Comparative Effectiveness of Anti-TNF in Combination With Low-Dose Methotrexate vs Anti-TNF Monotherapy in Pediatric Crohn's Disease: A Pragmatic Randomized Trial.

BACKGROUND & AIMS: Tumor necrosis factor inhibitors, including infliximab and adalimumab, are a mainstay of pediatric Crohn's disease therapy; however, nonresponse and loss of response are common. As combination therapy with methotrexate may improve response, we performed a multicenter, randomized, double-blind, placebo-controlled pragmatic trial to compare tumor necrosis factor inhibitors with oral methotrexate to tumor necrosis factor inhibitor monotherapy. METHODS: Patients with pediatric Crohn's disease initiating infliximab or adalimumab were randomized in 1:1 allocation to methotrexate or placebo and followed for 12-36 months. The primary outcome was a composite indicator of treatment failure. Secondary outcomes included anti-drug antibodies and patient-reported outcomes of pain interference and fatigue. Adverse events (AEs) and serious AEs (SAEs) were collected. RESULTS: Of 297 participants (mean age, 13.9 years, 35% were female), 156 were assigned to methotrexate (110 infliximab initiators and 46 adalimumab initiators) and 141 to placebo (102 infliximab initiators and 39 adalimumab initiators). In the overall population, time to treatment failure did not differ by study arm (hazard ratio, 0.69; 95% CI, 0.45-1.05). Among infliximab initiators, there were no differences between combination and monotherapy (hazard ratio, 0.93; 95% CI, 0.55-1.56). Among adalimumab initiators, combination therapy was associated with longer time to treatment failure (hazard ratio, 0.40; 95% CI, 0.19-0.81). A trend toward lower anti-drug antibody development in the combination therapy arm was not significant (infliximab: odds ratio, 0.72; 95% CI, 0.49-1.07; adalimumab: odds ratio, 0.71; 95% CI, 0.24-2.07). No differences in patient-reported outcomes were observed. Combination therapy resulted in more AEs but fewer SAEs. CONCLUSIONS: Among adalimumab but not infliximab initiators, patients with pediatric Crohn's disease treated with methotrexate combination therapy experienced a 2-fold reduction in treatment failure with a tolerable safety profile. CLINICALTRIALS: gov, Number: NCT02772965.

High Body Mass Index and Response to Anti-Tumor Necrosis Factor Therapy in Pediatric Crohn's Disease.

INTRODUCTION: Obesity is common among patients with pediatric Crohn's disease (PCD). Some adult studies suggest obese patients respond less well to anti-tumor necrosis factor (TNF) treatment. This study sought compares anti-TNF response and anti-TNF levels between pediatric patients with normal and high body mass index (BMI). METHODS: The COMBINE trial compared anti-TNF monotherapy with combination therapy with methotrexate in patients with PCD. In this secondary analysis, a comparison of time-to-treatment failure among patients with normal BMI vs BMI Z -score >1, adjusting for prescribed anti-TNF (infliximab [IFX] or adalimumab [ADA]), trial treatment assignment (combination vs monotherapy), and relevant covariates. Median anti-TNF levels across BMI category was also examined. RESULTS: Of 224 participants (162 IFX initiators and 62 ADA initiators), 111 (81%) had a normal BMI and 43 (19%) had a high BMI. High BMI was associated with treatment failure among ADA initiators (7/10 [70%] vs 12/52 [23%], hazard ratio 0.29, P = 0.007) but not IFX initiators. In addition, ADA-treated patients with a high BMI had lower ADA levels compared with those with normal BMI (median 5.8 vs 12.8 µg/mL, P = 0.02). IFX trough levels did not differ between BMI groups. DISCUSSION: Overweight and obese patients with PCD are more likely to experience ADA treatment failure than those with normal BMI. Higher BMI was associated with lower drug trough levels. Standard ADA dosing may be insufficient for overweight children with PCD. Among IFX initiators, there was no observed difference in clinical outcomes or drug levels, perhaps due to weight-based dosing and/or greater use of proactive drug monitoring.

Efficient testing of the biomarker positive and negative subgroups in a biomarker-stratified trial.

