Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Health Analytics.

Background: Data from multiple organizations are crucial for advancing learning health systems. However, ethical, legal, and social concerns may restrict the use of standard statistical methods that rely on pooling data. Although distributed algorithms offer alternatives, they may not always be suitable for health frameworks.

How to optimize and evaluate diversity in gynecologic cancer clinical trials: statements from the GCIG Barcelona Meeting.

Findings from clinical trials have led to advancement of care for patients with gynecologic malignancies. However, restrictive inclusion of patients into trials has been widely criticized for inadequate representation of the real-world population. Ideally, patients enrolled in clinical trials should represent a broader population to enhance external validity and facilitate translation of outcomes across all relevant groups.

From Treatment to Recovery: Gynecological Survivors' and Caregivers' Perspectives About the Usability of an Educational Resource.

The objective of this study was to understand gynecological cancer (GC) survivors' and their informal caregivers' perceptions about the usability of an educational resource to support their transition from primary cancer treatment into surveillance and/or recovery. After developing an empirical- and experiential-informed educational resource, we used a semi-structured questioning process to understand GC survivors and their caregivers' perceptions about its usability. Data were collected via online focus groups or 1:1 interviews that were audio recorded and transcribed.

Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Health Analytics.

Background: Data from multiple organizations are crucial for advancing learning health systems. However, ethical, legal, and social concerns may restrict the use of standard statistical methods that rely on pooling data. Although distributed algorithms offer alternatives, they may not always be suitable for health frameworks.

Predicting polymer solubility from phase diagrams to compatibility: a perspective on challenges and opportunities.

Polymer processing, purification, and self-assembly have significant roles in the design of polymeric materials. Understanding how polymers behave in solution (, their solubility, chemical properties, ) can improve our control over material properties their processing-structure-property relationships. For many decades the polymer science community has relied on thermodynamic and physics-based models to aid in this endeavor, but all rely on disparate data sets and use-case scenarios.

Rearing density and food variety impact growth, development, and survival of larvae in the declining amphibian, Pseudacris maculata.

Boreal chorus frogs (Pseudacris maculata Agassiz 1850) are a widespread amphibian in North America, but several populations are in decline. Specifically, we are developing captive breeding and reintroduction methods for the Great Lakes/St. Lawrence-Canadian Shield population.

Building ontology-based temporal databases for data reuse: An applied example on hospital organizational structures.

Keeping track of data semantics and data changes in the databases is essential to support retrospective studies and the reproducibility of longitudinal clinical analysis by preventing false conclusions from being drawn from outdated data. A knowledge model combined with a temporal model plays an essential role in organizing the data and improving query expressiveness across time and multiple institutions. This paper presents a modelling framework for temporal relational databases using an ontology to derive a shareable and interoperable data model.

Effect of on-demand vs continuous prescription of proton pump inhibitors on symptom burden and quality of life: results of a real-world randomized controlled trial in primary care patients with gastroesophageal reflux disease.

Objectives: This study aimed to assess the impact of on-demand versus continuous prescribing of proton pump inhibitors (PPIs) on symptom burden and health-related quality of life in patients with gastroesophageal reflux disease (GERD) presenting to primary care.

Methods: Thirty-six primary care centres across Europe enrolled adult GERD patients from electronic health records. Participants were randomised to on-demand or continuous PPI prescriptions and were followed for 8 weeks.

Real-world outcomes associated with bevacizumab combined with chemotherapy in platinum-resistant ovarian Cancer.

Objectives: The addition of bevacizumab to chemotherapy for platinum-resistant (PL-R) ovarian cancer (OC) improved progression-free (PFS) but not overall survival (OS) in clinical trials. We explored real-world outcomes in Ontario, Canada, and compared survival in the pre- and post-bevacizumab era.

Methods: Administrative databases were utilized to identify all patients treated with bevacizumab for PL-R OC.

NRF2 Deficiency Attenuates Diabetic Kidney Disease in Db/Db Mice via Down-Regulation of Angiotensinogen, SGLT2, CD36, and FABP4 Expression and Lipid Accumulation in Renal Proximal Tubular Cells.

