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Applications of Bayesian analysis to proof-of-concept trial planning and decision making

PHARMACEUTICAL STATISTICS 2020年第4期19卷 468-481页

作者： Quan, Hui Chen, Xun Lan, Yu Luo, Xiaodong Kubiak, Rene Bonnet, Nicolas Paux, Gautier Sanofi Biostat & Programming 55 Corp Dr Bridgewater NJ 08807 USA

Decision making is a critical component of a new drug development process. Based on results from an early clinical trial such as a proof of concept trial, the sponsor can decide whether to continue, stop, or defer the development of the drug. To simplify and harmonize the decision-making process, decision criteria have been proposed in the literature. One of them is to exam the location of a confidence bar relative to the target value and lower reference value of the treatment effect. In this research, we modify an existing approach by moving some of the "stop" decision to "consider" decision so that the chance of directly terminating the development of a potentially valuable drug can be reduced. As Bayesian analysis has certain flexibilities and can borrow historical information through an inferential prior, we apply the Bayesian analysis to the trial planning and decision making. Via a design prior, we can also calculate the probabilities of various decision outcomes in relationship with the sample size and the other parameters to help the study design. An example and a series of computations are used to illustrate the applications, assess the operating characteristics, and compare the performances of different approaches.

关键词： decision making design prior historical data borrowing inferential prior posterior distribution

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A variable selection approach for highly correlated predictors in high-dimensional genomic data

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BIOINFORMATICS 2021年第16期37卷 2238-2244页

作者： Zhu, Wencan Levy-Leduc, Celine Ternes, Nils Univ Paris Saclay AgroParisTech UMR MIA Paris INRAE F-75005 Paris France Sanofi R&D Biostat & Programming Dept F-91380 Chilly Mazarin France

Motivation: In genomic studies, identifying biomarkers associated with a variable of interest is a major concern in biomedical research. Regularized approaches are classically used to perform variable selection in high-dimensional linear models. However, these methods can fail in highly correlated settings. Results: We propose a novel variable selection approach called WLasso, taking these correlations into account. It consists in rewriting the initial high-dimensional linear model to remove the correlation between the biomarkers (predictors) and in applying the generalized Lasso criterion. The performance of WLasso is assessed using synthetic data in several scenarios and compared with recent alternative approaches. The results show that when the biomarkers are highly correlated, WLasso outperforms the other approaches in sparse high-dimensional frameworks. The method is also illustrated on publicly available gene expression data in breast cancer.

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A multi-arm two-stage (MATS) design for proof-of-concept and dose optimization in early-phase oncology trials

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CONTEMPORARY CLINICAL TRIALS 2023年第1期132卷 107278-107278页

作者： Jiang, Zhenghao Mi, Gu Lin, Ji Lorenzato, Christelle Ji, Yuan Univ Chicago Dept Stat 5747 South Ellis Ave Chicago IL 60637 USA Sanofi Biostat & Programming 450 Water St Cambridge MA 02141 USA Sanofi R&D Biostat & Programming Vitry sur Seine France Univ Chicago Dept Publ Hlth Sci 5841 South Maryland Ave Chicago IL 60637 USA

The Project Optimus initiative by the FDA's Oncology Center of Excellence is widely viewed as a groundbreaking effort to change the status quo of conventional dose-finding strategies in oncology. Unlike in other therapeutic areas where multiple doses are evaluated thoroughly in dose ranging studies, early-phase oncology dose-finding studies are characterized by the practice of identifying a single dose, such as the maximum tolerated dose (MTD) or the recommended phase 2 dose (RP2D). Following the spirit of Project Optimus, we propose an Multi-Arm Two-Stage (MATS) design for proof-of-concept (PoC) and dose optimization that allows the evaluation of two selected doses from a dose-escalation trial. The design assesses the higher dose first across multiple indications in the first stage, and adaptively enters the second stage for an indication if the higher dose exhibits promising antitumor activities. In the second stage, a randomized comparison between the higher and lower doses is conducted to achieve PoC and dose optimization. A Bayesian hierarchical model governs the statistical inference and decision making by borrowing information across doses, indications, and stages. Our simulation studies show that the proposed MATS design yield desirable performance. An R Shiny application has been developed and made available at https://***/mats/.