In many randomized placebo-controlled trials with a biomarker defined subgroup, it is believed that this subgroup has the same or higher treatment effect compared with its complement. These subgroups are often referred to as the biomarker positive and negative subgroups. Most biomarker-stratified pivotal trials are aimed at demonstrating a significant treatment effect either in the biomarker positive subgroup or in the overall population. A major shortcoming of this approach is that the treatment can be declared effective in the overall population even though it has no effect in the biomarker negative subgroup. We use the isotonic assumption about the treatment effects in the two subgroups to construct an efficient way to test for a treatment effect in both the biomarker positive and negative subgroups. A substantial reduction in the required sample size for such a trial compared with existing methods makes evaluating the treatment effect in both the biomarker positive and negative subgroups feasible in pivotal trials especially when the prevalence of the biomarker positive subgroup is less than 0.5.

A frequentist design for basket trials using adaptive lasso.

A basket trial aims to expedite the drug development process by evaluating a new therapy in multiple populations within the same clinical trial. Each population, referred to as a "basket", can be defined by disease type, biomarkers, or other patient characteristics. The objective of a basket trial is to identify the subset of baskets for which the new therapy shows promise. The conventional approach would be to analyze each of the baskets independently. Alternatively, several Bayesian dynamic borrowing methods have been proposed that share data across baskets when responses appear similar. These methods can achieve higher power than independent testing in exchange for a risk of some inflation in the type 1 error rate. In this paper we propose a frequentist approach to dynamic borrowing for basket trials using adaptive lasso. Through simulation studies we demonstrate adaptive lasso can achieve similar power and type 1 error to the existing Bayesian methods. The proposed approach has the benefit of being easier to implement and faster than existing methods. In addition, the adaptive lasso approach is very flexible: it can be extended to basket trials with any number of treatment arms and any type of endpoint.

Finding the best subgroup with differential treatment effect with multiple outcomes.

Precision medicine aims to identify specific patient subgroups that may benefit the most from a particular treatment than the whole population. Existing definitions for the best subgroup in subgroup analysis are based on a single outcome and do not consider multiple outcomes; specifically, outcomes of different types. In this article, we introduce a definition for the best subgroup under a multiple-outcome setting with continuous, binary, and censored time-to-event outcomes. Our definition provides a trade-off between the subgroup size and the conditional average treatment effects (CATE) in the subgroup with respect to each of the outcomes while taking the relative contribution of the outcomes into account. We conduct simulations to illustrate the proposed definition. By examining the outcomes of urinary tract infection and renal scarring in the RIVUR clinical trial, we identify a subgroup of children that would benefit the most from long-term antimicrobial prophylaxis.

Shape restricted additive hazards models: Monotone, unimodal, and U-shape hazard functions.

We consider estimation of the semiparametric additive hazards model with an unspecified baseline hazard function where the effect of a continuous covariate has a specific shape but otherwise unspecified. Such estimation is particularly useful for a unimodal hazard function, where the hazard is monotone increasing and monotone decreasing with an unknown mode. A popular approach of the proportional hazards model is limited in such setting due to the complicated structure of the partial likelihood. Our model defines a quadratic loss function, and its simple structure allows a global Hessian matrix that does not involve parameters. Thus, once the global Hessian matrix is computed, a standard quadratic programming method can be applicable by profiling all possible locations of the mode. However, the quadratic programming method may be inefficient to handle a large global Hessian matrix in the profiling algorithm due to a large dimensionality, where the dimension of the global Hessian matrix and number of hypothetical modes are the same order as the sample size. We propose the quadratic pool adjacent violators algorithm to reduce computational costs. The proposed algorithm is extended to the model with a time-dependent covariate with monotone or U-shape hazard function. In simulation studies, our proposed method improves computational speed compared to the quadratic programming method, with bias and mean square error reductions. We analyze data from a recent cardiovascular study.

Antimicrobial prophylaxis for vesicoureteral reflux: which subgroups of children benefit the most?

