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A method to address between-subject heterogeneity for identification of principal surrogate markers in repeated low-dose challenge HIV vaccine studies.

ABSTRACT: Repeated low-dose challenge designs in nonhuman primate studies have recently received attention in the literature as a means of evaluating vaccines for HIV prevention and identifying immune surrogates for their protective effects. Existing methods for surrogate identification in this type of study design rely on the assumption of homogeneity across subjects (namely, independent infection risks after each challenge within each subject and conditional on covariates). In practice, random variation across subjects is likely to occur because of unmeasured biologic factors. Failure to account for this heterogeneity or within-subject correlation can result in biased inference regarding the surrogate value of immune biomarkers and underpowered study designs for detecting surrogate endpoints. In this paper, we adopt a discrete-time survival model with random effects to account for between-subject heterogeneity, and we develop estimators and testing procedures for evaluating principal surrogacy of immune biomarkers. Simulation studies reveal that the heterogeneous model achieves substantial bias reduction compared to the homogeneous model, with little cost of efficiency. We recommend the use of this heterogeneous model as a complementary tool to existing methods when designing and analyzing repeated low-dose challenge studies for evaluating surrogate endpoints.

SUBMITTER: Spieker AJ

PROVIDER: S-EPMC5669638 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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A method to address between-subject heterogeneity for identification of principal surrogate markers in repeated low-dose challenge HIV vaccine studies.

Spieker Andrew J AJ Huang Ying Y

Statistics in medicine 20170731 25

Repeated low-dose challenge designs in nonhuman primate studies have recently received attention in the literature as a means of evaluating vaccines for HIV prevention and identifying immune surrogates for their protective effects. Existing methods for surrogate identification in this type of study design rely on the assumption of homogeneity across subjects (namely, independent infection risks after each challenge within each subject and conditional on covariates). In practice, random variation ...[more]

PMID: 28758224

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Project description:The promise of 'personalized cancer care' with therapies toward specific molecular aberrations has potential to improve outcomes. However, there is recognized heterogeneity within any given tumor-type from patient to patient (inter-patient heterogeneity), and within an individual (intra-patient heterogeneity) as demonstrated by molecular evolution through space (primary tumor to metastasis) and time (after therapy). These issues have become hurdles to advancing cancer treatment outcomes with novel molecularly targeted agents. Classic trial design paradigms are challenged by heterogeneity, as they are unable to test targeted therapeutics against low frequency genomic 'oncogenic driver' aberrations with adequate power. Usual accrual difficulties to clinical trials are exacerbated by low frequencies of any given molecular driver. To address these challenges, there is need for innovative clinical trial designs and strategies implementing novel diagnostic biomarker technologies to account for inter-patient molecular diversity and scarce tissue for analysis. Importantly, there is also need for pre-defined treatment priority algorithms given numerous aberrations commonly observed within any one individual sample. Access to multiple available therapeutic agents simultaneously is crucial. Finally intra-patient heterogeneity through time may be addressed by serial biomarker assessment at the time of tumor progression. This report discusses various 'next-generation' biomarker-driven trial designs and their potentials and limitations to tackle these recognized molecular heterogeneity challenges. Regulatory hurdles, with respect to drug and companion diagnostic development and approval, are considered. Focus is on the 'Expansion Platform Design Types I and II', the latter demonstrated with a first example, 'PANGEA: Personalized Anti-Neoplastics for Gastro-Esophageal Adenocarcinoma'. Applying integral medium-throughput genomic and proteomic assays along with a practical biomarker assessment and treatment algorithm, 'PANGEA' attempts to address the problem of heterogeneity towards successful implementation of molecularly targeted therapies.

Dataset Information

A method to address between-subject heterogeneity for identification of principal surrogate markers in repeated low-dose challenge HIV vaccine studies.

Publications

A method to address between-subject heterogeneity for identification of principal surrogate markers in repeated low-dose challenge HIV vaccine studies.

Similar Datasets

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