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Pediatric patients should have access to medicines that have been appropriately evaluated for safety and efficacy. Given this goal of revised labelling, the adequacy of the pediatric clinical development plan and resulting safety database must inform a favorable benefit-risk assessment for the intended use of the medicinal product. While extrapolation from adults can be used to support efficacy of drugs in children, there may be a reluctance to use the same approach in safety assessments, wiping out potential gains in trial efficiency through a reduction of sample size. To address this reluctance, we explore safety review in pediatric trials, including factors affecting these data, specific types of safety assessments, and precision on the estimation of event rates for specific adverse events (AEs) that can be achieved. In addition, we discuss the assessments which can provide a benchmark for the use of extrapolation of safety that focuses on on-target effects. Finally, we explore a unified approach for understanding precision using Bayesian approaches as the most appropriate methodology to describe/ascertain risk in probabilistic terms for the estimate of the event rate of specific AEs.

A fundamental problem in the regulatory evaluation of a therapy is assessing whether the benefit outweighs the associated risks. This work proposes designing a trial that assesses a composite endpoint consisting of benefit and risk, hence, making the core of the design of the study, to assess benefit and risk. The proposed benefit risk measure consists of efficacy measure(s) and a risk measure that is based on a composite score obtained from pre-defined adverse events of interest (AEI). This composite score incorporates full aspects of adverse events of interest (i.e. the incidence, severity, and duration of the events). We call this newly proposed score the AEI composite score. After specifying the priorities between the components of the composite endpoint, a win-statistic (i.e. win ratio, win odds, or net benefit) is used to assess the difference between treatments in this composite endpoint. The power and sample size requirements of such a trial design are explored via simulation. Finally, using Dupixent published adult study results, we show how we can design a paediatric trial where the primary outcome is a composite of prioritized outcomes consisting of efficacy endpoints and the AEI composite score endpoint. The resulting trial design can potentially substantially reduce sample size compared to a trial designed to assess the co-primary efficacy endpoints, therefore it may address the challenge of slow enrollment and patient availability for paediatric studies.

Background: Historically, pediatric medicines are developed after adult trials are completed, even when identical drug targets and disease similarities exist across the populations. This has resulted in significant delays in the authorization of medicines for adolescent use, limiting access to beneficial drugs. This study sought to understand how adolescent inclusion in adult trials is positioned in regulatory guidance documents as they set critical expectations for trial design and regulatory decision-making. Methods: This study utilized a qualitative analysis approach. Guidance documents were identified via Food and Drug Administration and European Medicines Agency websites. Utilizing a blinded adjudication process, the documents were classified as permissive, exclusionary, or silent regarding recommendations about adolescent inclusion in adult clinical trials. A post hoc analysis of similarities and differences between the Food and Drug Administration and European Medicines Agency guidance documents was conducted to assess the possible role of regional pediatric research laws on age-inclusive trial methodologies as well as emergent themes by therapeutic area. Results: In total, 96 Food and Drug Administration (1977 to 2019) and 106 European Medicines Agency (1987 to 2019) guidance documents were identified for analysis. The guidance contained explicit or implicit recommendations supporting adolescent inclusion in adult trials in 32% of Food and Drug Administration and 15% of European Medicines Agency documents, while 14% and 21%, respectively, were found to be exclusionary. A large number of guidance documents were silent regarding the applicability of adolescent-inclusive trial designs (53% and 64%, Food and Drug Administration and European Medicines Agency, respectively). Analysis by therapeutic area revealed the most permissive of adolescent inclusion in Food and Drug Administration guidance for infectious diseases and conditions requiring blood products in European Medicines Agency guidance. A more holistic approach to age-inclusive trial design was identified in disease guidance published by the Food and Drug Administration Oncology Center of Excellence. Discussion: There are many influences on the development and/or revision of regulatory guidance documents. Substantial scientific knowledge and regulatory precedence for the inclusion of adolescents within adult trials are available to inform research approaches. Our study has identified important opportunities for the enhancement of guidance. For example, contextualization of developmental factors influencing adolescent disease progression provides insights into the role of adolescent inclusion. If addressed, guidance documents can facilitate broader acceptance of age-inclusive trial methodologies and accelerate adolescent access to medicines.

Generalized pairwise comparisons and win statistics (i.e., win ratio, win odds and net benefit) are advantageous in analyzing and interpreting a composite of multiple outcomes in clinical trials. An important limitation of these statistics is their inability to adjust for covariates other than by stratified analysis. Because the win ratio does not account for ties, the win odds, a modification that includes ties, has attracted attention. We review and combine information on the win odds to articulate the statistical inferences for the win odds. We also show alternative variance estimators based on the exact permutation and bootstrap as well as statistical inference via the probabilistic index. Finally, we extend multiple-covariate regression probabilistic index models to the win odds with a univariate outcome. As an illustration we apply the regression models to the data in the CHARM trial.

There is an increasing interest in the use of win ratio with composite time-to-event due to its flexibility in combining component endpoints. Exploring this flexibility further, one interesting question is in assessing the impact when there is a difference in treatment effect in the component endpoints. For example, the active treatment may prolong the time to occurrence of the negative event such as death or ventilation; meanwhile, the treatment effect may also shorten the time to achieving positive events, such as recovery or improvement. Notably, this portrays a situation where the treatment effect on time to recovery is in a different direction of benefit compared to the time to ventilation or death. Under such circumstances, if a single endpoint is used, the benefit gained for other individual outcomes is not counted and is diminished. As consequence, the study may need a larger sample size to detect a significant effect of treatment. Such a scenario can be handled by win ratio in a novel way by ranking component events, which is different from the usual composite endpoint approach such as time-to-first event. To evaluate how the different directions of treatment effect on component endpoints will impact the win ratio analysis, we use a Clayton copula-based bivariate survival simulation to investigate the correlation of component time-to-event. Through simulation, we found that compared to the marginal model using single endpoints, the win ratio analysis on composite endpoint performs better, especially when the correlation between two events is weak. Then, we applied the methodology to an infectious disease progression simulated study motivated by COVID-19. The application demonstrates that the win ratio approach offers advantages in empirical power compared to the traditional Cox proportional hazard approach when there is a difference in treatment effect in the marginal events.

