. *****Lancet *****355:1041, 2000**

**Declines in Functional Scores ****Most Often Occur After Tumor Progression**

- N800

**Notes:**
The same is true for declines in EORTC QLQ C-30 functional scores... 

## Declines in Symptom Scores  Most Often Occur After Tumor Progression

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**Fatigue**

**Declines in Symptom Scores **** Most Often Occur After Tumor Progression**

***Definitive EORTC QLQ C-30 score worsening (last time score was no worse than baseline)****Data from Saltz *****et al*****. *****N Engl J Med *****343:905, 2000 and Douillard *****et al*****. *****Lancet *****355:1041, 2000**

- N800

**Notes:**
...and declines in EORTC QLQ C-30 symptom scores. 

## Symptom Progression When Patient is Off Study and is Receiving Second-Line Therapy Confounds Interpretation of Results

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**CT scans **

- Oxali/5-FU/LV

**Months**

**Symptom Progression When Patient is Off Study and is Receiving Second-Line Therapy Confounds Interpretation of Results**

**Notes:**
This situation clearly poses a serious analysis problem.  How would we interpret time to symptom progression results in a patient who  discontinues first-due therapy to tumor progression at 6 months and, assuming we were even still following symptoms,  has symptom progression several months later when the patient is off study and is receiving active second-line therapy?

## Implications for Evaluation of Symptoms as the Primary Measure of Clinical Benefit

- Problems with complexity, subjectivity, reliability, and interpretability make study design and analysis difficult

- Development in colorectal cancer takes on added risk and expense
- Antitumor therapies may not be studied

**Notes:**
Use of symptoms as the primary measure of clinical benefit creates problems with complexity, subjectivity, reliability, and interpretability -- all making study design and analysis difficult.  Relying on symptom control adds risk and expense to development in colorectal cancer and  again creates the risk that active antitumor therapies will not be studied.
What’s the solution...? 

## Premise (2)

- Time to tumor progression (TTP) offers an objective, reliable, and practical alternative to survival and symptom-control endpoints

- *	Time from randomization to the first of either objective tumor progression or death (where tumor progression is a >20% increase in sum of longest dimensions of measured tumors from nadir or the appearance of 1 new tumor [RECIST])

**Notes:**
We would put forward the premise that time to tumor progression (or TTP) offers an objective, reliable, and practical alternative to survival and symptom control endpoints.

## Why Consider TTP as an Endpoint?

**Notes:**
Why consider TTP as an endpoint...?

## Time to Tumor Progression

- Represents the most common cause of treatment failure

- Incorporates the value of time
- Offers direct assessment of disease burden that logically correlates with symptom progression and survival

**Notes:**
Time to tumor progression progression represents the most common cause of treatment failure,  it incorporates the value of time and  it offers a direct assessment of disease burden that logically correlates with symptom progression and survival. 

## Tumor Progression is the Most Common Cause of Treatment Failure in Patients with Metastatic Colorectal Cancer

| Reason for Treatment Discontinuation | % of Patients(N=1001) |
| --- | --- |
| Tumor Progression  | 70 |
| Patient Request | 10 |
| Adverse Events |   8 |
| On-Treatment Death |   4 |
| Other |   4 |
| Improvement |   3 |
| Noncompliance/lost to follow-up |   1 |

**Tumor Progression is the Most Common Cause of Treatment Failure in Patients ****with Metastatic Colorectal Cancer**

**Notes:**
When considering the reasons for treatment discontinuation in over 1000 patients receiving first-line therapy for metastatic colorectal cancer, tumor progression was clearly the most common cause for cessation of therapy. 

## By Incorporating the Value of Time, TTP Better Categorizes Tumor Control Than Response Rate

**By Incorporating the Value of Time, TTP Better Categorizes Tumor Control ****Than Response Rate**

**Notes:**
By incorporating the value of time, TTP better categorized tumor control than response rate.  With both TTP and response rate, failure is clearly assigned to a patient who experiences immediate tumor progression.  However, what is is the benefit implication for a patient who experiences a tumor response but then rapid progression within 18 weeks of study initiation?  By contrast, consider the benefit accrued by a patient who has only a minor reduction in tumor burden but one that persists for 1 year from the time of going on study. 