The role(s) of nuclear factor erythroid 2-related factor 2 (NRF2) in diabetic kidney disease (DKD) is/are controversial. We hypothesized that Nrf2 deficiency in type 2 diabetes (T2D) db/db mice (db/db knockout (KO)) attenuates DKD progression through the down-regulation of angiotensinogen (AGT), sodium-glucose cotransporter-2 (SGLT2), scavenger receptor CD36, and fatty -acid-binding protein 4 (FABP4), and lipid accumulation in renal proximal tubular cells (RPTCs). Db/db KO mice were studied at 16 weeks of age.

Continuous flow synthesis of pyridinium salts accelerated by multi-objective Bayesian optimization with active learning.

We report a human-in-the-loop implementation of the multi-objective experimental design a Bayesian optimization platform (EDBO+) towards the optimization of butylpyridinium bromide synthesis under continuous flow conditions. The algorithm simultaneously optimized reaction yield and production rate (or space-time yield) and generated a well defined Pareto front. The versatility of EDBO+ was demonstrated by expanding the reaction space mid-campaign by increasing the upper temperature limit.

Patients' and Members of the Public's Wishes Regarding Transparency in the Context of Secondary Use of Health Data: Scoping Review.

Background: Secondary use of health data has reached unequaled potential to improve health systems governance, knowledge, and clinical care. Transparency regarding this secondary use is frequently cited as necessary to address deficits in trust and conditional support and to increase patient awareness.

Objective: We aimed to review the current published literature to identify different stakeholders' perspectives and recommendations on what information patients and members of the public want to learn about the secondary use of health data for research purposes and how and in which situations.

Real-world outcomes associated with use of front-line bevacizumab in ovarian cancer.

Background: In the pivotal ICON7 study, addition of bevacizumab to front-line treatment of ovarian cancer (OC) significantly improved overall survival (OS) (p = 0.03) in a high-risk subgroup of patients with suboptimally debulked/unresectable stage III or IV disease, leading to approval in Ontario, Canada in March 2016. Here we describe utilization of bevacizumab for front-line, high-risk OC and determine outcomes in routine clinical practice.

CA-125 Early Dynamics to Predict Overall Survival in Women with Newly Diagnosed Advanced Ovarian Cancer Based on Meta-Analysis Data.

(1) Background: Cancer antigen 125 (CA-125) is a protein produced by ovarian cancer cells that is used for patients' monitoring. However, the best ways to analyze its decline and prognostic role are poorly quantified. (2) Methods: We leveraged individual patient data from the Gynecologic Cancer Intergroup (GCIG) meta-analysis (N = 5573) to compare different approaches summarizing the early trajectory of CA-125 before the prediction time (called the landmark time) at 3 or 6 months after treatment initiation in order to predict overall survival.

Clinical outcome and biomarker assessments of a multi-centre phase II trial assessing niraparib with or without dostarlimab in recurrent endometrial carcinoma.

This multi-centre, non-randomized, open-label, phase II trial (NCT03016338), assessed niraparib monotherapy (cohort 1, C1), or niraparib and dostarlimab (cohort 2, C2) in patients with recurrent serous or endometrioid endometrial carcinoma. The primary endpoint was clinical benefit rate (CBR), with ≥5/22 overall considered of interest. Secondary outcomes were safety, objective response rate (ORR), duration of response, progression free survival and overall survival.

State of the Biomarker Science in Ovarian Cancer: A National Cancer Institute Clinical Trials Planning Meeting Report.

Purpose: Despite therapeutic advances in the treatment of ovarian cancer (OC), 5-year survival remains low, and patients eventually die from recurrent, chemotherapy-resistant disease. The National Cancer Gynecologic Cancer Steering Committee identified the integration of scientifically defined subgroups as a top strategic priority in clinical trial planning.

Methods: A group of experts was convened to review the scientific literature in OC to identify validated predictive biomarkers that could inform patient selection and treatment stratification.

Using an Ontology to Derive a Sharable and Interoperable Relational Data Model for Heterogeneous Healthcare Data and Various Applications.

Background: A large volume of heavily fragmented data is generated daily in different healthcare contexts and is stored using various structures with different semantics. This fragmentation and heterogeneity make secondary use of data a challenge. Data integration approaches that derive a common data model from sources or requirements have some advantages.

