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Two-stage stratified designs with survival outcomes and adjustment for misclassification in predictive biomarkers

STATISTICS IN MEDICINE 2024年第10期43卷 1883-1904页

作者： Chen, Yanping Lin, Yong Lu, Shou-En Shih, Weichung J. Quan, Hui Bristol Myers Squibb Dept Biostat Berkeley Hts NJ USA Rutgers State Univ Sch Publ Hlth Biostat & Epidemiol Dept Piscataway NJ USA Rutgers Canc Inst New Jersey Biometr Div New Brunswick NJ USA Sanofi Biostat & Programming Bridgewater NJ USA Rutgers State Univ Sch Publ Hlth Biostat & Epidemiol Dept 683 Hoes Lane WestRM 214 Piscataway NJ 08854 USA

Biomarker stratified clinical trial designs are versatile tools to assess biomarker clinical utility and address its relationship with clinical endpoints. Due to imperfect assays and/or classification rules, biomarker status is prone to errors. To account for biomarker misclassification, we consider a two-stage stratified design for survival outcomes with an adjustment for misclassification in predictive biomarkers. Compared to continuous and/or binary outcomes, the test statistics for survival outcomes with an adjustment for biomarker misclassification is much more complicated and needs to take special care. We propose to use the information from the observed biomarker status strata to construct adjusted log-rank statistics for true biomarker status strata. These adjusted log-rank statistics are then used to develop sequential tests for the global (composite) hypothesis and component-wise hypothesis. We discuss the power analysis with the control of the type-I error rate by using the correlations between the adjusted log-rank statistics within and between the design stages. Our method is illustrated with examples of the recent successful development of immunotherapy in nonsmall-cell lung cancer.

关键词： adjusted log-rank statistics composite Hypothesis predictive biomarker sensitivity and specificity survival outcome

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Approaches to handling data when a phase II trial deviates from the pre-specified Simon's two-stage design

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STATISTICS IN MEDICINE 2008年第29期27卷 6190-6208页

作者： Wu, Yujun Shih, Weichung J. Univ Med & Dent New Jersey Canc Inst New Jersey Sch Publ Hlth Dept Biostat Piscataway NJ 08854 USA Univ Med & Dent New Jersey Canc Inst New Jersey Div Biometr Piscataway NJ 08854 USA Sanofi Aventis Dept Biostat & Programming Bridgewater NJ USA

Simon's 'optimal' and 'minimax' two-stage designs are common methods for conducting phase IIA studies investigating new cancer therapies. However. these designs are rather rigid in their settings because of the pre-specified rejection rules and fixed sample sizes at each stage. In practice, we often encounter the problem that a study is unable to adhere to the event number and sample sizes of the original two-stage design. In this paper, we consider some approaches in handling situations where deviations or interruptions from the original Simon's two-stage design occur because recruitment of patients is slower than expected. We consider four scenarios and use conditional probabilities to address the issues commonly inquired by the scientific review board. We also discuss how to report p-values in these situations. Copyright (C) 2008 John Wiley & Sons, Ltd.

关键词： phase IIA cancer trial Simon's two-stage design conditional probability p-value

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Hypothesis tests for stratified mark-specific proportional hazards models with missing covariates, with application to HIV vaccine efficacy trials

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BIOMETRICAL JOURNAL 2018年第3期60卷 516-536页

作者： Sun, Yanqing Qi, Li Yang, Guangren Gilbert, Peter B. Univ North Carolina Charlotte Dept Math & Stat Charlotte NC 28223 USA Sanofi Biostat & Programming Bridgewater MA 08807 USA Jinan Univ Sch Econ Dept Stat Guangzhou Guangdong Peoples R China Univ Washington Dept Biostat Seattle WA 98109 USA Fred Hutchinson Canc Res Ctr Seattle WA 98109 USA

This article develops hypothesis testing procedures for the stratified mark-specific proportional hazards model with missing covariates where the baseline functions may vary with strata. The mark-specific proportional hazards model has been studied to evaluate mark-specific relative risks where the mark is the genetic distance of an infecting HIV sequence to an HIV sequence represented inside the vaccine. This research is motivated by analyzing the RV144 phase 3 HIV vaccine efficacy trial, to understand associations of immune response biomarkers on the mark-specific hazard of HIV infection, where the biomarkers are sampled via a two-phase sampling nested case-control design. We test whether the mark-specific relative risks are unity and how they change with the mark. The developed procedures enable assessment of whether risk of HIV infection with HIV variants close or far from the vaccine sequence are modified by immune responses induced by the HIV vaccine;this question is interesting because vaccine protection occurs through immune responses directed at specific HIV sequences. The test statistics are constructed based on augmented inverse probability weighted complete-case estimators. The asymptotic properties and finite-sample performances of the testing procedures are investigated, demonstrating double-robustness and effectiveness of the predictive auxiliaries to recover efficiency. The finite-sample performance of the proposed tests are examined through a comprehensive simulation study. The methods are applied to the RV144 trial.

