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819 results on '"Toh, Sengwee"'

160. Leveraging the Capabilities of the FDA’s Sentinel System To Improve Kidney Care

Author

Adimadhyam, Sruthi, primary, Barreto, Erin F., additional, Cocoros, Noelle M., additional, Toh, Sengwee, additional, Brown, Jeffrey S., additional, Maro, Judith C., additional, Corrigan-Curay, Jacqueline, additional, Dal Pan, Gerald J., additional, Ball, Robert, additional, Martin, David, additional, Nguyen, Michael, additional, Platt, Richard, additional, and Li, Xiaojuan, additional

Published
2020
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163. Validity of diagnosis and procedure codes for identifying neural tube defects in infants

Author

Cheetham, T. Craig, primary, Dublin, Sascha, additional, Pocobelli, Gaia, additional, Bobb, Jennifer F., additional, Andrade, Susan, additional, Hechter, Rulin C., additional, Portugal, Cecilia, additional, Munis, Mercedes, additional, Albertson‐Junkans, Ladia, additional, Salgado, Gladys, additional, Wong, Lawrence, additional, Maarup, Timothy J., additional, Carroll, Kecia, additional, Griffin, Marie R., additional, Raebel, Marsha A., additional, Smith, David, additional, Li, De‐Kun, additional, Pawloski, Pamala A., additional, Toh, Sengwee, additional, Taylor, Lockwood, additional, Hua, Wei, additional, Dinatale, Miriam, additional, Ceresa, Carrie, additional, Trinidad, James P., additional, and Boudreau, Denise M., additional

Published
2020
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165. Developing a Standardized and Reusable Method to Link Distributed Health Plan Databases to the National Death Index: Methods Development Study Protocol (Preprint)

Author

Fuller, Candace C, primary, Hua, Wei, additional, Leonard, Charles E, additional, Mosholder, Andrew, additional, Carnahan, Ryan, additional, Dutcher, Sarah, additional, King, Katelyn, additional, Petrone, Andrew B, additional, Rosofsky, Robert, additional, Shockro, Laura A, additional, Young, Jessica, additional, Min, Jea Young, additional, Binswanger, Ingrid, additional, Boudreau, Denise, additional, Griffin, Marie R, additional, Adgent, Margaret A, additional, Kuntz, Jennifer, additional, McMahill-Walraven, Cheryl, additional, Pawloski, Pamala A, additional, Ball, Robert, additional, and Toh, Sengwee, additional

Published
2020
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173. Understanding utilization patterns of biologics and biosimilars in the United States to support postmarketing studies of safety and effectiveness

Author

Dutcher, Sarah K., primary, Fazio‐Eynullayeva, Elnara, additional, Eworuke, Efe, additional, Carruth, Amanda, additional, Dee, Elizabeth C., additional, Blum, Michael D., additional, Nguyen, Michael D., additional, Toh, Sengwee, additional, Panozzo, Catherine A., additional, and Lyons, Jennifer G., additional

Published
2019
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187. Variance estimation in inverse probability weighted Cox models.

Author

Shu, Di, Young, Jessica G., Toh, Sengwee, and Wang, Rui

Subjects
PATIENT readmissions, BARIATRIC surgery, LIKELIHOOD ratio tests, SCIENTIFIC observation
Abstract

Inverse probability weighted Cox models can be used to estimate marginal hazard ratios under different point treatments in observational studies. To obtain variance estimates, the robust sandwich variance estimator is often recommended to account for the induced correlation among weighted observations. However, this estimator does not incorporate the uncertainty in estimating the weights and tends to overestimate the variance, leading to inefficient inference. Here we propose a new variance estimator that combines the estimation procedures for the hazard ratio and weights using stacked estimating equations, with additional adjustments for the sum of terms that are not independently and identically distributed in a Cox partial likelihood score equation. We prove analytically that the robust sandwich variance estimator is conservative and establish the asymptotic equivalence between the proposed variance estimator and one obtained through linearization by Hajage et al. in 2018. In addition, we extend our proposed variance estimator to accommodate clustered data. We compare the finite sample performance of the proposed method with alternative methods through simulation studies. We illustrate these different variance methods in both independent and clustered data settings, using a bariatric surgery dataset and a multiple readmission dataset, respectively. To facilitate implementation of the proposed method, we have developed an R package ipwCoxCSV. [ABSTRACT FROM AUTHOR]

Published
2021
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188. A COVID‐19‐ready public health surveillance system: The Food and Drug Administration's Sentinel System.

Author

Cocoros, Noelle M., Fuller, Candace C., Adimadhyam, Sruthi, Ball, Robert, Brown, Jeffrey S., Dal Pan, Gerald J., Kluberg, Sheryl A., Lo Re, Vincent, Maro, Judith C., Nguyen, Michael, Orr, Robert, Paraoan, Dianne, Perlin, Jonathan, Poland, Russell E., Driscoll, Meighan Rogers, Sands, Kenneth, Toh, Sengwee, Yih, W. Katherine, Platt, Richard, and Measer, Gregory

Abstract

The US Food and Drug Administration's Sentinel System was established in 2009 to use routinely collected electronic health data for improving the national capability to assess post‐market medical product safety. Over more than a decade, Sentinel has become an integral part of FDA's surveillance capabilities and has been used to conduct analyses that have contributed to regulatory decisions. FDA's role in the COVID‐19 pandemic response has necessitated an expansion and enhancement of Sentinel. Here we describe how the Sentinel System has supported FDA's response to the COVID‐19 pandemic. We highlight new capabilities developed, key data generated to date, and lessons learned, particularly with respect to working with inpatient electronic health record data. Early in the pandemic, Sentinel developed a multi‐pronged approach to support FDA's anticipated data and analytic needs. It incorporated new data sources, created a rapidly refreshed database, developed protocols to assess the natural history of COVID‐19, validated a diagnosis‐code based algorithm for identifying patients with COVID‐19 in administrative claims data, and coordinated with other national and international initiatives. Sentinel is poised to answer important questions about the natural history of COVID‐19 and is positioned to use this information to study the use, safety, and potentially the effectiveness of medical products used for COVID‐19 prevention and treatment. [ABSTRACT FROM AUTHOR]

Published
2021
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189. The Certainty Framework for Assessing Real‐World Data in Studies of Medical Product Safety and Effectiveness.