Deep Learning of Binary Solution Phase Behavior of Polystyrene.

Predicting binary solution phase behavior of polymers has remained a challenge since the early theory of Flory-Huggins, hindering the processing, synthesis, and design of polymeric materials. Herein, we take a complementary data-driven approach by building a machine learning framework to make fast and accurate predictions of polymer solution cloud point temperatures. Using polystyrene, both upper and lower critical solution temperatures are predicted within experimental uncertainty (1-2 °C) with a deep neural network, Gaussian process regression (GPR) model, and a combination of polymer, solvent, and state features.

Neoadjuvant and Adjuvant Systemic Therapy for Newly Diagnosed Stage II-IV Epithelial Ovary, Fallopian Tube, or Primary Peritoneal Carcinoma: A Practice Guideline.

Background: This study aims to provide guidance for the use of neoadjuvant and adjuvant systemic therapy in women with newly diagnosed stage II-IV epithelial ovary, fallopian tube, or primary peritoneal carcinoma.

Methods: EMBASE, MEDLINE, and Cochrane Library were investigated for relevant systematic reviews and phase III trials. Articles focusing on consolidation and maintenance therapies were excluded.

The needs of gynecological cancer survivors at the end of primary treatment: A scoping review and proposed model to guide clinical discussions.

Objective: Gynecological cancer (GC) survivors have unmet needs when they complete primary cancer treatment. Despite this, no known research has summarized these needs and survivors' suggestions to address them. We conducted a scoping review to fill these gaps and develop a model useful to guide clinical discussions and/or interventions.

The Prescription of Drug Ontology 2.0 (PDRO): More Than the Sum of Its Parts.

While drugs and related products have profoundly changed the lives of people around the world, ongoing challenges remain, including inappropriate use of a drug product. Inappropriate uses can be explained in part by ambiguous or incomplete information, for example, missing reasons for treatments, ambiguous information on how to take a medication, or lack of information on medication-related events outside the health care system. In order to fully assess the situation, data from multiple systems (electronic medical records, pharmacy and radiology information systems, laboratory management systems, etc.

Expected clinical utility of automatable prediction models for improving palliative and end-of-life care outcomes: Toward routine decision analysis before implementation.

Objective: The study sought to evaluate the expected clinical utility of automatable prediction models for increasing goals-of-care discussions (GOCDs) among hospitalized patients at the end of life (EOL).

Materials And Methods: We built a decision model from the perspective of clinicians who aim to increase GOCDs at the EOL using an automated alert system. The alternative strategies were 4 prediction models-3 random forest models and the Modified Hospital One-year Mortality Risk model-to generate alerts for patients at a high risk of 1-year mortality.

Life history traits and reproductive ecology of North American chorus frogs of the genus Pseudacris (Hylidae).

Amphibian biodiversity is declining globally, with over 40% of species being considered threatened to become extinct. Crucial to the success of conservation initiatives are a comprehensive understanding of life history and reproductive ecology of target species. Here we provide an overview of the Pseudacris genus, including breeding behaviour, reproduction, development, survival and longevity.

Practice Patterns and Outcomes of Novel Targeted Agents for the Treatment of ERBB2-Positive Metastatic Breast Cancer.

Importance: Clinical trials have shown that the addition of pertuzumab to trastuzumab-based chemotherapy for first-line treatment of ERBB2-positive metastatic breast cancer is associated with considerable improvement in overall survival (OS). In the second-line setting, trastuzumab emtansine (T-DM1) improves OS compared with capecitabine/lapatinib in patients previously treated with trastuzumab-based chemotherapy. However, there are few data describing long-term real-world outcomes with these agents.

Meta-consent for the secondary use of health data within a learning health system: a qualitative study of the public's perspective.

Background: The advent of learning healthcare systems (LHSs) raises an important implementation challenge concerning how to request and manage consent to support secondary use of data in learning cycles, particularly research activities. Current consent models in Quebec were not established with the context of LHSs in mind and do not support the agility and transparency required to obtain consent from all involved, especially the citizens. Therefore, a new approach to consent is needed.