Real-world data (RWD) can contextualize findings from single-arm trials when randomized comparative trials are unethical or unfeasible. Findings from single-arm trials alone are difficult to interpret and a comparison, when feasible and meaningful, to patient-level information from RWD facilitates the evaluation. As such, there have been several recent regulatory applications including RWD or other external data to support the product's efficacy and safety. This paper summarizes some lessons learned from such contextualization from 20 notable new drug or biologic licensing applications in oncology and rare diseases.This review focuses on 20 notable new drug or biologic licensing applications that included patient-level RWD or other external data for contextualization of trial results. Publicly available regulatory documents including clinical and statistical reviews, advisory committee briefing materials and minutes, and approved product labeling were retrieved for each application. The authors conducted independent assessments of these documents focusing on the regulatory evaluation, in each case. Three examples are presented in detail to illustrate the salient issues and themes identified across applications.Regulatory decisions were strongly influenced by the quality and usability of the RWD. Comparability of cohort attributes such as endpoints, populations, follow-up, index and censoring criteria, as well as data completeness and accuracy of key variables appeared to be essential to ensure the quality and relevance of the RWD. Given adequate sample size of the clinical trials or external control, the use of appropriate analytic methods to properly account for confounding, such as regression or matching, and pre-specification of these methods while blinded to patient outcomes seemed good strategies to address baseline differences.Contextualizing single-arm trials with patient-level RWD appears to be an advance in regulatory science; however, challenges remain. Statisticians and epidemiologists have long focused on analytical methods for comparative effectiveness but hurdles in use of RWD have often occurred upstream of the analyses. More specifically, we noted hurdles in evaluating data quality, justifying cohort selection or initiation of follow-up, and demonstrating comparability of cohorts and endpoints.

In pediatric or orphan diseases, there are many instances where it is unfeasible to conduct randomized and controlled clinical trials. This is due in part to the difficulty of enrolling a sufficient number of patients over a reasonable time period to meet adequate statistical power to demonstrate the treatment efficacy. One solution to reduce the sample size or expedite the trial timeline is to complement the current trial with real-world data. To this end, several propensity score-based methods have been developed to create defined groups of patients that are controlled for confounding based on a set of measured covariates at baseline. However, balance checking on the measured covariates and tweaks to the propensity score models is usually inevitable to achieve the joint balance across all covariates. To mitigate this iterative procedure, we utilize the entropy balancing weighting technique which focuses on balancing the covariates of subjects between the experimental and control groups directly and augments the current trial with the external control data via a power prior. The finite-sample properties of the proposed method are assessed via simulations in the context of asymmetrically randomized controlled trials where only a small portion of patients are randomized to the control group. Other methods such as covariate-balancing propensity score (CBPS) and propensity score matching (PSM) and weighting (PSW) are also compared to provide context on the operating characteristics of the proposed method.

Pediatric drug development has many unique challenges, one of which is the evaluation of growth and development changes in children that are expected and are not due to the study intervention. Children grow and mature at different pace. The potential impact of the drug could vary with the developmental age of the participants receiving the treatment. For example, sexual maturation is a critical consideration in children of age 10 and above, but not in younger age groups. How the investigational drug impacts children is ultimately a risk-benefit consideration. In this paper, practical considerations and recommendations are provided on how to assess growth and development based on data collected from clinical trials in pediatric patients. The endpoints and measures related to growth, sexual maturation and neurocognitive development are discussed. Basic analysis approaches are recommended.

The use of Bayesian methodology to design and analyze pediatric efficacy trials is one of the possible options to reduce their sample size. This reduction of the sample size results from the use of an informative prior for the parameters of interest. In most of the applications, the principle of 'information borrowing' from adults' trials is applied, which means that the informative prior is constructed using efficacy results in adult of the drug under investigation. This implicitly assumes similarity in efficacy between the selected pediatric dose and the efficacious dose in adults. The goal of this article is to propose a method to construct prior distribution for the parameter of interest, not directly constructed from the efficacy results of the efficacious dose in adult patients but using pharmacodynamic modeling of a bridging biomarker using early phase pediatric data. When combined with a model bridging the biomarker with the clinical endpoints, the prior is constructed using a variational method after simulation of the parameters of interest. A use case application illustrates how the method can be used to construct a realistic informative prior.

In many orphan diseases and pediatric indications, the randomized controlled trials may be infeasible because of their size, duration, and cost. Leveraging information on the control through a prior can potentially reduce sample size. However, unless an objective prior is used to impose complete ignorance for the parameter being estimated, it results in biased estimates and inflated type-I error. Hence, it is essential to assess both the confirmatory and supplementary knowledge available during the construction of the prior to avoid "cherry-picking" advantageous information. For this purpose, propensity score methods are employed to minimize selection bias by weighting supplemental control subjects according to their similarity in terms of pretreatment characteristics to the subjects in the current trial. The latter can be operationalized through a proposed measure of overlap in propensity-score distributions. In this paper, we consider single experimental arm in the current trial and the control arm is completely borrowed from the supplemental data. The simulation experiments show that the proposed method reduces prior and data conflict and improves the precision of the of the average treatment effect.

Estimands play an important role for aligning study objectives, study design and analyses through a precise definition of the quantity of interest. For COVID-19 studies, apart from intercurrent events, high volume of missing data has been observed. We explore their impact on several estimands through a synthetic COVID-19 data generated from a discrete-time multi-state model. We compare estimators of these estimands based on their ability to closely match the true response rates and retain assumed power. The final choice of the estimand then needs to be aligned with clinically meaningful quantities of interest to patients, clinicians, regulators and payers.

