Assurance methods for designing a clinical trial with a delayed treatment effect.

An assurance calculation is a Bayesian alternative to a power calculation. One may be performed to aid the planning of a clinical trial, specifically setting the sample size or to support decisions about whether or not to perform a study. Immuno-oncology is a rapidly evolving area in the development of anticancer drugs.

Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds.

Models of electrical excitation and recovery in the heart have become increasingly detailed, but have yet to be used routinely in the clinical setting to guide personalized intervention in patients. One of the main challenges is calibrating models from the limited measurements that can be made in a patient during a standard clinical procedure. In this work, we propose a novel framework for the probabilistic calibration of electrophysiology parameters on the left atrium of the heart using local measurements of cardiac excitability.

Corrigendum: Bayesian Calibration of Electrophysiology Models Using Restitution Curve Emulators.

[This corrects the article DOI: 10.3389/fphys.2021.

Bayesian Calibration of Electrophysiology Models Using Restitution Curve Emulators.

Calibration of cardiac electrophysiology models is a fundamental aspect of model personalization for predicting the outcomes of cardiac therapies, simulation testing of device performance for a range of phenotypes, and for fundamental research into cardiac function. Restitution curves provide information on tissue function and can be measured using clinically feasible measurement protocols. We introduce novel "restitution curve emulators" as probabilistic models for performing model exploration, sensitivity analysis, and Bayesian calibration to noisy data.

Response (minimum clinically relevant change) in ASD symptoms after an intervention according to CARS-2: consensus from an expert elicitation procedure.

The lack of consensual measures to monitor core change in Autism Spectrum Disorder (ASD) or response to interventions leads to difficulty to prove intervention efficacy on ASD core symptoms. There are no universally accepted outcome measures developed for measuring changes in core symptoms. However, the CARS (Childhood Autism Rating Scale) is one of the outcomes recommended in the EMA Guideline on the clinical development of medicinal products for the treatment of ASD.

Short to long term outcomes of 154 cemented total hip arthroplasties in ankylosing spondylitis.

Background: Long-term outcome of Total Hip arthroplasty (THA) in Ankylosing Spondylitis (AS) remains unreported. Literature suggests a higher overall failure rate in ankylosing spondylitis as compared to osteoarthritis. Concern has been expressed regarding joint survival, given that recipients are generally young.

Assurance for clinical trial design with normally distributed outcomes: Eliciting uncertainty about variances.

The assurance method is growing in popularity in clinical trial planning. The method involves eliciting a prior distribution for the treatment effect, and then calculating the probability that a proposed trial will produce a "successful" outcome. For normally distributed observations, uncertainty about the variance of the normal distribution also needs to be accounted for, but there is little guidance in the literature on how to elicit a distribution for a variance parameter.

Gaussian process manifold interpolation for probabilistic atrial activation maps and uncertain conduction velocity.

In patients with atrial fibrillation, local activation time (LAT) maps are routinely used for characterizing patient pathophysiology. The gradient of LAT maps can be used to calculate conduction velocity (CV), which directly relates to material conductivity and may provide an important measure of atrial substrate properties. Including uncertainty in CV calculations would help with interpreting the reliability of these measurements.

Interventions to reduce the risk of surgically transmitted Creutzfeldt-Jakob disease: a cost-effective modelling review.

Background: Creutzfeldt-Jakob disease is a fatal neurological disease caused by abnormal infectious proteins called prions. Prions that are present on surgical instruments cannot be completely deactivated; therefore, patients who are subsequently operated on using these instruments may become infected. This can result in surgically transmitted Creutzfeldt-Jakob disease.

Quantifying atrial anatomy uncertainty from clinical data and its impact on electro-physiology simulation predictions.

Patient-specific computational models of structure and function are increasingly being used to diagnose disease and predict how a patient will respond to therapy. Models of anatomy are often derived after segmentation of clinical images or from mapping systems which are affected by image artefacts, resolution and contrast. Quantifying the impact of uncertain anatomy on model predictions is important, as models are increasingly used in clinical practice where decisions need to be made regardless of image quality.

Probabilistic Interpolation of Uncertain Local Activation Times on Human Atrial Manifolds.

Objective: Local activation time (LAT) mapping of the atria is important for targeted treatment of atrial arrhythmias, but current methods do not interpolate on the atrial manifold and neglect uncertainties associated with LAT observations. In this paper, we describe novel methods to, first, quantify uncertainties in LAT arising from bipolar electrogram analysis and assignment of electrode recordings to the anatomical mesh, second, interpolate uncertain LAT measurements directly on left atrial manifolds to obtain complete probabilistic activation maps, and finally, interpolate LAT jointly across both the manifold and different S1-S2 pacing protocols.

Methods: A modified center of mass approach was used to process bipolar electrograms, yielding a LAT estimate and error distribution from the electrogram morphology.

Choice of time horizon critical in estimating costs and effects of changes to HIV programmes.

Background: Uganda changed its antiretroviral therapy guidelines in 2014, increasing the CD4 threshold for antiretroviral therapy initiation from 350 cells/μl to 500 cells/μl. We investigate what effect this change in policy is likely to have on HIV incidence, morbidity, and programme costs, and estimate the cost-effectiveness of the change over different time horizons.

