Burst versus continuous delivery design in digital mental health interventions: Evidence from a randomized clinical trial.

Objective: Digital mental health interventions delivered via smartphone-based apps effectively treat various conditions; however, optimizing their efficacy while minimizing participant burden remains a key challenge. In this study, we investigated the potential benefits of a burst delivery design (i.e. interventions delivered only in pre-defined time intervals) in comparison to the continuous delivery of interventions. Methods: We randomly assigned 93 participants to the continuous delivery (CD) or burst delivery (BD) group. The CD group engaged in ReApp, a mobile app that increases positive cognitive reappraisal with a consistent delivery schedule that provides five prompts per day throughout the 3-week-long study, while the BD group received five daily prompts only in the first and third weeks of the study. Results: No significant differences were found between the groups in terms of adherence, mental health outcomes (specifically depressive and anxiety symptoms), level of perceived stress, and perceived helpfulness of intervention. The BD group showed a significantly decreased perceived difficulty of intervention over time. Conclusions: The results suggest that the burst delivery may be as suitable for digital mental health interventions as the continuous delivery. The perceived difficulty of the intervention declined more steeply for the BD group, indicating that it improved the feasibility of the positive cognitive reappraisal intervention without hurting its efficacy. This outcome may inform the design of less burdensome interventions with improved outcomes in future research.

Intraindividual time-varying dynamic network of affects: linear autoregressive mixed-effects models for ecological momentary assessment.

An interesting recent development in emotion research and clinical psychology is the discovery that affective states can be modeled as a network of temporally interacting moods or emotions. Additionally, external factors like stressors or treatments can influence the mood network by amplifying or dampening the activation of specific moods. Researchers have turned to multilevel autoregressive models to fit these affective networks using intensive longitudinal data gathered through ecological momentary assessment. Nonetheless, a more comprehensive examination of the performance of such models is warranted. In our study, we focus on simple directed intraindividual networks consisting of two interconnected mood nodes that mutually enhance or dampen each other. We also introduce a node representing external factors that affect both mood nodes unidirectionally. Importantly, we disregard the potential effects of a current mood/emotion on the perception of external factors. We then formalize the mathematical representation of such networks by exogenous linear autoregressive mixed-effects models. In this representation, the autoregressive coefficients signify the interactions between moods, while external factors are incorporated as exogenous covariates. We let the autoregressive and exogenous coefficients in the model have fixed and random components. Depending on the analysis, this leads to networks with variable structures over reasonable time units, such as days or weeks, which are captured by the variability of random effects. Furthermore, the fixed-effects parameters encapsulate a subject-specific network structure. Leveraging the well-established theoretical and computational foundation of linear mixed-effects models, we transform the autoregressive formulation to a classical one and utilize the existing methods and tools. To validate our approach, we perform simulations assuming our model as the true data-generating process. By manipulating a predefined set of parameters, we investigate the reliability and feasibility of our approach across varying numbers of observations, levels of noise intensity, compliance rates, and scalability to higher dimensions. Our findings underscore the challenges associated with estimating individualized parameters in the context of common longitudinal designs, where the required number of observations may often be unattainable. Moreover, our study highlights the sensitivity of autoregressive mixed-effect models to noise levels and the difficulty of scaling due to the substantial number of parameters.

Drivers and recent trends of hospitalisation costs related to acute pulmonary embolism.

