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  1. Book ; Online ; E-Book: Real-world evidence in a patient-centric digital era

    Salem, Lobna A. / Ray, Amrit / Zou, Kelly H.

    (Chapman & Hall/CRC biostatistics series)

    2023  

    Author's details Kelly H. Zou, Lobna A. Salem and Amrit Ray, editors
    Series title Chapman & Hall/CRC biostatistics series
    Keywords Medical statistics ; Biometry ; Evidence-based medicine
    Subject code 616
    Language English
    Size 1 online resource (209 pages)
    Edition First edition.
    Publisher CRC Press
    Publishing place Boca Raton, FL ; Abingdon, Oxon
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 1-00-301752-5 ; 1-000-61340-2 ; 1-000-61345-3 ; 1-003-01752-5 ; 0-367-86181-X ; 978-1-00-301752-3 ; 978-1-000-61340-7 ; 978-1-000-61345-2 ; 978-1-003-01752-3 ; 978-0-367-86181-0
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book: Statistical evaluation of diagnostic performance

    Zou, Kelly H.

    topics in ROC analysis

    (Chapman & Hall, CRC biostatistics series ; A Chapman & Hall book)

    2012  

    Author's details Kelly H. Zou
    Series title Chapman & Hall, CRC biostatistics series
    A Chapman & Hall book
    Language English
    Size XVIII, 227 S. : graph. Darst.
    Publisher CRC Press
    Publishing place Boca Raton u.a.
    Publishing country United States
    Document type Book
    HBZ-ID HT016761377
    ISBN 978-1-4398-1222-8 ; 1-4398-1222-5
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2011 A 4054 order for loan Magazin

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  3. Article: Enhanced Patient-Centricity: How the Biopharmaceutical Industry Is Optimizing Patient Care through AI/ML/DL.

    Zou, Kelly H / Li, Jim Z

    Healthcare (Basel, Switzerland)

    2022  Volume 10, Issue 10

    Abstract: Technologies utilizing cutting-edge methodologies, including artificial intelligence (AI), machine learning (ML) and deep learning (DL), present powerful opportunities to help evaluate, predict, and improve patient outcomes by drawing insights from real- ... ...

    Abstract Technologies utilizing cutting-edge methodologies, including artificial intelligence (AI), machine learning (ML) and deep learning (DL), present powerful opportunities to help evaluate, predict, and improve patient outcomes by drawing insights from real-world data (RWD) generated during medical care. They played a role during and following the Coronavirus Disease 2019 (COVID-19) pandemic by helping protect healthcare providers, prioritize care for vulnerable populations, predict disease trends, and find optimal therapies. Potential applications across therapeutic areas include diagnosis, disease management and patient journey mapping. Use of fit-for-purpose datasets for ML models is seeing growth and may potentially help additional enterprises develop AI strategies. However, biopharmaceutical companies often face specific challenges, including multi-setting data, system interoperability, data governance, and patient privacy requirements. There remains a need for evolving regulatory frameworks, operating models, and data governance to enable further developments and additional research. We explore recent literature and examine the hurdles faced by researchers in the biopharmaceutical industry to fully realize the promise of AI/ML/DL for patient-centric purposes.
    Language English
    Publishing date 2022-10-11
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2721009-1
    ISSN 2227-9032
    ISSN 2227-9032
    DOI 10.3390/healthcare10101997
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Image Perception and Diagnostic Accuracy of Digital Mammography: An Editorial.

    Zou, Kelly H / Evers, Kathryn

    Academic radiology

    2019  Volume 26, Issue 6, Page(s) 724–725

    MeSH term(s) Mammography ; Radiographic Image Enhancement
    Language English
    Publishing date 2019-03-20
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 1355509-1
    ISSN 1878-4046 ; 1076-6332
    ISSN (online) 1878-4046
    ISSN 1076-6332
    DOI 10.1016/j.acra.2019.02.017
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4594: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: The Next Horizon of Drug Development: External Control Arms and Innovative Tools to Enrich Clinical Trial Data.

    Zou, Kelly H / Vigna, Chelsea / Talwai, Aniketh / Jain, Rahul / Galaznik, Aaron / Berger, Marc L / Li, Jim Z

    Therapeutic innovation & regulatory science

    2024  Volume 58, Issue 3, Page(s) 443–455

    Abstract: Conducting clinical trials (CTs) has become increasingly costly and complex in terms of designing and operationalizing. These challenges exist in running CTs on novel therapies, particularly in oncology and rare diseases, where CTs increasingly target ... ...

