Simulating and reporting frequentist operating characteristics of clinical trials that borrow external information: Towards a fair comparison in case of one-arm and hybrid control two-arm trials.

Borrowing information from historical or external data to inform inference in a current trial is an expanding field in the era of precision medicine, where trials are often performed in small patient cohorts for practical or ethical reasons. Even though methods proposed for borrowing from external data are mainly based on Bayesian approaches that incorporate external information into the prior for the current analysis, frequentist operating characteristics of the analysis strategy are often of interest. In particular, type I error rate and power at a prespecified point alternative are the focus. We propose a procedure to investigate and report the frequentist operating characteristics in this context. The approach evaluates type I error rate of the test with borrowing from external data and calibrates the test without borrowing to this type I error rate. On this basis, a fair comparison of power between the test with and without borrowing is achieved. We show that no power gains are possible in one-sided one-arm and two-arm hybrid control trials with normal endpoint, a finding proven in general before. We prove that in one-arm fixed-borrowing situations, unconditional power (i.e., when external data is random) is reduced. The Empirical Bayes power prior approach that dynamically borrows information according to the similarity of current and external data avoids the exorbitant type I error inflation occurring with fixed borrowing. In the hybrid control two-arm trial we observe power reductions as compared to the test calibrated to borrowing that increase when considering unconditional power.

Robust incorporation of historical information with known type I error rate inflation.

Bayesian clinical trials can benefit from available historical information through the specification of informative prior distributions. Concerns are however often raised about the potential for prior-data conflict and the impact of Bayes test decisions on frequentist operating characteristics, with particular attention being assigned to inflation of type I error (TIE) rates. This motivates the development of principled borrowing mechanisms, that strike a balance between frequentist and Bayesian decisions. Ideally, the trust assigned to historical information defines the degree of robustness to prior-data conflict one is willing to sacrifice. However, such relationship is often not directly available when explicitly considering inflation of TIE rates. We build on available literature relating frequentist and Bayesian test decisions, and investigate a rationale for inflation of TIE rate which explicitly and linearly relates the amount of borrowing and the amount of TIE rate inflation in one-arm studies. A novel dynamic borrowing mechanism tailored to hypothesis testing is additionally proposed. We show that, while dynamic borrowing prevents the possibility to obtain a simple closed-form TIE rate computation, an explicit upper bound can still be enforced. Connections with the robust mixture prior approach, particularly in relation to the choice of the mixture weight and robust component, are made. Simulations are performed to show the properties of the approach for normal and binomial outcomes, and an exemplary application is demonstrated in a case study.

A decision-theoretic approach to Bayesian clinical trial design and evaluation of robustness to prior-data conflict.

Bayesian clinical trials allow taking advantage of relevant external information through the elicitation of prior distributions, which influence Bayesian posterior parameter estimates and test decisions. However, incorporation of historical information can have harmful consequences on the trial's frequentist (conditional) operating characteristics in case of inconsistency between prior information and the newly collected data. A compromise between meaningful incorporation of historical information and strict control of frequentist error rates is therefore often sought. Our aim is thus to review and investigate the rationale and consequences of different approaches to relaxing strict frequentist control of error rates from a Bayesian decision-theoretic viewpoint. In particular, we define an integrated risk which incorporates losses arising from testing, estimation, and sampling. A weighted combination of the integrated risk addends arising from testing and estimation allows moving smoothly between these two targets. Furthermore, we explore different possible elicitations of the test error costs, leading to test decisions based either on posterior probabilities, or solely on Bayes factors. Sensitivity analyses are performed following the convention which makes a distinction between the prior of the data-generating process, and the analysis prior adopted to fit the data. Simulation in the case of normal and binomial outcomes and an application to a one-arm proof-of-concept trial, exemplify how such analysis can be conducted to explore sensitivity of the integrated risk, the operating characteristics, and the optimal sample size, to prior-data conflict. Robust analysis prior specifications, which gradually discount potentially conflicting prior information, are also included for comparison. Guidance with respect to cost elicitation, particularly in the context of a Phase II proof-of-concept trial, is provided.

Hypoxia-Inducible Factor 1 Alpha-Mediated RelB/APOBEC3B Down-regulation Allows Hepatitis B Virus Persistence.

