non-proportional hazard in cancer immunotherapynon-proportional hazard in cancer immunotherapy...

Non-proportional Hazard in Cancer Immunotherapy

Aijing Zhang, Ph.D DISS, September 8th 2017

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OUTLINE

• The Presence of non-proportional hazard (NPH) in Cancer Immunotherapy (CIT)

• Motivation and Objectives of the Simulation Study

• Simulation Results and Discussions

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NPH Observed in CIT

Rittmeyer A et al, Lancert 2017 Jan 21; 389 (10066):255-265

Borghaei H et al. NEMJ 2015 October 22;373:1627-39

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Overall Survival Curves for NPH

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Time I I I I I I

I I I

Surv

ival P

robabili

ty

Proportional hazards: Target HR

Control arm CIT arm


Time I I I I I I

I I I

Surv

ival P

robabili

ty

Late separation

HR=1 Target HR

Observed: “average” HR

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Time I I I I I I

I I I

Surv

ival P

robabili

ty


Control arm CIT arm


Time I I I I I I

I I I

Surv

ival P

robabili

ty


“Diluted” HR

“Cross-over” in

control arm

≈Target HR

Time I I I I I I

I I I

Surv

ival P

robabili

ty

Late separation

HR=1 Target HR


6

Time I I I I I I

I I I

Surv

ival P

robabili

ty


Control arm CIT arm


Time I I I I I I

I I I

Surv

ival P

robabili

ty


“Diluted” HR

“Cross-over” in

control arm

≈Target HR

Time I I I I I I

I I I

Surv

ival P

robabili

ty

Late separation

HR=1 Target HR


Time I I I I I I

I I I

Surv

ival P

robabili

ty

HR=1 ≈Target HR “Diluted” HR


Late separation “Cross-over” in

control arm

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Time I I I I I I

I I I

Surv

ival P

robabili

ty


Control arm CIT arm

Motivation and Objectives

• In study design, study power/sample size is often calculated under PH assumption

• Use simulation to assess the impact on study power when OS is the primary endpoint with NPH coming from two sources: − Delayed treatment effect for the active treatment arm

− Dilution effect due to subsequent therapy in the control arm

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Patient-Level Survival Hazard due to Delayed Treatment and Dilution Effects

Survival Hazard

Progression

Dilution effect assumptions: • Probability that patients on control arm

would switch to new treatment after progression

• Hazard for control patients after switch

Control Arm

CIT Arm

Delayed treatment effect assumptions: • Hazard for patients on CIT arm

for the first x months

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Overall Survival Curve with Delayed Treatment and Dilution Effects

Time

I I I I I I

I I I

Overa

ll S

urv

ial

HR=1 ≈Target HR “Diluted” HR


Late separation

“Cross-over” in

control arm

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Control arm CIT arm

Simulation Settings: Trial Design Assumptions

• Median OS in control arm = 10 mon

• Target HR=0.65

• Sample size N =350 (two arms 1:1 randomized), analysis at 65% event patient ratio (i.e., 227 events)

• 90% power under PH assumption

• Type 1 error = 0.05, log-rank test, no interim analysis

• With the additional ramp-up accrual and dropout assumptions: accrual period is 25 months, analysis is done at 34 months

Simulation Settings: NPH Assumptions

• Delayed Treatment Effect − 1, 2 or 3 months

− before separation HR=1

• Dilution effect due to subsequent therapy − Timing of switch: mPFS in control arm

− 20, or 40% of the patients in control arm received subsequent therapy right after PD

− HR between study treatment and next line of therapy = 1 or 0.8

NPH Effect on Study Power – Simulation Results

Scenarios NPH Effects

Power Δ Power Median HR Observed

Delayed Tx Effect

% ”Switch” in Control Arm

Post-”Switch” Hazard Ratio

PH - - - 90% - 0.654

Delayed Tx Effect

1 mon - - 82% -8% 0.682

2 mon - - 74% -16% 0.711

3 mon - - 62% -28% 0.743

Switch to subsequent

therapy

- 20% 1 77% -13% 0.704

- 40% 1 56% -34% 0.759

- 20% 0.8 84% -6% 0.677

- 40% 0.8 77% -13% 0.703

Combined

1 mon 20% 0.8 76% -14% 0.708

2 mon 20% 0.8 64% -26% 0.735

3 mon 20% 0.8 52% -38% 0.765

Simulation runs: 10,000 PH: proportional hazard; Tx: treatment; HR: hazard ratio

NPH Effect on Study Power – Simulation Results (cont’d)

Scenarios Target HR Event

Number

NPH Effects


Delayed Tx Effect

% ”Switch” in Control

Arm

Post-”Switch”

Hazard Ratio

PH

0.65 227 - - - 90% - 0.654

0.55 120 - - - 90% - 0.554

0.75 505 - - - 90% - 0.749

Delayed Tx Effect

0.65 227 3 mon - - 62% -28% 0.743

0.55 120 3 mon - - 63% -27% 0.653

0.75 505 3 mon - - 64% -26% 0.812

How would the target HR after separation affect the study power?


NPH Effect on Study Power – Simulation Results (cont’d)

Scenarios mPFS NPH Effects


Delayed Tx Effect



PH 5 mon - - - 90% - 0.654

Switch to subsequent

therapy

4 mon - 40% 0.8 76.2% -13.8% 0.698

5 mon - 40% 0.8 77.4% -12.6% 0.703

6 mon - 40% 0.8 77.3% -12.7% 0.702

How would the control mPFS (timing of switch) affect the study power?


NPH Effect on Study Power

• Delayed treatment effect − The power decreases as the curve separation occurs later; the relationship is not linear

− The power decreases more dramatically as the delay increases

− The power decrease is not affected much by the magnitude of the HR after separation

• Switch to subsequent therapy − The power decreases as the proportion of subsequent therapy use increases; the relationship

is not linear

− The power decreases more dramatically as more patients initiated subsequent therapy

− The power decreases less dramatically when the subsequent therapy is less efficacious

− The power decrease is not affected much by the initiation time of subsequent therapy

• Combined impact on power is not simple addition of individual effects

Length of Followup – Simulation Results NPH Effects

Analysis Timing (mon from FPI) Power Δ Power

Median HR Observed

Delayed Tx Effect



PH - - - 34 90% -- 0.654

Delayed Tx Effect

2 mon - - 34 74% -16% 0.711

37 79% -11% 0.709

41 81% -9% 0.705

Combined

2 mon 20% 0.8 34 65% -25% 0.734

25% 37 67% -23% 0.742

30% 41 67% -23% 0.745

Length of Followup

• Analysis timing is determined when the pre-specified number of events are reached

• When there is delayed treatment effect, the power increases with longer follow up

• Increase FU time helps, however, with the cost of prolonged analysis timing

• In addition, when there is also dilution effect due to subsequent therapy, the length of FU need to be balanced considering NPH impact from both sources

NPH– Design Considerations

• When using the common practice of calculating the sample size and power under PH, assess the impact of potential NPH using simulation study considering difference types of NPH relevant to the study

• If there is evidence of strong NPH impact, points to be considered: • Assumption of treatment effect: using an “overall HR”, a weighted average of the

piecewise HR for sample size/power calculation

• Analyses: e.g. weighted log-rank test

• Endpoints: e.g. milestone OS

• Pre-specify the planned analyses method up front in the protocol and analysis plan and consult the HAs

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Acknowledgement

• Zhengrong Li

• Yijing Shen

• Yasuo Sugitani

• Ray Lin

• Dominik Heinzmann

• Almut Mecke

• Jing Yi

Doing now what patients need next

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