BACKGROUND AND AIMS: The socio-economic burden imposed by acute pulmonary embolism (PE) on European healthcare systems is largely unknown. We sought to determine temporal trends and identify cost drivers of hospitalisation for PE in Germany. METHODS AND RESULTS: We analysed the totality of reimbursed hospitalisation costs in Germany (G-DRG system) in the years 2016-2020. Overall, 484 884 PE hospitalisations were coded in this period. Direct hospital costs amounted to a median of 3572 (IQR, 2804 to 5869) euros, resulting in average total reimbursements of 710 million euros annually. Age, PE severity, comorbidities and in-hospital (particularly bleeding) complications were identified by multivariable logistic regression as significant cost drivers. Use of catheter-directed therapy (CDT) constantly increased (annual change in the absolute proportion of hospitalisations with CDT + 0.40% [95% CI + 0.32% to + 0.47%]; P < 0.001), and it more than doubled in the group of patients with severe PE (28% of the entire population) over time. Although CDT use was overall associated with increased hospitalisation costs, this association was no longer present (adjusted OR 1.02 [0.80-1.31]) in patients with severe PE and shock; this was related, at least in part, to a reduction in the median length of hospital stay (for 14.0 to 8.0 days). CONCLUSIONS: We identified current and emerging cost drivers of hospitalisation for PE, focusing on severe disease and intermediate/high risk of an adverse early outcome. The present study may inform reimbursement decisions by policymakers and help to guide future health economic analysis of advanced treatment options for patients with PE.

Modelling Costs of Interventional Pulmonary Embolism Treatment: Implications of US Trends for a European Healthcare System.

BACKGROUND: Catheter-directed treatment (CDT) of acute pulmonary embolism (PE) is entering a growth phase in Europe following a steady increase in the United States (US) in the past decade, but the potential economic impact on European healthcare systems remains unknown. METHODS AND RESULTS: We built two statistical models for the monthly trend of proportion of CDT among patients with severe (intermediate- or high-risk) PE in the US. The conservative model was based on admission data from the National Inpatient Sample (NIS) 2016-2020, and the model reflecting increasing access to advanced treatment from the PERTTM national quality assurance database registry 2018-2021. By applying these models to the forecast of annual PE-related hospitalizations in Germany, we calculated the annual number of severe PE cases and the expected increase in CDT use for the period 2025-2030. The NIS-based model yielded a slow increase, reaching 3.1% (95% CI 3.0-3.2%) among all hospitalizations with PE in 2030; in the PERT-based model, increase would be steeper, reaching 8.7% (8.3-9.2%). Based on current reimbursement rates, we estimated an increase of annual costs for PE-related hospitalizations in Germany ranging from 15.3 to 49.8 million euros by 2030. This calculation does not account for potential cost savings, including those from reduced length of hospital stay. CONCLUSION: Our approach and results, which may be adapted to other European healthcare systems, provide a benchmark for healthcare costs expected to result from CDT. Data from ongoing trials on clinical benefits and cost savings are needed to determine cost-effectiveness and inform reimbursement decisions.

Healthcare resource utilisation and associated costs after low-risk pulmonary embolism: pre-specified analysis of the Home Treatment of Pulmonary Embolism (HoT-PE) study.

BACKGROUND: Pulmonary embolism (PE) and its sequelae impact healthcare systems globally. Low-risk PE patients can be managed with early discharge strategies leading to cost savings, but post-discharge costs are undetermined. PURPOSE: To define healthcare resource utilisation and overall costs during follow-up of low-risk PE. METHODS: We used an incidence-based, bottom-up approach and calculated direct and indirect costs over 3-month follow-up after low-risk PE, with data from the Home Treatment of Patients with Low-Risk Pulmonary Embolism (HoT-PE) cohort study. RESULTS: Average 3-month costs per patient having suffered low-risk PE were 7029.62 €; of this amount, 4872.93 € were associated with PE, accounting to 69.3% of total costs. Specifically, direct costs totalled 3019.33 €, and of those, 862.64 € (28.6%) were associated with PE. Anticoagulation (279.00 €), rehospitalisations (296.83 €), and ambulatory visits (194.95 €) comprised the majority of the 3-month direct costs. The remaining costs amounting to 4010.29 € were indirect costs due to loss of productivity. CONCLUSION: In a patient cohort with acute low-risk PE followed over 3 months, the majority of costs were indirect costs related to productivity loss, whereas direct, PE-specific post-discharge costs were low. Effective interventions are needed to reduce the burden of PE and associated costs, especially those related to productivity loss.

Surgical site infection after trochanteric and subtrochanteric fractures: a single centre retrospective analysis.

