Distributed regression modeling for selecting markers under data protection constraints

Data protection constraints frequently require a distributed analysis of data, i.e., individual-level data remains at many different sites, but analysis nevertheless has to be performed jointly. The corresponding aggregated data is often exchanged manually, requiring explicit permission before transfer, i.e., the number of data calls and the amount of data should be limited. Thus, only simple aggregated summary statistics are typically transferred with just a single call. This does not allow for more complex tasks such as variable selection. As an alternative, we propose a multivariable regression approach for identifying important markers by automatic variable selection based on aggregated data from different locations in iterative calls. To minimize the amount of transferred data and the number of calls, we also provide a heuristic variant of the approach. When performing a global data standardization, the proposed methods yields the same results as when pooling individual-level data. In a simulation study, the information loss introduced by a local standardization is seen to be minimal. In a typical scenario, the heuristic decreases the number of data calls from more than 10 to 3, rendering manual data releases feasible. To make our approach widely available for application, we provide an implementation on top of the DataSHIELD framework

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge clinical manifestations that co-occur across subjects and could significantly hinder our understanding of clinical pathways connecting individual symptoms. Network analysis techniques have emerged as alternative approaches that could help shed light on the complex dynamics of early psychopathology. The present study attempts to address the two main limitations that have in our opinion hindered the application of network approaches in the clinical setting. Firstly, we show that a multi-layer network analysis approach, can move beyond a static view of psychopathology, by providing an intuitive characterization of the role of specific symptoms in contributing to clinical trajectories over time. Secondly, we show that a Graph-Signal-Processing approach, can exploit knowledge of longitudinal interactions between symptoms, to predict clinical trajectories at the level of the individual. We test our approaches in two independent samples of individuals with genetic and clinical vulnerability for developing psychosis. Novel network approaches can allow to embrace the dynamic complexity of early psychopathology and help pave the way towards a more a personalized approach to clinical care

From the northern ice shield to the Alpine glaciations

The route of the field trip described in this excursion guide follows a section through Germany from North to South, from the area of the Northern glaciation, to the Alpine glacial advances. It includes several places of historical importance, where milestones in Quaternary research have been achieved in the past, as well as new interesting sites where results of recent research is presented.excursionguid

Evaluation of Concomitant Systemic Treatment in Older Adults With Head and Neck Squamous Cell Carcinoma Undergoing Definitive Radiotherapy

IMPORTANCE The number of older adults with head and neck squamous cell carcinoma (HNSCC) is increasing, and these patients are underrepresented in clinical trials. It is unclear whether the addition of chemotherapy or cetuximab to radiotherapy is associated with improved survival in older adults with HNSCC. OBJECTIVE To examine whether the addition of chemotherapy or cetuximab to definitive radiotherapy is associated with improved survival in patients with locoregionally advanced (LA) HNSCC. DESIGN, SETTING, AND PARTICIPANTS The Special Care Patterns for Elderly HNSCC Patients Undergoing Radiotherapy (SENIOR) study is an international, multicenter cohort study including older adults (≥65 years) with LA-HNSCCs of the oral cavity, oropharynx/hypopharynx, or larynx treated with definitive radiotherapy, either alone or with concomitant systemic treatment, between January 2005 and December 2019 at 12 academic centers in the US and Europe. Data analysis was conducted from June 4 to August 10, 2022. INTERVENTIONS All patients underwent definitive radiotherapy alone or with concomitant systemic treatment. MAIN OUTCOMES AND MEASURES The primary outcome was overall survival. Secondary outcomes included progression-free survival and locoregional failure rate. RESULTS Among the 1044 patients (734 men [70.3%]; median [IQR] age, 73 [69-78] years) included in this study, 234 patients (22.4%) were treated with radiotherapy alone and 810 patients (77.6%) received concomitant systemic treatment with chemotherapy (677 [64.8%]) or cetuximab (133 [12.7%]). Using inverse probability weighting to attribute for selection bias, chemoradiation was associated with longer overall survival than radiotherapy alone (hazard ratio [HR], 0.61; 95% CI, 0.48-0.77; P < .001), whereas cetuximab-based bioradiotherapy was not (HR, 0.94; 95% CI, 0.70-1.27; P = .70). Progression-free survival was also longer after the addition of chemotherapy (HR, 0.65; 95% CI, 0.52-0.81; P < .001), while the locoregional failure rate was not significantly different (subhazard ratio, 0.62; 95% CI, 0.30-1.26; P = .19). The survival benefit of the chemoradiation group was present in patients up to age 80 years (65-69 years: HR, 0.52; 95% CI, 0.33-0.82; 70-79 years: HR, 0.60; 95% CI, 0.43-0.85), but was absent in patients aged 80 years or older (HR, 0.89; 95% CI, 0.56-1.41). CONCLUSIONS AND RELEVANCE In this cohort study of older adults with LA- HNSCC, chemoradiation, but not cetuximab-based bioradiotherapy, was associated with longer survival compared with radiotherapy alone

