Variable Selection in General Multinomial Logit Models

The use of the multinomial logit model is typically restricted to applications with few predictors, because in high-dimensional settings maximum likelihood estimates tend to deteriorate. In this paper we are proposing a sparsity-inducing penalty that accounts for the special structure of multinomial models. In contrast to existing methods, it penalizes the parameters that are linked to one variable in a grouped way and thus yields variable selection instead of parameter selection. We develop a proximal gradient method that is able to efficiently compute stable estimates. In addition, the penalization is extended to the important case of predictors that vary across response categories. We apply our estimator to the modeling of party choice of voters in Germany including voter-specific variables like age and gender but also party-specific features like stance on nuclear energy and immigration

Hypothesis testing in Bayesian network meta-analysis

Background: Network meta-analysis is an extension of the classical pairwise meta-analysis and allows to compare multiple interventions based on both head-to-head comparisons within trials and indirect comparisons across trials. Bayesian or frequentist models are applied to obtain effect estimates with credible or confidence intervals. Furthermore, p-values or similar measures may be helpful for the comparison of the included arms but related methods are not yet addressed in the literature. In this article, we discuss how hypothesis testing can be done in a Bayesian network meta-analysis. Methods: An index is presented and discussed in a Bayesian modeling framework. Simulation studies were performed to evaluate the characteristics of this index. The approach is illustrated by a real data example. Results: The simulation studies revealed that the type I error rate is controlled. The approach can be applied in a superiority as well as in a non-inferiority setting. Conclusions: Test decisions can be based on the proposed index. The index may be a valuable complement to the commonly reported results of network meta-analyses. The method is easy to apply and of no (noticeable) additional computational cost

Adaptive propensity score procedure improves matching in prospective observational trials

Background: Randomized controlled trials are the gold-standard for clinical trials. However, randomization is not always feasible. In this article we propose a prospective and adaptive matched case-control trial design assuming that a control group already exists. Methods: We propose and discuss an interim analysis step to estimate the matching rate using a resampling step followed by a sample size recalculation. The sample size recalculation is based on the observed mean resampling matching rate. We applied our approach in a simulation study and to a real data set to evaluate the characteristics of the proposed design and to compare the results to a naive approach. Results: The proposed design achieves at least 10% higher matching rate than the naive approach at final analysis, thus providing a better estimation of the true matching rate. A good choice for the interim analysis seems to be a fraction of around 1/2 to 2/3 of the control patients. Conclusion: The proposed resampling step in a prospective matched case-control trial design leads to an improved estimate of the final matching rate and, thus, to a gain in power of the approach due to sensible sample size recalculation

Intensity-modulated versus 3-dimensional conformal radiotherapy in the definitive treatment of esophageal cancer: comparison of outcomes and acute toxicity

Background: Though the vast majority of seminal trials for locally advanced esophageal cancer (EC) utilized three-dimensional conformal radiotherapy (3DCRT), the advanced and highly conformal technology known as intensity-modulated radiotherapy (IMRT) can decrease doses to critical cardiopulmonary organs. To date, there have been no studies comparing both modalities as part of definitive chemoradiation (dCRT) for EC. Herein, we investigated local control and survival and evaluated clinical factors associated with these endpoints between cohorts. Methods: We retrospectively analyzed 93 patients (3DCRT n = 49, IMRT n = 44) who received dCRT at our institution between 2000 and 2012 with the histologic diagnosis of nonmetastatic EC, a Karnofsky performance status of ≥70, curative treatment intent, and receipt of concomitant CRT. Patients were excluded if receiving <50 Gy. Kaplan-Meier analysis was used to evaluate the endpoints of local relapse rate (LR), progression-free survival (PFS), and overall survival (OS). Cox proportional hazards modeling addressed factors associated with outcomes with univariate and multivariate approaches. Rates of acute toxicities and basic dosimetric parameters were compared between 3DCRT and IMRT patients. Results: Mean follow-up was 34.7 months. The 3-year LR was 28.6% in the 3DCRT group and 22.7% in the IMRT group (p = 0.620). Median PFS were 13.8 and 16.6 months, respectively (p = 0.448). Median OS were 18.4 and 42.0 months, respectively (p = 0.198). On univariate analysis, only cumulative radiation dose was associated with superior LR (hazard ratio (HR) 0.736; 95% confidence interval (CI) 0.635 – 0.916, p = 0.004). Factors clearly affecting survival were not observed. Conclusions: When comparing 3DCRT- versus IMRT-based dCRT, no survival benefits were observed. However, we found a lower local recurrence rate in the IMRT group potentially owing to dose-escalation. Prospective data are needed to verify the presented results herein