Surgical site infection (SSI) following osteosynthesis of trochanteric or subtrochanteric fractures is a rare but serious complication with incidence rate ranging from 1 to 3%. SSIs are associated with higher mortality and increased length of hospital stay resulting in higher healthcare costs and loss of life quality. In this retrospective analysis all patients with SSI following osteosynthesis of trochanteric or subtrochanteric fractures at the Department of Trauma Surgery were identified. We included all surgical procedures performed from 1992 to 2018, using data from electronic health records and SSI-Trauma-Registry. The aim was to describe epidemiological data, as well as to identify parameters correlating with the occurrence of SSI and mortality. Of 2753 patients, 53 (1.9%) developed SSI. Longer operative time was demonstrated among patients with SSI (P = 0.008). Mortality during the first postoperative year was significantly higher in the SSI group (32.1% vs. 19.1%; P = 0.018), with detection of methicillin-sensitive (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA; HR 4.13, CI 95% 1.24-13.80; P = 0.021) or Enterococcus spp. (HR 5.58, CI 95% 1.67-18.65; P = 0.005) being independent risk factors. Male sex (HR 2.25, 95% CI 1.86-2.73; P < 0.001) and higher mean age (HR 1.05, 95% CI 1.04-1.06; P < 0.001) were found to be predictors for 1-year mortality in non-infected patients. SSI rate was low with 1.9% and longer duration of surgery was associated with infection. Patients with SSI had a higher 1-year mortality, with detection of MSSA, MRSA and enterococci significantly increasing the risk of dying. Male sex and higher age were risk factors for one-year mortality in patients without SSI.

Alpha-1-antitrypsin-deficiency is associated with lower cardiovascular risk: an approach based on federated learning.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an inflammatory multisystemic disease caused by environmental exposures and/or genetic factors. Inherited alpha-1-antitrypsin deficiency (AATD) is one of the best recognized genetic factors increasing the risk for an early onset COPD with emphysema. The aim of this study was to gain a better understanding of the associations between comorbidities and specific biomarkers in COPD patients with and without AATD to enable future investigations aimed, for example, at identifying risk factors or improving care. METHODS: We focused on cardiovascular comorbidities, blood high sensitivity troponin (hs-troponin) and lipid profiles in COPD patients with and without AATD. We used clinical data from six German University Medical Centres of the MIRACUM (Medical Informatics Initiative in Research and Medicine) consortium. The codes for the international classification of diseases (ICD) were used for COPD as a main diagnosis and for comorbidities and blood laboratory data were obtained. Data analyses were based on the DataSHIELD framework. RESULTS: Out of 112,852 visits complete information was available for 43,057 COPD patients. According to our findings, 746 patients with AATD (1.73%) showed significantly lower total blood cholesterol levels and less cardiovascular comorbidities than non-AATD COPD patients. Moreover, after adjusting for the confounder factors, such as age, gender, and nicotine abuse, we confirmed that hs-troponin is a suitable predictor of overall mortality in COPD patients. The comorbidities associated with AATD in the current study differ from other studies, which may reflect geographic and population-based differences as well as the heterogeneous characteristics of AATD. CONCLUSION: The concept of MIRACUM is suitable for the analysis of a large healthcare database. This study provided evidence that COPD patients with AATD have a lower cardiovascular risk and revealed that hs-troponin is a predictor for hospital mortality in individuals with COPD.

Rheuma-VOR study: optimising healthcare of rheumatic diseases by multiprofessional coordinating centres.

