Impact of wildfire air pollution on rates of cardiovascular events and mortality
There is an increasing frequency of large wildfires in California. Smoke from these wildfires can drastically increase short-term exposure to harmful air pollutants, especially particulate matter (PM), and some KPNC members may be at greater risk of the adverse health effects of wildfire smoke due to underlying comorbidities. We aim to investigate the health effects of wildfire-PM on cardiovascular events and mortality, and to determine which populations with underlying comorbidities may be at greatest risk during these wildfire events. By identifying clinical comorbidities that confer increased susceptibility to these deleterious effects, KPNC members who have higher risks could be targeted for specific interventions by their providers.
Investigator: Alexeeff, Stacey
Funder: Northern California Community Benefit Programs
Understanding the risk of ectopic pregnancies among people seeking abortion: a retrospective case control study
This study aims to assess the incidence of ectopic pregnancy among people wanting pregnancy compared to people seeking abortion. The specific research questions are: Are people seeking abortion at lower risk of experiencing an ectopic pregnancy compared to people not seeking abortion? What are the unique risk factors for experiencing an ectopic pregnancy among people seeking abortion? How do people seeking abortion who are eventually diagnosed with ectopic pregnancies initially present for care? We will conduct a case-control study using a retrospective review of electronic health records of approximately 2,200 randomly chosen cases of ectopic pregnancies and a comparison group of 1,100 randomly chosen intrauterine pregnancies.
Investigator: Armstrong, Mary Anne
Funder: Fidelity Charitable
Comparison of type 2 diabetes pharmacotherapy regimens using targeted learning
This study is designed to help patients with type 2 diabetes and their clinicians identify which glucose-lowering medications among SGLT2 inhibitors, GLP-1 receptor agonists, DPP4 inhibitors, or Sulfonylureas have the most favorable effects on heart health and other patient-important outcomes; inform the timing of medication initiation; and explore whether medication benefits apply equally to all adults with type 2 diabetes, or are different based on age, sex, race/ethnicity, baseline heart health status, baseline renal function, or other factors. Inferences are based on a modern causal inference methodology, Targeted Learning, applied within a trial emulation framework.
Investigator: Neugebauer, Romain
Funder: Patient-Centered Outcomes Research Institute
Development and Implementation of Evidence-based Risk Stratification Tools for Diabetic Retinopathy Screening and Population Management
This project aims to develop and implement evidence-based risk stratification tools
for diabetic retinopathy screening and population management.
Investigator: Sofrygin, Oleg
Funder: TPMG Delivery Science Projects Program
Leveraging Machine Learning to Improve Risk Prediction for Chemotherapy Induced Neuropathy
Chemotherapy-associated peripheral neuropathy (CPN) affects nearly 70% of cancer patients. An estimated 30% of cancer survivors have persistent CPN, which can have a devastating impact on their quality of life and functioning. Our objective is to develop and validate a predictive model that will identify those patients who are at high risk of developing severe CPN that can result in their receiving fewer planned chemotherapy cycles. We will focus on two subgroups our preliminary studies suggest have a higher risk for CPN: people who have diabetes or are African American/ Black.
Investigator: Neugebauer, Romain
Funder: National Cancer Institute
Evaluation of Complex Interventions on Drug (Re)Fill Behavior Using Electronic Health Care Data
This study develops generalized per-protocol analyses based on Inverse Probability Weighting and Targeted Learning to control for or evaluate the effect of medication nonadherence in observational studies that use electronic health databases to inform the management of chronic conditions. Unlike current implementations of these analyses that require investigators to make untestable and often arbitrary assumptions regarding patients’ use of drugs from pharmacy dispensing data, the proposed causal methodologies directly evaluate the health effects of drug (re)fill regimens. To develop these analytic approaches, we seek guidance from stakeholder partners representing a broad range of constituencies to illustrate and ensure the practical relevance of the proposed methods from two prior studies with electronic health databases conducted to inform the management of type 2 diabetes.
Investigator: Neugebauer, Romain
Funder: Patient-Centered Outcomes Research Institute
Study of Healthy Aging in African Americans (STAR)
Rates of dementia and Alzheimer’s disease are 40% to 100% higher among African Americans compared to non-Hispanic whites. STAR is a longitudinal cohort study of lifecourse vascular risk and brain aging in 700 African Americans ages 50 and older. The goals of the study are to understand the trajectory of normal cognitive aging from mid- to late life, the burden of cognitive impairment, and the long-term contributions of vascular disease on brain aging among African Americans, an understudied and rapidly expanding segment of the elderly population at higher risk for dementia.
Investigator: Quesenberry, Charles
Funder: National Institute on Aging
Study of Longevity in Diabetes (SOLID)
Type 1 diabetes is a complicated disease requiring constant adherence to glycemic targets and meticulous attention and vigilance of blood sugar. Individuals with type 1 diabetes are living longer than ever before, yet very little is known about how this group can age successfully. The goal of this study is to characterize cognitive and physical aging, and predictors of successful aging and longevity in a cohort including more than 800 elderly individuals with type 1 diabetes, 200 individuals with type 2 diabetes and 200 individuals without diabetes.
