Bayesian hierarchical meta‐analytic methods for modeling surrogate relationships that vary across treatment classes using aggregate data

Papanikos, Tasos; Thompson, John R.; Abrams, Keith R.; Städler, Nicolas; Ciani, Oriana; Taylor, Rod S; Bujkiewicz, Sylwia

doi:10.1002/sim.8465

Cited by 21 publications

(45 citation statements)

References 46 publications

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“…The method uses a series of studies to establish the relationships between treatment, potential surrogate marker, and the final endpoint. Several authors have considered and extended the framework 52,53,54 . The method relies on aggregate data from different trials, which may enroll potential diverse clinical populations.…”

Section: Discussionmentioning

confidence: 99%

A survival mediation model with Bayesian model averaging

Zhou

Jiang

Xia

et al. 2021

Stat Methods Med Res

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Determining the extent to which a patient is benefiting from cancer therapy is challenging. Criteria for quantifying the extent of “tumor response” observed within a few cycles of treatment have been established for various types of solids as well as hematologic malignancies. These measures comprise the primary endpoints of phase II trials. Regulatory approvals of new cancer therapies, however, are usually contingent upon the demonstration of superior overall survival with randomized evidence acquired with a phase III trial comparing the novel therapy to an appropriate standard of care treatment. With nearly two-thirds of phase III oncology trials failing to achieve statistically significant results, researchers continue to refine and propose new surrogate endpoints. This article presents a Bayesian framework for studying relationships among treatment, patient subgroups, tumor response, and survival. Combining classical components of a mediation analysis with Bayesian model averaging, the methodology is robust to model misspecification among various possible relationships among the observable entities. A posterior inference is demonstrated via an application to a randomized controlled phase III trial in metastatic colorectal cancer. Moreover, the article details posterior predictive distributions of survival and statistical metrics for quantifying the extent of direct and indirect, or tumor response mediated treatment effects.

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Section: Discussionmentioning

confidence: 99%

A survival mediation model with Bayesian model averaging

Zhou

Jiang

Xia

et al. 2021

Stat Methods Med Res

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“…The method uses a series of studies to establish the relationships between treatment, potential surrogate marker and the final endpoint. Sev-eral authors have considered and extended the framework (Gail et al, 2000;Bujkiewicz et al, 2016;Papanikos et al, 2020). The method relies on aggregate data from different trials, which may enroll potential diverse clinical populations.…”

Section: Discussionmentioning

confidence: 99%

A Survival Mediation Model with Bayesian Model Averaging

Zhou¹,

Jiang²,

Xia³

et al. 2020

Preprint

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Determining the extent to which a patient is benefiting from cancer therapy is challenging. Criteria for quantifying the extent of "tumor response" observed within a few cycles of treatment have been established for various types of solid as well as hematologic malignancies. These measures comprise the primary endpoints of phase II trials. Regulatory approvals of new cancer therapies, however, are usually contingent upon the demonstration of superior overall survival with randomized evidence acquired with a phase III trial comparing the novel therapy to an appropriate standard of care treatment. With nearly two thirds of phase III oncology trials failing to achieve statistically significant results, researchers continue to refine and propose new surrogate endpoints. This article presents a Bayesian framework for studying relationships among treatment, patient subgroups, tumor response and survival. Combining classical components of mediation analysis with Bayesian model averaging (BMA), the methodology is robust to model mis-specification among various possible relationships among the observable entities. Posterior inference is demonstrated via application to a randomized controlled phase III trial in metastatic colorectal cancer. Moreover, the article details posterior predictive distributions of survival and statistical metrics for quantifying the extent of direct and indirect, or tumor response mediated, treatment effects.

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“…The utility of an early clinical outcome as a good surrogate measure requires that the endpoints are likely to have a strong relationship to each other and that the change in surrogate outcome captures a large proportion of the treatment effect on meaningful outcomes such as OS ( 11 , 29 , 30 ). Among the methods developed to assess the predictive value of a surrogate outcome, trial-level surrogate validation in considered the most suited for regulatory approvals ( 11 , 29 ).…”

Section: Methodsmentioning

confidence: 99%

Correlation Between Early Time-to-Event Outcomes and Overall Survival in Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma Receiving Definitive Chemoradiation Therapy: Systematic Review and Meta-Analysis

Black

Keeping²,

Mojebi³

et al. 2022

Front. Oncol.

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BackgroundOverall survival (OS) is the most patient-relevant outcome in oncology; however, in early cancers, large sample sizes and extended follow-up durations are needed to detect statistically significant differences in OS between interventions. Use of early time-to-event outcomes as surrogates for OS can help facilitate faster approval of cancer therapies. In locally advanced head and neck squamous cell carcinoma (LA-HNSCC), event-free survival (EFS) was previously evaluated as a surrogate outcome (Michiels 2009) and demonstrated a strong correlation with OS. The current study aimed to further assess the correlation between EFS and OS in LA-HNSCC using an updated systematic literature review (SLR) focusing on patients receiving definitive chemoradiation therapy (CRT).MethodsAn SLR was conducted on May 27, 2021 to identify randomized controlled trials assessing radiotherapy alone or CRT in the target population. Studies assessing CRT and reporting hazard ratios (HRs) or Kaplan-Meier data for OS and EFS were eligible for the analysis. CRT included any systemic treatments administered concurrently or sequentially with radiation therapy. Trial-level EFS/OS correlations were assessed using regression models, and the relationship strength was measured with Pearson correlation coefficient (R). Correlations were assessed across all CRT trials and in trial subsets assessing concurrent CRT, sequential CRT, RT+cisplatin, targeted therapies and intensity-modulated RT. Subgroup analysis was conducted among trials with similar EFS definitions (i.e. EFS including disease progression and/or death as events) and longer length of follow-up (i.e.≥ 5 years).ResultsThe SLR identified 149 trials of which 31 were included in the analysis. A strong correlation between EFS and OS was observed in the overall analysis of all CRT trials (R=0.85, 95% confidence interval: 0.72-0.93). Similar results were obtained in the sensitivity analyses of trials assessing concurrent CRT (R=0.88), sequential CRT (R=0.83), RT+cisplatin (R=0.82), targeted therapies (R=0.83) and intensity-modulated RT (R=0.86), as well as in trials with similar EFS definitions (R=0.87), with longer follow-up (R=0.81).ConclusionEFS was strongly correlated with OS in this trial-level analysis. Future research using individual patient-level data can further investigate if EFS could be considered a suitable early clinical endpoint for evaluation of CRT regimens in LA-HNSCC patients receiving definitive CRT.

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Bayesian hierarchical meta‐analytic methods for modeling surrogate relationships that vary across treatment classes using aggregate data

Cited by 21 publications

References 46 publications

A survival mediation model with Bayesian model averaging

A survival mediation model with Bayesian model averaging

A Survival Mediation Model with Bayesian Model Averaging

Correlation Between Early Time-to-Event Outcomes and Overall Survival in Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma Receiving Definitive Chemoradiation Therapy: Systematic Review and Meta-Analysis

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