OBJECTIVES: Early diagnosis of inflammatory arthritis is critical to prevent joint damage and functional incapacities. However, the discrepancy between recommendations of early diagnosis and reality is remarkable. The Rheuma-VOR study aimed to improve the time to diagnosis of patients with early arthritis by coordinating cooperation between primary care physicians, specialists and patients in Germany. METHODS: This prospective non-randomised multicentre study involved 2340 primary care physicians, 72 rheumatologists, 4 university hospitals and 4 rheumatology centres in 4 German Federal States. The two coprimary endpoints (time to diagnosis and screening performance of primary care physicians) were evaluated for early versus late implementation phase. Additionally, time to diagnosis and secondary endpoints (decrease of disease activity, increase in quality of life and overall well-being, improvement of fatigue, depression, functional ability, and work ability, reduction in drug and medical costs and hospitalisation) were compared with a reference cohort of the German Rheumatism Research Centre (DRFZ) reflecting standard care. RESULTS: A total of 7049 patients were enrolled in the coordination centres and 1537 patients were diagnosed with a rheumatic disease and consented to further participation. A follow-up consultation after 1 year was realised in 592 patients. The time to diagnosis endpoint and the secondary endpoints were met. In addition, the calculation of cost-effectiveness shows that Rheuma-VOR has a dominant cost-benefit ratio compared with standard care. DISCUSSION: Rheuma-VOR has shown an improvement in rheumatological care, patient-reported outcome parameters and cost savings by coordinating the cooperation of primary care physicians, rheumatologists and patients, in a nationwide approach.

Imager-A mobile health mental imagery-based ecological momentary intervention targeting reward sensitivity: A randomized controlled trial.

Robust reward sensitivity may help preserve mental well-being in the face of adversity and has been proposed as a key stress resilience factor. Here, we present a mobile health application, "Imager," which targets reward sensitivity by training individuals to create mental images of future rewarding experiences. We conducted a two-arm randomized controlled trial with 95 participants screened for reward sensitivity. Participants in the intervention group received an ecological momentary intervention-Imager, which encouraged participants to create mental images of rewarding events for 1 week. The control group participants received only ecological momentary assessment, without the instruction to generate mental images. Adherence to Imager was high; participants in the intervention group engaged in 88% of the planned activities. In the follow-up assessment, the intervention group reported less mental health symptoms, mainly in depression (ß = -0.34, df = 93, p = .004) and less perceived stress (ß = -0.18, df = 93, p = .035), than control group participants and compared with the baseline assessment. Our results show the positive effects of Imager on mental health symptoms. The encouraging effects of the app on mental health outcomes may lead to greater use of ecological momentary interventions in the clinical preventive practice of affective disorders.

German Version of the Mobile Agnew Relationship Measure: Translation and Validation Study.

BACKGROUND: The mobile Agnew Relationship Measure (mARM) is a self-report questionnaire for the evaluation of digital mental health interventions and their interactions with users. With the global increase in digital mental health intervention research, translated measures are required to conduct research with local populations. OBJECTIVE: The aim of this study was to translate and validate the original English version of the mARM into a German version (mARM-G). METHODS: A total of 2 native German speakers who spoke English as their second language conducted forward translation of the original items. This version was then back translated by 2 native German speakers with a fluent knowledge of English. An independent bilingual reviewer then compared these drafts and created a final German version. The mARM-G was validated by 15 experts in the field of mobile app development and 15 nonexperts for content validity and face validity; 144 participants were recruited to conduct reliability testing as well as confirmatory factor analysis. RESULTS: The content validity index of the mARM-G was 0.90 (expert ratings) and 0.79 (nonexperts). The face validity index was 0.89 (experts) and 0.86 (nonexperts). Internal consistency for the entire scale was Cronbach α=.91. Confirmatory factor analysis results were as follows: the chi-square statistic to df ratio was 1.66. Comparative Fit Index was 0.87 and the Tucker-Lewis Index was 0.86. The root mean square error of approximation was 0.07. CONCLUSIONS: The mARM-G is a valid and reliable tool that can be used for future studies in German-speaking countries.

App-Controlled Treatment Monitoring and Support for Patients With Head and Neck Cancer Undergoing Radiotherapy: Results From a Prospective Randomized Controlled Trial.