    Abstract Conducting clinical trials (CTs) has become increasingly costly and complex in terms of designing and operationalizing. These challenges exist in running CTs on novel therapies, particularly in oncology and rare diseases, where CTs increasingly target narrower patient groups. In this study, we describe external control arms (ECA) and other relevant tools, such as virtualization and decentralized clinical trials (DCTs), and the ability to follow the clinical trial subjects in the real world using tokenization. ECAs are typically constructed by identifying appropriate external sources of data, then by cleaning and standardizing it to create an analysis-ready data file, and finally, by matching subjects in the external data with the subjects in the CT of interest. In addition, ECA tools also include subject-level meta-analysis and simulated subjects' data for analyses. By implementing the recent advances in digital health technologies and devices, virtualization, and DCTs, realigning of CTs from site-centric designs to virtual, decentralized, and patient-centric designs can be done, which reduces the patient burden to participate in the CTs and encourages diversity. Tokenization technology allows linking the CT data with real-world data (RWD), creating more comprehensive and longitudinal outcome measures. These tools provide robust ways to enrich the CT data for informed decision-making, reduce the burden on subjects and costs of trial operations, and augment the insights gained for the CT data.
    MeSH term(s) Humans ; Clinical Trials as Topic ; Drug Development ; Research Design
    Language English
    Publishing date 2024-03-25
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2708397-4
    ISSN 2168-4804 ; 2168-4790
    ISSN (online) 2168-4804
    ISSN 2168-4790
    DOI 10.1007/s43441-024-00627-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Clinical Practice Management of Primary Open-Angle Glaucoma in the United States: An Analysis of Real-World Evidence.

    Imperato, Joseph S / Zou, Kelly H / Li, Jim Z / Hassan, Tarek A

    Patient preference and adherence

    2022  Volume 16, Page(s) 2213–2227

    Abstract: Purpose: To investigate clinical management of primary open-angle glaucoma (POAG) in the United States using real-world evidence and to examine healthcare resource utilization (HCRU), medication adherence/persistence, and procedure use.: Design: A ... ...

    Abstract Purpose: To investigate clinical management of primary open-angle glaucoma (POAG) in the United States using real-world evidence and to examine healthcare resource utilization (HCRU), medication adherence/persistence, and procedure use.
    Design: A cross-sectional, retrospective analysis of Optum's de-identified Market Clarity Dataset (July 1, 2013-December 31, 2019).
    Patients and methods: Patients ≥18 years with POAG diagnosis and continuous enrollment for 1-year pre- and post-index were eligible and categorized into four mutually exclusive cohorts: CH1, treated with antiglaucoma medication(s) only; CH2, underwent glaucoma procedure(s) only; CH3, treated with antiglaucoma medication(s) and underwent procedure(s); and CH4, received no treatment for POAG. Adherence and persistence with antiglaucoma medications, and disease-specific HCRU were analyzed. Pairwise two-sample comparisons and multivariate regressions were conducted.
    Results: Examined 232,572 eligible patients (CH1=60,895; CH2=4330; CH3=6027; CH4=161,320). Prostaglandin analogs were most prescribed antiglaucoma medications (CH1: 69.7%; CH3: 62.7%), of which latanoprost was most common (CH1: 51.3%; CH3: 46.1%). Disease-specific office visits occurred in 26.3%, 78.2%, 75.0%, 23.8%, and surgical services visits occurred in 3.8%, 36.3%, 42.5%, 3.3%, in CH1-CH4, respectively. Adherence was higher (medication possession ratio: 47.1% vs 39.4%; P<0.0001), and more patients remained persistent across 1-year post-index period in CH1 vs CH3 (25.4% vs 16.1%; P<0.0001). Positive predictors of medication persistence included being female, ≥55 years, and history of dyslipidemia or thyroid disease (all P≤0.0003).
    Conclusion: Overall, 70% POAG patients might not have received antiglaucoma treatment. Since POAG is a slowly progressive blinding disease, the lack of antiglaucoma treatment and suboptimal adherence/persistence with medications are of major concerns. Targeted screening and educational approaches are needed to improve POAG management.
    Language English
    Publishing date 2022-08-18
    Publishing country New Zealand
    Document type Journal Article
    ZDB-ID 2455848-5
    ISSN 1177-889X
    ISSN 1177-889X
    DOI 10.2147/PPA.S367443
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

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  7. Article ; Online: Comment on: "Safety of Marketed Cancer Supportive Care Biosimilars in the U.S.: A Disproportionality Analysis Using the Food and Drug Administration Adverse Event Reporting System (FAERS) Database".

    Putzke, Joerg / Haughie, Scott / Zou, Kelly H / Ranganna, Gopinath M

    BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy

    2021  Volume 35, Issue 3, Page(s) 373–374

    MeSH term(s) Adverse Drug Reaction Reporting Systems ; Biosimilar Pharmaceuticals/adverse effects ; Databases, Factual ; Humans ; Neoplasms/drug therapy ; United States ; United States Food and Drug Administration
    Chemical Substances Biosimilar Pharmaceuticals
    Language English
    Publishing date 2021-04-16
    Publishing country New Zealand
    Document type Letter ; Comment
    ZDB-ID 1364202-9
    ISSN 1179-190X ; 1173-8804
    ISSN (online) 1179-190X
    ISSN 1173-8804
    DOI 10.1007/s40259-021-00476-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4112: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: Professor Charles E. Metz leaves profound legacy in ROC methodology: an introduction to the two Metz Memorial Issues.

