Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma

Stephen Palmer; Yi Lin; Thomas G. Martin; Sundar Jagannath; Andrzej Jakubowiak; Saad Z. Usmani; Nasuh Buyukkaramikli; Hilary Phelps; Rafal Slowik; Feng Pan; Satish Valluri; Lida Pacaud; Graham Jackson

doi:10.1007/s40487-023-00230-x

Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma

Stephen Palmer, Yi Lin, Thomas G. Martin, Sundar Jagannath, Andrzej Jakubowiak, Saad Z. Usmani, Nasuh Buyukkaramikli^*, Hilary Phelps, Rafal Slowik, Feng Pan, Satish Valluri, Lida Pacaud, Graham Jackson

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Introduction: Extrapolating long-term overall survival (OS) from shorter-term clinical trial data is key to health technology assessment in oncology. However, extrapolation using conventional methods is often subject to uncertainty. Using ciltacabtagene autoleucel (cilta-cel), a chimeric antigen receptor T-cell therapy for multiple myeloma, we used a flexible Bayesian approach to demonstrate use of external longer-term data to reduce the uncertainty in long-term extrapolation. Methods: The pivotal CARTITUDE-1 trial (NCT03548207) provided the primary efficacy data for cilta-cel, including a 12-month median follow-up snapshot of OS. Longer-term (48-month median follow-up) survival data from the phase I LEGEND-2 study (NCT03090659) were also available. Twelve-month CARTITUDE-1 OS data were extrapolated in two ways: (1) conventional survival models with standard parametric distributions (uninformed), and (2) Bayesian survival models whose shape prior was informed from 48-month LEGEND-2 data. For validation, extrapolations from 12-month CARTITUDE-1 data were compared with observed 28-month CARTITUDE-1 data. Results: Extrapolations of the 12-month CARTITUDE-1 data using conventional uninformed parametric models were highly variable. Using informative priors from the 48-month LEGEND-2 dataset, the ranges of projected OS at different timepoints were consistently narrower. Area differences between the extrapolation curves and the 28-month CARTITUDE-1 data were generally lower in informed Bayesian models, except for the uninformed log-normal model, which had the lowest difference. Conclusions: Informed Bayesian survival models reduced variation of long-term projections and provided similar projections as the uninformed log-normal model. Bayesian models generated a narrower and more plausible range of OS projections from 12-month data that aligned with observed 28-month data. Trial Registration: CARTITUDE-1 ClinicalTrials.gov identifier, NCT03548207. LEGEND-2 ClinicalTrials.gov identifier, NCT03090659, registered retrospectively on 27 March 2017, and ChiCTR-ONH-17012285.

Original language	English
Pages (from-to)	313-326
Number of pages	14
Journal	Oncology and Therapy
Volume	11
Issue number	3
Early online date	4 Jun 2023
DOIs	https://doi.org/10.1007/s40487-023-00230-x
Publication status	Published - 1 Sept 2023

Bibliographical note

Publisher Copyright:
© 2023, The Author(s).

Keywords

Ciltacabtagene autoleucel
Extrapolation
Overall survival
Relapsed/refractory multiple myeloma

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Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma
© The Author(s) 2023
Final published version, 840 KBLicence: CC BY-NC

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Palmer, S., Lin, Y., Martin, T. G., Jagannath, S., Jakubowiak, A., Usmani, S. Z., Buyukkaramikli, N., Phelps, H., Slowik, R., Pan, F., Valluri, S., Pacaud, L., & Jackson, G. (2023). Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma. Oncology and Therapy, 11(3), 313-326. https://doi.org/10.1007/s40487-023-00230-x

