# Presentation: 930694

## Disease Free Survival vs Overall Survival as an endpoint for Adjuvant Colon Cancer Studies:  Data from Randomized Trials  

- Oncologic Drugs Advisory Committee
- May 5, 2004

- Daniel Sargent, PhD
- Mayo Clinic

## Disease-free survival versus overall survival

**Disease-free survival ****versus overall survival**

**Prolong life without disease =    QoL**

**1****Sargent et at, NEJM, 2001**

** ****85% of deaths within 8 years of **
**	****diagnosis are following recurrence****1**

## Hypothesis	

- Disease free survival (DFS), assessed after 3 years, is an appropriate endpoint to replace overall survival (OS) in adjuvant colon trials
- Would allow more rapid completion, reporting of trials
- Allow promising agents to benefit patients more quickly

## Methods

- Data from large randomized trials
- Individual patient data from all trials
- Compare DFS, OS for each arm
- Landmarks:  3 years for DFS, 5 years for OS
- Compare difference between ‘control’ and experimental arms
- Most important comparisons:  Hazard ratios

## Definitions

- Overall survival:  Time from randomization to death from any cause
- Disease Free Survival:  Time from randomization to the first of recurrence or death
- 2nd primaries not included as events

## Surrogate Endpoints

- Multiple methods proposed
- No agreed upon best practice
- Analyzed using multiple approaches
- Weighted linear regression
- Prentice/Freedman - proportion explained1,2
- Begg and Leung3
- Burzykowski, Buyse, et al4

- 1Prentice, Stat Med, 1989                  2Freedman et al, Stat Med, 19923Begg and Leung, JRSSA, 2000        4Burzykowski et al, JRSSC, 2001

- Total:  33 treatment arms

## Trial Characteristics

- 33 Arms
- 9 surgery alone control
- 24 ‘Active’ rx
- Median follow-up 8 years
- 5 yr data on 93% of patients
- Due to inconsistent long-term follow-up, all analyses censored at 8 years

## Patient Characteristics

- Age
- < 50:   2237 (17%)
- 50-59: 3487 (27%)
- 60-69: 5039 (39%)
- > 70:   2071 (16%)
- Treatment
- Surgery alone: 2454  (18%)
- Treatment:  11610 (82%)

- Gender
- M:  7568 (54%)
- F:   6496 (46%)
- Stage
- I:    210   (2%)
- II:   5137 (36%)
- III:  8714 (62%)

## Recurrence Rate by 6 mo intervals

**Recurrence Rate by 6 mo intervals**

## Time from Recurrence to Death

**Time from Recurrence to Death**

## Rate of Agreement

## 3 Year DFS vs 5 Year OS

## Results

- Regression equation:
- 5 yr OS= 0.03+0.94*3 yr DFS
- Statistically, cannot reject
- 5 yr OS = 3 yr DFS
- Largest difference 6%, 27 of 33 _<_ 3%

## Conclusion (1)

- On an patient by patient basis, 3 years seems reasonable
- Rate of recurrence
- Survival following recurrence
- Per patient concordance
- On an arm by arm basis:
- 3 yr DFS excellent predictor of 5 yr OS

## Assessment of treatment effect

- Does a comparison of arms using DFS reach the same conclusion as using OS?

## Within study comparisons:  Methods

- Attempted to mimic actual trial conduct
- At 3 years minimum follow-up, some pts on-study > 3 years
- Based on individual patient data, attempted to replicate analysis that would have been completed at 3, 5 yr time points
- Also performed analyses at 3 years median follow-up

## Hazard Ratios: DFS vs OS

## Results

- Regression equation:
- OS HR = 0.09 + 0.93 * DFS HR
- Cannot reject OS HR = DFS HR

## Proportion Explained

- Compare 2 Cox survival models
- One without ‘surrogate’, one with
- Examine ‘proportion’ of the treatment effect explained by the surrogate
- Values close to 100% suggest surrogacy
- Not a true proportion

