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Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien PERON October 2016 Department of Biostatistics HCL – LBBE UCBL Department of Medical oncology HCL – LBBE UCBL

Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

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Page 1: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Analysing Survival Endpoints in Randomized Clinical

Trials using Generalized Pairwise Comparisons

Dr Julien PERON October 2016

Department of Biostatistics HCL – LBBE UCBL Department of Medical oncology HCL – LBBE UCBL

Page 2: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Outline

• The standard procedure of generalized pairwise comparisons

• An extension for right-censored data

• A patient-oriented measure of treatment benefit

• Benefit-risk balance • NCIC PA.3 trial => erlotinib in pancreatic cancer

2

Page 3: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Outline

• The standard procedure of generalized pairwise comparisons

• NCIC PA.3 trial => erlotinib in pancreatic cancer

3

Page 4: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Pairwise comparisons

Let xi be the outcome of

i th subject in T (i = 1. … . n )

R

Control (C ) Treatment (T )

Let yj be the outcome of

j th subject in C (j = 1. … . m )

Yj Xi

favors T (favorable)

favors C (unfavorable)

pairwise comparison

Neutral or Uninformative 4

Buyse M. stat in med 2010

Page 5: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Definition of thresholds

Coutinuous outcome

5 Buyse. stat in med 2010

Pair Rating

𝑥𝑖 𝑦𝑗 > Favorable

𝑥𝑖 𝑦𝑗 < ( ) Unfavorable

𝑥𝑖 𝑦𝑗 ≤ Neutral

𝑥𝑖 or 𝑦𝑗 missing Uninformative

Page 6: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Definition of priority

First priority outcome

Second priority outcome

Pair rating

Favorable NA Favorable

Unfavorable NA Unfavorable

Neutral/Uninf Favorable Favorable

Neutral/Uninf Unfavorable Unfavorable

Neutral/Uninf Neutral/Uninf Neutral/Uninf

6 Buyse. stat in med 2010

Page 7: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Definition of priority

First priority outcome

Second priority outcome

Pair rating

Favorable NA Favorable

Unfavorable NA Unfavorable

Neutral/Uninf Favorable Favorable

Neutral/Uninf Unfavorable Unfavorable

Neutral/Uninf Neutral/Uninf Neutral/Uninf

7 Buyse. stat in med 2010

Page 8: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Definition of priority

First priority outcome

Second priority outcome

Pair rating

Favorable NA Favorable

Unfavorable NA Unfavorable

Neutral/Uninf Favorable Favorable

Neutral/Uninf Unfavorable Unfavorable

Neutral/Uninf Neutral/Uninf Neutral/Uninf

8 Buyse. stat in med 2010

Page 9: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Standard procedure for pairwise scoring

Δ in named «net chance of a better outcome»

9 Buyse. stat in med 2010

n

i

m

j

Uijnm

U1 1

1

otherwise 0

eunfavorabl is pair when the1

favorable is pair when the1

Y j,X i

Y j,X i

U ij

Page 10: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

• 𝑥𝑖0 and 𝑦𝑗

0 : time-to-event

• 𝑥𝑖 and 𝑦𝑗 : time-to-observation

• Event indicator :

𝛿𝑖 = 1 𝑖𝑓 𝑥𝑖 = 𝑥𝑖

0

0 𝑖𝑓 𝑥𝑖 < 𝑥𝑖0 in group T

휀𝑗 = 1 𝑖𝑓 𝑦𝑗 = 𝑦𝑗

0

0 𝑖𝑓 𝑦𝑗 < 𝑦𝑗0 in group C

• Survival function:

𝑆𝑇𝑡𝑡 𝑡 = ℙ 𝑥𝑖0 ≥ 𝑡 and 𝑆𝐶𝑡𝑟𝑙 𝑡 = ℙ 𝑦𝑗

0 ≥ 𝑡

10

Some notations

Page 11: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

11

(𝛿𝑖 , 휀𝑗) 𝑥𝑖 − 𝑦𝑗 ≥ 𝜏 𝑥𝑖 − 𝑦𝑗 ≤ −𝜏 𝑥𝑖 − 𝑦𝑗 < 𝜏

(1, 1) Favorable Unfavorable Neutral

(0, 1) Favorable Uninformative Uninformative

(1, 0) Uninformative Unfavorable Uninformative

(0, 0) Uninformative Uninformative Uninformative

Buyse M. Stat in med, 2010

The standard procedure to include time-to-event’ outcome

Page 12: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

12

0,5

1,0

Surv

ival

Pro

bab

ility

0,0

Time

Patient i : censoring

Treatment group

Control group

Patient j : event

The standard procedure to include time-to-event outcome

Gehan. Biometrika, 1965

Page 13: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Outline

• An extension for right-censored data

• NCIC PA.3 trial => erlotinib in pancreatic cancer

13

Page 14: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Based on the Kaplan-Meier estimate of the survival function

𝕡 ( 𝑥𝑖0> 𝑦𝑗

0) 𝑥𝑖0> 𝑥𝑖 =

𝑆 𝑇𝑡𝑡 𝑦𝑗

𝑆 𝑇𝑡𝑡(𝑥𝑖)=

0,5

0,8

The extended procedure taking into account ‘non-informative’ pairs

0,5

1,0

Surv

ival

Pro

bab

ility

0,0

Time

0,8

Péron J et al, SMMR 2016

Patient i : censoring

Patient j : event

Treatment group

Control group

Page 15: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

15

𝕡 ( 𝑥𝑖0> 𝑦𝑗

0) 𝑥𝑖0> 𝑥𝑖 , 𝑦𝑗

0> 𝑦𝑗 = − 𝑆 𝑇𝑡𝑡 𝑡

𝑆 𝑇𝑡𝑡 𝑥𝑖 𝑆 𝐶𝑡𝑟𝑙 𝑦𝑗∙ 𝑆 𝐶𝑡𝑟𝑙 𝑡

+ − 𝑆 𝐶𝑡𝑟𝑙 𝑡−

𝑡>𝑦𝑗

Efron, Berkeley Symp, 1967

0,5

1,0

0,0

When the estimation of the survival function is discontinue :

Surv

ival

Pro

bab

ility

Time

Patient i : censoring

Treatment group

Control group

Patient j : censoring

The extended procedure taking into account ‘non-informative’ pairs

Page 16: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

For pairs that can not be decidely classified because of censoring, we compute:

ℙ 𝑥𝑖0 > 𝑦𝑗

0 + 𝜏 , et ℙ 𝑦𝑗0 > 𝑥𝑖

0 + 𝜏 , et ℙ 𝑥𝑖0 − 𝑦𝑗

0 < 𝜏

The pairwise score is: 𝑠𝑖𝑗 = ℙ 𝑥𝑖

0 > 𝑦𝑗0 + 𝜏 − ℙ 𝑦𝑗

0 > 𝑥𝑖0 + 𝜏

The net chance of a better outcome is then:

∆ = 1

𝑚 ∙ 𝑛 𝑠𝑖𝑗

𝑚

𝑗=1

𝑛

𝑖=1

The pairwise weight the analysis of an outcome of lower priority is: 𝜔𝑖𝑗= ℙ 𝑥𝑖

0 − 𝑦𝑗0 < 𝜏

16

The extended procedure taking into account ‘non-informative’ pairs

Page 17: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Simulation study - Design

• Objective: To compare the standard and the extended procedures of generalized pairwise comparison

• Simulation of M = 1000 datasets of with N = 200 patients – One time-to-event outcome

– Threshold 𝜏 = 0 months

Page 18: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

HR HR HR

18

• Survival time: exponential distributions

Scenario 1 : Proportional hazards

Scenario 2 : Late treatment effect

Scenario 3 : early treatment effect

Simulation study - Design

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19

• Several treatment effect sizes – Hazard ratio 0,5; 0,7; 1

• Administrative censoring proportion – Uniform distribution

– Between 0% and 70%

Simulation study - Design

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20

• For each simulated dataset – Estimation of the net chance of a better outcome (standard and extended

procedure)