BACKGROUND: While the Randomized Intervention for Children with Vesicoureteral Reflux (RIVUR) trial found that long-term antimicrobial prophylaxis reduced the risk of urinary tract infection (UTI) recurrences by 50%, 10 children had to be treated for one to benefit (i.e., observed number needed to treat (NNT) of 10). Accordingly, we re-analyzed RIVUR data to systematically identify subgroups of children with vesicoureteral reflux (VUR) with a smaller NNT. METHODS: Using patient-level data from the RIVUR trial, we applied penalized regression methods including the baseline age, VUR grade, type of index UTI, and bowel-bladder dysfunction (BBD) as covariates to identify subgroups. RESULTS: We identified four relevant subgroups of children that appear to benefit from long-term antimicrobial prophylaxis, all with observed NNTs smaller than or equal to 5: children with grade IV VUR, BBD, and febrile index UTI (1% of the sample), children with BBD and febrile index UTI (7% of the sample), children with BBD (12% of the sample), and children with grade IV VUR (8% of the sample). CONCLUSIONS: Use of long-term antimicrobial prophylaxis appears to be particularly relevant for children with BBD (and any grade of VUR) and those with grade IV VUR (regardless of BBD status). However, because details regarding the treatment of BBD are not available, further studies are needed to fully determine the role of prophylactic antimicrobials in the management of children with VUR who have BBD.

Gut Microbiota and Biomarkers of Endothelial Dysfunction in Cirrhosis.

Our aim was to study the association of endothelial dysfunction biomarkers with cirrhosis manifestations, bacterial translocation, and gut microbiota taxa. The fecal microbiome was assessed using 16S rRNA gene sequencing. Plasma levels of nitrite, big endothelin-1, asymmetric dimethylarginine (ADMA), presepsin, and claudin were measured as biomarkers of endothelial dysfunction, bacterial translocation, and intestinal barrier dysfunction. An echocardiography with simultaneous determination of blood pressure and heart rate was performed to evaluate hemodynamic parameters. Presepsin, claudin 3, nitrite, and ADMA levels were higher in cirrhosis patients than in controls. Elevated nitrite levels were associated with high levels of presepsin and claudin 3, the development of hemodynamic circulation, hypoalbuminemia, grade 2-3 ascites, overt hepatic encephalopathy, high mean pulmonary artery pressure, increased abundance of Proteobacteria and Erysipelatoclostridium, and decreased abundance of Oscillospiraceae, Subdoligranulum, Rikenellaceae, Acidaminococcaceae, Christensenellaceae, and Anaerovoracaceae. Elevated ADMA levels were associated with higher Child-Pugh scores, lower serum sodium levels, hypoalbuminemia, grade 2-3 ascites, milder esophageal varices, overt hepatic encephalopathy, lower mean pulmonary artery pressure, and low abundance of Erysipelotrichia and Erysipelatoclostridiaceae. High big endothelin-1 levels were associated with high levels of presepsin and sodium, low levels of fibrinogen and cholesterol, hypocoagulation, increased Bilophila and Coprobacillus abundances, and decreased Alloprevotella abundance.

Fully order restricted multi-arm multi-stage clinical trial design.

We consider a multi-arm trial with two or more active treatments plus a control where it is reasonable to assume an order for the treatment effects of the active arms compared to control. For example, the arms could be a high dose and low dose of a new drug and a placebo. The objective of the trial is to compare each active arm to control while maintaining strong control of the type 1 error rate. We show that when the study is powered to identify all promising treatments, a design that uses the order of the treatment effects to calculate the test statistic and to set the order of testing requires a smaller sample size than a design where each active arm is tested against the control arm independently. Under the considered settings, the sample size for a single-stage trial and a two-stage trial was reduced by at least 20%.

CRM and partial order CRM with adaptive rescaling for dose-finding in immunotherapy trials with a continuous outcome.

In many phase 1 oncology trials of immunotherapies, no dose-limiting toxicities are observed and the maximum tolerated dose cannot be identified. In these settings, dose-finding can be guided by a biomarker of response rather than the occurrences of dose-limiting toxicity. The recommended phase 2 dose can be defined as the dose with mean response equal to a prespecified value of a continuous response biomarker. To target the mean of a continuous biomarker, we build on the idea of the continual reassessment method and the quasi-Bernoulli likelihood. We extend the design to a problem of finding the recommended phase 2 dose combination in a trial with multiple immunotherapies.

The Back Pain Consortium (BACPAC) Research Program: Structure, Research Priorities, and Methods.