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title = "Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma",

abstract = "Introduction: Extrapolating long-term overall survival (OS) from shorter-term clinical trial data is key to health technology assessment in oncology. However, extrapolation using conventional methods is often subject to uncertainty. Using ciltacabtagene autoleucel (cilta-cel), a chimeric antigen receptor T-cell therapy for multiple myeloma, we used a flexible Bayesian approach to demonstrate use of external longer-term data to reduce the uncertainty in long-term extrapolation. Methods: The pivotal CARTITUDE-1 trial (NCT03548207) provided the primary efficacy data for cilta-cel, including a 12-month median follow-up snapshot of OS. Longer-term (48-month median follow-up) survival data from the phase I LEGEND-2 study (NCT03090659) were also available. Twelve-month CARTITUDE-1 OS data were extrapolated in two ways: (1) conventional survival models with standard parametric distributions (uninformed), and (2) Bayesian survival models whose shape prior was informed from 48-month LEGEND-2 data. For validation, extrapolations from 12-month CARTITUDE-1 data were compared with observed 28-month CARTITUDE-1 data. Results: Extrapolations of the 12-month CARTITUDE-1 data using conventional uninformed parametric models were highly variable. Using informative priors from the 48-month LEGEND-2 dataset, the ranges of projected OS at different timepoints were consistently narrower. Area differences between the extrapolation curves and the 28-month CARTITUDE-1 data were generally lower in informed Bayesian models, except for the uninformed log-normal model, which had the lowest difference. Conclusions: Informed Bayesian survival models reduced variation of long-term projections and provided similar projections as the uninformed log-normal model. Bayesian models generated a narrower and more plausible range of OS projections from 12-month data that aligned with observed 28-month data. Trial Registration: CARTITUDE-1 ClinicalTrials.gov identifier, NCT03548207. LEGEND-2 ClinicalTrials.gov identifier, NCT03090659, registered retrospectively on 27 March 2017, and ChiCTR-ONH-17012285.",

keywords = "Ciltacabtagene autoleucel, Extrapolation, Overall survival, Relapsed/refractory multiple myeloma",

author = "Stephen Palmer and Yi Lin and Martin, {Thomas G.} and Sundar Jagannath and Andrzej Jakubowiak and Usmani, {Saad Z.} and Nasuh Buyukkaramikli and Hilary Phelps and Rafal Slowik and Feng Pan and Satish Valluri and Lida Pacaud and Graham Jackson",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2023",

month = sep,

day = "1",

doi = "10.1007/s40487-023-00230-x",

language = "English",

volume = "11",

pages = "313--326",

journal = "Oncology and Therapy",

issn = "2366-1070",

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number = "3",

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Palmer, S, Lin, Y, Martin, TG, Jagannath, S, Jakubowiak, A, Usmani, SZ, Buyukkaramikli, N, Phelps, H, Slowik, R, Pan, F, Valluri, S, Pacaud, L & Jackson, G 2023, 'Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma', Oncology and Therapy, vol. 11, no. 3, pp. 313-326. https://doi.org/10.1007/s40487-023-00230-x

TY - JOUR

T1 - Extrapolation of Survival Data Using a Bayesian Approach

T2 - A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma

AU - Palmer, Stephen

AU - Lin, Yi

AU - Martin, Thomas G.

AU - Jagannath, Sundar

AU - Jakubowiak, Andrzej

AU - Usmani, Saad Z.