– Test of the null hypothesis (Permutation test, Log-Rank test)

• Endpoints – Bias

– Power

– Type 1 error

Simulation study - Design

Page 21: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

HR = 0,5

HR = 0,7

21

Scenario 1 – Proportionnal hazards

Péron, et al. SMMR 2016

Page 22: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

HR = 0,5

HR = 0,7

22

Scenario 1 – Proportionnal hazards

Péron, et al. SMMR 2016

Page 23: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

23

An explanation for this bias?

1,0

Surv

ival

Pro

bab

ility

0,0

Time

C𝐞𝐧𝐬𝐨𝐫𝐢𝐧𝐠 𝒚𝒋 E𝐯𝐞𝐧𝐭 𝒙𝒊

Standard procedure: U𝐧𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐯𝐞 → 𝑝𝑖𝑗= 0

Extended procedure: ℙ 𝑥𝑖

0>𝑦𝑗0+𝜏 = 1−

𝑆 𝐶 𝑥𝑖−𝜏

𝑆 𝐶(𝑦𝑗)

ℙ 𝑦𝑗0>𝑥𝑖

0+𝜏 = 𝑆 𝐶 𝑥𝑖+𝜏

𝑆 𝐶(𝑦𝑗)

U𝐧𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐯𝐞 𝐚𝐥𝐬𝐨 → 𝑝𝑖𝑗= 0

Treatment group

Control group

Page 24: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

24

A correction for this bias

𝑓𝑚 : Proportion of informative pairs for the trial 𝑚(𝑚 = 1,… ,𝑀)

∆ 𝑐𝑜𝑟𝑟𝑚 =∆ 𝑚

𝑓𝑚 : corrected net chance of a better outcome

HR=0,5

𝐵𝑖𝑎𝑠 = 𝔼 ∆ − ∆

Mean bias

Censoring rate

Péron, et al. SMMR 2016

Page 25: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

HR = 0,5

HR = 0,7

25

Scenario 1 – Proportional hazards

Censoring rate

Péron, et al. SMMR 2016

Page 26: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

26

Scenario 2 et 3 – Non Proportional hazards

Censoring rate Censoring rate

Po

we

r

Early treatment effect Late treatment effect

Type 1 error rate ≈ 5%

Péron, et al. SMMR 2016

Page 27: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

• Bias in the estimation of Δ – Less important

– Correction available when only one endpoint

• Power of the permutation test extended procedure > standard procedure – Exponential distribution

– Proportional hazards and administrative censoring < 67% (B Efron, Stanford

Univ, 1967)

– Late treatment effect

27

Conclusions of the simulation study

Page 28: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Outline

• A patient-oriented measure of treatment benefit

• NCIC PA.3 trial => erlotinib in pancreatic cancer

28

Page 29: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

29

Probability for a random patient in the Treatment group to have a ‘better outcome’ than a random patient in the Control group …

Δ = ℙ 𝑿 > 𝒀 )

The net chance of a better outcome

Buyse M. Stat in med, 2010

Treatement group Control group

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30

Δ = ℙ 𝑋 > 𝑌 − ℙ(𝒀 > 𝑿)

Buyse M. Stat in med, 2010

Treatement group Control group

…minus the opposite probability.