BACKGROUND AND AIMS: Therapeutic strategies against HBV focus, among others, on the activation of the immune system to enable the infected host to eliminate HBV. Hypoxia-inducible factor 1 alpha (HIF1α) stabilization has been associated with impaired immune responses. HBV pathogenesis triggers chronic hepatitis-related scaring, leading inter alia to modulation of liver oxygenation and transient immune activation, both factors playing a role in HIF1α stabilization. APPROACH AND RESULTS: We addressed whether HIF1α interferes with immune-mediated induction of the cytidine deaminase, apolipoprotein B mRNA editing enzyme catalytic subunit 3B (APOBEC3B; A3B), and subsequent covalently closed circular DNA (cccDNA) decay. Liver biopsies of chronic HBV (CHB) patients were analyzed by immunohistochemistry and in situ hybridization. The effect of HIF1α induction/stabilization on differentiated HepaRG or mice ± HBV ± LTßR-agonist (BS1) was assessed in vitro and in vivo. Induction of A3B and subsequent effects were analyzed by RT-qPCR, immunoblotting, chromatin immunoprecipitation, immunocytochemistry, and mass spectrometry. Analyzing CHB highlighted that areas with high HIF1α levels and low A3B expression correlated with high HBcAg, potentially representing a reservoir for HBV survival in immune-active patients. In vitro, HIF1α stabilization strongly impaired A3B expression and anti-HBV effect. Interestingly, HIF1α knockdown was sufficient to rescue the inhibition of A3B up-regulation and -mediated antiviral effects, whereas HIF2α knockdown had no effect. HIF1α stabilization decreased the level of v-rel reticuloendotheliosis viral oncogene homolog B protein, but not its mRNA, which was confirmed in vivo. Noteworthy, this function of HIF1α was independent of its partner, aryl hydrocarbon receptor nuclear translocator. CONCLUSIONS: In conclusion, inhibiting HIF1α expression or stabilization represents an anti-HBV strategy in the context of immune-mediated A3B induction. High HIF1α, mediated by hypoxia or inflammation, offers a reservoir for HBV survival in vivo and should be considered as a restricting factor in the development of immune therapies.

Filtering and inference for stochastic oscillators with distributed delays.

MOTIVATION: The time evolution of molecular species involved in biochemical reaction networks often arises from complex stochastic processes involving many species and reaction events. Inference for such systems is profoundly challenged by the relative sparseness of experimental data, as measurements are often limited to a small subset of the participating species measured at discrete time points. The need for model reduction can be realistically achieved for oscillatory dynamics resulting from negative translational and transcriptional feedback loops by the introduction of probabilistic time-delays. Although this approach yields a simplified model, inference is challenging and subject to ongoing research. The linear noise approximation (LNA) has recently been proposed to address such systems in stochastic form and will be exploited here. RESULTS: We develop a novel filtering approach for the LNA in stochastic systems with distributed delays, which allows the parameter values and unobserved states of a stochastic negative feedback model to be inferred from univariate time-series data. The performance of the methods is tested for simulated data. Results are obtained for real data when the model is fitted to imaging data on Cry1, a key gene involved in the mammalian central circadian clock, observed via a luciferase reporter construct in a mouse suprachiasmatic nucleus. AVAILABILITY AND IMPLEMENTATION: Programmes are written in MATLAB and Statistics Toolbox Release 2016 b, The MathWorks, Inc., Natick, Massachusetts, USA. Sample code and Cry1 data are available on GitHub https://github.com/scalderazzo/FLNADD. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Quantification of prior impact in terms of effective current sample size.

Bayesian methods allow borrowing of historical information through prior distributions. The concept of prior effective sample size (prior ESS) facilitates quantification and communication of such prior information by equating it to a sample size. Prior information can arise from historical observations; thus, the traditional approach identifies the ESS with such a historical sample size. However, this measure is independent of newly observed data, and thus would not capture an actual "loss of information" induced by the prior in case of prior-data conflict. We build on a recent work to relate prior impact to the number of (virtual) samples from the current data model and introduce the effective current sample size (ECSS) of a prior, tailored to the application in Bayesian clinical trial designs. Special emphasis is put on robust mixture, power, and commensurate priors. We apply the approach to an adaptive design in which the number of recruited patients is adjusted depending on the effective sample size at an interim analysis. We argue that the ECSS is the appropriate measure in this case, as the aim is to save current (as opposed to historical) patients from recruitment. Furthermore, the ECSS can help overcome lack of consensus in the ESS assessment of mixture priors and can, more broadly, provide further insights into the impact of priors. An R package accompanies the paper.

Power gains by using external information in clinical trials are typically not possible when requiring strict type I error control.