## It’s Only Logical That Halting Tumor Progression is Clinically Beneficial

**It’s Only Logical That Halting Tumor Progression is Clinically Beneficial**

- Healthy

**Notes:**
Finally -- let’s face it -- it’s only logical that halting tumor progression is clinically beneficial. Consider the extremes in cancer burden over time from healthy to adenoma to primary cancer diagnosis to metastatic carcinoma...

## It’s Only Logical That Halting Tumor Progression is Clinically Beneficial

**It’s Only Logical That Halting Tumor Progression is Clinically Beneficial**

- Healthy

*Symptoms*	None	None	Fatigue,	Fatigue, anorexia			 obstruction 	pain, dyspnea, DVT				ascites, obstruction

*Survival*	Decades	Decade	Years	Months

**Notes:**
It is incontrovertible that more neoplasia means more chance for symptoms.
It is also incontrovertible that more neoplasia adversely affects the probability of protracted survival.
However, for those who still might be skeptics... 

## Time to Tumor Progression

- Correlates with survival in metastatic colorectal cancer

**Notes:**
...the fact is that time to tumor progression actually does correlate with survival in metastatic colorectal cancer.

## Changes in Median Endpoint Values Suggest that TTP Appears to Correlate with Survival

**Changes in Median Endpoint Values Suggest that TTP Appears to Correlate with Survival**

**Data from Saltz *****et al*****. *****N Engl J Med *****343:905, 2000 and Douillard *****et al*****. *****Lancet *****355:1041, 2000**

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**5-FU/LV**

**CPT-11/5-FU/LV**

**13**

**16**

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**9**

**CPT-11**

**13**

- N=1068

**Notes:**
This seems to be evident from changes in median endpoint values in the Saltz and Douillard registration study experience. If we try to derive a simple linear algebraic equation for the relationship between survival and TTP, the correspondence between the increase in TTP and the increase in survival provides information about a potential slope (a),  while the 9-month fixed post-therapy survival time provides information regarding a likely y intercept (b).   
Based on these observations, we might hypothesize that... 

## Changes in Median Endpoint Values Suggest Hypothetical Equation Correlating TTP with Survival

**Changes in Median Endpoint Values Suggest Hypothetical Equation Correlating TTP with Survival**

**Data from Saltz *****et al*****. *****N Engl J Med *****343:905, 2000 and Douillard *****et al*****. *****Lancet *****355:1041, 2000**

**Notes:**
Survival equals one times TTP plus 9 months.

## Both Hypothetical and Actual Equation Correlate TTP with Survival

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**Survival (mo)**

**Data from Saltz *****et al*****. *****N Engl J Med *****343:905, 2000 and Douillard *****et al*****. *****Lancet *****355:1041, 2000**

**Notes:**
Plotted, our hypothetical equation looks like this. When the equation based on the data from the 1068 patients enrolled to the Saltz and Douillard studies is plotted, the actual equation is very close to the hypothetical one, confirming a near 1-to-1 correlation between increases in TTP with increases in survival -- plus approximately 8 months of post-TTP survival time. 

## One-One TTP-Survival Relationship is Constant Independent of Treatment, Performance Status, or LDH

| Factor | Value  | Slope | Intercept |
| --- | --- | --- | --- |
| Overall | All | 1.2 | 8.3 |
| Treatment | CPT-11
5-FU/LV
CPT-11/5-FU/LV | 1.1
1.2
1.2 | 8.7
8.2
8.1 |
| PS | 0 
1
2 | 0.9
1.2
1.3 | 11.8    
7.2
3.1 |
| LDH | UNL
>UNL | 1.0
1.3 | 11.2
6.1 |
| *UNL=upper normal limit  |  |  |  |

**Data from Saltz *****et al*****. *****N Engl J Med *****343:905, 2000 and Douillard *****et al*****. *****Lancet *****355:1041, 2000**

**Notes:**
Of note, in this experience, the 1-to-1 correlation between TTP and survival is preserved across treatment groups and when important prognostic variables are considered.  Of interest, the post-TTP survival time is also preserved across treatment groups,  but is altered by factors such as performance status and baseline LDH. 