关键词： Bayesian hierarchical model Oncology Project Optimus Proof-of-concept

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Seamless phase II/III/IIIb clinical trial designs with different endpoints for different phases

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2020年第22期49卷 5436-5454页

作者： Quan, Hui Luo, Xiaodong Zhou, Tianyue Zhao, Peng-Liang Sanofi Biostat & Programming 55C-335A55 Corp Dr Bridgewater MA 08807 USA

In a seamless phase II/III/IIIb trial, K (K >= 2) doses versus placebo control are evaluated at phase II. Based on phase II results, one dose will be selected for phases III and IIIb. Pre-specified additional numbers of patients will be enrolled into the selected dose and placebo control during phases III and IIIb. Results of the phase III endpoint may be submitted for an early New Drug Application. Final analyses will be conducted for ultimate claims of treatment effects for the selected dose on the phase III and IIIb endpoints. Multiplicity adjustment is performed for the overall type I error rate control.

关键词： Multiplicity adjustment combination test conditional power estimation of treatment effect

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Improved patient-reported outcomes with iGlarLixi versus premix BIAsp 30 in people with type 2 diabetes in the SoliMix trial

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DIABETES OBESITY & METABOLISM 2022年第12期24卷 2364-2372页

作者： Polonsky, William H. Giorgino, Francesco Rosenstock, Julio Whitmire, Katherine Lew, Elisheva Coudert, Mathieu Alvarez, Agustina Nicholls, Charlie McCrimmon, Rory J. Behav Diabet Inst 5230 Carroll Canyon Rd San Diego CA 92121 USA Univ Bari Aldo Moro Dept Emergency & Organ Transplantat Sect Internal Med Endocrinol Androl & Metab Dis Bari Italy Dallas Diabet Res Ctr Med City Dallas TX USA Southwest Med Associates Las Vegas NV USA Sanofi Chilly Mazarin France Sanofi Biostat & Programming Dept Chilly Mazarin France Sanofi Buenos Aires DF Argentina Sanofi Reading Berks England Univ Dundee Sch Med Div Syst Med Dundee Scotland

Aim To assess patient-reported outcomes (PROs) in the SoliMix trial, which compared the efficacy and safety of iGlarLixi versus BIAsp 30 in people with type 2 diabetes (T2D). Materials and Methods SoliMix (EudraCT: 2017-003370-13), a 26-week, open-label study, randomized (1:1) 887 adults with T2D and HbA1c >= 7.5%-<= 10.0% (>= 58-<= 86 mmol/mol) on basal insulin plus oral antihyperglycaemic drugs (OADs) to once-daily iGlarLixi or twice-daily premix insulin, BIAsp 30. PROs were assessed using the Treatment-Related Impact Measure Diabetes (TRIM-D) and Global Treatment Effectiveness Evaluation (GTEE) questionnaires. Results Over 26 weeks, iGlarLixi showed greater improvement from baseline versus BIAsp 30 in total TRIM-D score (least squares mean difference [95% confidence interval]: 5.08 [3.69, 6.47];effect size: 0.32) and in each TRIM-D domain, with the greatest differences seen in diabetes management (8.47 [6.11, 10.84]) and treatment burden (6.95 [4.83, 9.07]). GTEE scores showed a greater proportion of participants and physicians rated a complete or marked improvement of diabetes control with iGlarLixi (80.5%, 82.8%) versus BIAsp 30 (63.3%, 65.1%) at week 26. Post hoc analyses showed that after adjusting for HbA1c, body weight and hypoglycaemia outcomes, iGlarLixi continued to show greater improvements in TRIM-D total scores versus BIAsp 30. Conclusions In addition to better glycaemic control, weight benefit and less hypoglycaemia, once-daily iGlarLixi provided improved diabetes management, treatment burden and perceived effectiveness versus twice-daily premix BIAsp 30, further supporting iGlarLixi as an advanced treatment option in people with suboptimally controlled T2D on basal insulin plus OADs.

