Regulatory Issues of Platform Trials: Learnings from EU-PEARL

Although platform trials have many benefits, the complexity of these designs may result not only in increased methodological but also regulatory and ethical challenges. These aspects were addressed as part of the IMI project EU Patient-Centric Clinical Trial Platforms (EU-PEARL). We reviewed the available guidelines on platform trials in the European Union and the United States. This is supported and complemented by feedback received from regulatory interactions with the European Medicines Agency and the US Food and Drug Administration. Throughout the project we collected the needs of all relevant stakeholders including ethics committees, regulators, and health technology assessment bodies through active dialog and dedicated stakeholder workshops. Furthermore, we focused on methodological aspects and where applicable identified the corresponding guidance. Learnings from the guideline review, regulatory interactions, and workshops are provided. Based on these, a master protocol template was developed. Issues that still need harmonization or clarification in guidelines or where further methodological research is needed are also presented. These include questions around clinical trial submissions in Europe, the need for multiplicity control across the whole master protocol, the use of non-concurrent controls, and the impact of different randomization schemes. Master protocols are an efficient and patient-centered clinical trial design that can expedite drug development. However, they can also introduce additional operational and regulatory complexities. It is important to understand the different requirements of stakeholders upfront and address them in the trial. While relevant guidance is increasing, early dialog with relevant stakeholders can help to further support such designs.

Adaptive platform trials: the impact of common controls on type one error and power

Platform trials offer a framework to study multiple interventions in one trial with the opportunity of opening and closing arms. The use of common controls can increase efficiency as compared to individual controls. The need for multiplicity adjustment because of common controls is currently a debate among researchers, pharmaceutical companies, and regulators. The impact of common controls on the type one error in a fixed platform trial, i.e. when all treatments start and end recruitment at the same time, has been discussed in the literature before. We complement these findings by investigating the impact of a common control on the type one error and power in a flexible platform trial, i.e. when one arm joins the platform later. We derived the correlation of test statistics to assess the impact of the overlap and compared the results to a trial with individual controls. Furthermore, we evaluate the power, and the impact of multiplicity adjustment on the power in fixed and flexible platform trials. These methodological considerations are complemented by a regulatory guideline review. With multiple arms, the FWER is inflated when no multiplicity adjustment is applied. However, the FWER inflation is smaller with common controls than with individual controls. Even after multiplicity adjustment, a trial with common controls is often beneficial in terms of sample size and power. However, in some cases, the trial with common controls loses the efficiency gain and it might be advisable to run a separate trial rather than joining a platform trial.

Stochastic Dispersal Rather Than Deterministic Selection Explains the Spatio-Temporal Distribution of Soil Bacteria in a Temperate Grassland

Spatial and temporal processes shaping microbial communities are inseparably linked but rarely studied together. By Illumina 16S rRNA sequencing, we monitored soil bacteria in 360 stations on a 100 square meter plot distributed across six intra-annual samplings in a rarely managed, temperate grassland. Using a multi-tiered approach, we tested the extent to which stochastic or deterministic processes influenced the composition of local communities. A combination of phylogenetic turnover analysis and null modeling demonstrated that either homogenization by unlimited stochastic dispersal or scenarios, in which neither stochastic processes nor deterministic forces dominated, explained local assembly processes. Thus, the majority of all sampled communities (82%) was rather homogeneous with no significant changes in abundance-weighted composition. However, we detected strong and uniform taxonomic shifts within just nine samples in early summer. Thus, community snapshots sampled from single points in time or space do not necessarily reflect a representative community state. The potential for change despite the overall homogeneity was further demonstrated when the focus shifted to the rare biosphere. Rare OTU turnover, rather than nestedness, characterized abundance-independent β-diversity. Accordingly, boosted generalized additive models encompassing spatial, temporal and environmental variables revealed strong and highly diverse effects of space on OTU abundance, even within the same genus. This pure spatial effect increased with decreasing OTU abundance and frequency, whereas soil moisture – the most important environmental variable – had an opposite effect by impacting abundant OTUs more than the rare ones. These results indicate that – despite considerable oscillation in space and time – the abundant and resident OTUs provide a community backbone that supports much higher β-diversity of a dynamic rare biosphere. Our findings reveal complex interactions among space, time, and environmental filters within bacterial communities in a long-established temperate grassland.

EMA Review of Axicabtagene Ciloleucel (Yescarta) for the Treatment of Diffuse Large B-Cell Lymphoma

On June 28, 2018, the Committee for Advanced Therapies and the Committee for Medicinal Products for Human Use adopted a positive opinion, recommending the granting of a marketing authorization for the medicinal product Yescarta for the treatment of adult patients with relapsed or refractory diffuse large B-cell lymphoma and primary mediastinal large B-cell lymphoma, after two or more lines of systemic therapy. Yescarta, which was designated as an orphan medicinal product and included in the European Medicines Agency's Priority Medicines scheme, was granted an accelerated review timetable. The active substance of Yescarta is axicabtagene ciloleucel, an engineered autologous T-cell immunotherapy product whereby a patient's own T cells are harvested and genetically modified ex vivo by retroviral transduction using a retroviral vector to express a chimeric antigen receptor (CAR) comprising an anti-CD19 single chain variable fragment linked to CD28 costimulatory domain and CD3-zeta signaling domain. The transduced anti-CD19 CAR T cells are expanded ex vivo and infused back into the patient, where they can recognize and eliminate CD19-expressing cells. The benefits of Yescarta as studied in ZUMA-1 phase II (NCT02348216) were an overall response rate per central review of 66% (95% confidence interval, 56%-75%) at a median follow-up of 15.1 months in the intention to treat population and a complete response rate of 47% with a significant duration. The most common adverse events were cytokine release syndrome, neurological adverse events, infections, pyrexia, diarrhea, nausea, hypotension, and fatigue. IMPLICATIONS FOR PRACTICE: Yescarta (axicabtagene ciloleucel) was the first chimeric antigen receptor T-cell therapy to be submitted for evaluation to the European Medicines Agency and admitted into the "priority medicine" scheme; it was granted accelerated assessment on the basis of anticipated clinical benefit in relapsed/refractory diffuse large B-cell lymphoma, a condition of unmet medical need. Indeed, Yescarta showed an overall response rate of 66% and a complete response rate of 47% with a significant duration and a manageable toxicity that compared very favorably with historical controls. Here the analysis of benefits and risks is presented, and specific challenges with this important novel product are highlighted, providing further insights and reflections for future medical research.