## TTP Correlation with Survival

**TTP Correlation with Survival**

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**0-9**

**n=321**

**9-15**

**n=170**

**15-21**

**n=135**

**21-27**

**n=116**

**27-33**

**n=73**

**33-39**

**n=96**

**39-51**

**n=99**

**>51**

**n=58**

**TTP (wks)**

**Median Survival (mo) ******** 95% CI **

- N=1068

**Notes:**
When grouped by the approximately 6-week intervals in which tumor measurements were collected , the graphical correlation between TTP and survival is quite striking. 

## TTP is Highly Correlated with Survival in Cox Regression Analysis

| Factor |  | Value | Hazard Ratio | 2 | p-value |
| --- | --- | --- | --- | --- | --- |
| TTP | <6 mo vs 6 mo |  | 0.31 [0.26-0.37] | 157 | <0.0001 |
| PS | 0 vs 1 |  | 0.47[0.40-0.55] | 109 | <0.0001 |
| LDH | UNL vs >UNL |  | 0.51
[0.44-0.60] | 97 | <0.0001 |
| *UNL=upper normal limit |  |  |  |  |  |

**Data from Saltz *****et al*****. *****N Engl J Med *****343:905, 2000 and Douillard *****et al*****. *****Lancet *****355:1041, 2000**

**Notes:**
Testing of the TTP-survival correlation in a Cox regression analysis along with important prognostic factors of baseline performance status and LDH indicates that TTP is highly prognostic for survival within the population as whole. 

## Results Are Corroborated by a Publication Analysis of Correlation Between TTP and Survival*

| Output | Input  | Slope | Intercept | r† | p† |
| --- | --- | --- | --- | --- | --- |
| Survival(mo) | TTP(mo) | 0.68 | 8.74 | 0.481 | <0.0001 |
| *Includes published summary data from 29 phase III studies in 13,500 patients receiving first-line therapy (5-FU, 5-FU/LV, CPT-11, CPT-11/5-FU/LV, oxaliplatin/5-FU/LV) for metastatic colorectal cancer , with studies reported in years 1990 through 2000 |  |  |  |  |  |
| † Spearman  correlation coefficients/tests |  |  |  |  |  |

**Louvet C *****et al. ***** *****Cancer***** 91:2033, 2000**

**Notes:**
Of interest, these results are corroborated by a publication analysis of the correlation between TTP and survival in which a slope of 0.68 and an 8.74-month y intercept were documented and a highly significant correlation was described. 

## Time to Tumor Progression

- Provides a direct reflection of drug activity

- Is not confounded by subsequent (eg, 2nd-line) therapies
- Offers utility as an endpoint in non-inferiority trials

**Notes:**
Time to tumor progression also has advantages in that it provides a direct reflection of drug activity, is not confounded by subsequent therapies, and, as a consequence, offers utility as an endpoint in non-inferiority trials. 