关键词： basal insulin GLP-1 analogue glycaemic control iGlarLixi patient-reported outcomes type 2 diabetes

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A model-based clustering via mixture of hierarchical models with covariate adjustment for detecting differentially expressed genes from paired design

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BMC BIOINFORMATICS 2023年第1期24卷 423-423页

作者： Zhang, Yixin Liu, Wei Qiu, Weiliang Univ Sci & Technol China Sch Math Sci Hefei Anhui Peoples R China York Univ Dept Math & Stat Toronto ON Canada Sanofi Dept Biostat & Programming Cambridge MA USA

The causes of many complex human diseases are still largely unknown. Genetics plays an important role in uncovering the molecular mechanisms of complex human diseases. A key step to characterize the genetics of a complex human disease is to unbiasedly identify disease-associated gene transcripts on a whole-genome scale. Confounding factors could cause false positives. Paired design, such as measuring gene expression before and after treatment for the same subject, can reduce the effect of known confounding factors. However, not all known confounding factors can be controlled in a paired/match design. Model-based clustering, such as mixtures of hierarchical models, has been proposed to detect gene transcripts differentially expressed between paired samples. To the best of our knowledge, no model-based gene clustering methods have the capacity to adjust for the effects of covariates yet. In this article, we proposed a novel mixture of hierarchical models with covariate adjustment in identifying differentially expressed transcripts using high-throughput whole-genome data from paired design. Both simulation study and real data analysis show the good performance of the proposed method.

关键词： Curse of dimensionality Confounding EM algorithm RNAseq

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ZIAQ: a quantile regression method for differential expression analysis of single-cell RNA-seq data

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BIOINFORMATICS 2020年第10期36卷 3124-3130页

作者： Zhang, Wenfei Wei, Ying Zhang, Donghui Xu, Ethan Y. Sanofi Dept Biostat & Programming Framingham MA 01701 USA Columbia Univ Dept Biostat New York NY 10032 USA Sanofi Translat Sci Framingham MA 01701 USA

Motivation: Single-cell RNA sequencing (scRNA-seq) has enabled the simultaneous transcriptomic profiling of individual cells under different biological conditions. scRNA-seq data have two unique challenges that can affect the sensitivity and specificity of single-cell differential expression analysis: a large proportion of expressed genes with zero or low read counts ('dropout' events) and multimodal data distributions. Results: We have developed a zero-inflation-adjusted quantile (ZIAQ) algorithm, which is the first method to account for both dropout rates and complex scRNA-seq data distributions in the same model. ZIAQ demonstrates superior performance over several existing methods on simulated scRNA-seq datasets by finding more differentially expressed genes. When ZIAQ was applied to the comparison of neoplastic and non-neoplastic cells from a human glioblastoma dataset, the ranking of biologically relevant genes and pathways showed clear improvement over existing methods.

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Bayesian modeling of a bivariate toxicity outcome for early phase oncology trials evaluating dose regimens

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STATISTICS IN MEDICINE 2021年第23期40卷 5096-5114页

作者： Gerard, Emma Zohar, Sarah Lorenzato, Christelle Ursino, Moreno Riviere, Marie-Karelle Univ Paris Sorbonne Univ Ctr Rech Cordeliers INSERM 15 Rue Ecole Med F-75006 Paris France INRIA HeKA Paris France Sanofi R&D Oncol Biostat Biostat & Programming Dept Vitry Sur Seine France Sanofi R&D Stat Methodol Grp Biostat & Programming Dept Chilly Mazarin France Univ Paris CHU Robert Debre AP HP Unit Clin EpidemiolINSERMU1123Sorbonne Paris C Paris France CIC EC 1426 Paris France

Most phase I trials in oncology aim to find the maximum tolerated dose (MTD) based on the occurrence of dose limiting toxicities (DLT). Evaluating the schedule of administration in addition to the dose may improve drug tolerance. Moreover, for some molecules, a bivariate toxicity endpoint may be more appropriate than a single endpoint. However, standard dose-finding designs do not account for multiple dose regimens and bivariate toxicity endpoint within the same design. In this context, following a phase I motivating trial, we proposed modeling the first type of DLT, cytokine release syndrome, with the entire dose regimen using pharmacokinetics and pharmacodynamics (PK/PD), whereas the other DLT (DLTo) was modeled with the cumulative dose. We developed three approaches to model the joint distribution of DLT, defining it as a bivariate binary outcome from the two toxicity types, under various assumptions about the correlation between toxicities: an independent model, a copula model and a conditional model. Our Bayesian approaches were developed to be applied at the end of the dose-allocation stage of the trial, once all data, including PK/PD measurements, were available. The approaches were evaluated through an extensive simulation study that showed that they can improve the performance of selecting the true MTD-regimen compared to the recommendation of the dose-allocation method implemented. Our joint approaches can also predict the DLT probabilities of new dose regimens that were not tested in the study and could be investigated in further stages of the trial.