Baricitinib, an oral selective Janus kinase 1/Janus kinase 2 inhibitor, is being studied for moderate-to-severe atopic dermatitis (AD) in adults.To evaluate the efficacy and safety of baricitinib monotherapy in a North American phase 3 trial (BREEZE-AD5/NCT03435081) of adults with moderate-to-severe AD who responded inadequately or were intolerant to topical therapy.Patients (N = 440) were randomized 1:1:1 to once-daily placebo or baricitinib (1 mg or 2 mg). The primary endpoint was the proportion of patients achieving ≥75% reduction in the Eczema Area and Severity Index at week 16. A key secondary endpoint was the proportion of patients achieving a validated Investigator Global Assessment for AD score of 0 (clear)/1(almost clear) with ≥2-point improvement.At week 16, the proportion of patients achieving Eczema Area and Severity Index was 8%, 13%, and 30% (P .001, 2 mg vs placebo) and those with a validated Investigator Global Assessment for AD score of 0/1 were 5%, 13%, and 24% (P .001, 2 mg vs placebo) for placebo, baricitinib 1 mg, and baricitinib 2 mg, respectively. Safety findings were similar to those of other baricitinib AD studies.Short-term clinical trial results may not be generalizable to real-world settings.Baricitinib was efficacious for patients with moderate-to-severe AD with no new safety findings over 16 weeks.

As the regulatory environment becomes progressively receptive toward utilizing real-world evidence, a spectrum of real-world data incorporation techniques in trial conduct and analysis has seen increasing interest and adoption in different stages of drug development. Of particular interest is leveraging external control data to augment the control arm in a concurrent randomized controlled trial, where patients are enrolled in both investigational treatment arm and the control arm. Yet despite the emerging literature in external data borrowing in a hybrid trial setting, very little discussion focuses on delineating what should be matched and what is actually being estimated, especially when a variety of matching schemes can be considered. In general, external control can be matched in four different ways: (1) matching with the intersection between investigational treatment and concurrent control, (2) matching with the union of concurrent investigational treatment and concurrent control, (3) matching with concurrent control alone, and (4) matching with investigational treatment alone. In this article, the formulation of estimands for different matching schemes are detailed to describe what these matching methods facilitate to answer. Simulation studies are also conducted to evaluate the performance characteristics under different matching schemes, estimation methods, effect size assumptions, and missingness of confounders.

For the clinical studies in rare diseases or small patient populations, having an adequately powered randomized controlled trial is further complicated by variability. As such, sample size re-estimation can be a useful tool if at an interim look the trial sample size needs to be increased to achieve adequate power to reject the null hypothesis. Meanwhile, borrowing or extrapolating information from real-world data or real-world evidence has gained increasing use in trial design and analysis since 2014. Combining these two strategies, high-quality real-world data, if leveraged properly, has the potential to generate real-world evidence that can assist interim decision-making, lower enrollment burden, and reduce study timeline and costs. With proper borrowing from historical control, some of the challenges in these high unmet medical need studies could be resolved considerably. We examine the incorporation of real-world evidence within the framework of adaptive design strategy in pediatric type II diabetes trials where recruitment has been challenging and the completion is hardly on time. Simulations under various scenarios are conducted to assess the borrowing strategy, i.e., the matching method in combination of sample size re-estimation. Comparisons of performance metrics are presented to showcase the advantages of proposed method.

In every profession, trade, or craft, certain skills are needed to perform an action or to complete a task. A biostatistician in the pharmaceutical field is no exception. We have expectations on kn...

During one of a series of long 10-hour drives to Pennsylvania, I came across the Facebook page “Brain Pickings” by Maria Popova. The page covers topics across literature, science, art, philosophy, ...

The special issue on innovative design and analysis of complex clinical trials (Volume 30, Issue 6) is a compilation of invited papers from speakers at the April 2019 Duke-Industry Statistics Sympo...

There was a total of 74 original articles published in the Journal’s Volume 30 in 2020. Many of the articles talk about unique problems in the following broad research areas: Adaptive or group sequ...

Conventional analyses of a composite of multiple time-to-event outcomes use the time to the first event. However, the first event may not be the most important outcome. To address this limitation, generalized pairwise comparisons and win statistics (win ratio, win odds, and net benefit) have become popular and have been applied to clinical trial practice. However, win ratio, win odds, and net benefit have typically been used separately. In this article, we examine the use of these three win statistics jointly for time-to-event outcomes. First, we explain the relation of point estimates and variances among the three win statistics, and the relation between the net benefit and the Mann-Whitney U statistic. Then we explain that the three win statistics are based on the same win proportions, and they test the same null hypothesis of equal win probabilities in two groups. We show theoretically that the Z-values of the corresponding statistical tests are approximately equal; therefore, the three win statistics provide very similar p-values and statistical powers. Finally, using simulation studies and data from a clinical trial, we demonstrate that, when there is no (or little) censoring, the three win statistics can complement one another to show the strength of the treatment effect. However, when the amount of censoring is not small, and without adjustment for censoring, the win odds and the net benefit may have an advantage for interpreting the treatment effect; with adjustment (e.g., IPCW adjustment) for censoring, the three win statistics can complement one another to show the strength of the treatment effect. For calculations we use the R package WINS, available on the CRAN (Comprehensive R Archive Network).

