Individual participant data meta-analysis to examine interactions between treatment effect and participant-level covariates: statistical recommendations for conduct and planning

Precision medicine research often searches for treatment‐covariate interactions, which refers to when a treatment effect (eg, measured as a mean difference, odds ratio, hazard ratio) changes across values of a participant‐level covariate (eg, age, gender, biomarker). Single trials do not usually have sufficient power to detect genuine treatment‐covariate interactions, which motivate the sharing of individual participant data (IPD) from multiple trials for meta‐analysis. Here, we provide statistical recommendations for conducting and planning an IPD meta‐analysis of randomized trials to examine treatment‐covariate interactions. For conduct, two‐stage and one‐stage statistical models are described, and we recommend: (i) interactions should be estimated directly, and not by calculating differences in meta‐analysis results for subgroups; (ii) interaction estimates should be based solely on within‐study information; (iii) continuous covariates and outcomes should be analyzed on their continuous scale; (iv) nonlinear relationships should be examined for continuous covariates, using a multivariate meta‐analysis of the trend (eg, using restricted cubic spline functions); and (v) translation of interactions into clinical practice is nontrivial, requiring individualized treatment effect prediction. For planning, we describe first why the decision to initiate an IPD meta‐analysis project should not be based on between‐study heterogeneity in the overall treatment effect; and second, how to calculate the power of a potential IPD meta‐analysis project in advance of IPD collection, conditional on characteristics (eg, number of participants, standard deviation of covariates) of the trials (potentially) promising their IPD. Real IPD meta‐analysis projects are used for illustration throughout

Real-time imputation of missing predictor values in clinical practice

Use of prediction models is widely recommended by clinical guidelines, but usually requires complete information on all predictors that is not always available in daily practice. We describe two methods for real-time handling of missing predictor values when using prediction models in practice. We compare the widely used method of mean imputation (M-imp) to a method that personalizes the imputations by taking advantage of the observed patient characteristics. These characteristics may include both prediction model variables and other characteristics (auxiliary variables). The method was implemented using imputation from a joint multivariate normal model of the patient characteristics (joint modeling imputation; JMI). Data from two different cardiovascular cohorts with cardiovascular predictors and outcome were used to evaluate the real-time imputation methods. We quantified the prediction model's overall performance (mean squared error (MSE) of linear predictor), discrimination (c-index), calibration (intercept and slope) and net benefit (decision curve analysis). When compared with mean imputation, JMI substantially improved the MSE (0.10 vs. 0.13), c-index (0.70 vs 0.68) and calibration (calibration-in-the-large: 0.04 vs. 0.06; calibration slope: 1.01 vs. 0.92), especially when incorporating auxiliary variables. When the imputation method was based on an external cohort, calibration deteriorated, but discrimination remained similar. We recommend JMI with auxiliary variables for real-time imputation of missing values, and to update imputation models when implementing them in new settings or (sub)populations.Comment: 17 pages, 6 figures, to be published in European Heart Journal - Digital Health, accepted for MEMTAB 2020 conferenc

Planetary Migration and Extrasolar Planets in the 2/1 Mean-Motion Resonance

We analyze the possible relationship between the current orbital elements fits of known exoplanets in the 2/1 mean-motion resonance and the expected orbital configuration due to migration. It is found that, as long as the orbital decay was sufficiently slow to be approximated by an adiabatic process, all captured planets should be in apsidal corotations. In other words, they should show a simultaneous libration of both the resonant angle and the difference in longitudes of pericenter. We present a complete set of corotational solutions for the 2/1 commensurability, including previously known solutions and new results. Comparisons with observed exoplanets show that current orbital fits of three known planetary systems in this resonance are either consistent with apsidal corotations (GJ876 and HD82943) or correspond to bodies with uncertain orbits (HD160691). Finally, we discuss the applicability of these results as a test for the planetary migration hypothesis itself. If all future systems in this commensurability are found to be consistent with corotational solutions, then resonance capture of these bodies through planetary migration is a working hypothesis. Conversely, If any planetary pair is found in a different configuration, then either migration did not occur for those bodies, or it took a different form than currently believed.Comment: Submitted to MNRA

CD73 (ecto‐5′‐nucleotidase) hepatocyte levels differ across mouse strains and contribute to mallory‐denk body formation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100334/1/hep26525.pd