In 2019, the National Health Interview survey found that nearly 59% of adults reported pain some, most, or every day in the past 3 months, with 39% reporting back pain, making back pain the most prevalent source of pain, and a significant issue among adults. Often, identifying a direct, treatable cause for back pain is challenging, especially as it is often attributed to complex, multifaceted issues involving biological, psychological, and social components. Due to the difficulty in treating the true cause of chronic low back pain (cLBP), an over-reliance on opioid pain medications among cLBP patients has developed, which is associated with increased prevalence of opioid use disorder and increased risk of death. To combat the rise of opioid-related deaths, the National Institutes of Health (NIH) initiated the Helping to End Addiction Long-TermSM (HEAL) initiative, whose goal is to address the causes and treatment of opioid use disorder while also seeking to better understand, diagnose, and treat chronic pain. The NIH Back Pain Consortium (BACPAC) Research Program, a network of 14 funded entities, was launched as a part of the HEAL initiative to help address limitations surrounding the diagnosis and treatment of cLBP. This paper provides an overview of the BACPAC research program's goals and overall structure, and describes the harmonization efforts across the consortium, define its research agenda, and develop a collaborative project which utilizes the strengths of the network. The purpose of this paper is to serve as a blueprint for other consortia tasked with the advancement of pain related science.

Inference on subgroups identified based on a heterogeneous treatment effect in a post hoc analysis of a clinical trial.

Due to the many benefits of understanding treatment effect heterogeneity in a clinical trial, an exploratory post hoc subgroup analysis is often performed to find subpopulations of patients with conditional average treatment effect that suggests better treatment efficacy than in the overall population. A naive re-substitution approach uses all available data to identify a subgroup and then proceeds with estimation and inference using the same data set. This approach generally leads to an overly optimistic estimate of conditional average treatment effect. In this article, in a post hoc analysis, we estimate the target optimal subgroup through maximizing a utility function, from candidates systematically identified with a penalized regression. We then compare two resampling-based bias-correction methods, cross-validation and debiasing bootstrap, for obtaining approximately unbiased estimates and valid inference of conditional average treatment effect in the identified subgroup, with either an empirical or an augmented estimator. Our results show that both the cross-validation and the debiasing bootstrap methods reduce the re-substitution bias effectively. The cross-validation method appears to have less biased point estimates, smaller standard error estimates, but poorer coverages than the debiasing bootstrap method when using the empirical estimator and the sample size is moderate. Using the augmented estimator in the debiasing bootstrap method leads to less biased point estimates but poorer coverages. We conclude that bias correction should be a part of every exploratory post hoc subgroup analysis to eliminate re-substitution bias and to obtain a proper confidence interval for the estimated conditional average treatment effect in the selected subgroup.

The Precision Interventions for Severe and/or Exacerbation-Prone (PrecISE) Asthma Network: An overview of Network organization, procedures, and interventions.

Asthma is a heterogeneous disease, with multiple underlying inflammatory pathways and structural airway abnormalities that impact disease persistence and severity. Recent progress has been made in developing targeted asthma therapeutics, especially for subjects with eosinophilic asthma. However, there is an unmet need for new approaches to treat patients with severe and exacerbation-prone asthma, who contribute disproportionately to disease burden. Extensive deep phenotyping has revealed the heterogeneous nature of severe asthma and identified distinct disease subtypes. A current challenge in the field is to translate new and emerging knowledge about different pathobiologic mechanisms in asthma into patient-specific therapies, with the ultimate goal of modifying the natural history of disease. Here, we describe the Precision Interventions for Severe and/or Exacerbation-Prone Asthma (PrecISE) Network, a groundbreaking collaborative effort of asthma researchers and biostatisticians from around the United States. The PrecISE Network was designed to conduct phase II/proof-of-concept clinical trials of precision interventions in the population with severe asthma, and is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health. Using an innovative adaptive platform trial design, the PrecISE Network will evaluate up to 6 interventions simultaneously in biomarker-defined subgroups of subjects. We review the development and organizational structure of the PrecISE Network, and choice of interventions being studied. We hope that the PrecISE Network will enhance our understanding of asthma subtypes and accelerate the development of therapeutics for severe asthma.