[Current challenges in the assessment of ethical proposals-aspects of digitalization and personalization in the healthcare system]

The global aim of medical ethics committees is to judge the scientific quality and the integrity of the content of medical research projects (studies), thereby assessing the benefit-risk profile. Apart from judging content-related aspects and the legal correctness, the study design and the analysis strategy must also be assessed from a biostatistical point of view. This very sophisticated task is further complicated by the fact that medical research constantly faces new challenges.Within this work, current developments in medical research that directly impact the assessability of ethical proposals will be identified and discussed. The aim is to sensitize researchers to the opportunities and challenges of new developments.The work focusses on the topics of digitalization in the healthcare system and individualized medicine. The authors illustrate some problems resulting from these developments that affect the ethical justification of medical research projects. Problems related to medical as well as biostatistical aspects are presented and their direct implications on the legal justification and ethical and moral conceptual integrity are highlighted.New developments in medical research such as digitalization and individualized medicine offer new perspectives for optimized therapies. These promising developments must be further advanced. A critical view on the so far only poorly investigated consequences of embedding new data sources and study designs must urgently accompany this process. Transparency and clarity in formulating ethical proposals is thereby of utmost importance.

Long-term Results of Conservative Therapy of Adolescent Idiopathic Scoliosis Using the Cheneau Brace

Adolescent idiopathic scoliosis is a disease of the growing skeleton. The goal in therapy is to decelerate or to prevent progression of the spinal curve. As part of a retrospective study the patient group of the scoliosis surgery from 1995-2016 was analysed according to the inclusion criteria of the Scoliosis research Society (SRS). 159 of 643 of the patients fullfilled the specific criteria. The assessment of effectiveness was based on the progression of the angle of curvature. If it was ≤5° it was judged positively. The therapy in accordance to Cheneau is a full-time bracing orthosis. Data from 159 patients - 136 fem. (85.5%), 23 male (14.5%) was analysed. The average age at the beginning of treatment was 13.3±1.7 years. The average duration was 3.47±1.2 years. The average Cobb-angle before treatment was 28.39°±9.44°. At the completion is was 27.7°±12.34°. Stabilisation of scoliosis (≤5°) was achieved for 136 of the patients (85.5%). The final follow-up showed a progression of the Cobb angel>5° in 23 cases, of which 19 had to undergo secondary surgery. The length of therapy had a positive influence (p=0.057) on the result. Brace treatment constitutes an effective method of therapy at curvatures between 20-40°. Short duration of therapy correlates with a expressively increased risk towards progression (p=0.057). The Cheneau brace treatment constitutes an effective treatment at curvature angles between 20-40°. The risk of progression can be reduced by a timely and correct identification.

The betaboost package-a software tool for modelling bounded outcome variables in potentially high-dimensional epidemiological data

Motivation

To provide an integrated software environment for model fitting and variable selection in regression models with a bounded outcome variable.

Implementation

The proposed modelling framework is implemented in the add-on package betaboost of the statistical software environment R.

General features

The betaboost methodology is based on beta-regression, which is a state-of-the-art method for modelling bounded outcome variables. By combining traditional model fitting techniques with recent advances in statistical learning and distributional regression, betaboost allows users to carry out data-driven variable and/or confounder selection in potentially high-dimensional epidemiological data. The software package implements a flexible routine to incorporate linear and non-linear predictor effects in both the mean and the precision parameter (relating inversely to the variance) of a beta-regression model.

Availability

The software is hosted publicly at [http://github.com/boost-R/betaboost] and has been published under General Public License (GPL) version 3 or newer.

Natalizumab-associated progressive multifocal leukoencephalopathy in Germany

OBJECTIVE

To evaluate characteristics relevant to diagnosis of JC polyomavirus-associated progressive multifocal leukoencephalopathy (PML), and PML risk stratification in a large national cohort of patients with multiple sclerosis during therapy with natalizumab.

METHODS

Analysis of 292 adverse drug reaction forms on suspected cases of PML reported to the German national competent authority until July 2017. Patients not fulfilling PML diagnostic criteria or with insufficient information available were excluded.

RESULTS

Of the 142 confirmed patients with PML, 72.3% (95% confidence interval [CI] 64.4%-79.1%) were women, and the median age was 43 years (range 19-69). Of these patients, 7.7% (95% CI 4.3%-13.5%) were clinically asymptomatic at time of PML diagnosis. PML was fatal in 9.1% (95% CI 5.3%-15.1%) of the patients. Infratentorial lesions on imaging were reported in 40% (95% CI 32.0%-48.6%) of the patients. JC polyomavirus DNA in CSF was undetectable at time of first analysis in 23.8% (95% CI 17.3%-31.9%) of the patients. Three patients tested negative for anti-JC polyomavirus antibodies within 6 to 18 months before PML diagnosis, with seroconversion confirmed 5.5 months, 7 months (in a post hoc analysis only), or at time of PML diagnosis.