关键词： augmented inverse probability weighting auxiliary variables competing risks failure time data hypothesis testing semiparametric model two-phase sampling

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Mark-specific additive hazards regression with continuous marks

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LIFETIME DATA ANALYSIS 2017年第3期23卷 467-494页

作者： Han, Dongxiao Sun, Liuquan Sun, Yanqing Qi, Li Chinese Acad Sci Inst Appl Math Beijing 100190 Peoples R China Univ North Carolina Charlotte Dept Math & Stat Charlotte NC 28223 USA Sanofi Biostat & Programming Bridgewater NJ 08807 USA

For survival data, mark variables are only observed at uncensored failure times, and it is of interest to investigate whether there is any relationship between the failure time and the mark variable. The additive hazards model, focusing on hazard differences rather than hazard ratios, has been widely used in practice. In this article, we propose a mark-specific additive hazards model in which both the regression coefficient functions and the baseline hazard function depend nonparametrically on a continuous mark. An estimating equation approach is developed to estimate the regression functions, and the asymptotic properties of the resulting estimators are established. In addition, some formal hypothesis tests are constructed for various hypotheses concerning the mark-specific treatment effects. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a data set from the first HIV vaccine efficacy trial is provided.

关键词： Additive hazards model Competing risks Confidence bands and tests Continuous mark HIV vaccine trial Mark-specific vaccine effects Survival data

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Analysis of generalized semiparametric mixed varying-coefficients models for longitudinal data

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CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE 2019年第3期47卷 352-373页

作者： Sun, Yanqing Qi, Li Heng, Fei Gilbert, Peter B. Univ North Carolina Charlotte Dept Math & Stat Charlotte NC 28223 USA Sanofi Biostat & Programming Bridgewater NJ 08807 USA Univ Washington Dept Biostat Seattle WA 98195 USA Fred Hutchinson Canc Res Ctr Stat Ctr HIV AIDS Res & Prevent Seattle WA 98109 USA

The generalized semiparametric mixed varying-coefficient effects model for longitudinal data can accommodate a variety of link functions and flexibly model different types of covariate effects, including time-constant, time-varying and covariate-varying effects. The time-varying effects are unspecified functions of time and the covariate-varying effects are nonparametric functions of a possibly time-dependent exposure variable. A semiparametric estimation procedure is developed that uses local linear smoothing and profile weighted least squares, which requires smoothing in the two different and yet connected domains of time and the time-dependent exposure variable. The asymptotic properties of the estimators of both nonparametric and parametric effects are investigated. In addition, hypothesis testing procedures are developed to examine the covariate effects. The finite-sample properties of the proposed estimators and testing procedures are examined through simulations, indicating satisfactory performances. The proposed methods are applied to analyze the AIDS Clinical Trial Group 244 clinical trial to investigate the effects of antiretroviral treatment switching in HIV-infected patients before and after developing the T215Y antiretroviral drug resistance mutation. The Canadian Journal of Statistics 47: 352-373;2019 (c) 2019 Statistical Society of Canada

关键词： Link function local linear smoothing profile weighted least squares testing covariate-varying effects varying-coefficient effects

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Evaluation of Normalization Methods To Predict CYP3A4 Induction in Six Fully Characterized Cryopreserved Human Hepatocyte Preparations and HepaRG Cells

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DRUG METABOLISM AND DISPOSITION 2016年第1期44卷 50-60页

作者： Vermet, Helene Raoust, Nathalie Ngo, Robert Essermeant, Luc Klieber, Sylvie Fabre, Gerard Boulenc, Xavier Sanofi Rech & Dev Drug Disposit Domain Disposit Safety & Anim Res S F-34184 Montpellier France Sanofi Rech & Dev Biostat & Programming Clin Sci & Operat Sci Core F-34184 Montpellier France

