Adaptive Enrichment Design--A Case Study

Adaptive Enrichment Design--A Case Study

Lingyun Liu, PhD [email protected]

Cytel Inc.

•  Cyrus Mehta •  Sam Hsiao •  Pranab Ghosh

Cytel/Pfizer Symposium 25 Aug 2016 2

Acknowledgement

•  Background IntroducFon •  AdapFve Enrichment Design •  OperaFonal ConsideraFons •  Regulatory Experience •  Conclusions


Outline

•  A rare and aggressive cancer •  Reported incidence in EU 1/100000 •  5-‐year survival rate of less than 12% •  Current Standard Therapy – Limited treatment opFons – Modest benefit


Indication

•  Add-‐on to current drug A •  Drug A-‐-‐Oral inhibitor of VEGFR •  No complete responses observed for such paFents with Drug A

•  New drug B targeFng a different pathway •  targeFng both pathways concurrently is more effecFve than targeFng either pathway alone

•  Non-‐overlapping toxicity profile allowing prolonged dosing in responding paFents


New Drug B

•  Safety and acFvity being evaluated in a phase 1b/2 study

•  Interim efficacy data show radiographic reducFons in tumor volume

•  Some paFents with durable complete responses •  Two types of paFents (S+ and S-‐) characterized by disease locaFon

•  Be^er response observed for paFents in S+ than those in S-‐


Clinical development

•  Available safety and efficacy data are considered compelling and supporFve of a registraFon-‐enabling clinical study

•  Given the extremely small number of paFents in this populaFon

•  Single pivotal phase 3 trial to support the claimed orphan indicaFon


Single Pivotal Phase 3 Trial

•  Considerable uncertainty about the treatment effect of B given with A compared to single agent A

•  S-‐ is considered a more aggressive form of cancer and response between S+ and S-‐ may be disparate

•  Heterogeneity in response has been observed between S+ and S-‐ in ongoing phase 1b/2 study: S+ has been more responsive

•  The uncertainty of the treatment effect puts the study at risk of being underpowered.


Design Considerations


Design Strategy

124 pa'ents: 70/cohort 1 & 54/cohort 2 95 events: 60/cohort 1 & 30/cohort 2 IA: 40 events from cohort 1 Primary Endpoint: PFS

•  Extension of Jenkins, Stone, & Jennison, 2011 •  Type I error control is guaranteed by applying the closed tesFng principle together with the combinaFon test

•  Allow unblinding other secondary endpoints to facilitate interim decision


Type I Error Control

•  In case of no enrichment, declare significance on Full populaFon if 𝑤↓1 Φ↑−1 (𝑝↓1↑𝐹𝑆 )+ 𝑤↓2 Φ↑−1 (𝑝↓2↑𝐹𝑆 )> 𝑧↓𝛼  𝑤↓1 Φ↑−1 (𝑝↓1↑𝐹 )+ 𝑤↓2 Φ↑−1 (𝑝↓2↑𝐹 )> 𝑧↓𝛼 

•  In case of enrichment, declare significance on S+ if 𝑤↓1 Φ↑−1 (𝑝↓1↑𝐹𝑆 )+ 𝑤↓2 Φ↑−1 (𝑝↓2↑𝑆 )> 𝑧↓𝛼  𝑤↓1 Φ↑−1 (𝑝↓1↑𝑆 )+ 𝑤↓2 Φ↑−1 (𝑝↓2↑𝑆 )> 𝑧↓𝛼 