In the era of precision medicine, novel designs are developed to deal with flexible clinical trials that incorporate many treatment strategies for multiple diseases in one trial setting. This situation often leads to small sample sizes in disease-treatment combinations and has fostered the discussion about the benefits of borrowing of external or historical information for decision-making in these trials. Several methods have been proposed that dynamically discount the amount of information borrowed from historical data based on the conformity between historical and current data. Specifically, Bayesian methods have been recommended and numerous investigations have been performed to characterize the properties of the various borrowing mechanisms with respect to the gain to be expected in the trials. However, there is common understanding that the risk of type I error inflation exists when information is borrowed and many simulation studies are carried out to quantify this effect. To add transparency to the debate, we show that if prior information is conditioned upon and a uniformly most powerful test exists, strict control of type I error implies that no power gain is possible under any mechanism of incorporation of prior information, including dynamic borrowing. The basis of the argument is to consider the test decision function as a function of the current data even when external information is included. We exemplify this finding in the case of a pediatric arm appended to an adult trial and dichotomous outcome for various methods of dynamic borrowing from adult information to the pediatric arm. In conclusion, if use of relevant external data is desired, the requirement of strict type I error control has to be replaced by more appropriate metrics.

Telomere length, arsenic exposure and risk of basal cell carcinoma of skin.

Telomere length per se a heritable trait has been reported to be associated with different diseases including cancers. In this study, based on arsenic-exposed 528 cases with basal cell carcinoma (BCC) of skin and 533 healthy controls, we investigated effect of telomere length, measured by real-time PCR, on the disease risk. We observed a statistically significant association between decreased telomere length and increased BCC risk [odds ratio (OR) = 5.92, 95% confidence interval (CI) = 3.92 to 9.01, P < 0.0001]. Due to confounder effect of arsenic exposure, in a two-sample Mendelian randomization (MR), telomere length associated single-nucleotide polymorphisms as instrument variables violated valid assumptions; however, one-sample MR adjusted for arsenic exposure indicated an increased risk of BCC with short telomeres. The interaction between arsenic exposure and telomere length on BCC risk was statistically significant (P = 0.02). Within each tertile based on arsenic exposure, the individuals with shorter telomeres were at an increased risk of BCC, with highest risk being in the highest exposed group (OR = 16.13, 95% CI = 6.71 to 40.00, P < 0.0001), followed by those in medium exposure group and low exposure group. The combined effect of highest arsenic exposure and shortest telomeres on BCC risk (OR = 10.56, 95% CI = 5.14 to 21.70) showed a statistically significant departure from additivity (interaction contrast ratio 6.56, P = 0.03). Our results show that in the presence of arsenic exposure, decreased telomere length predisposes individuals to increased risk of BCC, with the effect being synergistic in individuals with highest arsenic exposure and shortest telomeres.

Model-based estimation of lowest observed effect concentration from replicate experiments to identify potential biomarkers of in vitro neurotoxicity.

A paradigm shift is occurring in toxicology following the report of the National Research Council of the USA National Academies entitled "Toxicity testing in the 21st Century: a vision and strategy". This new vision encourages the use of in vitro and in silico models for toxicity testing. In the goal to identify new reliable markers of toxicity, the responsiveness of different genes to various drugs (amiodarone: 0.312-2.5 [Formula: see text]; cyclosporine A: 0.25-2 [Formula: see text]; chlorpromazine: 0.625-10 [Formula: see text]; diazepam: 1-8 [Formula: see text]; carbamazepine: 6.25-50 [Formula: see text]) is studied in 3D aggregate brain cell cultures. Genes' responsiveness is quantified and ranked according to the Lowest Observed Effect Concentration (LOEC), which is estimated by reverse regression under a log-logistic model assumption. In contrast to approaches where LOEC is identified by the first observed concentration level at which the response is significantly different from a control, the model-based approach allows a principled estimation of the LOEC and of its uncertainty. The Box-Cox transform both sides approach is adopted to deal with heteroscedastic and/or non-normal residuals, while estimates from repeated experiments are summarized by a meta-analytic approach. Different inferential procedures to estimate the Box-Cox coefficient, and to obtain confidence intervals for the log-logistic curve parameters and the LOEC, are explored. A simulation study is performed to compare coverage properties and estimation errors for each approach. Application to the toxicological data identifies the genes Cort, Bdnf, and Nov as good candidates for in vitro biomarkers of toxicity.

Effect of a Single Aspirin Dose Prior to Fecal Immunochemical Testing on Test Sensitivity for Detecting Advanced Colorectal Neoplasms: A Randomized Clinical Trial.