The net chance of a better outcome

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31

ℙ(𝒀 = 𝑿)

Buyse M. Stat in med, 2010

Treatement group Control group

The net chance of a better outcome

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32

The net chance of a longer survival

Proportional hazards

Treatment group Control group

Time (months)

Net

ch

ance

of

a lo

nge

r su

rviv

al

Surv

ival

pro

bab

ility

Péron et al, JAMA oncology, 2016

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33

Proportional Hazards

Delayed treatment effect

Treatment group Control group

Treatment group Control group

Time (months)

Net

ch

ance

of

a lo

nge

r su

rviv

al

Surv

ival

pro

bab

ility

Time (months)

Net

ch

ance

of

a lo

nge

r su

rviv

al

Surv

ival

pro

bab

ility

Péron et al, JAMA oncology, 2016

The net chance of a longer survival

Page 34: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

34

Opposite hazards

Péron et al, JAMA oncology, 2016

Proportional Hazards

Treatment group Control group

Time (months)

Net

ch

ance

of

a lo

nge

r su

rviv

al

Surv

ival

pro

bab

ility

Treatment group Control group

Time (months)

Net

ch

ance

of

a lo

nge

r su

rviv

al

Surv

ival

pro

bab

ility

The net chance of a longer survival

Page 35: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Simulation study - Design

• Objective: To assess the power of tests based on generalized pairwise comparisons for delayed treatment effect

• Simulation of M = 1000 datasets of with N = 200 patients – One time-to-event outcome

Page 36: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

36

Scenario 1 : Proportional hazards

Scenario 2 : Late treatment effect

Simulation study - Design

Survival

Time (months)

Survival

Time (months)

Page 37: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

37

• Administrative censoring proportion – Uniform distribution

– Between 0% and 40%

• For each simulated dataset – Estimation of the net chance of a better outcome (extended procedure) with

threshold 𝜏 0 to 20 months

– Test of the null hypothesis (Permutation test, Log-Rank test)

Simulation study - Design

Page 38: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

38

Delayed treatment effect - POWER

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39

Proportional Hazards - POWER

Page 40: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

When a long-term survival benefit is expected (anticancer immune therapy)

The net chance of a longer survival is: – Arguably more relevant than traditional methods

– More powerful than traditional method

40

Conclusions

Page 41: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Outline

• Benefit-risk balance • NCIC PA.3 trial => erlotinib in pancreatic cancer

41

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42

The benefit-risk balance in the PA.3 trial

R

569 advanced pancreatic cancer

Gemcitabine + placebo Gemcitabine + erlotinib

284 285

Moore et al. JCO 2007

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43

The benefit-risk balance in the PA.3 trial

Page 44: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Worst grade

related AE

Erlotinib group (n=282) Placebo group (n=280)

Grade 1 48 (17%) 69 (24.6%)

Grade 2 118 (41.8%) 89 (31.8%)

Grade 3 72 (25.5%) 47 (16.8%)

Grade 4 11 (3.9%) 6 (2.1%)

Grade 5 4 (1.4%) 3 (1.1%)

44

The benefit-risk balance in the PA.3 trial

Page 45: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Worst grade

related AE

Erlotinib group (n=282) Placebo group (n=280)

Grade 1 48 (17%) 69 (24.6%)

Grade 2 118 (41.8%) 89 (31.8%)

Grade 3 72 (25.5%) 47 (16.8%)

Grade 4 11 (3.9%) 6 (2.1%)

Grade 5 4 (1.4%) 3 (1.1%)

45

The benefit-risk balance in the PA.3 trial

29,4% 18,9%

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46

Benefit-risk balance

Priority Erlotinib > Placebo Placebo > Erlotinib ∆∆[erlotinib]

1 : OS (Threshold = 2 months) 40.3 % 34.5 % 5.8 %

2 : Worst related AE grade 6.8 % 12.4 % -5.6 %

Global 47.1 % 46.9 % 0.2 % (P=.96)

Extended procedure

Péron J. Roy P. Ding K. Parulekar WR. Roche L and Buyse M. BJC 2015

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47

Benefit-risk balance

Péron J. Roy P. Ding K. Parulekar WR. Roche L and Buyse M. BJC 2015

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A package R corresponding to the standard procedure and to the extended procedure

• Available on CRAN (“BuyseTest”)

• Available on github (“https://github.com/bozenne/BuyseTest”)

