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  1. Article ; Online: Evidence for Biologic Drug Modifying Anti-Rheumatoid Drugs and Association with Cardiovascular Disease Risk Mitigation in Inflammatory Arthritis.

    Weber, Brittany / Liao, Katherine P

    Rheumatic diseases clinics of North America

    2024  Volume 49, Issue 1, Page(s) 165–178

    Abstract: Systemic auto-immune inflammatory arthritides are associated with increased cardiovascular (CV) risk compared to those without these conditions, and is a leading cause of morbidity and mortality. Newer biologic drug modifying antirheumatoid drugs (bDMARD) ...

    Abstract Systemic auto-immune inflammatory arthritides are associated with increased cardiovascular (CV) risk compared to those without these conditions, and is a leading cause of morbidity and mortality. Newer biologic drug modifying antirheumatoid drugs (bDMARD) and small molecules have transformed treatment paradigms enabling tighter control of disease activity and in some cases, remission. There is evidence to suggest that the majority of bDMARDs may also reduce cardiovascular risk, although prospective interventional data remain sparse. Additionally, recent results raise concern for treatments targeting specific pathways that may negatively affect cardiovascular risk. This review will cover key biologic pathways targeted in rheumatoid arthritis, psoriatic arthritis, and spondyloarthropathies.
    MeSH term(s) Humans ; Antirheumatic Agents/adverse effects ; Cardiovascular Diseases/epidemiology ; Cardiovascular Diseases/etiology ; Cardiovascular Diseases/prevention & control ; Prospective Studies ; Arthritis, Rheumatoid/drug therapy ; Arthritis, Rheumatoid/complications ; Biological Products/adverse effects
    Chemical Substances Antirheumatic Agents ; Biological Products
    Language English
    Publishing date 2024-02-02
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ZDB-ID 92118-x
    ISSN 1558-3163 ; 0889-857X
    ISSN (online) 1558-3163
    ISSN 0889-857X
    DOI 10.1016/j.rdc.2022.08.005
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Finding the Right Fit for Genes in Rheumatology Clinical Care.

    Vassy, Jason L / Knevel, Rachel / Liao, Katherine P

    Arthritis & rheumatology (Hoboken, N.J.)

    2024  Volume 76, Issue 5, Page(s) 675–676

    MeSH term(s) Humans ; Rheumatology ; Rheumatic Diseases/genetics ; Rheumatic Diseases/therapy
    Language English
    Publishing date 2024-01-09
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Editorial
    ZDB-ID 2756371-6
    ISSN 2326-5205 ; 2326-5191
    ISSN (online) 2326-5205
    ISSN 2326-5191
    DOI 10.1002/art.42769
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  3. Article ; Online: B-Cell Targeted Therapeutics in Systemic Lupus Erythematosus: From Paradox to Synergy?

    Barbhaiya, Medha / Liao, Katherine P

    Annals of internal medicine

    2021  Volume 174, Issue 12, Page(s) 1747–1748

    MeSH term(s) B-Lymphocytes ; Humans ; Lupus Erythematosus, Systemic
    Language English
    Publishing date 2021-10-26
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 336-0
    ISSN 1539-3704 ; 0003-4819
    ISSN (online) 1539-3704
    ISSN 0003-4819
    DOI 10.7326/M21-4124
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  4. Article ; Online: Semisupervised transfer learning for evaluation of model classification performance.

    Wang, Linshanshan / Wang, Xuan / Liao, Katherine P / Cai, Tianxi

    Biometrics

    2024  Volume 80, Issue 1

    Abstract: In many modern machine learning applications, changes in covariate distributions and difficulty in acquiring outcome information have posed challenges to robust model training and evaluation. Numerous transfer learning methods have been developed to ... ...