Background Janus kinase (JAK) inhibition is a new mode of action in atopic dermatitis (AD); clarity about drug class safety considerations in the context of AD is important. Baricitinib, an oral, reversible, selective inhibitor of JAK1/JAK2, is in late-stage development for adult patients with moderate-to-severe AD. Objective To report pooled safety data for baricitinib in patients with moderate-to-severe AD in the clinical development program including long-term extension (LTE) studies. Methods This analysis included patient-level safety data from six double-blinded, randomized, placebo-controlled studies (one phase 2 and five phase 3), one double-blinded, randomized, LTE study and one open-label LTE study, reported in three data sets: placebo-controlled, 2-mg - 4-mg extended and All-bari AD. Safety outcomes include treatment-emergent adverse events, adverse events of special interest and abnormal laboratory changes. Proportions of patients with events and incidence rates were calculated. Results Data were collected for 2531 patients who were given baricitinib for 2247 patient-years (median duration 310 days). The frequency of serious infections, opportunistic infections and conjunctival disorders was low and similar between treatment groups in the placebo-controlled period. The most common serious infections were eczema herpeticum [n = 11, incidence rates (IR) = 0.5], cellulitis (n = 6, IR = 0.3) and pneumonia (n = 3, IR = 0.1). There were four opportunistic infections (IR = 0.2). No malignancies, gastrointestinal perforations, positively adjudicated cardiovascular events or tuberculosis were reported in the placebo-controlled period in baricitinib-treated patients. Frequency of herpes simplex was higher in the 4-mg group (6.1%) vs. the 2-mg (3.6%) and placebo group (2.7%); IRs in the extended data set (2-mg IR = 9.6; 4-mg IR = 14.5) were lower vs. the placebo-controlled data set (2-mg IR = 12.4; 4-mg IR = 21.3). In the All-bari AD data set, there were two positively adjudicated major adverse cardiovascular events (2-mg group): two venous thrombosis events (4-mg group) and one death. Conclusion This integrated safety analysis in patients with moderate-to-severe AD confirms the established safety profile of baricitinib.

BACKGROUND Baricitinib, an oral selective Janus kinase 1 and 2 inhibitor, effectively reduced atopic dermatitis (AD) severity in a phase II study with concomitant topical corticosteroids. OBJECTIVES To evaluate the efficacy and safety of baricitinib in patients with moderate-to-severe AD who had an inadequate response to topical therapies. METHODS In two independent, multicentre, double-blind, phase III monotherapy trials, BREEZE-AD1 and BREEZE-AD2, adults with moderate-to-severe AD were randomized 2 : 1 : 1 : 1 to once-daily placebo, baricitinib 1 mg, 2 mg, or 4 mg for 16 weeks. RESULTS At week 16, more patients achieved the primary end point of Validated Investigator's Global Assessment of AD (0, 1) on baricitinib 4 mg and 2 mg compared with placebo in BREEZE-AD1 [N = 624; baricitinib 4 mg 16·8% (P < 0·001), 2 mg 11·4% (P < 0·05), 1 mg 11·8% (P < 0·05), placebo 4·8%], and BREEZE-AD2 [N = 615; baricitinib 4 mg 13·8% (P = 0·001), 2 mg 10·6% (P < 0·05), 1 mg 8·8% (P = 0·085), placebo 4·5%]. Improvement in itch was achieved as early as week 1 for 4 mg and week 2 for 2 mg. Improvements in night-time awakenings, skin pain and quality-of-life measures were observed by week 1 for both 4 mg and 2 mg (P ≤ 0·05, all comparisons). The most common adverse events in patients treated with baricitinib were nasopharyngitis and headache. No cardiovascular events, venous thromboembolism, gastrointestinal perforation, significant haematological changes, or death were observed with any baricitinib dosage. CONCLUSIONS Baricitinib improved clinical signs and symptoms in patients with moderate-to-severe AD within 16 weeks of treatment and induced rapid reduction of itch. The safety profile remained consistent with prior findings from baricitinib clinical development in AD, with no new safety concerns.

Among many efforts to facilitate timely access to safe and effective medicines to children, increased attention has been given to extrapolation. Loosely, it is the leveraging of conclusions or available data from adults or older age groups to draw conclusions for the target pediatric population when it can be assumed that the course of the disease and the expected response to a medicinal product would be sufficiently similar in the pediatric and the reference population. Extrapolation then can be characterized as a statistical mapping of information from the reference (adults or older age groups) to the target pediatric population. The translation, or loosely mapping of information, can be through a composite likelihood approach where the likelihood of the reference population is weighted by exponentiation and that this exponent is related to the value of the mapped information in the target population. The weight is bounded above and below recognizing the fact that similarity (of the disease and the expected response) is still valid despite variability of response between the cohorts. Maximum likelihood approaches are then used for estimation of parameters and asymptotic theory is used to derive distributions of estimates for use in inference. Hence, the estimation of effects in the target population borrows information from reference population. In addition, this manuscript also talks about how this method is related to the Bayesian statistical paradigm., Comment: 28 pages, 4 figures, 3 tables

Pediatric drug development lags adult development by about 8 years (Mulugeta et al. in Pediatr Clin 64(6):1185-1196, 2017). In such context, many incentives, regulations, and innovative techniques have been proposed to address the disparity for pediatric patients. One such strategy is extrapolation of efficacy from a reference population. Extrapolation is currently justified by providing evidence in support of the effective use of drugs in children when the course of the disease and the expected treatment response would be sufficiently similar in the pediatric and reference population. This paper's position is that, despite uncertainties, pediatric drug development programs should initially assume some degree of extrapolation. The degree to which extrapolation can be used lies along a continuum representing the uncertainties to be addressed through generation of new pediatric evidence. In addressing these uncertainties, the extrapolation strategy should reflect the level of tolerable uncertainty concerning the decision to expose a child to the risks of a new drug. This judgment about the level of tolerable uncertainty should vary with the context (e.g., disease severity, existing therapeutic options) and can be embedded into pediatric drug development archetypes to ascertain the extent of studies needed and whether simultaneous development for adults and adolescents be considered.