CONCLUSIONS

JC polyomavirus DNA detection in CSF has limited sensitivity in early PML, and clinical and imaging presentation may be atypical. Thus, critical revision of current PML diagnostic criteria is warranted. Negative anti-JC polyomavirus antibodies in sera do not preclude the later development of PML. This emphasizes the need for close and regular serologic, imaging, and clinical monitoring in patients treated with natalizumab.

Modeling spatiotemporal abundance of mobile wildlife in highly variable environments using boosted GAMLSS hurdle models

Modeling organism distributions from survey data involves numerous statistical challenges, including accounting for zero-inflation, overdispersion, and selection and incorporation of environmental covariates. In environments with high spatial and temporal variability, addressing these challenges often requires numerous assumptions regarding organism distributions and their relationships to biophysical features. These assumptions may limit the resolution or accuracy of predictions resulting from survey-based distribution models. We propose an iterative modeling approach that incorporates a negative binomial hurdle, followed by modeling of the relationship of organism distribution and abundance to environmental covariates using generalized additive models (GAM) and generalized additive models for location, scale, and shape (GAMLSS). Our approach accounts for key features of survey data by separating binary (presence-absence) from count (abundance) data, separately modeling the mean and dispersion of count data, and incorporating selection of appropriate covariates and response functions from a suite of potential covariates while avoiding overfitting. We apply our modeling approach to surveys of sea duck abundance and distribution in Nantucket Sound (Massachusetts, USA), which has been proposed as a location for offshore wind energy development. Our model results highlight the importance of spatiotemporal variation in this system, as well as identifying key habitat features including distance to shore, sediment grain size, and seafloor topographic variation. Our work provides a powerful, flexible, and highly repeatable modeling framework with minimal assumptions that can be broadly applied to the modeling of survey data with high spatiotemporal variability. Applying GAMLSS models to the count portion of survey data allows us to incorporate potential overdispersion, which can dramatically affect model results in highly dynamic systems. Our approach is particularly relevant to systems in which little a priori knowledge is available regarding relationships between organism distributions and biophysical features, since it incorporates simultaneous selection of covariates and their functional relationships with organism responses.

Quantification of Renal Function and Cardiovascular Mortality in Patients Admitted to the Emergency Department with Suspected Acute Coronary Syndromes

BACKGROUND

Increases in the novel serum marker cystatin C are detectable much earlier in the course of chronic kidney disease (CKD) even when levels of serum creatinine are still in the normal range. A major factor causing a decrease in serum creatinine is increasing age. Patients with CKD are more likely to develop cardiovascular disease (CVD) than a healthy population and to suffer premature deaths from CVD related to CKD. The aim of this study was to investigate whether cystatin C, serum creatinine, and estimated glomerular filtration rate (eGFR) predict cardiovascular mortality in patients admitted to the emergency department (ED) with suspected acute coronary syndromes (ACS).

METHODS

In 1,282 patients (mean age 62 ± 15 years, 477 women, 805 men) with suspected ACS, baseline cystatin C concentrations, serum creatinine, and estimated glomerular filtration rate (eGFR) were measured at the ED. Clinical assessment and serial high sensitivity cardiac troponin T (hs-cTnT) measurements were used for the diagnosis of ACS. Seventeen cardiovascular deaths were registered during a median follow-up of 365 days.

RESULTS

HRs from univariate Cox regression models for each of the potential biomarkers were 12.02 (95% CI 5.10 - 28.34) for cystatin C, 4.53 (1.75 - 11.70) for serum creatinine, and 0.97 (0.96 - 0.99) for eGFR. All three biomarkers showed a significant association with cardiovascular mortality in univariate analyses. The HRs from a model with all three potential biomarkers were 59.21 (95% CI 9.69 - 361.76) for cystatin C, 0.08 (0.01 - 0.58) for serum creatinine, and 0.98 (0.96 - 1.01) for eGFR. The risk association was significant for ln (cystatin C) and ln (serum creatinine).

CONCLUSIONS

Results of this prospective study show that the quantification of renal function using cystatin C is useful for predicting cardiovascular mortality in patients with suspected ACS at the ED.

Bouldering psychotherapy reduces depressive symptoms even when general physical activity is controlled for: A randomized controlled trial

Background

Bouldering psychotherapy (BPT) combines psychotherapeutic elements with physical activity (PA). It might be effective for reducing symptoms of depression, but so far, no study has assessed individuals' levels of PA to control for whether positive effects on depression can also be found when adjusting for participants' levels of PA. This is important because PA itself has been proven effective in reducing depression and therefore might be an important variable to account for – especially in therapies using sport as one therapeutic mechanism.

Methods

Using a waitlist control group design, outpatients with depression were assessed at baseline and after eight, 16, and 24 weeks. The intervention group took part in an eight-week bouldering psychotherapy which met once a week for three hours. Self-report measures before and after the intervention included the Symptom Checklist-90-R (SCL-90-R), the Beck Depression Inventory (BDI-II), and the questionnaire on resources and self-management skills (FERUS). PA was assessed during the first 16-week period via FitBit Zip accelerometers.

Results

Altogether, 47 complete cases (20 men and 27 women) were included in the final analyses. Depression scores dropped by up to 6.74 (CI 2.80–10.67) points on the SCL-90-R depression scale and by up to 8.26 (CI 4.21–12.31) points on the BDI-II during the BPT intervention, the control group remained stable (SCL-90-R Cohen's d = 0.60; BDI-II: Cohen's d = .50). All Participants accrued an average of 6,515 steps per day, which is considered “low-active.” Participants of the BPT intervention were significantly more likely to reduce their depressive symptoms (p = .025) than participants of the control group, even when PA was controlled for in a regression analysis.

Limitations

Limitations of the study are the relatively small number of patients and the assessment of outcome scores via self-report.