Investigator: Quesenberry, Charles
Funder: National Institute on Aging
Kaiser Healthy Aging and Diverse Life Experiences Study (KHANDLE)
Although there are marked ethnic disparities in rates of dementia, almost nothing is known about early-life contributors to dementia in ethnic minority groups, nor if the trajectory of cognitive decline or transition to cognitive impairment varies across ethnic groups. We propose a lifecourse study of ethnic disparities in the epidemiology of dementia using over 5 decades of data in relation to cognitive decline and brain pathology. The overall objectives are to define ethnic disparities in dementia incidence and to advance our understanding of such disparities by assessing early and midlife risk factors for cognitive impairment and MRI markers of brain injury.
Investigator: Quesenberry, Charles
Funder: National Institute on Aging
Life After 90
Alzheimer’s disease and other dementias affect 15 percent of those aged 65 and older, by age 90 and older this number increases to a startling 40 to 50 percent. The oldest-old, people aged 90 and older, are the fastest growing segment of the elderly population in the United States, currently comprising 4.7 percent, and they are expected to increase to almost 10 percent of the elderly population by 2050. Yet there’s an enormous dearth of information on mild cognitive impairment (MCI) and age-associated dementias in the oldest-old, particularly in nonwhites and those from lower socioeconomic classes. Our overall objectives are to determine there are ethnoracial differences among the oldest-old in the incidence of MCI/dementia; quantify mid- and late-life risk and protective factors for MCI/dementia; and understand the burden of cerebral and brain pathologies in this population.
Investigator: Quesenberry, Charles
Funder: National Institute on Aging
Particulate Air Pollution, Cardiovascular Events, and Susceptibility Factors (PACES)
This is a retrospective cohort study of 5 million adult members of Kaiser Permanente Northern California during 2000 to 2012, linked to state-of-the-art estimates of exposure to PM2.5 (particulate matter less than 2.5 micrometers in diameter) generated at 1km x 1km resolution using a novel hybrid model that incorporates meteorologic, land-use, and satellite measures. This project will quantify the associations between ambient PM2.5 exposure and risk of cardiovascular disease events, and determine whether demographic characteristics (age, sex, race/ethnicity, and socioeconomic status) and clinical comorbidities (obesity, diabetes, hypertension, and hyperlipidemia) are susceptibility factors that confer elevated risk to the effects of PM2.5.
Investigator: Alexeeff, Stacey
Funder: National Institute of Environmental Health Sciences
Study on the Association of Uterine Perforation and IUD expulsion With Breastfeeding Status at the Time of IUD insertion and Postpartum Timing of IUD Insertion in Electronic Medical Record Databases – A Post-marketing Requirement for Mirena
The Food and Drug Administration (FDA) has required Bayer AG to conduct a post-marketing study in the U.S. to determine the incidence of uterine perforation and IUD expulsion by type of intrauterine device (IUD) used. The goal of this study is to quantify the risk of uterine perforation and IUD expulsion by: (1) breastfeeding status at the time of IUD insertion, (2) time periods postpartum when the IUD was inserted (e.g., 6 weeks or less, after 6 weeks and up to 14 weeks, more than 14 weeks and up to 52 weeks, or more than 52 weeks), and (3) type of IUD.
Investigator: Armstrong, Mary Anne
Funder: Bayer AG
Mini-Sentinel Efforts to Develop the Sentinel Initiative: The Use of Propensity-Score Matching for Estimating Hazard Ratios in Post-Market Surveillance with Heavy Censoring
Mini-Sentinel Task Order
Investigator: Fireman, Bruce
Funder: U.S. Food and Drug Administration
Software to Automate Implementation of Causal Inference Methods with Time-Varying Interventions
This project aims to develop SAS macros to automate the data structuring required for implementation of Causal Inference methods with electronic health records data in studies with time-varying exposures, confounding and selection bias (e.g., marginal structural modeling with inverse probability weighting). SAS macros are validated with simulated data and their applicability is evaluated using secondary data analyses in cardiovascular, diabetes, and health services research. End-user feedback is used to validate and refine the implementation and documentation of the SAS software.
Investigator: Neugebauer, Romain
Feasibility and Performance Assessments of TMLE and hdPS Methodologies to Fit MSM in a Real-World CER Study
This study aims to evaluate the practicability and practical advantages of: 1) Targeted Minimum Loss based Estimation (TMLE), and 2) a high-dimensional propensity score (hdPS) algorithm to fit dynamic Marginal Structural Models (MSM) in a longitudinal comparative effectiveness research (CER) study of adults with type 2 diabetes.
Investigator: Neugebauer, Romain
Funder: Agency for Healthcare Research and Quality
Risk of Uterine Perforation among Women Using different types of IUDs and the Association with Timing of Insertion and Breastfeeding
The goal of the study is to compare the incidence of uterine perforation within 12 months after IUD insertion between: (1) postpartum insertions within 12 months of delivery (with breastfeeding status), (2) post abortion or pregnancy loss IUD insertions and (3) interval IUD insertions not associated with a pregnancy, and to determine if IUD insertion immediately postpartum and/or breastfeeding are associated with an increased risk of perforation.
Investigator: Armstrong, Mary Anne
Funder: Bayer AG