Introduction BREEZE-AD1 ( NCT03334396 ) et BREEZE-AD2 ( NCT03334422 ) sont les premieres de 7 etudes cliniques de phase 3 evaluant le baricitinib, un inhibiteur des JAK 1/2, dans le traitement de la dermatite atopique (DA) moderee a severe. Ces etudes evaluent l’efficacite et la tolerance du baricitinib dans la DA moderee a severe insuffisamment controlee par des traitements topiques chez l’adulte. Materiel et methodes BREEZE-AD1 et BREEZE-AD2 sont des etudes identiques de phase 3 randomisees, en double-aveugle, controlees versus placebo, en monotherapie. La randomisation s’effectuait en 2: 1: 1: 1 comprenant les bras placebo, baricitinib 1 mg, 2 mg ou 4 mg, tous les jours, pendant 16 semaines. Le critere de jugement principal etait le pourcentage de patients atteignant un score Validated Investigator's Global Assessement pour la DA (vIGA-AD) de 0 (blanchi) ou 1 (presque blanchi) avec une amelioration ≥ 2 points entre l’inclusion et S16. Des analyses avec ajustements multiples ont ete utilisees pour le critere principal et les criteres secondaires. Resultats Un nombre de patients significativement plus eleve a atteint le critere principal de vIGA-AD (0/1) dans les bras baricitinib 4 mg et 2 mg compare au placebo (baricitinib 4 mg 16,8 %/13,8 % [p Conclusion Le traitement par baricitinib a ameliore de facon significative les signes cliniques et symptomes de la DA moderee a severe versus placebo et represente une potentielle nouvelle option therapeutique.

The conduct of pediatric clinical trials is legally required, monitored, and encouraged in major geographic areas such as the United States and Europe. However, because pediatric patients are considered vulnerable populations, they should only be enrolled as research subjects in a clinical trial if enrolling adult subjects will not be able to answer the scientific question related to the health and welfare of children. Thus, there is an ethical obligation to build the foundation for the use of pediatric extrapolation and related innovative analytical strategies with appropriately designed pediatric and adult clinical trials to reduce the amount of, or general need for, additional information needed from children to reach conclusions. This manuscript discusses innovative applications of clinical trial designs, analytic strategies to more efficiently leverage prior information, and modeling approaches that impact the data required to determine efficacy of an investigational drug in pediatrics. The planning of pediatric trials and regulatory interactions related to required pediatric studies and the expectations for innovative analytics are also discussed.

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get t...

Determining whether there are differential treatment effects in subgroups of trial participants remains an important topic in clinical trials as precision medicine becomes ever more relevant. Any assessment of differential treatment effect is predicated on being able to estimate the treatment response accurately while satisfying constraints of balancing the risk of overlooking an important subgroup with the potential to make a decision based on a false discovery. While regression models, such as marginal interaction model, have been widely used to improve accuracy of subgroup parameter estimates by leveraging the relationship between treatment and covariate, there is still a possibility that it can lead to excessively conservative or anti-conservative results. Conceivably, this can be due to the use of the normal distribution as a default prior, which forces outlying subjects to have their means over-shrunk towards the population mean, and the data from such subjects may be excessively influential in estimation of both the overall mean response and the mean response for each subgroup, or a model mis-specification. To address this issue, we investigate the use of nonparametric Bayes, particularly Dirichlet process priors, to create semi-parametric models. These models represent uncertainty in the prior distribution for the overall response while accommodating heterogeneity among individual subgroups. They also account for the effect and variation due to the unaccounted terms. As a result, the models do not force estimates to excessively shrink but still retain the attractiveness of improved precision given by the narrower credible intervals. This is illustrated in extensive simulations investigating bias, mean squared error, coverage probability and credible interval widths. We applied the method on a simulated data based closely on the results of a cystic fibrosis Phase 2 trial.

Randomized and controlled clinical trials are an important tool to provide definitive evidence about effects of treatments for COVID-19. Because of the novelty of this disease, designing these prov...

The COVID-19 pandemic presents unprecedented challenges for drug developers seeking to evaluate the safety and efficacy of potential treatments for COVID-19. Clinical researchers must work quickly ...

Background There are no treatments approved by the Food and Drug Administration for alopecia areata. Objective To evaluate the efficacy and safety of baricitinib in patients with ≥50% scalp hair loss in a phase 2 study of adults with alopecia areata (BRAVE-AA1). Methods Patients were randomized 1:1:1:1 to receive placebo or baricitinib 1 mg, 2 mg, or 4 mg once daily. Two consecutive interim analyses were performed after all patients completed weeks 12 and 36 or had discontinued treatment prior to these time points. The primary endpoint was the proportion of patients achieving a Severity of Alopecia Tool (SALT) score ≤20 at week 36. Logistic regression was used with nonresponder imputation for missing data. Results A total of 110 patients were randomized (placebo, 28; baricitinib 1-mg, 28; 2-mg, 27; 4-mg, 27). The baricitinib 1-mg dose was dropped after the first interim analysis based on lower SALT30 response rate. At week 36, the proportion of patients achieving a SALT score of ≤20 was significantly greater in baricitinib 2-mg (33.3%, P = .016) and 4-mg (51.9%, P = .001) groups versus placebo (3.6%). Baricitinib was well tolerated with no new safety findings. Limitations Small sample size limits generalizability of results. Conclusion These results support the efficacy and safety of baricitinib in patients with ≥50% scalp hair loss.