Conclusions

This study provides evidence that short-term BPT can be effective for reducing symptoms of depression even if controlled for other therapeutically active confounders including antidepressant medication, psychotherapy and general level of PA.

Boosting for statistical modelling-A non-technical introduction

Boosting algorithms were originally developed for machine learning but were later adapted to estimate statistical models—offering various practical advantages such as automated variable selection and implicit regularization of effect estimates. The interpretation of the resulting models, however, remains the same as if they had been fitted by classical methods. Boosting, hence, allows to use an advanced machine learning scheme to estimate various types of statistical models. This tutorial aims to highlight how boosting can be used for semi-parametric modelling, what practical implications follow from the design of the algorithm and what kind of drawbacks data analysts have to expect. We illustrate the application of boosting in the analysis of a stunting score from children in India and a high-dimensional dataset of tumour DNA to develop a biomarker for the occurrence of metastases in breast cancer patients.

An Update on Statistical Boosting in Biomedicine

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

Randomised phase-III-trial of concurrent chemoradiation (CRT) for locally advanced head and neck cancer (stage III-IVB): Comparing dose reduced radiotherapy (63,6 Gy) with paclitaxel/cisplatinum to standard radiotherapy (70,6 Gy) with fluorouracil/cisplatinum

6016

Background: Concurrent CRT with 70.6 Gy is the standard treatment for locally advanced head and neck cancer (LA-SCCHN). There exist no prospective data on safety and efficacy of a reduced radiation (RT) dose. Methods: Pts with stage III-IVB LA-SCCHN were randomized 1:1 to receive 70.6 Gy with concurrent cisplatinum (20mg/m²/d IV on days 1-5 and 29-33) and fluorouracil (600 mg/m²/d CIV on days 1-5 and 29-33) (standard arm A) versus 63,6 Gy with intensified chemotherapy using concurrent cisplatinum (20mg/m²/d IV on days 1-4 and 29-32) and paclitaxel (20mg/m²/d IV on days 2, 5, 8, 11 and 25, 30, 33, 36) (experimental arm B). After a planned interim analysis recruitment was stopped due to statistical reasons. Results: Between 06/2010 and 02/2015 a total of 221 pts were randomized with 105 pts receiving treatment in arm A and 112 in arm B (4 pts dropped out). Median follow-up was 38 months. Pts’ characteristics: Oral cavity (15%), oropharynx (54%), hypopharynx (28%), larynx (14%); 17 pts had more than one primary site; tumor stage: III (14%), IV (86%); HPV-status (p16) was positive in 20%, negative in 38%, currently pending in 42%. A total of 96 PFS-related events occurred. 3-year PFS (ITT) was 58% in the standard arm A and 48% in experimental arm B (p = 0.454). 3-year OS (ITT) was 64% in arm A and 59% in arm B (p = 0.688). 3-year rates of distant metastases, loco-regional recurrences and death were 10% vs 12%, 17% vs 21% and 15% vs 19% for pts in arm A and B, respectively. As for the p16-positive subgroup, 3-year PFS/OS were 77%/76% in arm A (n = 21) and 69%/80% in arm B (n = 22), respectively. Grade 3+ hematologic adverse events during therapy (arm A/arm B): Anemia 11%/4% (p = 0.038); neutropenia 40%/16% (p < 0.001); thrombocytopenia 8%/3% (p = 0.130). Conclusions: These preliminary results indicate that pts receiving concurrent CRT for LA-SCCHN did not benefit from a lower total RT dose of 63.6Gy despite intensified chemotherapy. However, in the subgroup of p16-positive pts a reduced RT dose may be sufficiently effective. Clinical trial information: NCT01126216.

Boosting the discriminatory power of sparse survival models via optimization of the concordance index and stability selection

Background

When constructing new biomarker or gene signature scores for time-to-event outcomes, the underlying aims are to develop a discrimination model that helps to predict whether patients have a poor or good prognosis and to identify the most influential variables for this task. In practice, this is often done fitting Cox models. Those are, however, not necessarily optimal with respect to the resulting discriminatory power and are based on restrictive assumptions. We present a combined approach to automatically select and fit sparse discrimination models for potentially high-dimensional survival data based on boosting a smooth version of the concordance index (C-index). Due to this objective function, the resulting prediction models are optimal with respect to their ability to discriminate between patients with longer and shorter survival times. The gradient boosting algorithm is combined with the stability selection approach to enhance and control its variable selection properties.

Results

The resulting algorithm fits prediction models based on the rankings of the survival times and automatically selects only the most stable predictors. The performance of the approach, which works best for small numbers of informative predictors, is demonstrated in a large scale simulation study: C-index boosting in combination with stability selection is able to identify a small subset of informative predictors from a much larger set of non-informative ones while controlling the per-family error rate. In an application to discover biomarkers for breast cancer patients based on gene expression data, stability selection yielded sparser models and the resulting discriminatory power was higher than with lasso penalized Cox regression models.

Conclusion

The combination of stability selection and C-index boosting can be used to select small numbers of informative biomarkers and to derive new prediction rules that are optimal with respect to their discriminatory power. Stability selection controls the per-family error rate which makes the new approach also appealing from an inferential point of view, as it provides an alternative to classical hypothesis tests for single predictor effects. Due to the shrinkage and variable selection properties of statistical boosting algorithms, the latter tests are typically unfeasible for prediction models fitted by boosting.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1149-8) contains supplementary material, which is available to authorized users.

Perioperative complications of scoliosis surgery in patients with Duchenne muscular dystrophy and spinal muscular atrophy, focussing on wound healing disorders

PURPOSE

Patients with Duchenne muscular dystrophy (DMD) or spinal muscular atrophy (SMA), both neuromuscular diseases, sustain spinal scoliosis in the course of their disease. To reduce the concomitant major morbidity and to improve their quality of life, patients require surgical spine stabilization. This can lead to complications like respiratory, cardiac or neurological complications or wound healing disorders (WHD). To find out the different complexities and risk factors increasing the chance to develop a WHD, the inpatient database was analyzed.