关键词： Bayesian joint modeling bivariate toxicity cumulative probability of toxicity dose regimen early phase oncology pharmacokinetics pharmacodynamics

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Trial monitoring via a futility criterion for interim results on a count data endpoint and a continuous endpoint

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CONTEMPORARY CLINICAL TRIALS 2021年 103卷 106316-106316页

作者： Quan, Hui Kang, Tong Fan, Chunpeng Lu, Xin Chen, Xun Luo, Xiaodong Wei, Lynn Sanofi Biostat & Programming 55 Corp Dr Bridgewater NJ 08807 USA

Assumptions made at design stage regarding the true treatment effect, background event rate and other factors may not always hold. Thus, long-term and large-scale studies may be designed with an interim analysis in order that the trials may be stopped early due to futility to save resource. There are many considerations of trial conducts for this type of trials. In this paper, we use a mock study to illustrate systematically the thinking and procedures for trial monitoring with a futility criterion for the interim results on a count data endpoint and a continuous endpoint. We focus on the discussions of blinded trial monitoring, the probability of meeting the futility criterion, conditional power/probability of success, Bayesian inference, potential delayed treatment effect and subgroup analysis. The experience should be applicable to future studies with similar features.

关键词： Conditional power Probability of success Posterior distribution Decision making Delayed treatment effect Subgroup analysis

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Sargramostim (rhu GM-CSF) Improves Survival of Non-Human Primates with Severe Bone Marrow Suppression after Acute, High-Dose, Whole-Body Irradiation

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RADIATION RESEARCH 2021年第2期195卷 191-199页

作者： Clayton, Nicholas P. Khan-Malek, Richard C. Dangler, Charles A. Zhang, Donghui Ascah, Alexis Gains, Malcolm Gardner, Brent Mockbee, Colleen Keutzer, Joan M. McManus, John Authier, Simon Sanofi Genzyme Global Rare Dis Cambridge MA USA Sanofi Global Biostat & Programming Bridgewater NJ USA Sanofi Preclin Safety Framingham MA USA Liminal Biosci Laval PQ Canada Partner Therapeut Inc Lexington MA USA Charles River Labs 445 Boul Armand Frappier Laval PQ H7V 4B3 Canada

Exposure to acute, high-dose, whole-body ionizing radiation results in bone marrow failure (hematopoietic acute radiation syndrome with resultant infection, bleeding, anemia, and increased risk of death). Sargramostim (yeast-derived rhu GM-CSF), a yeast-derived, molecularly cloned, hematopoietic growth factor and pieiotropic cytokine supports proliferation, differentiation, maturation and survival of cells of several myeloid lineages. We evaluated the efficacy of sargramostim in non-human primates (rhesus macaques) exposed to whole-body ionizing radiation at a 50-60% lethal dose. The primary end point was day 60 survival. Non-human primates received daily subcutaneous sargramostim (7 mcg/kg/day) or control. To reflect the anticipated setting of a nuclear or radiologic event, treatment began 48 h postirradiation, and non-human primates received only moderate supportive care (no whole blood transfusions or individualized antibiotics). Sargramostim significantly increased day 60 survival to 78% (95% confidence interval, 61-90%) vs. 42% (26-59%;P = 0.0018) in controls. Neutrophil, platelet and lymphocyte recovery rates were accelerated and infection rates decreased. Improved survival when sargramostim was started 48 h postirradiation, without use of intensive supportive care, suggests sargramostim may be effective in treating humans exposed to acute, high-dose whole-body, ionizing radiation in a scenario such as a mass casualty event. (C) 2021 by Radiation Research Society

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