Anatilimnocola floriformis sp. nov., a novel member of the family Pirellulaceae from a boreal lake, and emended description of the genus Anatilimnocola.

Planctomycetes of the family Pirellulaceae are commonly addressed as budding aquatic bacteria with a complex lifestyle. Although this family is well represented by cultured and taxonomically characterized isolates, nearly all of them were obtained from brackish or marine habitats. The examples of described freshwater Pirellulaceae planctomycetes are limited to two species only, Pirellula staley and 'Anatilimnocola aggregata'. In this study, we characterized a novel freshwater planctomycete of the genus 'Anatilimnocola', strain PX40T, which was isolated from a boreal eutrophic lake. Strain PX40T was represented by budding, unpigmented, ellipsoidal to pear-shaped cells, which often occurred in characteristic flower-like rosettes. Cells were covered by bundles of fimbriae; crateriform-like structures were localized on a reproductive cell pole only. These planctomycetes were obligately aerobic, heterotrophic bacteria that utilized various sugars and some polysaccharides, and were highly sensitive to NaCl. Growth occurred in the pH range 5.0-7.5 (with an optimum at pH 6.5-7.0), and at temperatures between 15 and 30 °C (with an optimum at 22-25 °C). The major fatty acids of strain PX40T were C18:1ω9c, C16:0, and 16:1ω7c; cells also contained a wide variety of hydroxy- and dihydroxy-fatty acids and a C31:9 alkene. The major intact polar lipids were diacylglyceryl-(N,N,N)-trimethylhomoserines. The 16S rRNA gene sequence of strain PX40T displayed 96.6% similarity to that of 'Anatilimnocola aggregata' ETA_A8T. The genome of strain PX40T was 8.93 Mb in size and contained one copy of rRNA operon, 76 tRNA genes and 7092 potential protein-coding genes. The DNA G+C content was 57.8%. The ANI value between strain PX40T and 'Anatilimnocola aggregata' ETA_A8T was 78.3%, suggesting that these planctomycetes represent distinct species. We, therefore, propose a novel species of the genus 'Anatilimnocola', 'A. floriformis' sp. nov., with strain PX40T (= KCTC 92369T = VKM B-3621T = UQM 41463T) as the type strain.

Randomization tests in clinical trials with multiple imputation for handling missing data.

Randomization-based inference is a useful alternative to traditional population model-based methods. In trials with missing data, multiple imputation is often used. We describe how to construct a randomization test in clinical trials where multiple imputation is used for handling missing data. We illustrate the proposed methodology using Fisher's combining function applied to individual scores in two post-traumatic stress disorder trials.

Wide distribution of Phycisphaera-like planctomycetes from WD2101 soil group in peatlands and genome analysis of the first cultivated representative.

Phycisphaera-like WD2101 'soil group' is one of the as-yet-uncultivated phylogenetic clades within the phylum Planctomycetes. Members of this clade are commonly detected in various terrestrial habitats. This study shows that WD2101 represented one of the major planctomycete groups in 10 boreal peatlands, comprising up to 76% and 36% of all Planctomycetes-affiliated 16S rRNA gene reads in raised bogs and eutrophic fens respectively. These types of peatlands displayed clearly distinct intra-group diversity of WD2101-affiliated planctomycetes. The first isolate of this enigmatic planctomycete group, strain M1803, was obtained from a humic lake surrounded by Sphagnum peat bogs. Strain M1803 displayed 89.2% 16S rRNA gene similarity to Tepidisphaera mucosa and was represented by motile cocci that divided by binary fission and grew under micro-oxic conditions. The complete 7.19 Mb genome of strain M1803 contained an array of genes encoding Planctomycetal type bacterial microcompartment organelle likely involved in l-rhamnose metabolism, suggesting participation of M1803-like planctomycetes in polysaccharide degradation in peatlands. The corresponding cellular microcompartments were revealed in ultrathin cell sections. Strain M1803 was classified as a novel genus and species, Humisphaera borealis gen. nov., sp. nov., affiliated with the formerly recognized WD2101 'soil group'.

Consistency of the CRM when the dose-toxicity curve is not monotone and its application to the POCRM.