METHODS

We performed a retrospective statistical study. Therefore, we analyzed the inpatient database of 180 patients (142 DMD and 38 SMA patients). The focus was on WHD. To figure out the risk factors leading to WHD, we conducted a logistic regression.

RESULTS

Cardiac complications occurred most frequently, followed by pulmonary complications and neurological lesions. Fifty-seven out of 180 patients developed a WHD. In 23 cases the WHD was aseptic, in the other 34 cases dermal organisms, Pseudomonas species and intestinal organisms were responsible. By means of the logistic regression, we were able to identify two more risk factors, in addition to diagnosis and gender, for developing a WHD in our patients: the year of surgery and the direction of pelvic tilt.

CONCLUSIONS

Most common complications following scoliosis surgery are respiratory and cardiac complications. WHD is a severe complication that implies a prolonged therapy. Some risk factors for developing WHD could be identified in this analysis. Specifically, these were the date of surgery and the direction of pelvic tilt.

Prognostic value of different biomarkers for cardiovascular death in unselected older patients in the emergency department

BACKGROUND

Risk stratification of elderly patients presenting with heart failure (HF) to an emergency department (ED) is an unmet challenge. We prospectively investigated the prognostic performance of different biomarkers in unselected older patients in the ED.

METHODS

We consecutively enrolled 302 non-surgical patients ⩾70 years presenting to the ED with a wide range of cardiovascular and non-cardiovascular comorbid conditions. N-terminal pro-B-type natriuretic peptide (NT-proBNP), mid-regional pro-adrenomedullin (MR-proADM), mid-regional pro-atrial natriuretic peptide (MR-proANP), C-terminal pro-endothelin-1 (CT-proET-1), ultrasensitive C-terminal pro-arginine-vasopressin (Copeptin-us) and high-sensitivity cardiac troponin T (hs-cTnT) were measured at admission. Two cardiologists independently adjudicated the final diagnosis of HF after reviewing all available baseline data using circulating NT-proBNP levels. A final diagnosis of HF was found in 120 (40%) of the 302 patients. All patients were followed up for cardiovascular death within the following 12 months. In order to test the prognostic performance of the investigated biomarkers we used boosting models with age and sex as mandatory covariates. Boosting is a statistical learning technique with built-in variable selection developed to obtain sparse and interpretable prediction models.

RESULTS

Follow-up was 100% complete. During a median follow-up time of 225 days (interquartile range (IQR) 156-319 days), 30 (9.9%) of 302 patients (aged 81±6 years) had cardiovascular deaths. Of these 30 patients, 21 had HF and nine had no HF diagnosed prior to admission. The boosting model selected MR-proADM and hs-cTNT as predictors of cardiovascular deaths. The median values of MR-proADM and hs-cTnT at presentation were significantly higher in patients with cardiovascular deaths compared to surviving patients during follow-up (2.56 nmol/L (IQR 1.62-4.48) vs. 1.11 nmol/L (IQR 0.83-1.80), P<0.001 and 81 ng/L (IQR 38-340) vs. 17 ng/L (IQR 0.9-38), P=0.004). One unit increase in the log-transformed MR-proADM levels was associated with a 1.99-fold risk of death (95% confidence interval (CI) 1.61-2.45, P<0.001). The second marker, hs-cTnT, showed an increased predicted risk but was not significantly correlated to event-free survival (hazard ratio 3.22, 95% CI 0.97-10.68, P=0.056).

CONCLUSION

Within different biomarkers, MR-proADM was the only predictor of cardiovascular deaths in unselected older patients presenting to the ED.

Fracture Rates and Lifetime Estimations of CAD/CAM All-ceramic Restorations

The gathering of clinical data on fractures of dental restorations through prospective clinical trials is a labor- and time-consuming enterprise. Here, we propose an unconventional approach for collecting large datasets, from which clinical information on indirect restorations can be retrospectively analyzed. The authors accessed the database of an industry-scale machining center in Germany and obtained information on 34,911 computer-aided design (CAD)/computer-aided manufacturing (CAM) all-ceramic posterior restorations. The fractures of bridges, crowns, onlays, and inlays fabricated from different all-ceramic systems over a period of 3.5 y were reported by dentists and entered in the database. Survival analyses and estimations of future life revealed differences in performance among ZrO2-based restorations and lithium disilicate and leucite-reinforced glass-ceramics.

Controlling false discoveries in high-dimensional situations: boosting with stability selection

BACKGROUND

Modern biotechnologies often result in high-dimensional data sets with many more variables than observations (n≪p). These data sets pose new challenges to statistical analysis: Variable selection becomes one of the most important tasks in this setting. Similar challenges arise if in modern data sets from observational studies, e.g., in ecology, where flexible, non-linear models are fitted to high-dimensional data. We assess the recently proposed flexible framework for variable selection called stability selection. By the use of resampling procedures, stability selection adds a finite sample error control to high-dimensional variable selection procedures such as Lasso or boosting. We consider the combination of boosting and stability selection and present results from a detailed simulation study that provide insights into the usefulness of this combination. The interpretation of the used error bounds is elaborated and insights for practical data analysis are given.

RESULTS

Stability selection with boosting was able to detect influential predictors in high-dimensional settings while controlling the given error bound in various simulation scenarios. The dependence on various parameters such as the sample size, the number of truly influential variables or tuning parameters of the algorithm was investigated. The results were applied to investigate phenotype measurements in patients with autism spectrum disorders using a log-linear interaction model which was fitted by boosting. Stability selection identified five differentially expressed amino acid pathways.