Sustainable reduction of antibiotic-induced antimicrobial resistance (ARena) in German ambulatory care: study protocol of a cluster randomised trial

Background: Despite many initiatives to enhance the rational use of antibiotics, there remains substantial room for improvement. The overall aim of this study is to optimise the appropriate use of antibiotics in German ambulatory care in patients with acute non-complicated infections (respiratory tract infections, such as bronchitis, sinusitis, tonsillitis and otitis media), community-acquired pneumonia and non-complicated cystitis, in order to counter the advancing antimicrobial resistance development. Methods: A three-armed cluster randomised trial will be conducted in 14 practice networks in two German federal states (Bavaria and North Rhine-Westphalia) and an added cohort that reflects standard care. The trial is accompanied by a process evaluation. Each arm will receive a different set of implementation strategies. Arm A receives a standard set, comprising of e-learning on communication with patients and quality circles with data-based feedback for physicians, information campaigns for the public, patient information material and performance-based additional reimbursement. Arm B receives this standard set plus e-learning on communication with patients and quality circles with data-based feedback tailored for non-physician health professionals of the practice team and information material for tablet computers (culture sensitive). Arm C receives the standard set as well as a computerised decision support system and quality circles in local multidisciplinary groups. The study aims to recruit 193 practices which will provide data on 23,934 patients each year (47,867 patients in total). The outcome evaluation is based on claims data and refers to established indicators of the European Surveillance of Antimicrobial Consumption Network (ESAC-Net). Primary and secondary outcomes relate to prescribing of antibiotics, which will be analysed in multivariate regression models. The process evaluation is based on interviews with surveys among physicians, non-physician health professionals of the practice team and stakeholders. A patient survey is conducted in one of the study arms. Interview data will be qualitatively analysed using thematic framework analysis. Survey data of physicians, non-physician health professionals of the practice team and patients will use descriptive and exploratory statistics for analysis. Discussion: The ARena trial will examine the effectiveness of large scale implementation strategies and explore their delivery in routine practice. Trial registration: ISRCTN, ISRCTN58150046 . Registered 24 August 2017

Development and internal validation of prognostic models to predict negative health outcomes in older patients with multimorbidity and polypharmacy in general practice

Background Polypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices. Methods Design: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: >= 60 years, >= 5 drugs, >= 3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses. Results Most important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke's R-2 0.507) were depressive symptoms (-2.73 (95% CI: -3.56 to -1.91)), MAI (-0.39 (95% CI: -0.7 to -0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R-2 values. In claims data-based model with highest explanatory power (R-2=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables. Conclusions Best trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status

Immunosuppressive therapy influences the accelerated age-dependent T-helper cell differentiation in systemic lupus erythematosus remission patients

Background: CD4+ T cells are of great importance in the pathogenesis of systemic lupus erythematosus (SLE), as an imbalance between CD4+ regulatory T cells (Tregs) and CD4+ responder T cells (Tresps) causes flares of active disease in SLE patients. In this study, we aimed to find the role of aberrant Treg/Tresp cell differentiation for maintaining Treg/Tresp cell balance and Treg functionality. Methods: To determine differences in the differentiation of Tregs/Tresps we calculated the percentages of CD45RA+CD31+ recent thymic emigrant (RTE) Tregs/Tresps and CD45RA+CD31− mature naive (MN) Tregs/Tresps, as well as CD45RA−CD31+ and CD45RA−CD31− memory Tregs/Tresps (CD31+ and CD31− memory Tregs/Tresps) within the total Treg/Tresp pool of 78 SLE remission patients compared with 94 healthy controls of different ages. The proliferation capacity of each Treg/Tresp subset was determined by staining the cells with anti-Ki67 monoclonal antibodies. Differences in the autologous or allogeneic Treg function between SLE remission patients and healthy controls were determined using suppression assays. Results: With age, we found an increased differentiation of RTE Tregs via CD31+ memory Tregs and of RTE Tresps via MN Tresps into CD31− memory Tregs/Tresp in healthy volunteers. This opposite differentiation of RTE Tregs and Tresps was associated with an age-dependent increase in the suppressive activity of both naive and memory Tregs. SLE patients showed similar age-dependent Treg cell differentiation. However, in these patients RTE Tresps differentiated increasingly via CD31+ memory Tresps, whereby CD31− memory Tresps arose that were much more difficult to inhibit for Tregs than those that emerged through differentiation via MN Tresps. Consequently, the increase in the suppressive activity of Tregs with age could not be maintained in SLE patients. Testing the Tregs of healthy volunteers and SLE patients with autologous and nonautologous Tresps revealed that the significantly decreased Treg function in SLE patients was not exclusively attributed to an age-dependent diminished sensitivity of the Tresps for Treg suppression. The immunosuppressive therapy reduced the accelerated age-dependent Tresp cell proliferation to normal levels, but simultaneously inhibited Treg cell proliferation below normal levels. Conclusions: Our data reveal that the currently used immunosuppressive therapy has a favorable effect on the differentiation and proliferation of Tresps but has a rather unfavorable effect on the proliferation of Tregs. Newer substances with more specific effects on the immune system would be desirable