A Multicenter Evaluation of Different Chemotherapy Regimens in Older Adults With Head and Neck Squamous Cell Carcinoma Undergoing Definitive Chemoradiation

PURPOSE: The number of older adults with head-and-neck squamous cell carcinoma (HNSCC) is increasing, and treatment of these patients is challenging. Although cisplatin-based chemotherapy concomitantly with radiotherapy is considered standard regimen for patients with locoregionally advanced HNSCC, there is substantial real-world heterogeneity regarding concomitant chemotherapy in older HNSCC patients. METHODS: The XXX study is an international multicenter cohort study including older (≥65 years) HNSCC patients treated with definitive radiotherapy at 13 academic centers in the United States and Europe. Here, patients with concomitant chemoradiation were analyzed regarding overall survival (OS) and progression-free survival (PFS) using Kaplan-Meier analyses, while Fine-Gray competing risks regressions were performed regarding the incidence of locoregional failures (LRFs) and distant metastases (DMs). RESULTS: Six hundred ninety-seven patients with a median age of 71 years were included in this analysis. Single-agent cisplatin was the most common chemotherapy regimen (n=310; 44%), followed by cisplatin plus 5-fluorouracil (n=137; 20%), carboplatin (n=73; 10%), and mitomycin c plus 5-fluorouracil (n=64; 9%). Carboplatin-based regimens were associated with diminished PFS (HR=1.39 [1.03-1.89], p.05). Median cumulative dose of cisplatin was 180 mg/m2 (IQR, 120-200 mg/m2). Cumulative cisplatin doses ≥200 mg/m2 were associated with increased OS (HR=0.71 [0.53-0.95], p=.02), PFS (HR=0.66 [0.51-0.87], p=.003), and lower incidence of LRFs (SHR=0.50 [0.31-0.80], p=.004). Higher cumulative cisplatin doses remained an independent prognostic variable in the multivariate regression analysis for OS (HR=0.996 [0.993-0.999], p=.009). CONCLUSIONS: Single-agent cisplatin can be considered as the standard chemotherapy regimen for older HNSCC patients who can tolerate cisplatin. Cumulative cisplatin doses are prognostically relevant also in older HNSCC patients

Metabolic profiling of Arabidopsis thaliana epidermal cells

Metabolic phenotyping at cellular resolution may be considered one of the challenges in current plant physiology. A method is described which enables the cell type-specific metabolic analysis of epidermal cell types in Arabidopsis thaliana pavement, basal, and trichome cells. To achieve the required high spatial resolution, single cell sampling using microcapillaries was combined with routine gas chromatography-time of flight-mass spectrometry (GC-TOF-MS) based metabolite profiling. The identification and relative quantification of 117 mostly primary metabolites has been demonstrated. The majority, namely 90 compounds, were accessible without analytical background correction. Analyses were performed using cell type-specific pools of 200 microsampled individual cells. Moreover, among these identified metabolites, 38 exhibited differential pool sizes in trichomes, basal or pavement cells. The application of an independent component analysis confirmed the cell type-specific metabolic phenotypes. Significant pool size changes between individual cells were detectable within several classes of metabolites, namely amino acids, fatty acids and alcohols, alkanes, lipids, N-compounds, organic acids and polyhydroxy acids, polyols, sugars, sugar conjugates and phenylpropanoids. It is demonstrated here that the combination of microsampling and GC-MS based metabolite profiling provides a method to investigate the cellular metabolism of fully differentiated plant cell types in vivo

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge clinical manifestations that co-occur across subjects and could significantly hinder our understanding of clinical pathways connecting individual symptoms. Network analysis techniques have emerged as alternative approaches that could help shed light on the complex dynamics of early psychopathology. The present study attempts to address the two main limitations that have in our opinion hindered the application of network approaches in the clinical setting. Firstly, we show that a multi-layer network analysis approach, can move beyond a static view of psychopathology, by providing an intuitive characterization of the role of specific symptoms in contributing to clinical trajectories over time. Secondly, we show that a Graph-Signal-Processing approach, can exploit knowledge of longitudinal interactions between symptoms, to predict clinical trajectories at the level of the individual. We test our approaches in two independent samples of individuals with genetic and clinical vulnerability for developing psychosis. Novel network approaches can allow to embrace the dynamic complexity of early psychopathology and help pave the way towards a more a personalized approach to clinical care