48

Software implementation

Page 49: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

The net chance of a better outcome

– Is flexible

– Is meaningful

– Allows multicriteria analysis

– Can focus on long-term survival differences

– Is OK when hazards are not proportionals

– Is available

49

Conclusions

Page 50: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Thank you

50

Page 51: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

𝑀𝑒𝑎𝑛 𝑠𝑞𝑢𝑎𝑟𝑒𝑑 𝑒𝑟𝑟𝑜𝑟 = 𝔼 ∆ − ∆2

51

Scénario 1 – Mean squared error

HR=0,5

Mean squared

error

Page 52: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Pairwise comparisons

Let xi be the outcome of

i th subject in T (i = 1. … . n )

R

Control (C ) Treatment (T )

Let yj be the outcome of

j th subject in C (j = 1. … . m )

Yj Xi

favors T (favorable)

favors C (unfavorable)

pairwise comparison

Neutral or Uninformative 52

Buyse M. stat in med 2010

Page 53: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Definition of thresholds

Coutinuous outcome

53 Buyse. stat in med 2010

Pair Rating

𝑥𝑖 𝑦𝑗 > Favorable

𝑥𝑖 𝑦𝑗 < ( ) Unfavorable

𝑥𝑖 𝑦𝑗 ≤ Neutral

𝑥𝑖 or 𝑦𝑗 missing Uninformative

Page 54: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Definition of thresholds

Coutinuous outcome

54 Buyse. stat in med 2010

Pair Rating

𝑥𝑖 𝑦𝑗 > Favorable

𝑥𝑖 𝑦𝑗 < ( ) Unfavorable

𝑥𝑖 𝑦𝑗 ≤ Neutral

𝑥𝑖 or 𝑦𝑗 missing Uninformative

Page 55: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Definition of priority

First priority outcome

Second priority outcome

Pair rating

Favorable NA Favorable

Unfavorable NA Unfavorable

Uninformative Favorable Favorable

Uninformative Unfavorable Unfavorable

Uninformative Uninformative Uninformative

55 Buyse. stat in med 2010

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Methods – Definition of priority

First priority outcome

Second priority outcome

Pair rating

Favorable NA Favorable

Unfavorable NA Unfavorable

Uninformative Favorable Favorable

Uninformative Unfavorable Unfavorable

Uninformative Uninformative Uninformative

56 Buyse. stat in med 2010

Page 57: Analysing Survival Endpoints in Randomized Clinical Trials ...€¦ · Analysing Survival Endpoints in Randomized Clinical Trials using Generalized Pairwise Comparisons Dr Julien

Methods – Definition of priority

First priority outcome

Second priority outcome

Pair rating

Favorable NA Favorable

Unfavorable NA Unfavorable

Uninformative Favorable Favorable

Uninformative Unfavorable Unfavorable

Uninformative Uninformative Uninformative

57 Buyse. stat in med 2010

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Méthodes – Standard procedure for pairwise

scoring

Δ in named «chance of a better outcome»

58 Buyse. stat in med 2010

n

i

m

j

Uijnm

U1 1

1

otherwise 0

eunfavorabl is pair when the1

favorable is pair when the1

Y j,X i

Y j,X i

U ij

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Based on the Kaplan-Meier estimate of the survival function

𝕡 ( 𝑥𝑖0> 𝑦𝑗

0) 𝑥𝑖0> 𝑥𝑖 = −

𝑆 𝑇 𝑡

𝑆 𝑇 𝑥𝑖 𝑆 𝐶 𝑦𝑗𝑑𝑆 𝐶 𝑡

𝑡>𝑦𝑗

𝑡∈ 𝑦𝑗𝜀𝑗=1

The extended procedure taking into account ‘non-informative’ pairs

0,5

1,0

Surv

ival

Pro

bab

ility

0,0

Time

0,8

Péron J et al, SMMR 2016

Patient i : censoring

Patient j : censoring

Treatment group

Control group

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60

𝕡 ( 𝑥𝑖0> 𝑦𝑗

0) 𝑥𝑖0> 𝑥𝑖 , 𝑦𝑗

0> 𝑦𝑗 = − 𝑆 𝑇𝑡𝑡 𝑡

𝑆 𝑇𝑡𝑡 𝑥𝑖 𝑆 𝐶𝑡𝑟𝑙 𝑦𝑗∙ 𝑆 𝐶𝑡𝑟𝑙 𝑡

+ − 𝑆 𝐶𝑡𝑟𝑙 𝑡−

𝑡>𝑦𝑗

Efron, Berkeley Symp, 1967

0,5

1,0

0,0

When the estimation of the survival function is discontinue :