Methods: We used a complex individual-based model of HIV transmission and antiretroviral therapy scale-up in Uganda.

Incorporating Genuine Prior Information about Between-Study Heterogeneity in Random Effects Pairwise and Network Meta-analyses.

Background: Pairwise and network meta-analyses using fixed effect and random effects models are commonly applied to synthesize evidence from randomized controlled trials. The models differ in their assumptions and the interpretation of the results. The model choice depends on the objective of the analysis and knowledge of the included studies.

Improving ART programme retention and viral suppression are key to maximising impact of treatment as prevention - a modelling study.

Background: UNAIDS calls for fewer than 500,000 new HIV infections/year by 2020, with treatment-as-prevention being a key part of their strategy for achieving the target. A better understanding of the contribution to transmission of people at different stages of the care pathway can help focus intervention services at populations where they may have the greatest effect. We investigate this using Uganda as a case study.

Universal test, treat, and keep: improving ART retention is key in cost-effective HIV control in Uganda.

Background: With ambitious new UNAIDS targets to end AIDS by 2030, and new WHO treatment guidelines, there is increased interest in the best way to scale-up ART coverage. We investigate the cost-effectiveness of various ART scale-up options in Uganda.

Methods: Individual-based HIV/ART model of Uganda, calibrated using history matching.

Estimating the Expected Value of Sample Information Using the Probabilistic Sensitivity Analysis Sample: A Fast, Nonparametric Regression-Based Method.

Health economic decision-analytic models are used to estimate the expected net benefits of competing decision options. The true values of the input parameters of such models are rarely known with certainty, and it is often useful to quantify the value to the decision maker of reducing uncertainty through collecting new data. In the context of a particular decision problem, the value of a proposed research design can be quantified by its expected value of sample information (EVSI).

Bayesian history matching of complex infectious disease models using emulation: a tutorial and a case study on HIV in Uganda.

Advances in scientific computing have allowed the development of complex models that are being routinely applied to problems in disease epidemiology, public health and decision making. The utility of these models depends in part on how well they can reproduce empirical data. However, fitting such models to real world data is greatly hindered both by large numbers of input and output parameters, and by long run times, such that many modelling studies lack a formal calibration methodology.

Estimating multiparameter partial expected value of perfect information from a probabilistic sensitivity analysis sample: a nonparametric regression approach.

The partial expected value of perfect information (EVPI) quantifies the expected benefit of learning the values of uncertain parameters in a decision model. Partial EVPI is commonly estimated via a 2-level Monte Carlo procedure in which parameters of interest are sampled in an outer loop, and then conditional on these, the remaining parameters are sampled in an inner loop. This is computationally demanding and may be difficult if correlation between input parameters results in conditional distributions that are hard to sample from.

Assurance calculations for planning clinical trials with time-to-event outcomes.

We consider the use of the assurance method in clinical trial planning. In the assurance method, which is an alternative to a power calculation, we calculate the probability of a clinical trial resulting in a successful outcome, via eliciting a prior probability distribution about the relevant treatment effect. This is typically a hybrid Bayesian-frequentist procedure, in that it is usually assumed that the trial data will be analysed using a frequentist hypothesis test, so that the prior distribution is only used to calculate the probability of observing the desired outcome in the frequentist test.

An efficient method for computing single-parameter partial expected value of perfect information.

The value of learning an uncertain input in a decision model can be quantified by its partial expected value of perfect information (EVPI). This is commonly estimated via a 2-level nested Monte Carlo procedure in which the parameter of interest is sampled in an outer loop, and then conditional on this sampled value, the remaining parameters are sampled in an inner loop. This 2-level method can be difficult to implement if the joint distribution of the inner-loop parameters conditional on the parameter of interest is not easy to sample from.

Modern management of patellar instability.

Recurrent patellofemoral instability is a disabling condition, attributed to a variety of anatomical aetiologies. Trochlear dysplasia, patella alta, an increased tibial tubercle trochlear groove distance of greater than 20 mm and soft tissue abnormalities such as a torn medial patellofemoral ligament and inadequate vastus medialis obliquus are all factors to be considered. Management of this condition remains difficult and controversial and knowledge of the functional anatomy and biomechanics of the patellofemoral joint, a detailed history and clinical examination, and an accurate patient assessment are all imperative to formulate an appropriate management plan.

Avulsion fracture of the medial malleolus following posterior tibialis tendon dislocation: a case report.

Dislocation of the posterior tibialis tendon as an isolated injury is rare. The diagnosis is often delayed due to its rarity and the need for various second line imaging modalities. We present a case of a dislocated posterior tibialis tendon that resulted in an avulsion type fracture of the medial malleolus.

Bayesian inference for comorbid disease risks using marginal disease risks and correlation information from a separate source.

Background: Public health interventions are increasingly being evaluated for their cost-effectiveness. Such interventions act 'upstream' on the determinants of ill health and commonly reduce the incidence of several diseases. Diseases that share determinants are usually correlated at an individual level, which we observe as comorbidity.

Tenosynovial osteochondromatosis of the flexor hallucis longus tendon.

We present a case of tenosynovial osteochondromatosis affecting the flexor hallucis longus tendon in a 29-year-old male with chronic ankle pain. Clinical examination was normal. Plain radiographs and MRI revealed multiple calcified lesions.