Prediction of drug-drug interactions due to cytochrome P450 isoform 3A4 (CYP3A4) overexpression is important because this CYP isoform is involved in the metabolism of about 30% of clinically used drugs from almost all therapeutic categories. Therefore, it is mandatory to attempt to predict the potential of a new compound to induce CYP3A4. Among several in vitro-in vivo extrapolation methods recently proposed in the literature, an approach using a scaling factor, called a d factor, for a given hepatocyte batch to provide extrapolation between in vitro induction data and clinical outcome has been adopted by leading health authorities. We challenged the relevance of the calibration factor determined using a set of 15 well-known clinical CYP3A4 inducers or the potent CYP3A4 inducer rifampicin only. These investigations were conducted using six batches of human hepatocytes and an established HepaRG cell line. Our findings show that use of a calibration factor is preferable for clinical predictions, as shown previously by other investigators. Moreover, the present results also suggest that the accuracy of prediction through calculation of this factor is sufficient when rifampicin is considered alone, and the use of a larger set of fully characterized CYP3A4 clinical inducers is not required. For the established HepaRG cell line, the findings obtained in three experiments using a single batch of cells show a good prediction accuracy with or without the d factor. Additional investigations with different batches of HepaRG cell lines are needed to confirm these results.

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Pharmacokinetic Variability of Long-Acting Stimulants in the Treatment of Children and Adults with Attention-Deficit Hyperactivity Disorder

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CNS DRUGS 2010年第12期24卷 1009-1025页

作者： Ermer, James C. Adeyi, Ben A. Pucci, Michael L. Shire Dev Inc Pharmaceut Sci Clin Pharmacol & Pharmacokinet Wayne PA USA Shire Dev Inc Biostat & Stat Programming Wayne PA USA Ogilvy CommonHlth Sci Commun Med Affairs Parsippany NJ USA

Methylphenidate- and amfetamine-based stimulants are first-line pharmacotherapies for attention-deficit hyperactivity disorder, a common neurobehavioural disorder in children and adults. A number of long-acting stimulant formulations have been developed with the aim of providing once-daily dosing, employing various means to extend duration of action, including a transdermal delivery system, an osmotic-release oral system, capsules with a mixture of immediate-and delayed-release beads, and prodrug technology. Coefficients of variance of pharmacokinetic measures can estimate the levels of pharmacokinetic variability based on the measurable variance between different individuals receiving the same dose of stimulant (interindividual variability) and within the same individual over multiple administrations (intraindividual variability). Differences in formulation clearly impact pharmacokinetic profiles. Many medications exhibit wide interindividual variability in clinical response. Stimulants with low levels of inter- and intraindividual variability may be better suited to provide consistent levels of medication to patients. The pharmacokinetic profile of stimulants using pH-dependent bead technology can vary depending on food consumption or concomitant administration of medications that alter gastric pH. While delivery of methylphenidate with the transdermal delivery system would be unaffected by gastrointestinal factors, intersubject variability is nonetheless substantial. Unlike the beaded formulations and, to some extent (when considering total exposure) the osmotic-release formulation, systemic exposure to amfetamine with the prodrug stimulant lisdexamfetamine dimesylate appears largely unaffected by such factors, likely owing to its dependence on systemic enzymatic cleavage of the precursor molecule, which occurs primarily in the blood involving red blood cells. The high capacity but as yet unidentified enzymatic system for conversion of lisdexamfetamine dimesylate

关键词： TREATMENT of attention-deficit hyperactivity disorder NEUROBEHAVIORAL disorders DISEASE risk factors PATIENT monitoring PHARMACOKINETICS MEDICAL research TREATMENT

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An Alternative Way to Classify Missing Data Mechanism in Clinical TrialsA Dialogue on Missing Data

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JOURNAL OF BIOPHARMACEUTICAL STATISTICS 2011年第2期21卷 355-361页

作者： Wei, Lynn Sanofi Aventis US Biostat & Programming Bridgewater NJ 08807 USA

Statisticians in pharmaceutical field are constantly challenged by missing data caused by patient dropout in clinical trials. What the targeted population parameter for statistical inference should be when missing data are present has been a much-debated point. Many missing data methods aim at the so-called hypothetical parameter, i.e., treatment effect of a drug assuming no patients dropout from a clinical trial for the drug. Other methods intend to combine all dropout information into the treatment effect estimate. We believe that patient dropouts should not be treated equally when determining the population parameter of treatment effect. The objective of clinical trials, after all, is to evaluate a drug's effect on patients. Dropouts due to drug-related reasons such as drug-induced adverse experience are part of the drug's attributes, while dropout due to non-drug-related reasons, such as protocol deviation, are not inherent characteristics of the drug. Hence we propose to classify the patient dropouts into two classes: intrinsic (drug-related) and extrinsic (non-drug-related) dropouts. The former should be taken into account when defining the population parameter of the treatment effect, while the latter should not be. This classification will help determine a target population parameter that depicts a fair picture of a drug's effect, while the common classification of missing data as missing completely random (MCAR), missing at random (MAR), and missing not at random (MNAR) will help define appropriate statistical approach to analysis when missing data exist. Other related issues, such as statistical inference under this classification and implementing the classification in real clinical trials, are also touched upon here.