Surv

ival

Pro

bab

ility

Time

Patient i : censoring

Treatment group

Control group

Patient j : censoring

The extended procedure taking into account ‘non-informative’ pairs

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61

(𝜹𝒊, 𝜺𝒋) 𝒙𝒊 − 𝒚𝒋 > 𝝉 𝒙𝒊 − 𝒚𝒋 < −𝝉 𝒙𝒊 − 𝒚𝒋 < 𝝉

(𝟏, 𝟏) 1 -1 0

(𝟎, 𝟏) 1 𝑆 𝑇 𝑦𝑗 + 𝜏 + 𝑆 𝑇 𝑦𝑗 − 𝜏

𝑆 𝑇(𝑥𝑖)− 1

𝑆 𝑇 𝑦𝑗 + 𝜏

𝑆 𝑇 𝑥𝑖

(𝟏, 𝟎) 1 −𝑆 𝐶 𝑥𝑖 + 𝜏 + 𝑆 𝐶 𝑥𝑖 − 𝜏

𝑆 𝐶(𝑦𝑗) -1 −

𝑆 𝐶 𝑥𝑖 + 𝜏

𝑆 𝐶 𝑦𝑗

(𝟎, 𝟎)

1 −𝑆 𝐶 𝑥𝑖 − 𝜏 + 𝑆 𝐶 𝑥𝑖 + 𝜏

𝑆 𝐶 𝑦𝑗

− 𝑆 𝑇 𝑡 + 𝜏

𝑆 𝑇 𝑥𝑖 𝑆 𝐶 𝑦𝑗

𝑡>𝑥𝑖−𝜏

𝑡∈ 𝑦𝑗𝜀𝑗=1

𝑑𝑆 𝐶 𝑡

− 𝑆 𝑇 𝑡 − 𝜏

𝑆 𝑇 𝑥𝑖 𝑆 𝐶 𝑦𝑗

𝑡>𝑥𝑖+𝜏

𝑡∈ 𝑦𝑗𝜀𝑗=1

𝑑𝑆 𝐶 𝑡

− 𝑆 𝑇 𝑡 + 𝜏 + 𝑆 𝑇 𝑡 − 𝜏

𝑆 𝑇 𝑥𝑖 𝑆 𝐶 𝑦𝑗𝑑𝑆 𝐶 𝑡

𝑡>𝑦𝑗

𝑡∈ 𝑦𝑗𝜀𝑗=1

− 1

− 𝑆 𝑇 𝑡 + 𝜏

𝑆 𝑇 𝑥𝑖 𝑆 𝐶 𝑦𝑗𝑑𝑆 𝐶 𝑡

𝑡>𝑦𝑗

𝑡∈ 𝑦𝑗𝜀𝑗=1

− 𝑆 𝑇 𝑡 − 𝜏

𝑆 𝑇 𝑥𝑖 𝑆 𝐶 𝑦𝑗

𝑡>𝑥𝑖+𝜏

𝑡∈ 𝑦𝑗𝜀𝑗=1

𝑑𝑆 𝐶 𝑡

−𝑆 𝐶 𝑥𝑖 + 𝜏

𝑆 𝐶 𝑦𝑗

Extension prenant en compte les temps jusqu’à

censure

Valeurs du score attribué à chaque paire en fonction d’un seuil τ représentant la différence minimale cliniquement significative

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62

proportion of pairs (%)

