Using Joint Longitudinal and Time-to-Event Models to Improve the Parameterization of Chronic Disease Microsimulation Models: an Application to Cardiovascular Disease.

Background: Chronic disease microsimulation models often simulate disease incidence as a function of risk factors that evolve over time (e.g., blood pressure increasing with age) in order to facilitate decision analyses of different disease screening and prevention strategies.

Cost-Effectiveness of Screening Asymptomatic Carotid Stenosis by Atherosclerotic Cardiovascular Risk.

Importance: Extracranial internal carotid artery stenosis (50-99% arterial narrowing) is an important risk factor for ischemic stroke. Yet, the benefits and harms of targeted screening for asymptomatic carotid artery stenosis (ACAS) have not been assessed in population-based studies.

Objective: To estimate the cost-effectiveness of one-time, targeted ACAS screening stratified by atherosclerotic cardiovascular disease (ASCVD) risk using the American Heart Association's Pooled Cohort Equations.

Screening Strategies to Reduce COVID-19 Mortality in Nursing Homes.

Importance: Nursing home residents continue to bear a disproportionate share of COVID-19 morbidity and mortality, accounting for 9% of all US COVID-19 deaths in 2023, despite comprising only 0.4% of the population.

Objective: To evaluate the cost-effectiveness of screening strategies in reducing COVID-19 mortality in nursing homes.

Integrating decision modeling and machine learning to inform treatment stratification.

There is increasing interest in moving away from "one size fits all (OSFA)" approaches toward stratifying treatment decisions. Understanding how expected effectiveness and cost-effectiveness varies with patient covariates is a key aspect of stratified decision making. Recently proposed machine learning (ML) methods can learn heterogeneity in outcomes without pre-specifying subgroups or functional forms, enabling the construction of decision rules ('policies') that map individual covariates into a treatment decision.

Estimated Transmission Outcomes and Costs of SARS-CoV-2 Diagnostic Testing, Screening, and Surveillance Strategies Among a Simulated Population of Primary School Students.

Importance: In addition to illness, the COVID-19 pandemic has led to historic educational disruptions. In March 2021, the federal government allocated $10 billion for COVID-19 testing in US schools.

Objective: Costs and benefits of COVID-19 testing strategies were evaluated in the context of full-time, in-person kindergarten through eighth grade (K-8) education at different community incidence levels.

Model-Estimated Association Between Simulated US Elementary School-Related SARS-CoV-2 Transmission, Mitigation Interventions, and Vaccine Coverage Across Local Incidence Levels.

Importance: With recent surges in COVID-19 incidence and vaccine authorization for children aged 5 to 11 years, elementary schools face decisions about requirements for masking and other mitigation measures. These decisions require explicit determination of community objectives (eg, acceptable risk level for in-school SARS-CoV-2 transmission) and quantitative estimates of the consequences of changing mitigation measures.

Objective: To estimate the association between adding or removing in-school mitigation measures (eg, masks) and COVID-19 outcomes within an elementary school community at varying student vaccination and local incidence rates.

Model-estimated relationship between elementary school-related SARS-CoV-2 transmission, mitigation interventions, and vaccination coverage across community incidence levels.

Background: While CDC guidance for K-12 schools recommends indoor masking regardless of vaccination status, final decisions about masking in schools will be made at the local and state level. The impact of the removal of mask restrictions, however, on COVID-19 outcomes for elementary students, educators/staff, and their households is not well known.

Methods: We used a previously published agent-based dynamic transmission model of SARS-CoV-2 in K-12 schools to simulate an elementary school with 638 students across 12 scenarios: combinations of three viral infectiousness levels (reflecting wild-type virus, alpha variant, and delta variant) and four student vaccination levels (0%, 25%, 50% and 70% coverage).

Assessing the quality of shared decision making for elective orthopedic surgery across a large healthcare system: cross-sectional survey study.

Background: Clinical guidelines recommend engaging patients in shared decision making for common orthopedic procedures; however, limited work has assessed what is occurring in practice. This study assessed the quality of shared decision making for elective hip and knee replacement and spine surgery at four network-affiliated hospitals.

Methods: A cross-sectional sample of 875 adult patients undergoing total hip or knee joint replacement (TJR) for osteoarthritis or spine surgery for lumbar herniated disc or lumbar spinal stenosis was selected.

Fatty acid metabolism and colon cancer protection by dietary methyl donor restriction.

Introduction: A methyl donor depleted (MDD) diet dramatically suppresses intestinal tumor development in Apc-mutant mice, but the mechanism of this prevention is not entirely clear.

Objectives: We sought to gain insight into the mechanisms of cancer suppression by the MDD diet and to identify biomarkers of cancer risk reduction.

Methods: A plasma metabolomic analysis was performed on Apc mice maintained on either a methyl donor sufficient (MDS) diet or the protective MDD diet.

SARS-CoV-2 testing strategies to contain school-associated transmission: model-based analysis of impact and cost of diagnostic testing, screening, and surveillance.

Background: In March 2021, the Biden administration allocated $10 billion for COVID-19 testing in schools. We evaluate the costs and benefits of testing strategies to reduce the infection risks of full-time in-person K-8 education at different levels of community incidence.

Methods: We used an agent-based network model to simulate transmission in elementary and middle school communities, parameterized to a US school structure and assuming dominance of the delta COVID-19 variant.

Passing the Test: A Model-Based Analysis of Safe School-Reopening Strategies.

Background: The COVID-19 pandemic has induced historic educational disruptions. In April 2021, about 40% of U.S.

Passing the Test: A model-based analysis of safe school-reopening strategies.

Background: The COVID-19 pandemic has induced historic educational disruptions. In December 2020, at least two-thirds of US public school students were not attending full-time in-person education. The Biden Administration has expressed that reopening schools is a priority.

Validation of an electronic coding algorithm to identify the primary indication of orthopedic surgeries from administrative data.

Background: Determining the primary indication of a surgical procedure can be useful in identifying patients undergoing elective surgery where shared decision-making is recommended. The purpose of this study was to develop and validate an algorithm to identify patients receiving the following combinations of surgical procedure and primary indication as part of a study to promote shared decision-making: (1) knee arthroplasty to treat knee osteoarthritis (KOA); (2) hip arthroplasty to treat hip osteoarthritis (HOA); (3) spinal surgery to treat lumbar spinal stenosis (SpS); and (4) spinal surgery to treat lumbar herniated disc (HD).

Methods: Consecutive surgical procedures performed by participating spine, hip, and knee surgeons at four sites within an integrated care network were included.