## TTP Provides an Accurate and Direct Reflection of Drug Activity, Unaffected by Subsequent Therapies

**4**

**4**

**4**

**7**

**7**

**7**

**3**

**3**

**9**

**9**

**9**

**9**

**9**

**9**

**3**

**0**

**5**

**10**

**15**

**20**

**25**

**30**

**A**

**A+B**

**A********B**

** ****A+B**

**A+C**

**A+B********C**

**Treatments**

**Time (mo)**

**Alternative Therapy (C)**

**Tumor Control HR = 1.75****Survival HR = 1.23**

**Tumor Control HR = 1.00****Survival HR = 1.14**

**13**

**16**

**16**

**TTP Provides an Accurate and Direct Reflection of Drug Activity, ****Unaffected by Subsequent Therapies**

**Tumor Control HR = 1.75****Survival HR = 1.00**

**16**

**16**

**19**

**7**

**Notes:**
If we reconsider the various scenarios that we reviewed earlier, evaluating TTP provides an accurate and direct reflection of drug activity, unaffected by subsequent therapies.  In both of the first two situations, TTP analysis clearly tells us that A+B is more efficacious than A alone.  In the last situation, TTP analysis clearly tells us that A+B has similar efficacy to that of A+C. 

## Reduces sample sizes
Shortens accrual time
Speeds time until final analysis
Decrease costs
Makes first-line development in colorectal cancer practical

- Shortens accrual time
- Speeds time until final analysis
- Decrease costs
- Makes first-line development in colorectal cancer practical

**Time to Tumor Progression**

**Notes:**
Relative to survival, use of time to tumor progression as an endpoint reduces sample sizes, shortens accrual time, speeds time until final analysis, decreases costs, and makes first-line development in colorectal cancer practical. 

## Sample Size Requirements for a Study

| TherapeuticPlatform |  | Median TTP (mo) |  |  |  | Required Sample Size* |
| --- | --- | --- | --- | --- | --- | --- |
|  |  | PlatformAlone |  | Platform+Investigational  |  |  |
| 5-FU/LV  No therapy |  | 4 |  | 7 |  | 150 |
| CPT-11/5-FU/LV  No therapy |  | 7 |  | 10 |  | 400 |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 7 |  | 10 |  | 400 |
| *Assumes 2-sided =0.05; =0.20; accrual = 100 patients/mo; follow-up = longest median + 2 months |  |  |  |  |  |  |

- Superiority TTP Study

**Notes:**
In hypothetical superiority TTP studies of a new agent in combination with registered therapeutic platforms,  required sample sizes are quite reasonable.  Of note, because TTP evaluates only first-line therapy effects, the addition of oxaliplatin/5-FU/LV as second-line treatment does not adversely alter sample size. 

## Sample Size Requirements for a Study

| TherapeuticPlatform |  | Median TTP (mo) |  |  |  | Required Sample Size* |
| --- | --- | --- | --- | --- | --- | --- |
|  |  | Existing |  | Investigational  |  |  |
| 5-FU/LV  No therapy |  | 4 |  | 2.5 |  | 200 |
| CPT-11/5-FU/LV  No therapy |  | 7 |  | 5.5 |  | 750 |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 7 |  | 5.5 |  | 750 |
| *Assumes retention of 50% of survival benefit relative to prior therapy,1-sided =0.025; =0.20; accrual = 100 patients/mo; follow-up = longest median + 2 months |  |  |  |  |  |  |

- Non-inferiority TTP Study

**Notes:**
In similar non-inferiority hypothetical TTP studies, required sample sizes are quite approachable.  Again, it is notable that because TTP evaluates only first-line therapy effects, the addition of oxaliplatin/5-FU/LV as second-line treatment does not increase the sample size. 

## Time to Accrue Sufficient Number of Patients

| TherapeuticPlatform |  | Sample Size |  |  |  | Time to Accrue (mo) |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
|  |  | Superiority |  | Non-inferiority  |  | Superiority |  | Non-inferiority  |
| 5-FU/LV  No therapy |  | 150 |  | 200 |  | 1.5 |  | 2.0 |
| CPT-11/5-FU/LV  No therapy |  | 400 |  | 750 |  | 4.0 |  | 7.5 |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 400 |  | 750 |  | 4.0 |  | 7.5 |
| *Assumes accrual = 100 patients/mo |  |  |  |  |  |  |  |  |