The continual reassessment method (CRM) is a well-known design for dose-finding trials with the goal of estimating the maximum tolerated dose (MTD), the dose with a given probability of toxicity. The standard assumption is that the probability of toxicity monotonically increases with dose. We show that the CRM can still be consistent and correctly identify the MTD even when the dose-toxicity curve is not monotone as long as there is monotonicity of the true toxicity probabilities right below and right above the true MTD. In the case of multiple therapies, where it is unclear how to order combinations of dose levels of multiple therapies, our findings provide insight into the performance of the partial order CRM (POCRM). To select the correct dose combination at the end of a trial, the POCRM does not have to select a monotone ordering of drug combinations. We illustrate the connection between our results for the CRM with a nonmonotone dose-toxicity curve and the POCRM via simulations.

Lamin A as a Determinant of Mechanical Properties of the Cell Nucleus in Health and Disease.

One of the main factors associated with worse prognosis in oncology is metastasis, which is based on the ability of tumor cells to migrate from the primary source and to form secondary tumors. The search for new strategies to control migration of metastatic cells is one of the urgent issues in biomedicine. One of the strategies to stop spread of cancer cells could be regulation of the nuclear elasticity. Nucleus, as the biggest and stiffest cellular compartment, determines mechanical properties of the cell as a whole, and, hence, could prevent cell migration through the three-dimensional extracellular matrix. Nuclear rigidity is maintained by the nuclear lamina, two-dimensional network of intermediate filaments in the inner nuclear membrane (INM). Here we present the most significant factors defining nucleus rigidity, discuss the role of nuclear envelope composition in the cell migration, as well consider possible approaches to control lamina composition in order to change plasticity of the cell nucleus and ability of the tumor cells to metastasize.

100-year-old enigma solved: identification, genomic characterization and biogeography of the yet uncultured Planctomyces bekefii.

The first representative of the phylum Planctomycetes, Planctomyces bekefii, was described nearly one century ago. This morphologically conspicuous freshwater bacterium is a rare example of as-yet-uncultivated prokaryotes with validly published names and unknown identity. We report the results of molecular identification of this elusive bacterium, which was detected in a eutrophic boreal lake in Northern Russia. By using high-performance cell sorting, P. bekefii-like cell rosettes were selectively enriched from lake water. The retrieved 16S rRNA gene sequence was nearly identical to those in dozens of metagenomes assembled from freshwater lakes during cyanobacterial blooms and was phylogenetically placed within a large group of environmental sequences originating from various freshwater habitats worldwide. In contrast, 16S rRNA gene sequence similarity to all currently described members of the order Planctomycetales was only 83%-92%. The metagenome assembled for P. bekefii reached 43% genome coverage and showed the potential for degradation of peptides, pectins, and sulfated polysaccharides. Tracing the seasonal dynamics of P. bekefii by Illumina paired-end sequencing of 16S rRNA gene fragments and by fluorescence in situ hybridization revealed that these bacteria only transiently surpass the detection limit, with a characteristic population peak of up to 104 cells ml-1 following cyanobacterial blooms.

Chemotherapy Following PD-1 Inhibitor Blockade in Patients with Unresectable Stage III/Stage IV Metastatic Melanoma: A Single Academic Institution Experience.

Retrospective case studies in various cancers have shown clinical benefit from chemotherapy following PD-1 inhibitor progression. We asked whether we see a similar clinical benefit with chemotherapy following PD-1 inhibitor progression in metastatic melanoma. We performed a retrospective study in patients with metastatic melanoma, who had received PD-1 inhibitor-based treatments, subsequently progressed, and eventually received chemotherapy. We identified 25 patients (median age 58 years; range 31-77 years; 13 females). Most patients had cutaneous melanoma (72%), were BRAFV600E-negative (75%), and received single-agent temozolomide (84%). At a median follow-up of 21.0 months (range: 4.1-154.2 months), 2 patients had durable response to chemotherapy (progression-free survival is 31.9+ and 21.6+ months, respectively), and 1 patient had a partial, short-term response. We conclude that in this poor prognosis group administration of chemotherapy has a 12% response rate that can be durable. Overall, the clinical benefit is not inferior to that of PD-1 inhibitor-based treatments.