Modeling of Locally Scaled Spatial Point Processes, and Applications in Image Analysis

Spatial point processes provide a statistical framework for modeling random arrangements of objects, which is of relevance in a variety of scientific disciplines, including ecology, spatial epidemiology and material science. Describing systematic spatial variations within this framework and developing methods for estimating parameters from empirical data constitute an active area of research. Image analysis, in particular, provides a range of scenarios to which point process models are applicable. Typical examples are images of trees in remote sensing, cells in biology, or composite structures in material science. Due to its real-world orientation and versatility, the class of the recently developed locally scaled point processes appears particularly suitable for the modeling of spatial object patterns. An unknown normalizing constant in the likelihood, however, makes inference complicated and requires elaborate techniques. This work presents an efficient Bayesian inference concept for locally scaled point processes. The suggested optimization procedure is applied to images of cross-sections through the stems of maize plants, where the goal is to accurately describe and classify different genotypes based on the spatial arrangement of their vascular bundles. A further spatial point process framework is specifically provided for the estimation of shape from texture. Texture learning and the estimation of surface orientation are two important tasks in pattern analysis and computer vision. Given the image of a scene in three-dimensional space, a frequent goal is to derive global geometrical knowledge, e.g. information on camera positioning and angle, from the local textural characteristics in the image. The statistical framework proposed comprises locally scaled point process strategies as well as the draft of a Bayesian marked point process model for inferring shape from texture

Rheumatoid arthritis patients treated in trial and real world settings: comparison of randomized trials with registries.

Objective To investigate whether patients with RA enrolled in randomized controlled trials (RCTs) and observational studies may differ in terms of characteristics that could modify treatment effects, leading to an efficacy-effectiveness gap. Methods We conducted systematic literature reviews to identify RCTs and observational studies with RA, treated with rituximab, tocilizumab or etanercept. We extracted baseline characteristics and compared the data of RCTs and observational studies using fixed-effects meta-analyses for the RCTs and random-effects meta-analyses for the observational studies. We also assessed whether the baseline characteristics changed over time. Results Compared with patients enrolled in RCTs, those from observational studies were on average 3.0 years older (P < 0.001), suffered from RA for 3.1 years longer (P < 0.001), had 1.6 more prior disease modifying drugs (P = 0.001), and had a lower DAS-28 (difference -0.6, P < 0.001). CRP and ESR levels were slightly higher in RCTs. The HAQ-Disability Index (HAQ-DI) score was slightly lower in the RCT group. No differences were found in the percentages of included females or RF positivity. Over time, we found a significant decrease of - 0.08 in DAS-28 and a decrease of - 0.04 in HAQ-DI both in patients in RCTs and in patients from registries. Furthermore, ESR and CRP declined over time in RCT patients, but not in patients participating in observational studies. Conclusion There are substantial systematic differences in patient characteristics between RCTs and registries in RA. The efficacy seen in RCTs may not reflect real-world effectiveness

DS_10.1177_0272989X18775975 – Supplemental material for Prediction of Real-World Drug Effectiveness Prelaunch: Case Study in Rheumatoid Arthritis

<p>Supplemental material, DS_10.1177_0272989X18775975 for Prediction of Real-World Drug Effectiveness Prelaunch: Case Study in Rheumatoid Arthritis by Eva-Maria Didden, Yann Ruffieux, Noemi Hummel, Orestis Efthimiou, Stephan Reichenbach, Sandro Gsteiger, Axel Finckh, Christine Fletcher, Georgia Salanti and Matthias Egger in Medical Decision Making</p

Electronic health records (EHRs) in clinical research and platform trials:Application of the innovative EHR-based methods developed by EU-PEARL

Objective: Electronic Health Record (EHR) systems are digital platforms in clinical practice used to collect patients’ clinical information related to their health status and represents a useful storage of real-world data. EHRs have a potential role in research studies, in particular, in platform trials. Platform trials are innovative trial designs including multiple trial arms (conducted simultaneously and/or sequentially) on different treatments under a single master protocol. However, the use of EHRs in research comes with important challenges such as incompleteness of records and the need to translate trial eligibility criteria into interoperable queries. In this paper, we aim to review and to describe our proposed innovative methods to tackle some of the most important challenges identified. This work is part of the Innovative Medicines Initiative (IMI) EU Patient-cEntric clinicAl tRial pLatforms (EU-PEARL) project's work package 3 (WP3), whose objective is to deliver tools and guidance for EHR-based protocol feasibility assessment, clinical site selection, and patient pre-screening in platform trials, investing in the building of a data-driven clinical network framework that can execute these complex innovative designs for which feasibility assessments are critically important. Methods: ISO standards and relevant references informed a readiness survey, producing 354 criteria with corresponding questions selected and harmonised through a 7-round scoring process (0–1) in stakeholder meetings, with 85% of consensus being the threshold of acceptance for a criterium/question. ATLAS cohort definition and Cohort Diagnostics were mainly used to create the trial feasibility eligibility (I/E) criteria as executable interoperable queries. Results: The WP3/EU-PEARL group developed a readiness survey (eSurvey) for an efficient selection of clinical sites with suitable EHRs, consisting of yes-or-no questions, and a set-up of interoperable proxy queries using physicians’ defined trial criteria. Both actions facilitate recruiting trial participants and alignment between study costs/timelines and data-driven recruitment potential.Conclusion: The eSurvey will help create an archive of clinical sites with mature EHR systems suitable to participate in clinical trials/platform trials, and the interoperable proxy queries of trial eligibility criteria will help identify the number of potential participants. Ultimately, these tools will contribute to the production of EHR-based protocol design.</p

Current state-of-the-art and gaps in platform trials: 10 things you should know, insights from EU-PEARL

Summary: Platform trials bring the promise of making clinical research more efficient and more patient centric. While their use has become more widespread, including their prominent role during the COVID-19 pandemic response, broader adoption of platform trials has been limited by the lack of experience and tools to navigate the critical upfront planning required to launch such collaborative studies. The European Union-Patient-cEntric clinicAl tRial pLatform (EU-PEARL) initiative has produced new methodologies to expand the use of platform trials with an overarching infrastructure and services embedded into Integrated Research Platforms (IRPs), in collaboration with patient representatives and through consultation with U.S. Food and Drug Administration and European Medicines Agency stakeholders. In this narrative review, we discuss the outlook for platform trials in Europe, including challenges related to infrastructure, design, adaptations, data sharing and regulation. Documents derived from the EU-PEARL project, alongside a literature search including PubMed and relevant grey literature (e.g., guidance from regulatory agencies and health technology agencies) were used as sources for a multi-stage collaborative process through which the 10 more important points based on lessons drawn from the EU-PEARL project were developed and summarised as guidance for the setup of platform trials. We conclude that early involvement of critical stakeholder such as regulatory agencies or patients are critical steps in the implementation and later acceptance of platform trials. Addressing these gaps will be critical for attaining the full potential of platform trials for patients. Funding: Innovative Medicines Initiative 2 Joint Undertaking with support from the European Union’s Horizon 2020 research and innovation programme and EFPIA