The win ratio method has received much attention in methodological research, ad hoc analyses, and designs of prospective studies. As the primary analysis, it supported the approval of tafamidis for the treatment of cardiomyopathy to reduce cardiovascular mortality and cardiovascular-related hospitalization. However, its dependence on censoring is a potential shortcoming. In this article, we propose the inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic (i.e., the IPCW-adjusted win ratio statistic) to overcome censoring issues. We consider independent censoring, common censoring across endpoints, and right censoring. We develop an asymptotic variance estimator for the logarithm of the IPCW-adjusted win ratio statistic and evaluate it via simulation. Our simulation studies show that, as the amount of censoring increases, the unadjusted win proportions may decrease greatly. Consequently, the bias of the unadjusted win ratio estimate may increase greatly, producing either an overestimate or an underestimate. We demonstrate theoretically and through simulation that the IPCW-adjusted win ratio statistic gives an unbiased estimate of treatment effect.

The US Food and Drug Administration (FDA) has shown scientific discretion in interpreting the substantial evidence requirement for the approval of new drugs with its considerations on the use of single controlled or uncontrolled trials (Federal Food, Drug, and Cosmetic Act § 505(d), 21 USC 355(d), 1962). With the passage of the 21st Centuries Cures Act (21st Century Cures-patients. House, Energy and Commerce Committee, Washington, DC, 2019 available at: https://energycommerce.house.gov/sites/republicans.energycommerce.house.gov/files/analysis/21stCenturyCures/20140516PatientsWhitePaper.pdf ), the FDA is mandated to expand the role of real-world evidence (RWE) in support of drug approval. This mandate further broadens the scope of scientific discretion to include data collected outside clinical trials. We summarize the agency's past acceptance of real-world data (RWD) sources for supporting drug approval in new indications which have been reflected in US labels. In our summary, we focus on the type of RWD and statistical methodologies presented in these labels. Furthermore, two labels were selected for in-depth assessment of the RWE presented in these labels. Through these examples, we demonstrate the issues that can be raised in data collection that could affect interpretation. In addition, a brief discussion of statistical methods that can be used to incorporate RWE to clinical development is presented.

Importance Baricitinib, an oral selective Janus kinase 1 and 2 inhibitor, effectively reduced disease severity in moderate to severe atopic dermatitis (AD) in 2 phase 3 monotherapy studies. Objective To assess the efficacy and safety of 4 mg and 2 mg of baricitinib in combination with background topical corticosteroid (TCS) therapy in adults with moderate to severe AD who previously had an inadequate response to TCS therapy. Design, setting, and participants This double-blind, placebo-controlled, phase 3 randomized clinical trial, BREEZE-AD7 (Study of Baricitinib [LY3009104] in Combination With Topical Corticosteroids in Adults With Moderate to Severe Atopic Dermatitis) was conducted from November 16, 2018, to August 22, 2019, at 68 centers across 10 countries in Asia, Australia, Europe, and South America. Patients 18 years or older with moderate to severe AD and an inadequate response to TCSs were included. After completing the study, patients were followed up for up to 4 weeks or enrolled in a long-term extension study. Interventions Patients were randomly assigned (1:1:1) to receive 2 mg of baricitinib once daily (n = 109), 4 mg of baricitinib once daily (n = 111), or placebo (n = 109) for 16 weeks. The use of low-to-moderate potency TCSs was allowed. Main outcomes and measures The primary end point was the proportion of patients achieving a validated Investigator Global Assessment for Atopic Dermatitis (vIGA-AD) score of 0 (clear) or 1 (almost clear), with a 2-point or greater improvement from baseline at week 16. Results Among 329 patients (mean [SD] age, 33.8 [12.4] years; 216 [66%] male), at week 16, a vIGA-AD score of 0 (clear) or 1 (almost clear) was achieved by 34 patients (31%) receiving 4 mg of baricitinib and 26 (24%) receiving 2 mg of baricitinib compared with 16 (15%) receiving placebo (odds ratio vs placebo, 2.8 [95% CI, 1.4-5.6]; P = .004 for the 4-mg group; 1.9 [95% CI, 0.9-3.9]; P = .08 for the 2-mg group). Treatment-emergent adverse events were reported in 64 of 111 patients (58%) in the 4-mg group, 61 of 109 patients (56%) in the 2-mg group, and 41 of 108 patients (38%) in the placebo group. Serious adverse events were reported in 4 patients (4%) in the 4-mg group, 2 (2%) in the 2-mg group, and 4 (4%) in the placebo group. The most common adverse events were nasopharyngitis, upper respiratory tract infections, and folliculitis. Conclusions and relevance A dose of 4 mg of baricitinib in combination with background TCS therapy significantly improved the signs and symptoms of moderate to severe AD, with a safety profile consistent with previous studies of baricitinib in AD. Trial registration ClinicalTrials.gov Identifier: NCT03733301.