- Prentice, Stat Med, 1989
- Freedman et al, Stat Med, 1992

## Proportion Explained

- Calculated proportion explained:
- 1 -  -0.051 / 0.133 = 138%
- Implies this may be a valid surrogate

## Trial, Individual level surrogacy

- Burzykowski et al (2001) define trial, individual surrogacy based on bivariate copula survival model
- Trial level R2 : Trial level concordance
- Individual level Per patient concordance
- Values close to 1 indicate good surrogacy for both measures

- Burzykowski et al, JRSSC, 2001

## Burzykowski et al

- Results:
- Trial level:  R2 = 0.85 (0.72-0.99)
- Individual level:  = 0.90 (0.89-0.90)
- Example from their paper with virtually identical results, concluded *‘seems plausible to conclude a valid surrogate’*

- Burzykowski et al, JRSSC, 2001

## Effects for DFS & OS

## Begg and Leung (2000)

- ‘The validity of a surrogate endpoint should be judged by the probability that the trial results based on the surrogate endpoint alone are ‘concordant’ with the trial results that would be obtained if the true endpoint were observed and used for the analysis’

- Begg and Leung, JRSSA, 2000

## Results

- Of 18 total within-trial comparisons
- Compared arms using log-rank tests
- 16 same conclusion both DFS & OS
- 11 No difference, 5 significant difference
- 2 significant only for DFS
- Both had p = 0.03 for DFS

## Hazard Ratios for DFS & OS

- OS HR attenuated from
- DFS HR toward unity in
- 12 of 18 comparisons

## Conclusion (2)

- As an endpoint for comparison:
- Hazard ratio for DFS an excellent predictor of HR for OSwith slight attenuation
- Marginally significant improvements in DFS may not translate into improvements in OS
- Formal measures suggest surrogacy

## Predicting OS from DFS

**Predicting OS from DFS**

- An Observed DFS
- Hazard Ratio of 0.8...

**N=2000**

## Predicting OS from DFS

**Predicting OS from DFS**

**N=2000**

- Translates into a
- Predicted OS Hazard
- Ratio of 0.837

## Predicting OS from DFS

**Predicting OS from DFS**

**N=2000**

- With a 95% Prediction
- Interval of 0.77-0.91

## Predicting OS from DFS

**Predicting OS from DFS**

**N=2000**

## Predicting OS from DFS

**Predicting OS from DFS**

## Predicting OS from DFS

**Predicting OS from DFS**

## Predicting OS from DFS

**Predicting OS from DFS**

## Predicting OS from DFS

**Predicting OS from DFS**

## Predicting OS from DFS

**Predicting OS from DFS**

## Predicted and Actual OS Hazard Ratios

## Discussion

- Individual patient data from all trials
- All trials tested 5-FU based regimens
- Trials included mixture of stage II and stage III patients
- Preliminary work: concordance stronger for stage III than II

## Discussion

- Relevance to current practice
- More effective advanced disease therapy
- Improved detection of recurrence
- Relevance for targeted or other non-cytotoxic agents
- If agent delays (as opposed to prevents) recurrence, concordance may decrease

## Conclusions

- Disease Free survival an excellent predictor of Overall survival
- Meets most formal definitions of surrogacy
- Modest attenuation of treatment effect between the two endpoints
- Model allows prediction of OS effect based on DFS effect

## Collaborators

- S Wieand, M O’Connell - NSABP
- J Benedetti - SWOG
- R Labianca - Ospedali Riuniti (Italy)
- D Haller - ECOG
- L Shepherd - NCIC
- JF Seitz - University of the Mediterranean (France)
- G Francini - University of Siena (Italy)
- A deGramont - Hospital Saint Antoine (France)
- R Goldberg - NCCTG/UNC
- M Buyse - IDDI (Belgium)
- Acknowledgement:  E Green (Mayo)