    Abstract In many modern machine learning applications, changes in covariate distributions and difficulty in acquiring outcome information have posed challenges to robust model training and evaluation. Numerous transfer learning methods have been developed to robustly adapt the model itself to some unlabeled target populations using existing labeled data in a source population. However, there is a paucity of literature on transferring performance metrics, especially receiver operating characteristic (ROC) parameters, of a trained model. In this paper, we aim to evaluate the performance of a trained binary classifier on unlabeled target population based on ROC analysis. We proposed Semisupervised Transfer lEarning of Accuracy Measures (STEAM), an efficient three-step estimation procedure that employs (1) double-index modeling to construct calibrated density ratio weights and (2) robust imputation to leverage the large amount of unlabeled data to improve estimation efficiency. We establish the consistency and asymptotic normality of the proposed estimator under the correct specification of either the density ratio model or the outcome model. We also correct for potential overfitting bias in the estimators in finite samples with cross-validation. We compare our proposed estimators to existing methods and show reductions in bias and gains in efficiency through simulations. We illustrate the practical utility of the proposed method on evaluating prediction performance of a phenotyping model for rheumatoid arthritis (RA) on a temporally evolving EHR cohort.
    MeSH term(s) Humans ; Supervised Machine Learning ; Machine Learning ; ROC Curve ; Research Design ; Bias
    Language English
    Publishing date 2024-03-11
    Publishing country England
    Document type Journal Article
    ZDB-ID 213543-7
    ISSN 1541-0420 ; 0099-4987 ; 0006-341X
    ISSN (online) 1541-0420
    ISSN 0099-4987 ; 0006-341X
    DOI 10.1093/biomtc/ujae002
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  5. Article ; Online: From real-world electronic health record data to real-world results using artificial intelligence.

    Knevel, Rachel / Liao, Katherine P

    Annals of the rheumatic diseases

    2022  Volume 82, Issue 3, Page(s) 306–311

    Abstract: With the worldwide digitalisation of medical records, electronic health records (EHRs) have become an increasingly important source of real-world data (RWD). RWD can complement traditional study designs because it captures almost the complete variety of ... ...

    Abstract With the worldwide digitalisation of medical records, electronic health records (EHRs) have become an increasingly important source of real-world data (RWD). RWD can complement traditional study designs because it captures almost the complete variety of patients, leading to more generalisable results. For rheumatology, these data are particularly interesting as our diseases are uncommon and often take years to develop. In this review, we discuss the following concepts related to the use of EHR for research and considerations for translation into clinical care: EHR data contain a broad collection of healthcare data covering the multitude of real-life patients and the healthcare processes related to their care. Machine learning (ML) is a powerful method that allows us to leverage a large amount of heterogeneous clinical data for clinical algorithms, but requires extensive training, testing, and validation. Patterns discovered in EHR data using ML are applicable to real life settings, however, are also prone to capturing the local EHR structure and limiting generalisability outside the EHR(s) from which they were developed. Population studies on EHR necessitates knowledge on the factors influencing the data available in the EHR to circumvent biases, for example, access to medical care, insurance status. In summary, EHR data represent a rapidly growing and key resource for real-world studies. However, transforming RWD EHR data for research and for real-world evidence using ML requires knowledge of the EHR system and their differences from existing observational data to ensure that studies incorporate rigorous methods that acknowledge or address factors such as access to care, noise in the data, missingness and indication bias.
    MeSH term(s) Humans ; Electronic Health Records ; Artificial Intelligence ; Algorithms ; Machine Learning ; Research Design
    Language English
    Publishing date 2022-09-23
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 7090-7
    ISSN 1468-2060 ; 0003-4967
    ISSN (online) 1468-2060
    ISSN 0003-4967
    DOI 10.1136/ard-2022-222626
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    Zs.MO 167: Show issues

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  6. Article ; Online: Sore, Hot, and at Risk: The Emerging Specialty of Cardio-Rheumatology.

    Weber, Brittany / Garshick, Michael / Liao, Katherine P / Di Carli, Marcelo

    Journal of the American Heart Association

    2023  Volume 12, Issue 11, Page(s) e027846

    MeSH term(s) Humans ; Rheumatology ; Heart ; Pain ; Skin Diseases
    Language English
    Publishing date 2023-05-26
    Publishing country England
    Document type Editorial ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2653953-6
    ISSN 2047-9980 ; 2047-9980
    ISSN (online) 2047-9980
    ISSN 2047-9980
    DOI 10.1161/JAHA.122.027846
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  7. Article ; Online: Shared inflammatory pathways of rheumatoid arthritis and atherosclerotic cardiovascular disease.

    Weber, Brittany N / Giles, Jon T / Liao, Katherine P

    Nature reviews. Rheumatology

    2023  Volume 19, Issue 7, Page(s) 417–428

    Abstract: The association between chronic inflammation and increased risk of cardiovascular disease in rheumatoid arthritis (RA) is well established. In the general population, inflammation is an established independent risk factor for cardiovascular disease, and ... ...