- TTP Study

**Notes:**
The more modest sample sizes have a salutary impact on accrual times. 

## Time to Acquisition of Mature Data

| ExistingTherapy |  | Number of Events |  |  |  | Time to Analysis (mo) |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
|  |  | Superiority |  | Non-inferiority  |  | Superiority |  | Non-inferiority  |
| 5-FU/LV  No therapy |  | 102 |  | 112 |  | 10.5 |  | 8.0 |
| CPT-11/5-FU/LV  No therapy |  | 250 |  | 426 |  | 16.0 |  | 16.5 |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 250 |  | 426 |  | 16.0 |  | 16.5 |
| *Based on assumptions from prior slides |  |  |  |  |  |  |  |  |

- TTP Study

**Notes:**
Time to acquisition of mature TTP data is quite manageable. 

## Cost to Conduct A Study

| ExistingTherapy |  | Sample Size |  |  |  | Trial Cost* |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
|  |  | Superiority |  | Non-inferiority  |  | Superiority |  | Non-inferiority  |
| 5-FU/LV  No therapy |  | 150 |  | 200 |  | $6M |  | $8M |
| CPT-11/5-FU/LV  No therapy |  | 400 |  | 750 |  | $16M |  | $30M |
| CPT-11/5-FU/LV  Oxali/5-FU/LV |  | 400 |  | 750 |  | $16M |  | $30M |
| *Assumes total fully loaded internal and external costs of $40,000/patient |  |  |  |  |  |  |  |  |

- TTP Study

**Notes:**
And trial costs remain in a rationale range. 

## Time to Tumor Progression

- Is based on simple, standardized, radiographic tumor measurement criteria

- Can be physically described and objectively quantified
- Is supported by data available in the primary patient record for FDA audit
- Can be subjected to central, uniform, blinded review

**Notes:**
What other, more functional characteristics favor use of TTP.  Of import,  it is based on simple, standardized, radiographic tumor measurement criteria,  it can be physically described and objectively quantified,  it is supported by data available in the primary patient record for FDA audit, and  it can be subjected to central, uniform, blinded review. 

## Tumor Measurement Criteria Have Been Standardized

**New Guidelines to Evaluate the ****Response to Treatment in Solid Tumors**
*P Therasse, SG Arbuck, EA Eisenhauer,**J Wanders, RS Kaplan, L Rubinstein, **J Verweij, M Van Glabbeke, AT van Oosterom, **MC Christian, SG Gwyther*
- Journal of the National Cancer Institute 92: 205-216, 2000

**TUMOR RESPONSE CRITERIA WORLD HEALTH ORGANIZATION****(WHO) **
**WHO Handbook for Reporting ****Results of Cancer Treatment**
** **
- World Health Organization Offset Publication No. 48Geneva, Switzerland, 1979
- ————————————————————————————
**Reporting Results of Cancer Treatment**
*AB Miller, B Hogestraeten, M Staquet, A Winkler*
- Cancer 47:207–14, 1981

**Tumor Measurement Criteria ****Have Been Standardized**

**Notes:**
Initially WHO and now RECIST guidelines for tumor measurement assessment have standardized time to progression determinations. 

## Tumor Measurements Can be Readily Described and Quantified

| Lesion | Longest Target Lesion Diameter (cm) |  |  |  |  |
| --- | --- | --- | --- | --- | --- |
|  | Baseline | Week 6 | Week 12 | Week 18 | Week 24 |
| Right lung #1 | 3 | 2 | 2 | 2 | 3 |
| Right lung #2 | 2.5 | 2 | 2 | 2 | 3 |
| Left liver lobe | 6 | 5 | 3 | 3 | 5 |
| Right liver lobe | 2.5 | 2 | 2 | 2 | 2 |
| Total Length | 14 | 11 | 9 | 9 | 13 |
| % Change |  | -21% | -36% | -36% | +44%* |
| Disease Status |  | SD | PR | PR | PD |
| *Change from nadir |  |  |  |  |  |

**Notes:**
In case report forms or tumor measurement flow sheets,  individual lesion dimensions can be described,  changes over time can be quantified,  total length and percentage changes can be recorded, and  clinician assessment of response status can be documented and verified. 