Introduction La monotherapie par le baricitinib, un inhibiteur selectif des JAK1/2, a reduit efficacement la gravite de la DA moderee a severe lors de precedentes etudes de phase 3. L’etude de phase 3 en double aveugle, randomisee et controlee par placebo BREEZE-AD7 (NCT03733301) a evalue l’efficacite et la securite du baricitinib associe a des TCS chez les adultes atteints de DA moderee a severe. Materiel et methodes La randomisation etait de 1 :1 :1 pour le placebo, le baricitinib 2 mg ou 4 mg pris par voie orale chaque jour pendant 16 semaines. L’utilisation d’un TCS de puissance faible a moderee etait autorisee. Le critere principal etait la proportion de patients avec un score de 0 (blanchi)/1 (quasi blanchi) de l’evaluation globale validee par l’investigateur pour la dermatite atopique (vIGA-AD™), avec une amelioration ≥ 2 points entre l’inclusion et la semaine 16. Resultats Au total, 329 patients ont ete inclus. La proportion de patients ayant atteint le critere principal etait significativement plus elevee avec la dose de 4 mg qu’avec le placebo (30,6 % vs 14,7 %, p ≤ 0,01). A la semaine 16, un nombre significativement plus eleve de patients a atteint un score EASI 75 avec 4 mg (47,7 %, p ≤ 0,01) et 2 mg (43,1 %, p ≤ 0,01) qu’avec le placebo (22,9 %). Une amelioration significative des demangeaisons a ete detectee des la semaine 2 pour 4 mg et des la semaine 3 pour 2 mg. Une amelioration des reveils nocturnes, des douleurs cutanees, du DLQI et du POEM a ete observee des la semaine 1 avec 4 mg et entre les semaines 1 a 3 pour 2 mg. Cette amelioration s’est maintenue jusqu’a la semaine 16. Le baricitinib a reduit de maniere significative la quantite de TCS de puissance moderee utilisee (39 % et 28 % [p ≤ 0,01] pour 4 mg et 2 mg, respectivement, vs placebo). Des evenements indesirables (EI) survenus en cours de traitement ont ete rapportes pour 38 %, 56 % et 58 % des patients, et des EI graves pour 3,7 %, 1,8 % et 3,6 % des patients sous placebo, 2 mg et 4 mg, respectivement. Les EI les plus frequents etaient des rhinopharyngites, des infections des voies aeriennes superieures, des folliculites. Une embolie pulmonaire a ete signalee dans le groupe 4 mg ; une infection opportuniste (toxoplasmose oculaire) a ete signalee dans le groupe placebo. Aucun cancer, evenement indesirable cardiovasculaire majeur ou deces n’a ete signale. Discussion Le baricitinib, associe a des TCS, a permis d’ameliorer de maniere significative les signes et symptomes de la DA moderee a severe par rapport au placebo. Les EI etaient comparables a ceux observes dans les precedentes etudes sur la DA.

Introduction Le baricitinib (bari), un inhibiteur selectif des Janus kinase (JAK) 1 et 2 administre par voie orale, a permis d’ameliorer significativement les signes et symptomes de la DA moderee a severe en monotherapie (BREEZE-AD1 et AD2) et associe a des corticosteroides topiques (TCS) de fond (BREEZE-AD7). Nous presentons les resultats de BREEZE-AD4 en matiere d’efficacite et de tolerance. Materiel et methodes Des patients adultes atteints de DA moderee a severe en echec, intolerance ou contre-indication a la CsA ont ete randomises (1:1:2:1) afin de recevoir un placebo (PBO, N = 93), bari 1 mg (N = 93), 2 mg (N = 185) ou 4 mg (N = 92) par jour. L’utilisation d’un TCS de puissance faible a moderee etait autorisee pour les lesions actives. Le critere principal etait la proportion de patients traites par bari 4 mg ou 2 mg presentant une amelioration ≥ 75 % de l’Eczema Area and Severity Index (EASI 75) a la semaine 16 par rapport a l’inclusion. Des analyses ajustees pour comparaisons multiples ont ete realisees sur les criteres principaux et secondaires majeurs. L’efficacite a ete analysee dans la population en intention de traiter. La tolerance a ete analysee pour les patients ayant pris ≥ 1 dose de bari. Resultats Sur les 463 patients randomises, 410 (89 %) ont atteint la 16eme semaine d’evaluation (n = 334 [72 %] sans traitement de secours ; n = 76 [16 %] avec traitement de secours). Parmi eux, le critere principal (EASI 75) a ete atteint chez 32 % (4 mg, p = 0,031), 28 % (2 mg, p = 0,071) et 17 % (PBO). Le traitement par bari 4 mg etait superieur au PBO pour les criteres secondaires majeurs d’amelioration ≥ 4 points sur l’echelle numerique d’evaluation (NRS) du prurit aux semaines 2, 4 et 16 ; le pourcentage moyen d’amelioration par rapport a l’inclusion (CFB) du score EASI a la semaine 16, le CFB moyen du NRS des douleurs cutanees a la semaine 16 et le CFB moyen de l’item 2 de l’ADSS (nombre de reveils nocturnes dus au prurit) a la semaine 16 (tableau ci-dessous). Des evenements indesirables apparus en cours de traitement (EICT) ont ete rapportes chez 53,8 % (PBO), 62,4 % (1 mg), 67,9 % (2 mg) et 75,0 % (4 mg) des patients ; des evenements indesirables graves ont ete rapportes chez 2,2 % (PBO), 4,3 % (1 mg), 1,6 % (2 mg) et 6,5 % (4 mg) des patients. EICT les plus frequents : rhinopharyngite et cephalee. Aucun evenement cardiovasculaire majeur, aucune thrombose veineuse (notamment embolie pulmonaire) ni aucun deces n’ont ete signales. Discussion Le traitement par bari 4 mg, associe a des TCS, etait superieur au PBO pour l’amelioration des signes et symptomes de la DA moderee a severe chez les patients en echec, intolerance ou contre-indications a la CsA. Soumis a l’EADV, la decision est en attente au moment de la soumission aux JDP.

Children represent a large underserved population of "therapeutic orphans," as an estimated 80% of children are treated off-label. However, pediatric drug development often faces substantial challenges, including economic, logistical, technical, and ethical barriers, among others. Among many efforts trying to remove these barriers, increased recent attention has been paid to extrapolation; that is, the leveraging of available data from adults or older age groups to draw conclusions for the pediatric population. The Bayesian statistical paradigm is natural in this setting, as it permits the combining (or "borrowing") of information across disparate sources, such as the adult and pediatric data. In this paper, authored by the pediatric subteam of the Drug Information Association Bayesian Scientific Working Group and Adaptive Design Working Group, we develop, illustrate, and provide suggestions on Bayesian statistical methods that could be used to design improved pediatric development programs that use all available information in the most efficient manner. A variety of relevant Bayesian approaches are described, several of which are illustrated through 2 case studies: extrapolating adult efficacy data to expand the labeling for Remicade to include pediatric ulcerative colitis and extrapolating adult exposure-response information for antiepileptic drugs to pediatrics.