BACKGROUND: Head and neck cancers (HNCs) are very common malignancies, and treatment often requires multimodal approaches, including radiotherapy and chemotherapy. Patients with HNC often display a high symptom burden, both due to the disease itself and the adverse effects of the multimodal therapy. Close telemonitoring of symptoms and quality of life during the course of treatment may help to identify those patients requiring early medical support. OBJECTIVE: The App-Controlled Treatment Monitoring and Support for Patients With Head and Neck Cancer (APCOT) trial aimed to investigate the feasibility of integrating electronic patient-reported outcomes (ePROs) in the treatment surveillance pathway of patients with HNC during the course of their radiotherapy. Additionally, the influence of app-based ePRO monitoring on global and disease-specific quality of life and patient satisfaction with treatment was assessed. METHODS: Patients undergoing radiotherapy for histologically proven HNCs at the Department of Radiation Oncology, University Medical Center Freiburg, Germany, were enrolled in this trial and monitored by weekly physician appointments. Patients were randomized between additional ePRO monitoring on each treatment day or standard-of-care monitoring. Feasibility of ePRO monitoring was defined as ≥80% of enrolled patients answering ≥80% of their daily app-based questions. Quality of life and patient satisfaction were assessed by the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire (QLQ-C30), the head and neck cancer module (H&N35), and the validated Patient Satisfaction Questionnaire Short Form (PSQ-18) at the completion of treatment and compared between trial arms. RESULTS: A total of 100 patients were enrolled in this trial, and 93 patients were evaluable. All patients (100%) in the experimental arm answered ≥80% of the ePRO questions during treatment, reaching the predefined threshold for the feasibility of ePRO monitoring (P<.001 in the binomial test). No clinical or patient-specific factor was found to influence feasibility. Global health and most domains of the general quality of life were comparable between trial arms, but an increased HNC-specific symptom burden was reported by patients undergoing ePRO surveillance. ePRO monitoring resulted in improved patient satisfaction regarding interpersonal manners (P=.01), financial aspects (P=.01), and time spent with a doctor (P=.01). CONCLUSIONS: This trial demonstrated the feasibility of incorporating daily app-based ePRO surveillance for patients with HNC undergoing radiotherapy. Our data, for the first time, demonstrate that telemonitoring in this setting led to increased reporting of HNC-specific symptom burden and significantly improved several domains of patient satisfaction. Further analyses are needed to assess whether our findings hold true outside the context of a clinical trial. TRIAL REGISTRATION: German Clinical Trials Register DRKS00020491; https://drks.de/search/en/trial/DRKS00020491.

Predicting Patient Death after Allogeneic Stem Cell Transplantation for Inborn Errors Using Machine Learning (PREPAD): A European Society for Blood and Marrow Transplantation Inborn Errors Working Party Study.

Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative treatment for many inborn errors of immunity, metabolism, and hematopoiesis. No predictive models are available for these disorders. We created a machine learning model using XGBoost to predict survival after HSCT using European Society for Blood and Marrow Transplant registry data of 10,888 patients who underwent HSCT for inborn errors between 2006 and 2018, and compared it to a simple linear Cox model, an elastic net Cox model, and a random forest model. The XGBoost model had a cross-validated area under the curve value of .73 at 1 year, which was significantly superior to the other models, and it accurately predicted for countries excluded while training. It predicted close to 0% and >30% mortality more often than other models at 1 year, while maintaining good calibration. The 5-year survival was 94.7% in the 25% of patients at lowest risk and 62.3% in the 25% at highest risk. Within disease and donor subgroups, XGBoost outperformed the best univariate predictor. We visualized the effect of the main predictors-diagnosis, performance score, patient age and donor type-using the SHAP ML explainer and developed a stand-alone application, which can predict using the model and visualize predictions. The risk of mortality after HSCT for inborn errors can be accurately predicted using an explainable machine learning model. This exceeds the performance of models described in the literature. Doing so can help detect deviations from expected survival and improve risk stratification in trials.

Dynamic Modelling of Mental Resilience in Young Adults: Protocol for a Longitudinal Observational Study (DynaM-OBS).