## Primary Data Can be Collected, Stored and Saved for Later Audit

**Notes:**
Obviously, primary radiographic data can be collected, stored, and saved for quality assurance audits... 

## Central, Independent, Blinded Radiographic Review Can Enhance Confidence in Results

**Central, Independent, Blinded Radiographic Review Can Enhance Confidence in Results**

**Notes:**
...and these films can be subjected to central independent, blinded radiographic review in order to enhance sponsor and investigator confidence in the validity of the results.

## Provides a clear method of presentation and interpretation

**Time to Tumor Progression**

- Offers straightforward analysis that incorporates all available data
- Can be supported by secondary analyses

**Notes:**
Further advantages to TTP include the fact that it provides a clear method of presentation and interpretation, that its analysis is straightforward and incorporates all available data, and that it can be supported by secondary analyses to strengthen understanding of the results. 

## Kaplan-Meier Plotting and Log-Rank Testing Allows Comprehensive Display and Analysis of All Available Data 

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**Months**

**Probability**

- p<0.001(log-rank test)

**Time To Tumor Progression**

- Median                                Median4.4 mo       		     6.7 mo

- CPT-11/5-FU/LV (N=198)

- 5-FU/LV (N=187)

**Douillard *****et al*****. *****Lancet *****355:1041, 2000**

**Notes:**
Kaplain-Meier plotting and log-rank testing permits comprehensive display and analysis of all available data. 

## Assessment of Time to Treatment Failure Allows Confirmatory Analysis of Treatment Effect and Any Censoring Issues 

**Assessment of Time to Treatment Failure Allows Confirmatory Analysis of ****Treatment Effect and Any Censoring Issues **

**Time To Tumor Progression**

**Time To Treatment Failure**

**Notes:**
Assessment of time to treatment failure can confirm the TTP treatment effect and assist in the understanding of any censoring issues that might arise out of unequal drop-outs due to adverse events across study arms. 

## Cox Regression Analysis PermitsConfirmatory Analysis of Treatment Effect in the Context of Important Prognostic Variables

-      Factor	         Value	[95% CI]	p-value
- LDH	 UNL vs >UNL 	0.59	0.0001
- 		[.49-.71]
- PS	0 vs  1	0.79 	0.0051 		[.67–.93]
- Treatment	CPT-11/5-FU/LV	0.62	0.0001
- 	  vs 5-FU/LV 	 [.53–.73]

***ULN=upper limit of normal**

**Cox Regression Analysis Permits****Confirmatory Analysis of Treatment Effect in the Context of Important Prognostic Variables**

**Saltz LB *****et al*****. *****Proc Amer Soc Clin Oncol***** 19:242a, 2000**** **

**Time To Tumor Progression**

**Notes:**
Finally, Cox regression analysis permits confirmation of the effect of treatment on TTP, allowing post-facto adjustment of any imbalances in baseline prognostic factors while providing hazard ratio information. 

## What Caveats Must be Considered in Assessing TTP?

**Notes:**
However, certain caveats must be considered in assessing  TTP. 

## Tumor assessment frequency should be the same across study arms even when cycles are of different lengths

**Time to Tumor Progression Measurement Considerations**

- Minimum interval between tumor assessments should be less than the expected treatment effect size

**Notes:**
It may seem evident, but it is best if the minimum interval between tumor assessments should be less than the expected treatment effect size.  Detecting an increase in tumor size of 3 months when scans are only obtained every 6 months poses an obvious problem.  
 A particularly important consideration is that tumor assessment frequency should be the same across study arms even when cycles are of different lengths  

## Unequal Tumor Assessment Intervals Between Study Arms Can Bias TTP Assessment

**1/1**

**1/1.5**

**1/2**

**1/2.5**

**1/3**

**7**

**8**

**9**

**10**

- Median TTP (mo)

- Tumor Assessment Intervals (mo)

***Based on 1000 simulations of studies with exponential TTP curves where true median for ****both Arm A and Arm B is 7 months, N=400 patients/arm, log-rank ********=0.0025 (0.25%)**

**Notes:**
As shown here, extremes in unequal tumor assessment intervals between study arms can bias TTP analysis.  When 2 treatments, A and B, both with the same TTP, are compared,  increasing disparity in tumor assessment intervals can produce an artifactual increase in TTP in one arm of the study.  In a thousand simulations under the study assumptions shown here, this increasing disparity is associated with an exponential increase in statistically significant false positives. 