Importance: Fecal immunochemical tests for hemoglobin are widely used for colorectal cancer (CRC) screening. Observational studies suggested that sensitivity of fecal immunochemical tests for detecting advanced neoplasms could be increased by acetylsalicylic acid (aspirin), especially among men. Objective: To evaluate the potential to increase sensitivity of fecal immunochemical tests by administering a single 300-mg oral aspirin dose 2 days before stool sampling. Design, Setting, and Participants: A randomized, placebo-controlled, double-blind trial was conducted in 14 gastroenterology practices and 4 hospitals in Germany, and included 2422 men and women aged 40 to 80 years scheduled for colonoscopy, with no recent use of aspirin or other drugs with antithrombotic effects (enrollment from June 2013 to November 2016, and final follow-up January 27, 2017). Interventions: Administration of a single tablet containing 300 mg of aspirin (n = 1208) or placebo (n = 1214) 2 days before fecal sampling for fecal immunochemical test. Main Outcome and Measures: The primary outcome was sensitivity of a quantitative fecal immunochemical test at 2 predefined cutoffs (10.2 and 17-µg Hb/g stool) for detecting advanced neoplasms (colorectal cancer or advanced adenoma). Results: Among 2422 randomized patients (mean [SD] age, 59.6 [7.9] years; 1219, 50%, men), 2134 were included in the analysis (78% for primary screening colonoscopy, 22% for diagnostic colonoscopy). Advanced neoplasms were identified in 224 participants (10.5%), including 8 participants (0.4%) with CRC and 216 participants (10.1%) with advanced adenoma. Sensitivity was 40.2% in the aspirin group and 30.4% in the placebo group (difference 9.8%, 95% CI, -3.1% to 22.2%, P = .14) at cutoff 10.2-µg Hb/g stool and 28.6% in the aspirin and 22.5% in the placebo group (difference 6.0%, 95% CI, -5.7% to 17.5%, P = .32) at cutoff 17-µg Hb/g stool. Conclusions and Relevance: Among adults aged 40 to 80 years not using aspirin or other antithrombotic medications, administration of a single dose of oral aspirin prior to fecal immunochemical testing, compared with placebo, did not significantly increase test sensitivity for detecting advanced colorectal neoplasms at 2 predefined cutoffs of a quantitative fecal immunochemical test. Trial registration: Deutsches Register Klinischer Studien Identifier: DRKS00003252; EudraCT Identifier: 2011-005603-32/DE.

Would initiating colorectal cancer screening from age of 45 be cost-effective in Germany? An individual-level simulation analysis.

Background: Colorectal cancer (CRC) screening has been shown to be effective and cost-saving. However, the trend of rising incidence of early-onset CRC challenges the current national screening program solely for people ≥50 years in Germany, where extending the screening to those 45-49 years might be justified. This study aims to evaluate the cost-effectiveness of CRC screening strategies starting at 45 years in Germany. Method: DECAS, an individual-level simulation model accounting for both adenoma and serrated pathways of CRC development and validated with German CRC epidemiology and screening effects, was used for the cost-effectiveness analysis. Four CRC screening strategies starting at age 45, including 10-yearly colonoscopy (COL), annual/biennial fecal immunochemical test (FIT), or the combination of the two, were compared with the current screening offer starting at age 50 years in Germany. Three adherence scenarios were considered: perfect adherence, current adherence, and high screening adherence. For each strategy, a cohort of 100,000 individuals with average CRC risk was simulated from age 20 until 90 or death. Outcomes included CRC cases averted, prevented death, quality-adjusted life-years gained (QALYG), and total incremental costs considering both CRC treatment and screening costs. A 3% discount rate was applied and costs were in 2023 Euro. Result: Initiating 10-yearly colonoscopy-only or combined FIT + COL strategies at age 45 resulted in incremental gains of 7-28 QALYs with incremental costs of €28,360-€71,759 per 1,000 individuals, compared to the current strategy. The ICER varied from €1,029 to €9,763 per QALYG, and the additional number needed for colonoscopy ranged from 129 to 885 per 1,000 individuals. Among the alternatives, a three times colonoscopy strategy starting at 45 years of age proves to be the most effective, while the FIT-only strategy was dominated by the currently implemented strategy. The findings remained consistent across probabilistic sensitivity analyses. Conclusion: The cost-effectiveness findings support initiating CRC screening at age 45 with either colonoscopy alone or combined with FIT, demonstrating substantial gains in quality-adjusted life-years with a modest increase in costs. Our findings emphasize the importance of implementing CRC screening 5 years earlier than the current practice to achieve more significant health and economic benefits.

A diagnostic phase III/IV seamless design to investigate the diagnostic accuracy and clinical effectiveness using the example of HEDOS and HEDOS II.