Final Analysis


Simulations

HR for S+, S-‐, Full Popula'on

Zone Prob of Zone

Power

Average Study Dura'on Average Sample Size

Fxd Fxd & SSR

Fxd & SSR & Enrich

Fxd Fxd & SSR

Fxd & SSR & Enrich

Fxd Fxd & SSR

Fxd & SSR & Enrich

0.6 0.6 0.6 Enrich 17% 32% 32% 43% 20 20 25 124 124 168

Prom 44% 67% 86% 86% 20 27 27 124 200 200

Fav 39% 92% 92% 92% 20 20 20 124 124 124

Total 100% 70% 79% 81% 20 23 24 124 157 165

0.5 0.8 0.64 Enrich 23% 43% 43% 75% 20 20 25 124 124 169

Prom 46% 73% 90% 90% 20 27 27 124 200 200

Fav 31% 93% 93% 93% 20 20 20 124 124 124

Total 100% 73% 80% 88% 20 23 24 124 159 169

0.5 1.0 0.72 Enrich 35% 41% 41% 76% 19 19 26 124 124 169

Prom 45% 70% 87% 87% 19 26 26 124 200 200

Fav 20% 90% 90% 91% 19 19 19 124 124 124

Total 100% 64% 71% 84% 19 23 25 124 158 174

•  Monitoring of enrolment and event arrival –  Track paFents belonging to each cohort and when the enrolment switches from cohort 1 to cohort 2

–  Track PFS events belonging to each cohort •  Establish appropriate firewall to protect the study integrity –  Document who saw what and when –  Only DMC and ISC have access to unblinded data

•  Web based system and document management system (ACES) to manage the storage of data and documents –  Role based access –  Full audit tracking capabiliFes


Operation Considerations

•  Handling Fme difference between arrival of 70 paFents for cohort 1 and arrival of 40 PFS events 1)  The 40 PFS events arrive before 70 paFents are enrolled

!  Arrival of 40 PFS events will trigger the interim analysis for adapFve decision !  Data cleaning and data base lock !  Transfer data to independent staFsFcian for unblinded analysis !  DMC meeFng !  AdapFve decision !  For final analysis, cohort 1 will comprise the first 70 paFents who will be followed unFl arrival

of 60 events

2)  The 40 PFS events arrive aher 70 paFents are enrolled !  Cohort 1 is closed as soon as the 70 patents have been enrolled who will be followed unFl 60

events !  All future arrivals belong to cohort 2 !  Limit the Fme between start of cohort 2 recruitment and interim adapFve decision making !  Perform interim analysis either 30 days aher the arrival of 70th subject or 14 days aher the

arrival of the 40th event whichever is earlier


Operation Considerations

•  To maintain the independence of cohort 1 and cohort 2 – Cohort 1 is closed when 70 paFents and 60 events arrive

–  In case of SSR or enrichment, only cohort 2 will be expanded or modified

– AddiFonal events from cohort 1 other than the 60 events will not be included in the final analysis


Independence between Cohort 1 and Cohort 2

•  JusFficaFon of the adapFve design proposal •  Large convenFonal design should be considered and discussed

•  Impact of adapFve enrichment on hypothesis test and parameter esFmaFon – Type I error is strongly controlled – Parameter esFmaFon is sFll an acFve research topic

– No rigorous soluFon to esFmaFon problem in case of adapFve enrichment


Regulatory Feedback

•  If the interim result from cohort 1 enters the favorable zone, use the convenFonal maximum likelihood esFmate of hazard raFo from the Cox model.

•  If the interim result from cohort 1 enters the promising zone, use the "backward image" method of Gao, Liu and Mehta (2013) to esFmate the log of the hazard raFo.

•  If the interim result from cohort 1 enters the enrichment zone, use only the enriched data from cohort 2 to esFmate the hazard raFo. This ensures that the parameter esFmate will be unbiased though the resulFng confidence interval may not be consistent with the hypothesis test.


Proposal for estimation

•  There is ohen significant uncertainty and heterogeneity with the treatment effect among subpopulaFons for rare oncology area

•  The adapFve enrichment design provides an alternaFve opFon to miFgate the risk of being under powered

•  Pros and cons of such adapFve design need to be evaluated thoroughly on a case-‐by-‐case basis

•  ProspecFve planning is criFcal for successful implementaFon of such design


Conclusions

Adaptive Enrichment Design--A Case Study

Documents

Transcript of Adaptive Enrichment Design--A Case Study