BACKGROUND: Stress-related mental disorders are highly prevalent and pose a substantial burden on individuals and society. Improving strategies for the prevention and treatment of mental disorders requires a better understanding of their risk and resilience factors. This multicenter study aims to contribute to this endeavor by investigating psychological resilience in healthy but susceptible young adults over 9 months. Resilience is conceptualized in this study as the maintenance of mental health or quick recovery from mental health perturbations upon exposure to stressors, assessed longitudinally via frequent monitoring of stressors and mental health. OBJECTIVE: This study aims to investigate the factors predicting mental resilience and adaptive processes and mechanisms contributing to mental resilience and to provide a methodological and evidence-based framework for later intervention studies. METHODS: In a multicenter setting, across 5 research sites, a sample with a total target size of 250 young male and female adults was assessed longitudinally over 9 months. Participants were included if they reported at least 3 past stressful life events and an elevated level of (internalizing) mental health problems but were not presently affected by any mental disorder other than mild depression. At baseline, sociodemographic, psychological, neuropsychological, structural, and functional brain imaging; salivary cortisol and α-amylase levels; and cardiovascular data were acquired. In a 6-month longitudinal phase 1, stressor exposure, mental health problems, and perceived positive appraisal were monitored biweekly in a web-based environment, while ecological momentary assessments and ecological physiological assessments took place once per month for 1 week, using mobile phones and wristbands. In a subsequent 3-month longitudinal phase 2, web-based monitoring was reduced to once a month, and psychological resilience and risk factors were assessed again at the end of the 9-month period. In addition, samples for genetic, epigenetic, and microbiome analyses were collected at baseline and at months 3 and 6. As an approximation of resilience, an individual stressor reactivity score will be calculated. Using regularized regression methods, network modeling, ordinary differential equations, landmarking methods, and neural net-based methods for imputation and dimension reduction, we will identify the predictors and mechanisms of stressor reactivity and thus be able to identify resilience factors and mechanisms that facilitate adaptation to stressors. RESULTS: Participant inclusion began in October 2020, and data acquisition was completed in June 2022. A total of 249 participants were assessed at baseline, 209 finished longitudinal phase 1, and 153 finished longitudinal phase 2. CONCLUSIONS: The Dynamic Modelling of Resilience-Observational Study provides a methodological framework and data set to identify predictors and mechanisms of mental resilience, which are intended to serve as an empirical foundation for future intervention studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39817.

How do (false) positively screened patients experience a screening programme for liver cirrhosis or fibrosis in Germany? A qualitative study.

OBJECTIVE: This study aimed to explore psychosocial consequences of (false) positive liver screening results and to identify influencing factors for perceived strain within a multistage screening programme for liver cirrhosis and fibrosis in Germany. METHODS: Between June 2018 and May 2019, all positively screened patients were asked to participate in the study (n = 158). N = 11 telephone interviews and n = 4 follow-up interviews were conducted. Semi-structured telephone interviews were carried out. The analysis followed a structuring content analysis approach. Thereby, categories were first defined deductively. Second, the categories were revised inductively based on the data. RESULTS: The main themes found regarding the consequences of the screening were categorised in emotional reactions and behavioural reactions. Few respondents described negative emotional consequences related to screening. Those seem to be mostly driven by suboptimal patient-provider communication and might be worsened when transparent information transfer fails to happen. As a result, patients sought information and support in their social environment. All patients reported positive attitudes towards liver screening. CONCLUSION: To reduce the potential occurrence of psychosocial consequences during the screening process, medical screening should be performed in the context of transparent information. Regular health communication on the side of health professionals and increasing patients' health literacy might contribute to avoiding negative emotions in line with screening. PATIENT OR PUBLIC CONTRIBUTION: This study recognises the wide-ranging patients' perspectives regarding the consequences of liver screening which should be taken into consideration when implementing a new screening programme to ensure a patient-centred approach.

Positive Prospective Mental Imagery Characteristics in Young Adults and Their Associations with Depressive Symptoms.