Fully digital data processing during cardiovascular implantable electronic device follow-up in a high-volume tertiary center

Background Increasing numbers of patients with cardiovascular implantable electronic devices (CIEDs) and limited follow-up capacities highlight unmet challenges in clinical electrophysiology. Integrated software (MediConnect®) enabling fully digital processing of device interrogation data has been commercially developed to facilitate follow-up visits. We sought to assess feasibility of fully digital data processing (FDDP) during ambulatory device follow-up in a high-volume tertiary hospital to provide guidance for future users of FDDP software. Methods A total of 391 patients (mean age, 70 years) presenting to the outpatient department for routine device follow-up were analyzed (pacemaker, 44%; implantable cardioverter defibrillator, 39%; cardiac resynchronization therapy device, 16%). Results Quality of data transfer and follow-up duration were compared between digital (n = 265) and manual processing of device data (n = 126). Digital data import was successful, complete and correct in 82% of cases when early software versions were used. When using the most recent software version the rate of successful digital data import increased to 100%. Software-based import of interrogation data was complete and without failure in 97% of cases. The mean duration of a follow-up visit did not differ between the two groups (digital 18.7 min vs. manual data transfer 18.2 min). Conclusions FDDP software was successfully implemented into the ambulatory follow-up of patients with implanted pacemakers and defibrillators. Digital data import into electronic patient management software was feasible and supported the physician’s workflow. The total duration of follow-up visits comprising technical device interrogation and clinical actions was not affected in the present tertiary center outpatient cohort

Improving continuity of patient care across sectors: study protocol of a quasi-experimental multi-centre study regarding an admission and discharge model in Germany (VESPEERA)

Background: Hospitalisations are a critical event in the care process. Insufficient communication and uncoordinated follow-up care often impede the recovery process of the patient resulting in a high number of rehospitalisations and increased health care costs. The overall aim of this study is the development, implementation and evaluation of a structured programme (VESPEERA) to improve the admission and discharge process. Methods: We will conduct an open quasi-experimental multi-centre study with four intervention arms. A cohort selected from insurance claims data will serve as a control group reflecting usual care. The intervention will be implemented in 25 hospital departments and 115 general practices in 9 districts in Baden-Wurttemberg. Eligibility criteria for patients are: age &gt; 18 years, hospital admission or hospitalisation, insurance at the sickness fund “AOK Baden-Wurttemberg”, enrolment in general practice-centred care contract. Each study arm will receive different intervention components based on the point of study enrolment and the patient’s medical need. The interventions comprise a) a structured assessment in the general practice prior to admission resulting in an admission letter b) a discharge conversation by phone between hospital and general practice, c) a structured assessment and care plan post-discharge and d) telephone monitoring for patients with a high risk of rehospitalisation. The assessments are supported by a software tool (“CareCockpit”), originally developed for structured case management programmes. The primary outcome (rehospitalisation due to the same indication within 90 days) and a range of secondary outcomes (rehospitalisation due to the same indication within 30 days; hospitalisations due to ambulatory care-sensitive conditions; delayed prescription of medication and medical products/ devices and referral to other health practitioner/s after discharge; utilisation of emergency or rescue services within 3 months; average care cost per year and patient participating in the VESPEERA programme) and quality indicators will be determined based on insurance claims data and CareCockpit data. Additionally, a patient survey on satisfaction with cross-sectoral care and health related quality of life will be conducted. Discussion: Based on the results, area-wide implementation in usual care is well sought. This study will contribute to an improvement of cross-sectoral care during the admission and discharge process. Trial registration: DRKS00014294 on DRKS / Universal Trial Number (UTN): U1111–1210-9657, Date of registration 12/06/2018