CONCLUSION

Stability selection is implemented in the freely available R package stabs (http://CRAN.R-project.org/package=stabs). It proved to work well in high-dimensional settings with more predictors than observations for both, linear and additive models. The original version of stability selection, which controls the per-family error rate, is quite conservative, though, this is much less the case for its improvement, complementary pairs stability selection. Nevertheless, care should be taken to appropriately specify the error bound.

Amino alcohol- (NPS-2143) and quinazolinone-derived calcilytics (ATF936 and AXT914) differentially mitigate excessive signalling of calcium-sensing receptor mutants causing Bartter syndrome Type 5 and autosomal dominant hypocalcemia

INTRODUCTION

Activating calcium sensing receptor (CaSR) mutations cause autosomal dominant hypocalcemia (ADH) characterized by low serum calcium, inappropriately low PTH and relative hypercalciuria. Four activating CaSR mutations cause additional renal wasting of sodium, chloride and other salts, a condition called Bartter syndrome (BS) type 5. Until today there is no specific medical treatment for BS type 5 and ADH. We investigated the effects of different allosteric CaSR antagonists (calcilytics) on activating CaSR mutants.

METHODS

All 4 known mutations causing BS type 5 and five ADH mutations were expressed in HEK 293T cells and receptor signalling was studied by measurement of intracellular free calcium in response to extracellular calcium ([Ca2+]o). To investigate the effect of calcilytics, cells were stimulated with 3 mM [Ca2+]o in the presence or absence of NPS-2143, ATF936 or AXT914.

RESULTS

All BS type 5 and ADH mutants showed enhanced signalling activity to [Ca2+]o with left shifted dose response curves. In contrast to the amino alcohol NPS-2143, which was only partially effective, the quinazolinone calcilytics ATF936 and AXT914 significantly mitigated excessive cytosolic calcium signalling of all BS type 5 and ADH mutants studied. When these mutants were co-expressed with wild-type CaSR to approximate heterozygosity in patients, ATF936 and AXT914 were also effective on all mutants.

CONCLUSION

The calcilytics ATF936 and AXT914 are capable of attenuating enhanced cytosolic calcium signalling activity of CaSR mutations causing BS type 5 and ADH. Quinazolinone calcilytics might therefore offer a novel treatment option for patients with activating CaSR mutations.

Geodermatophilus poikilotrophi sp. nov.: a multitolerant actinomycete isolated from dolomitic marble

A novel Gram-reaction-positive, aerobic actinobacterium, tolerant to mitomycin C, heavy metals, metalloids, hydrogen peroxide, desiccation, and ionizing- and UV-radiation, designated G18T, was isolated from dolomitic marble collected from outcrops in Samara (Namibia). The growth range was 15-35°C, at pH 5.5-9.5 and in presence of 1% NaCl, forming greenish-black coloured colonies on GYM Streptomyces agar. Chemotaxonomic and molecular characteristics of the isolate matched those described for other representatives of the genus Geodermatophilus. The peptidoglycan contained meso-diaminopimelic acid as diagnostic diaminoacid. The main phospholipids were phosphatidylethanolamine, phosphatidylcholine, phosphatidylinositol, and small amount of diphosphatidylglycerol. MK-9(H4) was the dominant menaquinone and galactose was detected as diagnostic sugar. The major cellular fatty acids were branched-chain saturated acids iso-C16:0 and iso-C15:0 and the unsaturated C17:1 ω8c and C16:1 ω7c. The 16S rRNA gene showed 97.4-99.1% sequence identity with the other representatives of genus Geodermatophilus. Based on phenotypic results and 16S rRNA gene sequence analysis, strain G18T is proposed to represent a novel species, Geodermatophilus poikilotrophi. Type strain is G18T (=DSM 44209T=CCUG 63018T). The INSDC accession number is HF970583. The novel R software package lethal was used to compute the lethal doses with confidence intervals resulting from tolerance experiments.

Multiple biomarker strategy for improved diagnosis of acute heart failure in older patients presenting to the emergency department

AIM

Biomarkers can help to identity acute heart failure (AHF) as the cause of symptoms in patients presenting to the emergency department (ED). Older patients may prove a diagnostic challenge due to co-morbidities. Therefore we prospectively investigated the diagnostic performance of N-terminal pro-B-type natriuretic peptide (NT-proBNP) alone or in combination with other biomarkers for AHF upon admission at the ED.

METHODS

302 non-surgical patients aged ≥ 70 years were consecutively enrolled upon admission to the ED. In addition to NT-proBNP, mid-regional pro-adrenomedullin (MR-proADM), mid-regional pro-atrial natriuretic peptide (MR-proANP), C-terminal pro-endothelin-1 (CT-proET-1) and ultra-sensitive C-terminal pro-vasopressin (Copeptin-us) were measured at admission. Two cardiologists independently adjudicated the final diagnosis of AHF after reviewing all available baseline data excluding the biomarkers. We assessed changes in C-index, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) for the multimarker approach.

RESULTS

AHF was diagnosed in 120 (40%) patients (age 81±6 years, 64 men, 56 women). Adding MR-ADM to NT-proBNP levels improved C-index (0.84 versus 0.81; p=0.045), and yielded IDI (3.3%; p=0.002), NRI (17%, p<0.001) and continuous NRI (33.3%; p=0.002). Adding CT-proET-1 to NT-proBNP levels improved C index (0.86 versus 0.81, p=0.031), and yielded robust IDI (12.4%; p<0.001), NRI (31.3%, p<0.001) and continuous NRI (69.9%; p<0.001). No other dual or triple biomarker combination showed a significant improvement of both C-index and IDI.

