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Using a surrogate marker for early testing of a treatment effect.

ABSTRACT: The development of methods to identify, validate, and use surrogate markers to test for a treatment effect has been an area of intense research interest given the potential for valid surrogate markers to reduce the required costs and follow-up times of future studies. Several quantities and procedures have been proposed to assess the utility of a surrogate marker. However, few methods have been proposed to address how one might use the surrogate marker information to test for a treatment effect at an earlier time point, especially in settings where the primary outcome and the surrogate marker are subject to censoring. In this paper, we propose a novel test statistic to test for a treatment effect using surrogate marker information measured prior to the end of the study in a time-to-event outcome setting. We propose a robust nonparametric estimation procedure and propose inference procedures. In addition, we evaluate the power for the design of a future study based on surrogate marker information. We illustrate the proposed procedure and relative power of the proposed test compared to a test performed at the end of the study using simulation studies and an application to data from the Diabetes Prevention Program.

SUBMITTER: Parast L

PROVIDER: S-EPMC6810708 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Using a surrogate marker for early testing of a treatment effect.

Parast Layla L Cai Tianxi T Tian Lu L

Biometrics 20190422 4

The development of methods to identify, validate, and use surrogate markers to test for a treatment effect has been an area of intense research interest given the potential for valid surrogate markers to reduce the required costs and follow-up times of future studies. Several quantities and procedures have been proposed to assess the utility of a surrogate marker. However, few methods have been proposed to address how one might use the surrogate marker information to test for a treatment effect ...[more]

PMID: 31009073

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Project description:BACKGROUND: Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images), such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r) is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. METHODOLOGY/PRINCIPAL FINDINGS: The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions) of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform). Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. CONCLUSIONS/SIGNIFICANCE: The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy). We explore the potential of the method for association tests involving a lattice of binary data and discuss its potential for validation of species distribution models. An implementation of the method in Java for the generation of wavelet-based surrogates is available online as supporting material.

Project description:PurposeSecond-generation tau radiotracers for use with positron emission tomography (PET) have been developed for visualization of tau deposits in vivo. For several β-amyloid and first-generation tau-PET radiotracers, it has been shown that early-phase images can be used as a surrogate of neuronal injury. Therefore, we investigated the performance of early acquisitions of the novel tau-PET radiotracer [18F]PI-2620 as a potential substitute for [18F]fluorodeoxyglucose ([18F]FDG).MethodsTwenty-six subjects were referred with suspected tauopathies or overlapping parkinsonian syndromes (Alzheimer's disease, progressive supranuclear palsy, corticobasal syndrome, multi-system atrophy, Parkinson's disease, multi-system atrophy, Parkinson's disease, frontotemporal dementia) and received a dynamic [18F]PI-2620 tau-PET (0-60 min p.i.) and static [18F]FDG-PET (30-50 min p.i.). Regional standardized uptake value ratios of early-phase images (single frame SUVr) and the blood flow estimate (R1) of [18F]PI-2620-PET were correlated with corresponding quantification of [18F]FDG-PET (global mean/cerebellar normalization). Reduced tracer uptake in cortical target regions was also interpreted visually using 3-dimensional stereotactic surface projections by three more and three less experienced readers. Spearman rank correlation coefficients were calculated between early-phase [18F]PI-2620 tau-PET and [18F]FDG-PET images for all cortical regions and frequencies of disagreement between images were compared for both more and less experienced readers.ResultsHighest agreement with [18F]FDG-PET quantification was reached for [18F]PI-2620-PET acquisition from 0.5 to 2.5 min p.i. for global mean (lowest R = 0.69) and cerebellar scaling (lowest R = 0.63). Correlation coefficients (summed 0.5-2.5 min SUVr & R1) displayed strong agreement in all cortical target regions for global mean (RSUVr 0.76, RR1 = 0.77) and cerebellar normalization (RSUVr 0.68, RR1 = 0.68). Visual interpretation revealed high regional correlations between early-phase tau-PET and [18F]FDG-PET. There were no relevant differences between more and less experienced readers.ConclusionEarly-phase imaging of [18F]PI-2620 can serve as a surrogate biomarker for neuronal injury. Dynamic imaging or a dual time-point protocol for tau-PET imaging could supersede additional [18F]FDG-PET imaging by indexing both the distribution of tau and the extent of neuronal injury.

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Using a surrogate marker for early testing of a treatment effect.

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Using a surrogate marker for early testing of a treatment effect.

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