Child abuse inventory at emergency rooms: CHAIN-ER rationale and design

<p>Abstract</p> <p>Background</p> <p>Child abuse and neglect is an important international health problem with unacceptable levels of morbidity and mortality. Although maltreatment as a cause of injury is estimated to be only 1% or less of the injured children attending the emergency room, the consequences of both missed child abuse cases and wrong suspicions are substantial. Therefore, the accuracy of ongoing detection at emergency rooms by health care professionals is highly important. Internationally, several diagnostic instruments or strategies for child abuse detection are used at emergency rooms, but their diagnostic value is still unknown. The aim of the study 'Child Abuse Inventory at Emergency Rooms' (CHAIN-ER) is to assess if active structured inquiry by emergency room staff can accurately detect physical maltreatment in children presenting at emergency rooms with physical injury.</p> <p>Methods/design</p> <p>CHAIN-ER is a multi-centre, cross-sectional study with 6 months diagnostic follow-up. Five thousand children aged 0-7 presenting with injury at an emergency room will be included. The index test - the SPUTOVAMO-R questionnaire- is to be tested for its diagnostic value against the decision of an expert panel. All SPUTOVAMO-R positives and a 15% random sample of the SPUTOVAMO-R negatives will undergo the same systematic diagnostic work up, which consists of an adequate history being taken by a pediatrician, inquiry with other health care providers by structured questionnaires in order to obtain child abuse predictors, and by additional follow-up information. Eventually, an expert panel (reference test) determines the <it>true </it>presence or absence of child abuse.</p> <p>Discussion</p> <p>CHAIN-ER will determine both positive and negative predictive value of a child abuse detection instrument used in the emergency room. We mention a benefit of the use of an expert panel and of the use of complete data. Conducting a diagnostic accuracy study on a child abuse detection instrument is also accompanied by scientific hurdles, such as the lack of an accepted reference standard and potential (non-) response. Notwithstanding these scientific challenges, CHAIN-ER will provide accurate data on the predictive value of SPUTOVAMO-R.</p

Predictie van functionele achteruitgang bij ambulante geriatrische patiënten op de spoedgevallendienst

Doel Het doel van deze studie is de predictieve validiteit te onderzoeken van vijf screeningsinstrumenten in het voorspellen van functionele achteruitgang bij ouderen die ambulant verzorgd werden op een spoedgevallendienst. Methode Bij 83 ouderen die ambulant op de spoedgevallendienst van UZ Leuven werden verzorgd, werden de Identification of Seniors at Risk (ISAR), Triage Risk Screening Tool (TRST), de vragenlijst van Runciman, de vragenlijst van Rowland en de Voorlopige Indicator voor Plaatsing (VIP) afgenomen. De functionele status 14 dagen voor opname, bij opname, en 14, 30 en 90 dagen na ontslag werd in kaart gebracht met behulp van de Katz schaal. Resultaten De screeningsinstrumenten met de beste verhouding tussen de sensitiviteit en negatief predictieve waarde 14 dagen na ontslag zijn de vragenlijst van Rowland en de ISAR. Dertig en negentig dagen na ontslag is dit de ISAR. Conclusie Uit dit onderzoek blijkt dat, in aanmerking genomen dat voor een screeningsinstrument de sensitiviteit en negatief predictieve waarde de belangrijkste parameters zijn, de ISAR het meest geschikte instrument is om functionele achteruitgang bij ouderen na een ambulante verzorging op de spoedgevallendienst te voorspellen. De ISAR is eenvoudig in het verpleegdossier te integreren en kan standaard bij elke patiënt op de spoedgevallendienst afgenomen worden

The AppNL-G-F mouse retina is a site for preclinical Alzheimer's disease diagnosis and research

In this study, we report the results of a comprehensive phenotyping of the retina of the AppNL-G-F mouse. We demonstrate that soluble Aβ accumulation is present in the retina of these mice early in life and progresses to Aβ plaque formation by midlife. This rising Aβ burden coincides with local microglia reactivity, astrogliosis, and abnormalities in retinal vein morphology. Electrophysiological recordings revealed signs of neuronal dysfunction yet no overt neurodegeneration was observed and visual performance outcomes were unafected in the AppNL-G-F mouse. Furthermore, we show that hyperspectral imaging can be used to quantify retinal Aβ, underscoring its potential as a biomarker for AD diagnosis and monitoring. These fndings suggest that the AppNL-G-F retina mimics the early, preclinical stages of AD, and, together with retinal imaging techniques, ofers unique opportunities for drug discovery and fundamental research into preclinical AD