Extrapolation from adults to youth with type 2 diabetes (T2D) is challenged by differences in disease progression and manifestation. This manuscript presents the results of a mock-team workshop focused on examining the typical team-based decision process used to propose a pediatric development plan for T2D addressing the viability of extrapolation. The workshop was held at the American Society for Clinical Pharmacology and Therapeutics (ASCPT) in Orlando, Florida on March 21, 2018.

Pediatric clinical trials are often requested according to specific age ranges. In the past and still today, these ages may correspond to developmental stages, such as newborn, infancy, childhood, and adolescence. Selection of ages for pediatric participation in medication studies should correspond to ages of rapid changes in pharmacokinetics and pharmacodynamics. Age-related changes in several enzymes involved in drug metabolism and glomerular filtration are described as examples of optimal ages for study of specific drugs according to their pathways of disposition.

In the absence of placebo-controlled trials, the efficacy of a test treatment can be alternatively examined by showing its non-inferiority to an active control; that is, the test treatment is not worse than the active control by a pre-specified margin. The margin is based on the effect of the active control over placebo in historical studies. In other words, the non-inferiority setup involves a network of direct and indirect comparisons between test treatment, active controls, and placebo. Given this framework, we consider a Bayesian network meta-analysis that models the uncertainty and heterogeneity of the historical trials into the non-inferiority trial in a data-driven manner through the use of the Dirichlet process and power priors. Depending on whether placebo was present in the historical trials, two cases of non-inferiority testing are discussed that are analogs of the synthesis and fixed-margin approach. In each of these cases, the model provides a more reliable estimate of the control given its effect in other trials in the network, and, in the case where placebo was only present in the historical trials, the model can predict the effect of the test treatment over placebo as if placebo had been present in the non-inferiority trial. It can further answer other questions of interest, such as comparative effectiveness of the test treatment among its comparators. More importantly, the model provides an opportunity for disproportionate randomization or the use of small sample sizes by allowing borrowing of information from a network of trials to draw explicit conclusions on non-inferiority.

Existing statutes in the United States and Europe require manufacturers to demonstrate evidence of effectiveness through the conduct of adequate and well-controlled studies to obtain marketing approval of a therapeutic product. What constitutes adequate and well-controlled studies is usually interpreted as randomized controlled trials (RCTs). However, these trials are sometimes unfeasible because of their size, duration, cost, patient preference, or in some cases, ethical concerns. For example, RCTs may not be fully powered in rare diseases or in infections caused by multidrug resistant pathogens because of the low number of enrollable patients. In this case, data available from external controls (including historical controls and observational studies or data registries) can complement information provided by RCT. Propensity score matching methods can be used to select or "borrow" additional patients from the external controls, for maintaining a one-to-one randomization between the treatment arm and active control, by matching the new treatment and control units based on a set of measured covariates, ie, model-based pairing of treatment and control units that are similar in terms of their observable pretreatment characteristics. To this end, 2 matching schemes based on propensity scores are explored and applied to a real clinical data example with the objective of using historical or external observations to augment data in a trial where the randomization is disproportionate or asymmetric.

Drug developers are required to demonstrate substantial evidence of effectiveness through the conduct of adequate and well-controlled (A&WC) studies to obtain marketing approval of their medicine. What constitutes A&WC is interpreted as the conduct of randomized controlled trials (RCTs). However, these trials are sometimes unfeasible because of their size, duration, and cost. One way to reduce sample size is to leverage information on the control through a prior. One consideration when forming data-driven prior is the consistency of the external and the current data. It is essential to make this process less susceptible to choosing information that only helps improve the chances toward making an effectiveness claim. For this purpose, propensity score methods are employed for two reasons: (1) it gives the probability of a patient to be in the trial, and (2) it minimizes selection bias by pairing together treatment and control within the trial and control subjects in the external data that are similar in terms of their pretreatment characteristics. Two matching schemes based on propensity scores, estimated through generalized boosted methods, are applied to a real example with the objective of using external data to perform Bayesian augmented control in a trial where the allocation is disproportionate. The simulation results show that the data augmentation process prevents prior and data conflict and improves the precision of the estimator of the average treatment effect.

Background Baricitinib, an oral selective inhibitor of Janus kinase 1 and Janus kinase 2, modulates proinflammatory cytokine signaling. Objectives The efficacy and safety of baricitinib were evaluated in patients with moderate-to-severe atopic dermatitis (AD). Methods In this phase 2, randomized, double-blind, placebo-controlled study, 124 patients with moderate-to-severe AD applied topical corticosteroids (TCSs) for 4 weeks before randomization to once-daily placebo, 2 mg of baricitinib, or 4 mg of baricitinib for 16 weeks. Use of TCSs was permitted during the study. The primary outcome was the proportion of patients achieving at least a 50% reduction in the Eczema Area and Severity Index (EASI-50) compared with placebo. Results Significantly more patients who received baricitinib, 4 mg, achieved EASI-50 than did patients receiving placebo (61% vs 37% [P = .027]) at 16 weeks. The difference between the proportion of patients receiving baricitinib, 2 or 4 mg, who achieved EASI-50 and the proportion of patients receiving placebo and achieving EASI-50 was significant as early as week 4. Baricitinib also improved pruritus and sleep loss. Treatment-emergent adverse events were reported in 24 of the patients receiving placebo (49%), 17 of those receiving 2 mg of baricitinib (46%), and 27 of those receiving 4 mg of baricitinib (71%). Limitations A TCS standardization period before randomization reduced disease severity, limiting the ability to compare results with those of baricitinib monotherapy. Longer studies are required to confirm baricitinib's efficacy and safety in patients with AD. Conclusions Baricitinib used with TCSs reduced inflammation and pruritus in patients with moderate-to-severe AD.