The development process of medical devices can be streamlined by combining different study phases. Here, for a diagnostic medical device, we present the combination of confirmation of diagnostic accuracy (phase III) and evaluation of clinical effectiveness regarding patient-relevant endpoints (phase IV) using a seamless design. This approach is used in the Thyroid HEmorrhage DetectOr Study (HEDOS & HEDOS II) investigating a post-operative hemorrhage detector named ISAR-M THYRO® in patients after thyroid surgery. Data from the phase III trial are reused as external controls in the control group of the phase IV trial. An unblinded interim analysis is planned between the two study stages which includes a recalculation of the sample size for the phase IV part after completion of the first stage of the seamless design. The study concept presented here is the first seamless design proposed in the field of diagnostic studies. Hence, the aim of this work is to emphasize the statistical methodology as well as feasibility of the proposed design in relation to the planning and implementation of the seamless design. Seamless designs can accelerate the overall trial duration and increase its efficiency in terms of sample size and recruitment. However, careful planning addressing numerous methodological and procedural challenges is necessary for successful implementation as well as agreement with regulatory bodies.

Modeling the Natural History and Screening Effects of Colorectal Cancer Using Both Adenoma and Serrated Neoplasia Pathways: The Development, Calibration, and Validation of a Discrete Event Simulation Model.

Background. Existing colorectal cancer (CRC) screening models mostly focus on the adenoma pathway of CRC development, overlooking the serrated neoplasia pathway, which might result in overly optimistic screening predictions. In addition, Bayesian inference methods have not been widely used for model calibration. We aimed to develop a CRC screening model accounting for both pathways, calibrate it with approximate Bayesian computation (ABC) methods, and validate it with large CRC screening trials. Methods. A discrete event simulation (DES) of the CRC natural history (DECAS) was constructed using the adenoma and serrated pathways in R software. The model simulates CRC-related events in a specific birth cohort through various natural history states. Calibration took advantage of 74 prevalence data points from the German screening colonoscopy program of 5.2 million average-risk participants using an ABC method. CRC incidence outputs from DECAS were validated with the German national cancer registry data; screening effects were validated using 17-y data from the UK Flexible Sigmoidoscopy Screening sigmoidoscopy trial and a German screening colonoscopy cohort study. Results. The Bayesian calibration rendered 1,000 sets of posterior parameter samples. With the calibrated parameters, the observed age- and sex-specific CRC prevalences from the German registries were within the 95% DECAS-predicted intervals. Regarding screening effects, DECAS predicted a 41% (95% intervals 30%-51%) and 62% (95% intervals 55%-68%) reduction in 17-y cumulative CRC mortality for a single screening sigmoidoscopy and colonoscopy, respectively, falling within 95% confidence intervals reported in the 2 clinical studies used for validation. Conclusions. We presented DECAS, the first Bayesian-calibrated DES model for CRC natural history and screening, accounting for 2 CRC tumorigenesis pathways. The validated model can serve as a valid tool to evaluate the (cost-)effectiveness of CRC screening strategies. Highlights: This article presents a new discrete event simulation model, DECAS, which models both adenoma-carcinoma and serrated neoplasia pathways for colorectal cancer (CRC) development and CRC screening effects.DECAS is calibrated based on a Bayesian inference method using the data from German screening colonoscopy program, which consists of more than 5 million first-time average-risk participants aged 55 years and older in 2003 to 2014.DECAS is flexible for evaluating various CRC screening strategies and can differentiate screening effects in different parts of the colon.DECAS is validated with large screening sigmoidoscopy and colonoscopy clinical study data and can be further used to evaluate the (cost-)effectiveness of German colorectal cancer screening strategies.

Distinct HLA-E Peptide Complexes Modify Antibody-Driven Effector Functions of Adaptive NK Cells.

Adaptive NK cells are characterized by profound alterations in multiple signaling molecules, transcription factors, and epigenetic modifications compared with canonical NK cells. Although their existence is associated with prior exposure to human cytomegalovirus (HCMV), key questions regarding their regulation and function remain. A large proportion of adaptive NK cells express the activating receptor CD94/NKG2C, binding to human leukocyte antigen E (HLA-E), that presents a limited set of peptides. We show that adaptive NK cells discriminate differences between HLA-E-peptide complexes with exquisite specificity. Prolonged exposure to an environment displaying the HLA-E peptide ligand VMAPRTLFL, derived from the leader sequence of HLA-G, enriched adaptive NK cells with low FcεRγ expression, upregulated CD25 expression, increased proliferative activity, and resulted in elevated antibody-dependent cellular cytotoxicity and IFN-γ responses compared with other HLA-E peptide complexes. Our study demonstrates that recognition of alterations in the HLA-E ligandome via an activating receptor can influence heterologous effector mechanisms and proliferation in adaptive NK cells.