Background: Positive prospective mental imagery plays an important role in mental well-being, and depressive symptoms have been associated with difficulties in generating positive prospective mental images (PPMIs). We used a mobile app to gather PPMIs generated by young adults during the COVID-19 pandemic and analyzed content, characteristics, and associations with depressive symptoms. Methods: This is a secondary analysis of a randomized controlled trial with 95 healthy young adults allocated into two groups (intervention and control). Participants used the mobile app decreasing mental health symptoms for seven consecutive days. Fifty participants in the intervention group reported PPMIs at least three times per day using a mobile app inducing PPMI generation. We categorized entries into themes and applied moderation models to investigate associations between PPMI characteristics and depressive symptoms. Results: We distinguished 25 PPMI themes. The most frequent were related to consuming food and drinks, watching TV/streaming platforms, and doing sports. Vividness and ease of generation of PPMIs, but not their anticipation, pleasure intensity or number of engagements with the app were associated with fewer depressive symptoms. Conclusions: We identified PPMI themes in young adults and found significant negative associations between depressive symptoms and vividness and generation ease of PPMIs. These results may inform prevention and intervention science, including the design of personalized interventions. We discuss implications for future studies and treatment development for individuals experiencing diminished PPMI. Supplementary Information: The online version contains supplementary material available at 10.1007/s10608-023-10378-5.

DOT1L activity affects neural stem cell division mode and reduces differentiation and ASNS expression.

Cortical neurogenesis depends on the balance between self-renewal and differentiation of apical progenitors (APs). Here, we study the epigenetic control of AP's division mode by focusing on the enzymatic activity of the histone methyltransferase DOT1L. Combining lineage tracing with single-cell RNA sequencing of clonally related cells, we show at the cellular level that DOT1L inhibition increases neurogenesis driven by a shift of APs from asymmetric self-renewing to symmetric neurogenic consumptive divisions. At the molecular level, DOT1L activity prevents AP differentiation by promoting transcription of metabolic genes. Mechanistically, DOT1L inhibition reduces activity of an EZH2/PRC2 pathway, converging on increased expression of asparagine synthetase (ASNS), a microcephaly associated gene. Overexpression of ASNS in APs phenocopies DOT1L inhibition, and also increases neuronal differentiation of APs. Our data suggest that DOT1L activity/PRC2 crosstalk controls AP lineage progression by regulating asparagine metabolism.

Statistical analysis of high-dimensional biomedical data: a gentle introduction to analytical goals, common approaches and challenges.

BACKGROUND: In high-dimensional data (HDD) settings, the number of variables associated with each observation is very large. Prominent examples of HDD in biomedical research include omics data with a large number of variables such as many measurements across the genome, proteome, or metabolome, as well as electronic health records data that have large numbers of variables recorded for each patient. The statistical analysis of such data requires knowledge and experience, sometimes of complex methods adapted to the respective research questions. METHODS: Advances in statistical methodology and machine learning methods offer new opportunities for innovative analyses of HDD, but at the same time require a deeper understanding of some fundamental statistical concepts. Topic group TG9 "High-dimensional data" of the STRATOS (STRengthening Analytical Thinking for Observational Studies) initiative provides guidance for the analysis of observational studies, addressing particular statistical challenges and opportunities for the analysis of studies involving HDD. In this overview, we discuss key aspects of HDD analysis to provide a gentle introduction for non-statisticians and for classically trained statisticians with little experience specific to HDD. RESULTS: The paper is organized with respect to subtopics that are most relevant for the analysis of HDD, in particular initial data analysis, exploratory data analysis, multiple testing, and prediction. For each subtopic, main analytical goals in HDD settings are outlined. For each of these goals, basic explanations for some commonly used analysis methods are provided. Situations are identified where traditional statistical methods cannot, or should not, be used in the HDD setting, or where adequate analytic tools are still lacking. Many key references are provided. CONCLUSIONS: This review aims to provide a solid statistical foundation for researchers, including statisticians and non-statisticians, who are new to research with HDD or simply want to better evaluate and understand the results of HDD analyses.

Functional outcome of an 'all-inside' technique in female anterior cruciate ligament reconstruction at long-term follow-up: A gender-sensitive analysis.