AU - Buyukkaramikli, Nasuh

AU - Phelps, Hilary

AU - Slowik, Rafal

AU - Pan, Feng

AU - Valluri, Satish

AU - Pacaud, Lida

AU - Jackson, Graham

PY - 2023/9/1

Y1 - 2023/9/1

N2 - Introduction: Extrapolating long-term overall survival (OS) from shorter-term clinical trial data is key to health technology assessment in oncology. However, extrapolation using conventional methods is often subject to uncertainty. Using ciltacabtagene autoleucel (cilta-cel), a chimeric antigen receptor T-cell therapy for multiple myeloma, we used a flexible Bayesian approach to demonstrate use of external longer-term data to reduce the uncertainty in long-term extrapolation. Methods: The pivotal CARTITUDE-1 trial (NCT03548207) provided the primary efficacy data for cilta-cel, including a 12-month median follow-up snapshot of OS. Longer-term (48-month median follow-up) survival data from the phase I LEGEND-2 study (NCT03090659) were also available. Twelve-month CARTITUDE-1 OS data were extrapolated in two ways: (1) conventional survival models with standard parametric distributions (uninformed), and (2) Bayesian survival models whose shape prior was informed from 48-month LEGEND-2 data. For validation, extrapolations from 12-month CARTITUDE-1 data were compared with observed 28-month CARTITUDE-1 data. Results: Extrapolations of the 12-month CARTITUDE-1 data using conventional uninformed parametric models were highly variable. Using informative priors from the 48-month LEGEND-2 dataset, the ranges of projected OS at different timepoints were consistently narrower. Area differences between the extrapolation curves and the 28-month CARTITUDE-1 data were generally lower in informed Bayesian models, except for the uninformed log-normal model, which had the lowest difference. Conclusions: Informed Bayesian survival models reduced variation of long-term projections and provided similar projections as the uninformed log-normal model. Bayesian models generated a narrower and more plausible range of OS projections from 12-month data that aligned with observed 28-month data. Trial Registration: CARTITUDE-1 ClinicalTrials.gov identifier, NCT03548207. LEGEND-2 ClinicalTrials.gov identifier, NCT03090659, registered retrospectively on 27 March 2017, and ChiCTR-ONH-17012285.

AB - Introduction: Extrapolating long-term overall survival (OS) from shorter-term clinical trial data is key to health technology assessment in oncology. However, extrapolation using conventional methods is often subject to uncertainty. Using ciltacabtagene autoleucel (cilta-cel), a chimeric antigen receptor T-cell therapy for multiple myeloma, we used a flexible Bayesian approach to demonstrate use of external longer-term data to reduce the uncertainty in long-term extrapolation. Methods: The pivotal CARTITUDE-1 trial (NCT03548207) provided the primary efficacy data for cilta-cel, including a 12-month median follow-up snapshot of OS. Longer-term (48-month median follow-up) survival data from the phase I LEGEND-2 study (NCT03090659) were also available. Twelve-month CARTITUDE-1 OS data were extrapolated in two ways: (1) conventional survival models with standard parametric distributions (uninformed), and (2) Bayesian survival models whose shape prior was informed from 48-month LEGEND-2 data. For validation, extrapolations from 12-month CARTITUDE-1 data were compared with observed 28-month CARTITUDE-1 data. Results: Extrapolations of the 12-month CARTITUDE-1 data using conventional uninformed parametric models were highly variable. Using informative priors from the 48-month LEGEND-2 dataset, the ranges of projected OS at different timepoints were consistently narrower. Area differences between the extrapolation curves and the 28-month CARTITUDE-1 data were generally lower in informed Bayesian models, except for the uninformed log-normal model, which had the lowest difference. Conclusions: Informed Bayesian survival models reduced variation of long-term projections and provided similar projections as the uninformed log-normal model. Bayesian models generated a narrower and more plausible range of OS projections from 12-month data that aligned with observed 28-month data. Trial Registration: CARTITUDE-1 ClinicalTrials.gov identifier, NCT03548207. LEGEND-2 ClinicalTrials.gov identifier, NCT03090659, registered retrospectively on 27 March 2017, and ChiCTR-ONH-17012285.

KW - Ciltacabtagene autoleucel

KW - Extrapolation

KW - Overall survival

KW - Relapsed/refractory multiple myeloma

UR - http://www.scopus.com/inward/record.url?scp=85160837367&partnerID=8YFLogxK

U2 - 10.1007/s40487-023-00230-x

DO - 10.1007/s40487-023-00230-x

M3 - Article

AN - SCOPUS:85160837367

SN - 2366-1070

VL - 11

SP - 313

EP - 326

JO - Oncology and Therapy

JF - Oncology and Therapy

IS - 3

ER -

Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma

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Keywords

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