## Plan for Uniform Tumor Assessment Frequency Despite Discordant Cycle Lengths 

**Plan for Uniform Tumor Assessment Frequency Despite Discordant Cycle Lengths **

**Notes:**
Can this be done in actual practice.  In fact, it can.  
In designing the Saltz registration study, we were faced with the problem that the Saltz regimen was given in 6-week cycles and CT scans were to be done at 6-week intervals for the first 24 weeks and then at 12-week intervals after Week 24.
As a consequence, in the Mayo Clinic 5-FU/LV control arm given in 4-week cycles, we were required to insert CT scan assessments in the middle of some initial cycles. 

## Actual Investigator Performance in Maintaining Tumor Assessment Frequency 

**Weeks from Prior Assessment**

**12 Wks**

**6  Wks**

**Weeks from Start of Treatment**

**12 Wks**

**6  Wks**

**Actual Investigator Performance in Maintaining Tumor Assessment Frequency **

- CPT-11/5-FU/LV

- 5-FU/LV

**Notes:**
Actual investigator performance was quite good across the two treatment arms.  Median scan frequency was 6 weeks through Week 30, and  then, as was planned in the protocol, rose to 12 weeks thereafter. 

## Conservative censoring rules should limit TTP to time on study therapy

**Time to Tumor Progression Measurement Considerations**

**Notes:**
Also a consideration is that conservative censoring rules should limit TTP to time on study therapy. 

## Conservative Censoring Rules

| Situation |  | Date | Censored |
| --- | --- | --- | --- |
| No baseline or on-treatment tumor assessment |  | Randomization | Yes |
| Treatment discontinuation for PD |  | Last on-study assessment | No |
| Treatment discontinuation for other than PD or death |  | Last on-study assessment without PD | Yes |
| New anticancer treatment started |  | Last on-study assessment before start of new treatment | Yes |
| Death before first PD assessment |  | Death | No |
| Death after 1 assessment but before PD |  | Last on-study assessment without PD | Yes |
| Patients still on treatment |  | Last on-study assessment without PD | Yes |

**Notes:**
Shown here just for information purposes is the standard set of censoring rules that should be considered in conducting a registration trial in order to take into account all clinical situations that are likely to influence TTP analysis.  

## Nonconservative Censoring Rule Includes 2nd-line Therapy and Potential Biases TTP

- 0

- 3

- 6

- 9

- 12

**Months**

- Therapy A

**Discontinuation due to adverse event**

- Therapy B

**CT scans **

**Notes:**
These rules are designed to avoid the problem shown here.  In this situation, a non-conservative censoring rule is applied to hypothetical data from a patient who discontinues first-line therapy due to an adverse event.  Assuming tumor assessments are even being done regularly during second-line therapy, it is obvious that the potential therapeutic effects of Therapy B are being inappropriately included in the determination of TTP as it relates to Therapy A.  

## Conservative Censoring Rule Confines TTP Determination to 1st-line Study Period 

- 0

- 3

- 6

- 9

- 12

- Therapy A

**CT scans **

**Discontinuation due to adverse event**

- Therapy B

**Months**

**Conservative Censoring Rule Confines TTP Determination to 1st-line Study Period **

**Notes:**
Applying the conservative censoring rules to this same patient, we see that TTP would be censored at a time when the patient was still known to be progression-free while on Therapy A, thus avoiding inappropriate inclusion of off-study data in the TTP determination.  