关键词： Extrinsic Intrinsic Missing data in clinical trials

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The probability of observing negative subgroup results when the treatment effect is positive and homogeneous across all subgroups

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DRUG INFORMATION JOURNAL 2007年第1期41卷 47-56页

作者： Li, Zhengqing Chuang-Stein, Christy Hoseyni, Cyrus Bristol Myers Squibb Co Global Biometr Sci Wallingford CT 06492 USA Pfizer Global Res & Dev Clin Stat Ann Arbor MI USA Wyeth Pharmaceut Global Biostat & Programming Collegeville PA USA

Subgroup analysis is an important part in the design and analysis of clinical trials. The importance arises from the scientific and commercial implications of such analysis. The predominant concerns about subgroup analysis related to the increased false-positive and false-negative rates. Much of the existing literature on subgroup analysis focuses on the former. In this article, we will concentrate on the false-negative aspect. Using theoretical derivation and simulations, we investigate factors that affect the probability of observing at least one negative subgroup result (ie, numerically negative treatment effect estimate) even though the true treatment effect is positive (ie, the new treatment is more efficacious than the comparator) and homogeneous across all subgroups. This probability, conditioning or unconditioning on a statistically significant overall treatment effect, is assessed for design scenarios that are commonly encountered in practice. In additions, we assess the probability of observing at least one statistically significant negative sub-group result, again conditioning or unconditioning on a statistically significant overall treatment effect. We submit that knowledge of such probabilities could provide clinical researchers with insight into the reliability of subgroup results and help set proper expectations vis-a-vis such analysis. The later facilitates a balanced interpretation of subgroup results.

关键词： conditional probability effect size exploratory false-negative power

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Drug-Drug Interaction Study to Assess the Effect of Cytochrome P450 Inhibition and Induction on the Pharmacokinetics of the Novel Cereblon Modulator Avadomide (CC-122) in Healthy Adult Subjects

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JOURNAL OF CLINICAL PHARMACOLOGY 2019年第12期59卷 1620-1631页

作者： Ogasawara, Ken MacGorman, Kimberly Liu, Liangang Chen, Jian Carayannopoulos, Leonidas N. Zhou, Simon Palmisano, Maria Li, Yan Celgene Corp Translat Dev & Clin Pharmacol 556 Morris Ave Summit NJ 07901 USA Celgene Corp Biostat & Stat Programming Berkeley Hts NJ USA Celgene Corp Nonclin Dev Summit NJ USA

Avadomide (CC-122) is a novel immunomodulatory drug that binds to cereblon, a member of the Cullin 4-RING E3 ubiquitin ligase complex. Avadomide has multiple pharmacologic activities including potent immune modulation, antiangiogenic, antitumor, and antiproliferative activity and is being evaluated as an oncology treatment for hematologic malignancies and advanced solid tumors. In vitro study has indicated that cytochrome P450 (CYP) 3A and CYP1A2 appear to be the major enzymes involved in the oxidative metabolism of avadomide. The effects of CYP3A inhibition/induction and CYP1A2 inhibition on the pharmacokinetics of avadomide in healthy adult subjects were assessed in 3 parts of an open-label, nonrandomized, 2-period, single-sequence crossover study. Following a single oral dose of 3 mg, avadomide exposure when coadministered with the CYP1A2 inhibitor fluvoxamine was 154.81% and 107.59% of that when administered alone, for area under the plasma concentration-time curve from time 0 to infinity (AUC(0-inf)) and maximum observed plasma concentration (C-max), respectively. Avadomide exposures, when coadministered with the CYP3A inhibitor itraconazole, were 100.0% and 93.64% of that when administered alone, for AUC(0-inf) and C-max, respectively. Avadomide exposures when coadministered with the CYP3A inducer rifampin were 62.83% and 88.17% of that when administered alone, for AUC(0-inf) and C-max, respectively. Avadomide was well tolerated when administered as a single oral dose of 3 mg alone or coadministered with fluvoxamine, itraconazole, or rifampin. These results should serve as the basis for avadomide dose recommendations when it is coadministered with strong CYP3A and CYP1A2 inhibitors and with rifampin.

关键词： avadomide CYP3A drug-drug interactions immunomodulatory drug

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