CONCLUSION

In older patients presenting to the ED, the addition of CT-proET-1 or MR-proADM to NT-proBNP improves diagnostic accuracy of AHF. Both dual biomarker approaches offer significant risk reclassification improvement over NT-proBNP.

opm: an R package for analysing OmniLog(R) phenotype microarray data

SUMMARY

opm is an R package designed to analyse multidimensional OmniLog® phenotype microarray (PM) data. opm provides management, visualization and statistical analysis of PM data, including curve-parameter estimation and discretization, dedicated and customizable plots, metadata management, automated generation of textual and tabular reports, mapping of substrates to databases, batch conversion of files and export to phylogenetic software in the YAML markup language.

AVAILABILITY

opm is distributed under the GPL through the Comprehensive R Archive Network (http://cran.r-project.org/package=opm) along with a comprehensive manual and a user-friendly tutorial. Further information may be found at http://www.dsmz.de/research/microorganisms/projects/.

CONTACT

johannes.sikorski@dsmz.de.

Are the effects of a non-drug multimodal activation therapy of dementia sustainable? Follow-up study 10 months after completion of a randomised controlled trial

BACKGROUND

Little is known about the long-term success of non-drug therapies for treating dementia, especially whether the effects are sustained after therapy ends. Here, we examined the effects of a one-year multimodal therapy 10 months after patients completed the therapy.

METHODS

This randomised, controlled, single-blind, longitudinal trial involved 61 patients (catamnesis: n = 52) with primary degenerative dementia in five nursing homes in Bavaria, Germany. The highly standardised intervention, MAKS, consisted of motor stimulation, practice of activities of daily living (ADLs), and cognitive stimulation. Each group of 10 patients was treated for 2 h, 6 days a week for 12 months. Control patients received standard nursing home care. At baseline, at the end of therapy (month 12), and 10 months thereafter (month 22), cognitive functioning was assessed using the cognitive subscale of the Alzheimer's Disease Assessment Scale, and the ability to perform ADLs was assessed using the Erlangen Test of Activities of Daily Living.

RESULTS

During the therapy phase, the MAKS patients maintained their cognitive function and ability to carry out ADLs. After the end of therapy, both the control and the MAKS groups deteriorated in both their cognitive function (control, p = 0.02; MAKS, p < 0.001) and their ability to carry out ADLs (control, p < 0.001; MAKS, p = 0.001). However, in a confound-adjusted multiple regression model, the ability of the MAKS group to perform ADLs remained significantly higher than that of the control group even 10 months after the end of therapy (H0: βMAKS + βMAKS month 22 = 0; χ2 = 3.8568, p = 0.0496). Cohen's d for the difference between the two groups in ADLs and cognitive abilities 10 months after the end of therapy was 0.40 and 0.22, respectively.

CONCLUSIONS

A multimodal non-drug therapy of dementia resulted in stabilisation of the ability to perform ADLs, even beyond the end of therapy. To prevent functional decline for as long as possible, therapy should be performed continuously until the benefit for the patient ends. Follow-up studies on larger numbers of patients are needed to definitively confirm these results.

TRIAL REGISTRATION

http://www.isrctn.com Identifier: ISRCTN87391496.

The importance of knowing when to stop. A sequential stopping rule for component-wise gradient boosting

OBJECTIVES

Component-wise boosting algorithms have evolved into a popular estimation scheme in biomedical regression settings. The iteration number of these algorithms is the most important tuning parameter to optimize their performance. To date, no fully automated strategy for determining the optimal stopping iteration of boosting algorithms has been proposed.

METHODS

We propose a fully data-driven sequential stopping rule for boosting algorithms. It combines resampling methods with a modified version of an earlier stopping approach that depends on AIC-based information criteria. The new "subsampling after AIC" stopping rule is applied to component-wise gradient boosting algorithms.

RESULTS

The newly developed sequential stopping rule outperformed earlier approaches if applied to both simulated and real data. Specifically, it improved purely AIC-based methods when used for the microarray-based prediction of the recurrence of metastases for stage II colon cancer patients.

CONCLUSIONS

The proposed sequential stopping rule for boosting algorithms can help to identify the optimal stopping iteration already during the fitting process of the algorithm, at least for the most common loss functions.

Monotonicity-constrained species distribution models

Flexible modeling frameworks for species distribution models based on generalized additive models that allow for smooth, nonlinear effects and interactions are of increasing importance in ecology. Commonly, the flexibility of such smooth function estimates is controlled by means of penalized estimation procedures. However, the actual shape remains unspecified. In many applications, this is not desirable as researchers have a priori assumptions on the shape of the estimated effects, with monotonicity being the most important. Here we demonstrate how monotonicity constraints can be incorporated in a recently proposed flexible framework for species distribution models. Our proposal allows monotonicity constraints to be imposed on smooth effects and on ordinal, categorical variables using an additional asymmetric L2 penalty. Model estimation and variable selection for Red Kite (Milvus milvus) breeding was conducted using the flexible boosting framework implemented in R package mboost.