## Model of Potential Bias of TTP Due to Nonconservative Censoring Rule

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**Probability of Progression**

| Dropout rate (%) | 0 | 5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Median TTP | 5.4 | 5.6 | 6.2 | 6.8 | 7.1 | 7.4 | 7.6 | 8.0 | 8.2 | 8.4 | 8.6 |

**Model of Potential Bias of TTP Due to Nonconservative Censoring Rule**

**Simulated (100x) TTP curves created by adding 3-month follow-up intervals for various percentages (5% to 40%) of patients who discontinue therapy due to toxicity**

**Notes:**
Application of this rule is important to avoid bias that can result in artifactual prolongation of TTP.  As shown in this simulation, non-conservative censoring can lead to a perverse situation in which the higher the drop-out rate due to excessive toxicity, the better the TTP appears to be. 

Assumptions: Started with TTF curve from Saltz Study CPT-11/5-FU/LV arm. Added follow-up data for randomly selected percentages of patients, based on median TTP=7.0 mo.
Censoring at a follow-up visit is determined by where the patient is on the TTP curve at that time.so that patient who fails for toxicity at 2 month had a better chance of reaching 5 month than a patient who fails at 8 months has at reaching 11 month.  This method is meant to account for the cumulative nature of a cumulative toxicity.  Each curve represents 100 simulations.

## Summary

**Notes:**
In summary... 

## TTP Satisfies Critical Requirements as A Regulatory Clinical Benefit Endpoint

- Directly evaluates changes in disease burden
- Correlates with other outcomes (in particular, survival)
- Is not confounded by subsequent (eg, 2nd-line) therapies
- Offers utility as an endpoint in non-inferiority trials
- Can be objectively quantified, reviewed, and audited
- Offers clear interpretation and straightforward analysis
- Conserves patient resources and hastens development

***When Evaluated Properly, TTP:***

**Notes:**
TTP satisfies critical requirements as a regulatory clinical benefit endpoint. 
When evaluated properly, TTP:
 Directly evaluates changes in disease burden 
 Correlates with other outcomes (in particular, survival)
 Is not confounded by subsequent (eg, 2nd-line) therapies
 Offers utility as an endpoint in non-inferiority trials
 Can be objectively quantified, reviewed, and audited
 Offers clear interpretation and straightforward analysis
 Conserves patient resources and hastens development. 

## Survival Superiority Study Offers Too Little, Too Late, For Too Much

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**Probability**

******=0.05**
**1-********=0.80**
**2200 patients**
**4 years**
**$88M**

** ****19 mo           22 mo**

**Assumes accrual = 100 patients/mo; follow-up = largest median + 2 mo (TTP) or 4 mo (survival)**

**Survival Superiority Study ****Offers Too Little, Too Late, For Too Much**

***Survival***

**Notes:**
At this point in the history of metastatic colorectal cancer drug therapy, survival superiority studies offer too little, too, late and for too much in terms of patient and dollar resources...

## Single Superiority Study Can Offer Highly Robust TTP Assessment (=0.0025) 

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**Probability**

******=0.0025**
**1-********=0.90**
**800 patients**
**20 months**
**$32M**

***Survival***

***TTP***

**7 mo               10 mo**

******=0.05**
**1-********=0.80**
**2200 patients**
**4 years**
**$88M**

** ****19 mo           22 mo**

**Assumes accrual = 100 patients/mo; follow-up = largest median + 2 mo (TTP) or 4 mo (survival)**

**Single Superiority Study Can Offer Highly Robust TTP Assessment (********=0.0025) **

**Notes:**
...when a single superiority study can offer highly robust TTP assessment at an significance level of 0.0025, a power of 90% and with less than half of the expenditure in patient resources, time, and money.

## It’s Time to Move to TTP As the Primary Regulatory Endpoint in Metastatic Colorectal Cancer

**Conclusion **

**Notes:**
It’s really is time to move to TTP as the primary regulatory endpoint in metastatic colorectal cancer.