    Abstract The association between chronic inflammation and increased risk of cardiovascular disease in rheumatoid arthritis (RA) is well established. In the general population, inflammation is an established independent risk factor for cardiovascular disease, and much interest is placed on controlling inflammation to reduce cardiovascular events. As inflammation encompasses numerous pathways, the development of targeted therapies in RA provides an opportunity to understand the downstream effect of inhibiting specific pathways on cardiovascular risk. Data from these studies can inform cardiovascular risk management in patients with RA, and in the general population. This Review focuses on pro-inflammatory pathways targeted by existing therapies in RA and with mechanistic data from the general population on cardiovascular risk. Specifically, the discussions include the IL-1, IL-6 and TNF pathways, as well as the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signalling pathway, and the role of these pathways in RA pathogenesis in the joint alongside the development of atherosclerotic cardiovascular disease. Overall, some robust data support inhibition of IL-1 and IL-6 in decreasing the risk of cardiovascular disease, with growing data supporting IL-6 inhibition in both patients with RA and the general population to reduce the risk of cardiovascular disease.
    MeSH term(s) Humans ; Interleukin-6 ; Cardiovascular Diseases/etiology ; Arthritis, Rheumatoid/metabolism ; Inflammation ; Janus Kinases/metabolism ; Atherosclerosis ; Interleukin-1
    Chemical Substances Interleukin-6 ; Janus Kinases (EC 2.7.10.2) ; Interleukin-1
    Language English
    Publishing date 2023-05-25
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2491532-4
    ISSN 1759-4804 ; 1759-4790
    ISSN (online) 1759-4804
    ISSN 1759-4790
    DOI 10.1038/s41584-023-00969-7
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  8. Article ; Online: Through the looking glass of rheumatoid arthritis to study inflammation and high-density lipoprotein.

    Liao, Katherine P

    Heart (British Cardiac Society)

    2017  Volume 103, Issue 10, Page(s) 734–735

    MeSH term(s) Arthritis, Rheumatoid ; Humans ; Inflammation ; Lipoproteins, HDL
    Chemical Substances Lipoproteins, HDL
    Language English
    Publishing date 2017-01-09
    Publishing country England
    Document type Editorial ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Comment
    ZDB-ID 1303417-0
    ISSN 1468-201X ; 1355-6037
    ISSN (online) 1468-201X
    ISSN 1355-6037
    DOI 10.1136/heartjnl-2016-310764
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  9. Article ; Online: Cardiovascular disease in patients with rheumatoid arthritis.

    Liao, Katherine P

    Trends in cardiovascular medicine

    2017  Volume 27, Issue 2, Page(s) 136–140

    Abstract: The risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) is 1.5-2-fold higher than age- and sex-matched individuals from the general population. This excess risk is attributed to the systemic chronic inflammation which is a ... ...

    Abstract The risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) is 1.5-2-fold higher than age- and sex-matched individuals from the general population. This excess risk is attributed to the systemic chronic inflammation which is a hallmark of RA. Challenges to optimizing CV risk management in RA include the need for improved methods to predict CV risk, and defining the target risk factor(s) to reduce CV risk. Lessons learned from RA studies can also inform CV risk prevention in the general population, where inflammation also has an important role in the pathogenesis of atherosclerosis.
    MeSH term(s) Arthritis, Rheumatoid/complications ; Arthritis, Rheumatoid/diagnosis ; Arthritis, Rheumatoid/immunology ; Arthritis, Rheumatoid/therapy ; Biomarkers/blood ; Cardiovascular Diseases/diagnosis ; Cardiovascular Diseases/etiology ; Cardiovascular Diseases/immunology ; Cardiovascular Diseases/prevention & control ; Humans ; Inflammation Mediators/blood ; Lipids/blood ; Prognosis ; Risk Assessment ; Risk Factors
    Chemical Substances Biomarkers ; Inflammation Mediators ; Lipids
    Language English
    Publishing date 2017-02
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 1097434-9
    ISSN 1873-2615 ; 1050-1738
    ISSN (online) 1873-2615
    ISSN 1050-1738
    DOI 10.1016/j.tcm.2016.07.006
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  10. Article ; Online: Lipids and Cardiovascular Risk Through the Lens of Rheumatoid Arthritis.

    Liao, Katherine P / Solomon, Daniel H

    Arthritis & rheumatology (Hoboken, N.J.)

    2019  Volume 71, Issue 9, Page(s) 1393–1395

    MeSH term(s) Arthritis, Rheumatoid ; Atorvastatin ; Cardiovascular Diseases ; Humans ; Lipids ; Primary Prevention ; Risk Factors
    Chemical Substances Lipids ; Atorvastatin (A0JWA85V8F)
    Language English
    Publishing date 2019-07-22
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 2756371-6
    ISSN 2326-5205 ; 2326-5191
    ISSN (online) 2326-5205
    ISSN 2326-5191
    DOI 10.1002/art.40891
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