Author

Cocoros, Noelle M., Arlett, Peter, Dreyer, Nancy A., Ishiguro, Chieko, Iyasu, Solomon, Sturkenboom, Miriam, Zhou, Wei, and Toh, Sengwee

Subjects
MEDICAL supplies, PRODUCT safety, CERTAINTY, DECISION making, EXPERIMENTAL design
Abstract

A fundamental question in using real‐world data for clinical and regulatory decision making is: How certain must we be that the algorithm used to capture an exposure, outcome, cohort‐defining characteristic, or confounder is what we intend it to be? We provide a practical framework to help researchers and regulators assess and classify the fit‐for‐purposefulness of real‐world data by study variable for a range of data sources. The three levels of certainty (optimal, sufficient, and probable) must be considered in the context of each study variable, the specific question being studied, the study design, and the decision at hand. [ABSTRACT FROM AUTHOR]

Published
2021
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190. Comparative cardiovascular safety of nonsteroidal anti‐inflammatory drugs in patients with hypertension: a population‐based cohort study

Author

Dong, Yaa‐Hui, Chang, Chia‐Hsuin, Wu, Li‐Chiu, Hwang, Jing‐Shiang, and Toh, Sengwee

Subjects
Male, Diclofenac, Cyclooxygenase 2 Inhibitors, Databases, Pharmaceutical, Anti-Inflammatory Agents, Non-Steroidal, Ibuprofen, Middle Aged, Cardiovascular System, Hospitalization, Mefenamic Acid, Naproxen, Drug Safety, Celecoxib, Risk Factors, Hypertension, Humans, Female, Aged
Abstract

AIMS: Previous studies have suggested that nonsteroidal anti‐inflammatory drugs (NSAIDs) may be associated with higher cardiovascular risks. However, few have been active comparison studies that directly assessed the potential differential cardiovascular risk between NSAID classes or across individual NSAIDs. We compared the risk of major cardiovascular events between cyclooxygenase 2 (COX‐2)‐selective and nonselective NSAIDs in patients with hypertension. METHODS: We conducted a cohort study of patients with hypertension who initiated COX‐2‐selective or nonselective NSAIDs in a population‐based Taiwanese database. The outcomes included hospitalization for the following major cardiovascular events: ischaemic stroke, acute myocardial infarction, congestive heart failure, transient ischaemic attack, unstable angina or coronary revascularization. We followed patients for up to 4 weeks, based on the as‐treated principle. We used inverse probability weighting to control for baseline and time‐varying covariates, and estimated the on‐treatment hazard ratios (HRs) and 95% conservative confidence interval (CIs). RESULTS: We identified 2749 eligible COX‐2‐selective NSAID users and 52 880 eligible nonselective NSAID users. The HR of major cardiovascular events comparing COX‐2‐selective with nonselective NSAIDs after adjusting for baseline and time‐varying covariates was 1.07 (95% CI 0.65, 1.74). We did not observe a differential risk when comparing celecoxib to diclofenac (HR 1.17; 95% CI 0.61, 2.25), ibuprofen (HR 1.36; 95% CI 0.58, 3.18) or naproxen (HR 0.75; 95% CI 0.23, 2.44). There was an increased risk with COX‐2‐selective NSAIDs, however, when comparing COX‐2‐selective NSAIDs with mefenamic acid (HR 2.11; 95% CI 1.09, 4.09). CONCLUSIONS: Our results provide important information about the comparative cardiovascular safety of NSAIDs in patients with hypertension.

Published
2018

197. Antipsychotic Use and Stroke

Author

Taylor, Lockwood G., primary, Panucci, Genna, additional, Mosholder, Andrew D., additional, Toh, Sengwee, additional, and Huang, Ting-Ying, additional

Published
2019
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198. Evaluating the use of bootstrapping in cohort studies conducted with 1:1 propensity score matching—A plasmode simulation study

Author

Desai, Rishi J., primary, Wyss, Richard, additional, Abdia, Younathan, additional, Toh, Sengwee, additional, Johnson, Margaret, additional, Lee, Hana, additional, Karami, Sara, additional, Major, Jacqueline M., additional, Nguyen, Michael, additional, Wang, Shirley V., additional, Franklin, Jessica M., additional, and Gagne, Joshua J., additional

Published
2019
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200. Comparing Prescribing and Dispensing Data of the PCORnet Common Data Model Within PCORnet Antibiotics and Childhood Growth Study

Author

Lin, Pi-I D., primary, Daley, Matthew F., additional, Boone-Heinonen, Janne, additional, Rifas-Shiman, Sheryl L., additional, Bailey, L. Charles, additional, Forrest, Christopher B., additional, Horgan, Casie E., additional, Sturtevant, Jessica L., additional, Toh, Sengwee, additional, Young, Jessica G., additional, Block, Jason P., additional, and PCORnet Antibiotics and Childhood Growth Study Group, On behalf of the, additional

Published
2019
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