BACKGROUND: As the awareness towards gender-specific therapies continues to increase among all fields of medicine, so does the need for gender-sensitive evaluations of established surgical techniques. With a higher likelihood of anterior cruciate ligament injury in women, a critical assessment of the functional outcome of anterior cruciate ligament reconstruction regarding patient sex is indispensable. Almost all pre-existing literature on this subject is based on anterior cruciate ligament reconstructions carried out before 2008, when 'all-inside' techniques did not exist. This implicates the need to investigate this technique towards its differences in outcome between male and female patients. OBJECTIVES: The purpose of this study was to determine whether there is a difference concerning the functional outcome of an 'all-inside' technique for anterior cruciate ligament reconstruction in female patients when compared to a cohort of male patients matched for body mass index and age. DESIGN: Retrospective analysis. METHODS: All female patients who underwent anterior cruciate ligament reconstruction using an all-inside technique between 2011 and 2012 were examined for inclusion. Functional outcome parameters investigated included the Lysholm Knee Score, International Knee Documentation Committee score, Visual Analogue Scale score and the Tegner Activity Scale. All parameters were documented before surgery and at 3-, 6-, 12- and >24 months follow-up. At 24-month follow-up, anterior-posterior knee laxity was tested using the KT-2000 arthrometer device. For comparison, an equivalent group of male patients who underwent the same procedure was matched. RESULTS: 27 female patients were matched with 27 male patients. The average age was 29 years, and a mean follow-up of 90 months could be achieved with 27 of patients reaching a follow-up of > 10 years. The evaluated scores showed no significant difference between female and male patients. Women presented with poorer functional outcome at 3- as well as 6-month follow-ups compared to men, without reaching statistical significance. After 12 months, no further differences could be found. CONCLUSION: This study proved that an all-inside technique for anterior cruciate ligament reconstruction is able to produce the same functional outcome in female as in male patients at long-term follow-up. The results on short-term outcome indicate the need for further research towards gender-specific differences after anterior cruciate ligament reconstruction, their potential causes and potential of improvement. LEVEL OF EVIDENCE: Level III, retrospective comparative study.

Needs assessment towards research data management at the Medical Faculty of the University of Freiburg - Data of the BE-KONFORM study.

In order to investigate employees' needs of the Medical Faculty of the University of Freiburg regarding research data management, the BE-KONFORM study was performed in a two-step approach. First, guideline-based qualitative video interviews with four researchers were performed to identify key constructs of relevance. Second, a standardized online survey was conducted from 1st to 15th of November 2020 based on e-mail invitation by the dean and a faculty newsletter. The questionnaire was provided bilingual (English and German) using a backward-forward translation method, no reminders and incentives were used to increase the response rate. The online survey was programmed in REDCap and was accessible via online link. The target population were members of the Medical Faculty (listed in the newsletter mailing list) regardless of the type of working contract signed. The final dataset contains 236 complete cases (90% German and 10% English). The study includes a randomised module asking for data publication (group A) or not (group B). 113 cases were randomized into group A and 99% of them consented to the publication of the collected research data in anonymized form (n=112). The dataset comprised questions about work-related characteristics (professional status, working experience, scientific field of work), data management-related items (definition of research data management, type of data used, type of storage used for saving data, use of electronic laboratory notebooks), experience and attitudes towards data publication in data repositories, as well as needs and preferences regarding research data management support. The produced data offers the possibility to connect with other data collected in this field in other contexts (faculties or universities).

Recurrence analysis of glioblastoma cases based on distance and dose information.

BACKGROUND AND PURPOSE: Radiation therapy for glioblastoma (GBM) typically involves large target volumes. The aim of this study was to examine the recurrence pattern of GBM following modern radiochemotherapy according to EORTC guidelines and provide dose and distance information for the choice of optimal target volume margins. MATERIALS AND METHODS: In this study, the recurrences of 97 GBM patients, treated with radiochemotherapy from 2013 to 2017 at the Medical Center- University of Freiburg, Germany were analysed. Dose and distance based metrices were used to derive recurrence patterns. RESULTS: The majority of recurrences (75%) occurred locally within the primary tumor area. Smaller GTVs had a higher rate of distant recurrences. Larger treated volumes did not show a clinical benefit regarding progression free and overall survival. CONCLUSION: The identified recurrence pattern suggests that adjustments or reductions in target volume margins are feasible and could result in similar survival rates, potentially combined with a lower risk of side effects.