Orexin A expression and promoter methylation in patients with alcohol dependence comparing acute and protracted withdrawal

The orexins (hypocretins) are neuropeptides deriving from the lateral hypothalamus and may be of importance within the context of drug craving, withdrawal, and relapse. Therefore, the orexin A expression and promoter methylation in peripheral blood cells of 68 patients (41 male and 27 female patients at three different time points during withdrawal and 27 patients during stationary dehabituation therapy) suffering from alcohol dependence were assessed by quantitative reverse transcription-polymerase chain reaction and bisulfite sequencing. There was a statistically significant difference of orexin A expression between the three time points of withdrawal and long-term (LT) abstinence (F=4.16, P=.011). This difference was most prominent in comparison with LT abstinence (t=-3.08, P=.0032). Expression was significantly associated with the severity of withdrawal symptoms measured with the Withdrawal Syndrome Scale for Alcohol and Related Psychoactive Drugs (WSA) (t=2.17, P=.0356). The stronger the withdrawal symptoms, the lower the orexin A expression (F=4.69, P=.036). Body mass index (t=2.15, P=.041), the severity of withdrawal measured with the WSA (t=2.595, P=.0133), craving measured either by the Obsessive Compulsive Drinking Scale (t=2.77, P=.0085) or the Lübecker Craving Questionnaire (t=-2.23, P=.0314) had a significant influence on orexin A expression taking into account mean methylation of the CpG island of the orexin A promoter during withdrawal. Orexin A may be a possible candidate to further elucidate mechanisms of alcohol withdrawal taking into account energy homoeostasis in the circuit of reward and motivation.

Short-term prognosis of critically ill surgical patients: the impact of duration of invasive organ support therapies

PURPOSE

We wanted to identify the importance of the duration of invasive ventilation and of renal replacement therapy for short-term prognosis of surgical patients treated in an intensive care unit (ICU).

METHODS

We analyzed adult patients (n = 1462) who had an ICU length of stay of more than 4 days and who were followed up until the end of the short-term phase after ICU admission. Duration of different invasive therapies was evaluated by constructing specific vectors that tested effects of time-dependent variables on outcome after a lag time of 7 days.

MEASUREMENTS AND MAIN RESULTS

Eight hundred eight patients (56.6%) were still alive at the end of the short-term phase. During the short-term phase, 85.3% of the 1462 patients required invasive ventilation, and 16.1%, a continuous renal replacement therapy. Besides the underlying disease and disease severity at ICU admission, the need for invasive ventilation or renal replacement therapy was associated with poorer outcome. Duration of invasive ventilation shortened survival if treatment lasted for more than 11 days (nonlinear association). In contrast, duration of renal replacement therapy was unimportant for short-term prognosis.

CONCLUSION

Prolonged duration of invasive ventilation but not of renal replacement therapy is inversely related to short-term survival.

Intrauterine growth restriction (IUGR) is associated with increased leptin synthesis and binding capability in neonates

OBJECTIVE

Animal studies suggest pathological foetal programming of hypothalamic circuits regulating food intake in the setting of leptin deficiency and intrauterine growth restriction (IUGR). We aimed to compare placental leptin synthesis and leptin-binding capability in venous cord blood between IUGR newborns and neonates born appropriate for gestational age (AGA).

DESIGN

Prospective controlled multicentre study.

PATIENTS

Twenty-one ultrasound-proven IUGR and 33 AGA neonates.

MEASUREMENTS

The concentration of leptin and soluble leptin receptor (sOB-R) in venous cord blood at birth was determined. Moreover, placental gene and protein expression of leptin and placental mRNA expression of functional and total leptin receptor isoforms were measured.

RESULTS

Whereas log-leptin concentration in venous cord blood did not differ between IUGR and AGA newborns, the concentration of log-sOB-R was elevated in IUGR neonates (p(confounder adjusted)=0·009). Placental leptin protein synthesis as well as leptin mRNA was significantly higher in IUGR than in AGA infants (log-transformed, relative gene expression, p(confounder adjusted)=0·004). Analysis of gene expression of functional and total leptin receptor isoforms did not show any difference between both groups.

CONCLUSIONS

Leptin-binding capability in venous cord blood is increased in IUGR newborns. Thus, via foetal programming, reduced biologically active leptin levels might contribute to a perturbed regulation of appetite.

Building Cox-type structured hazard regression models with time-varying effects

In recent years, flexible hazard regression models based on penalized splines have been developed that allow us to extend the classical Cox model via the inclusion of time-varying and nonparametric effects. Despite their immediate appeal in terms of flexibility, these models introduce additional difficulties when a subset of covariates and the corresponding modelling alternatives have to be chosen. We present an analysis of data from a specific patient population with 90-day survival as the response variable. The aim is to determine a sensible prognostic model where some variables have to be included due to subject-matter knowledge while other variables are subject to model selection. Motivated by this application, we propose a two-stage stepwise model building strategy to choose both the relevant covariates and the corresponding modelling alternatives within the choice set of possible covariates simultaneously. For categorical covariates, competing modelling approaches are linear effects and time-varying effects, whereas nonparametric modelling provides a further alternative in case of continuous covariates. In our data analysis, we identified a prognostic model containing both smooth and time-varying effects.

Prognostic factors in critically ill surgical patients requiring continuous renal replacement therapy

BACKGROUND

Acute mortality of unselected critically ill patients has improved during the last 15 years. Whether these benefits also affect long-term survival of critically ill surgical patients with severe acute renal failure is unclear, as are the prognostic factors relevant for survival time or mortality.

METHODS

We performed a retrospective analysis of data collected prospectively from March 1993, through February 2005. Data from a cohort of 170 consecutive postoperative patients without preceding kidney diseases but requiring continuous renal replacement therapy (CRRT) during intensive care unit (ICU) stay were analyzed.

RESULTS

Six-month survival rate after ICU admission was 20.6%. In patients surviving more than 6 months, 5-year survival was 71.6%. After adjustment for relevant covariates, older age, disease severity at ICU admission, peritonitis and a large number of red cell units transfused during ICU stay were associated with worse 6-month prognosis. Duration of CRRT, and the origin and type of kidney failure were unimportant for prognosis, as was ICU admission date.

CONCLUSION

Six-month prognosis of critically ill surgical patients with severe acute renal failure is poor and mostly determined by the disease severity at ICU admission and by the frequency of surgical complications. Outcome had not improved over the study period, but after successful surgical and intensive care therapy, long-term survival appears to be reasonably good.