Priority Threshold Erlotinib >

Placebo

Placebo >

Erlotinib

∆erlotinib

1 : OS 6 months 16.8 13.1 3.6

2 : PFS 6 months 3.0 1.8 1.2

3 : Worst related AE grade 3 grades 2.3 5.8 -3.5

4 : OS 3 months 11.2 10.8 0.4

5 : PFS 3 months 3.4 2.7 0.7

6 : Worst related AE grade 2 grades 2.3 6.0 -3.7

7 : OS 0 months 9.5 9.1 0.4

8 : PFS 0 months 0.5 0.6 -0.1

9 : Worst related AE grade 1 grade 0.2 0.5 -0.3

Overall 49.2 50.4 -1.2 (P=.82)

Sensitivity analysis

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63

Hypothesis of the correction

1,0

0,0

Temps

Surv

ival

Pro

bab

ility

C𝐞𝐧𝐬𝐨𝐫𝐢𝐧𝐠 𝒚𝒋 E𝐯𝐞𝐧𝐭 𝒙𝒊

Treatment group

Control group

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proportion of pairs (%)

Priority Erlotinib > Placebo Placebo > Erlotinib ∆∆erlotinib

1 : OS (Threshold = 2 months) 37.0 32.3 4.7

2 : Worst related AE grade 7.5 15.7 -8.3

Overall 44.5 48.1 -3.6 (P=.51)

64

Main analysis of the benefit-risk balance of the erlotinib and gemcitabine

combination

Péron J. Roy P. Ding K. Parulekar WR. Roche L and Buyse M. BJC 2015

With the standard procedure

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65

Sensitivity analysis

Péron J. Roy P. Ding K. Parulekar WR. Roche L and Buyse M. BJC 2015

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66

Priority Erlotinib > Placebo Placebo > Erlotinib ∆∆[erlotinib]

1 : OS (Threshold = 2 months) 37.0 % 32.3 % 4.7 %

2 : Worst related AE grade 7.5 % 15.7 % -8.3 %

Global 44.5 % 48.1 % -3.6% (P=.51)

Standard procedure

Benefit-risk balance

Priority Erlotinib > Placebo Placebo > Erlotinib ∆∆[erlotinib]

1 : OS (Threshold = 2 months) 40.3 % 34.5 % 5.8 %

2 : Worst related AE grade 6.8 % 12.4 % -5.6 %

Global 47.1 % 46.9 % 0.2 % (P=.96)

Extended procedure

Péron J. Roy P. Ding K. Parulekar WR. Roche L and Buyse M. BJC 2015

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67

Extended procedure

Benefit-risk balance

Standard procedure

Péron J. Roy P. Ding K. Parulekar WR. Roche L and Buyse M. BJC 2015

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Priority FOLFIRINOX >

Gemcitabine

Gemcitabine >

FOLFIRINOX

∆∆[FOLFIRINOX]

1 : OS (Threshold = 2 months) 43.0% 21.7% 21.3%

2 : Worst related AE grade 8.2% 15.4% -7.2%

Global 51.2% 37.1% 14.0% (P=0.029)

68

PRODIGE 4 trial

Benefit-risk balance

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69

Priority Erlotinib > Placebo Placebo > Erlotinib ∆∆[erlotinib]

1 : OS (Threshold = 2 months) 37.0 % 32.3 % 4.7 %

2 : Worst related AE grade 7.5 % 15.7 % -8.3 %

Global 44.5 % 48.1 % -3.6% (P=.51)

PRODIGE 4 trial

NCIC PA-3 trial

Benefit-risk balance

Priority FOLFIRINOX >

Gemcitabine

Gemcitabine >

FOLFIRINOX

∆∆[FOLFIRINOX]

1 : OS (Threshold = 2 months) 43.0% 21.7% 21.3%

2 : Worst related AE grade 8.2% 15.4% -7.2%

Global 51.2% 37.1% 14.0% (P=0.029)

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70

NCIC PA-3 trial