Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees

Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.Article / Letter to editorInstituut Psychologi

The expanding bipolar shell of the helium nova V445 Puppis

From multi-epoch adaptive optics imaging and integral field unit spectroscopy, we report the discovery of an expanding and narrowly confined bipolar shell surrounding the helium nova V445 Puppis (Nova Puppis 2000). An equatorial dust disc obscures the nova remnant, and the outflow is characterized by a large polar outflow velocity of 6720 +/- 650 km s(-1) and knots moving at even larger velocities of 8450 +/- 570 km s(-1). We derive an expansion parallax distance of 8.2 +/- 0.5 kpc and deduce a pre-outburst luminosity of the underlying binary of log L/L-circle dot = 4.34 +/- 0.36. The derived luminosity suggests that V445 Puppis probably contains a massive white dwarf accreting at high rate from a helium star companion making it part of a population of binary stars that potentially lead to supernova Ia explosions due to accumulation of helium-rich material on the surface of a massive white dwarf

Administration of drinking water supplement containing organic acids and medium chain fatty acids to sows significantly reduced incidence of Clostridium-associated diarrhoea in neonatal piglets: a case study

Neonatal diarrhoea in newborn piglets is an important problem in pig production that is frequently diagnosed as being the result of Clostridium perfringens infections. During parturition and in the first hours of life, the sow transmits the pathogen to its offspring. The objective of this study was to examine the possible prophylactic effect of a drinking water supplement containing organic acids and medium chain fatty acids (Selko-4-Health©), administered to sows on prevalence of neonatal diarrhoea in piglets during early lactation. The study was carried out at a farm with 1300 sows with a high incidence of neonatal diarrhoea. Gestating sows received the water supplement (0.1% per litre) daily from day 35 to end of gestation and during the lactation phase for 2 days a week

Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees

Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.Multivariate analysis of psychological dat

The coronal line regions of planetary nebulae NGC6302 and NGC6537: 3-13um grating and echelle spectroscopy

We report on advances in the study of the cores of NGC6302 and NGC6537 using infrared grating and echelle spectroscopy. In NGC6302, emission lines from species spanning a large range of ionization potential, and in particular [SiIX]3.934um, are interpreted using photoionization models (including CLOUDY), which allow us to reestimate the central star's temperature to be about 250000K. All of the detected lines are consistent with this value, except for [AlV] and [AlVI]. Aluminium is found to be depleted to one hundredth of the solar abundance, which provides further evidence for some dust being mixed with the highly ionized gas (with photons harder than 154eV). A similar depletion pattern is observed in NGC6537. Echelle spectroscopy of IR coronal ions in NGC6302 reveals a stratified structure in ionization potential, which confirms photoionization to be the dominant ionization mechanism. The lines are narrow (< 22km/s FWHM), with no evidence of the broad wings found in optical lines from species with similar ionization potentials, such as [NeV]3426A. We note the absence of a hot bubble, or a wind blown bipolar cavity filled with a hot plasma, at least on 1'' and 10km/s scales. We also provide accurate new wavelengths for several of the infrared coronal lines observed with the echelle.Comment: Accepted for publication in MNRA

Biliary effects of liraglutide and sitagliptin, a 12-week randomized placebo-controlled trial in type 2 diabetes patients

Aims: Treatment with glucagon-like peptide (GLP)-1 receptor agonists or dipeptidyl peptidase (DPP)-4 inhibitors might increase gallstone formation; however, the mechanisms involved are unknown. We aimed to assess the effects of these drugs on gallbladder volume and bile acid profile. Materials and methods: A total of 57 type 2 diabetes patients (mean±SD age, 62.8±6.9years; BMI, 31.8±4.1kg/m2; HbA1c, 7.3%±0.6%), treated with metformin and/or sulfonylureas, were included in this 12-week randomized, placebo-controlled, double-blind, single-centre trial between July 2013 and August 2015 at the VU University Medical Center, the Netherlands. Patients received the GLP-1 receptor agonist liraglutide, the DPP-4 inhibitor sitagliptin or matching placebo for 12weeks. Gallbladder fasting volume and ejection fraction were measured using ultrasonography after a high-fat meal. Serum bile acids were measured in the fasting and postprandial state and in faecal samples. The trial was registered at ClinicalTrials.gov (NCT01744236). Results: Neither liraglutide nor sitagliptin had an effect on gallbladder fast

Acute renal effects of the GLP-1 receptor agonist exenatide in overweight type 2 diabetes patients: a randomised, double-blind, placebo-controlled trial

Aims/hypothesis: This study aimed to investigate the acute renal effects of the glucagon-like peptide-1 receptor agonist (GLP-1RA) exenatide in type 2 diabetes patients. Methods: We included overweight (BMI 25–40 kg/m2) men and postmenopausal women, aged 35–75 years with type 2 diabetes (HbA1c 48–75 mmol/mol; 6.5–9.0%) and estimated GFR ≥ 60 ml min−1 1.73 m−2. Exenatide or placebo (NaCl solution, 154 mmol/l) was administrated intravenously in an acute, randomised, double-blind, placebo-controlled trial conducted at the Diabetes Center VU University Medical Center (VUMC). GFR (primary endpoint) and effective renal plasma flow (ERPF) were determined by inulin and para-aminohippurate clearance, respectively, based on timed urine sampling. Filtration fraction (FF) and effective renal vascular resistance (ERVR) were calculated, and glomerular hydrostatic pressure (PGLO) and vascular resistance of the afferent (RA) and efferent (RE) renal arteriole were estimated. Tubular function was assessed by absolute and fractional excretion of sodium (FENa), potassium (FEK) and urea (FEU), in addition to urine osmolality, pH and free water clearance. Renal damage markers, BP and plasma glucose were also determined. Results: Of the 57 patients randomised by computer, 52 were included in the final analyses. Exenatide (n = 24) did not affect GFR (mean difference +2 ± 3 ml min−1 1.73 m−2, p = 0.489), ERPF, FF, ERVR or PGLO, compared with placebo (n = 28). Exenatide increased RA (p < 0.05), but did not change RE. Exenatide increased FENa, FEK, urine osmolality and pH, while FEU, urinary flow and free water clearance were decreased (all p < 0.05). Osmolar clearance and renal damage makers were not affected. Diastolic BP and mean arterial pressure increased by 3 ± 1 and 6 ± 2 mmHg, respectively, whereas plasma glucose decreased by 1.4 ± 0.1 mmol/l (all p < 0.05). Conclusions/interpretation: Exenatide infusion does not acutely affect renal haemodynamics in overweight type 2 diabetes patients at normal filtration levels. Furthermore, acute GLP-1RA administration increases proximal sodium excretion in these patients. Trial registration: ClincialTrials.gov NCT01744236 Funding: The research leading to these results has been funded from: (1) the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement number 282521 – the SAFEGUARD project; and (2) the Dutch Kidney Foundation, under grant agreement IP12.87