    Zou, Kelly H

    Academic radiology

    2012  Volume 19, Issue 12, Page(s) 1447–1448

    MeSH term(s) History, 20th Century ; Humans ; ROC Curve ; Radiology/history ; United States
    Language English
    Publishing date 2012-12
    Publishing country United States
    Document type Biography ; Historical Article ; Journal Article
    ZDB-ID 1355509-1
    ISSN 1878-4046 ; 1076-6332
    ISSN (online) 1878-4046
    ISSN 1076-6332
    DOI 10.1016/j.acra.2012.09.010
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4594: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  9. Article: Real world data: an opportunity to supplement existing evidence for the use of long-established medicines in health care decision making.

    Katkade, Vaibhav B / Sanders, Kafi N / Zou, Kelly H

    Journal of multidisciplinary healthcare

    2018  Volume 11, Page(s) 295–304

    Abstract: Evidence from medication use in the real world setting can help to extrapolate and/or augment data obtained in randomized controlled trials and establishes a broad picture of a medication's place in everyday clinical practice. By supplementing and ... ...

    Abstract Evidence from medication use in the real world setting can help to extrapolate and/or augment data obtained in randomized controlled trials and establishes a broad picture of a medication's place in everyday clinical practice. By supplementing and complementing safety and efficacy data obtained in a narrowly defined (and often optimized) patient population in the clinical trial setting, real world evidence (RWE) may provide stakeholders with valuable information about the safety and effectiveness of a medication in large, heterogeneous populations. RWE is emerging as a credible information source; however, there is scope for enhancements to real world data (RWD) sources by understanding their complexities and applying the most appropriate analytical tools in order to extract relevant information. In addition to providing information for clinicians, RWE has the potential to meet the burden of evidence for regulatory considerations and may be used in approval of new indications for medications. Further understanding of RWD collection and analysis is needed if RWE is to achieve its full potential.
    Language English
    Publishing date 2018-07-02
    Publishing country New Zealand
    Document type Journal Article
    ZDB-ID 2453343-9
    ISSN 1178-2390
    ISSN 1178-2390
    DOI 10.2147/JMDH.S160029
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Considerations for Conducting Bring Your Own "Device" (BYOD) Clinical Studies.

    Demanuele, Charmaine / Lokker, Cynthia / Jhaveri, Krishna / Georgiev, Pirinka / Sezgin, Emre / Geoghegan, Cindy / Zou, Kelly H / Izmailova, Elena / McCarthy, Marie

    Digital biomarkers

    2022  Volume 6, Issue 2, Page(s) 47–60

    Abstract: Background: Digital health technologies are attracting attention as novel tools for data collection in clinical research. They present alternative methods compared to in-clinic data collection, which often yields snapshots of the participants' ... ...

    Abstract Background: Digital health technologies are attracting attention as novel tools for data collection in clinical research. They present alternative methods compared to in-clinic data collection, which often yields snapshots of the participants' physiology, behavior, and function that may be prone to biases and artifacts, e.g., white coat hypertension, and not representative of the data in free-living conditions. Modern digital health technologies equipped with multi-modal sensors combine different data streams to derive comprehensive endpoints that are important to study participants and are clinically meaningful. Used for data collection in clinical trials, they can be deployed as provisioned products where technology is given at study start or in a bring your own "device" (BYOD) manner where participants use their technologies to generate study data.
    Summary: The BYOD option has the potential to be more user-friendly, allowing participants to use technologies that they are familiar with, ensuring better participant compliance, and potentially reducing the bias that comes with introducing new technologies. However, this approach presents different technical, operational, regulatory, and ethical challenges to study teams. For example, BYOD data can be more heterogeneous, and recruiting historically underrepresented populations with limited access to technology and the internet can be challenging. Despite the rapid increase in digital health technologies for clinical and healthcare research, BYOD use in clinical trials is limited, and regulatory guidance is still evolving.
    Key messages: We offer considerations for academic researchers, drug developers, and patient advocacy organizations on the design and deployment of BYOD models in clinical research. These considerations address: (1) early identification and engagement with internal and external stakeholders; (2) study design including informed consent and recruitment strategies; (3) outcome, endpoint, and technology selection; (4) data management including compliance and data monitoring; (5) statistical considerations to meet regulatory requirements. We believe that this article acts as a primer, providing insights into study design and operational requirements to ensure the successful implementation of BYOD clinical studies.
    Language English
    Publishing date 2022-07-04
    Publishing country Switzerland
    Document type Journal Article ; Review
    ISSN 2504-110X
    ISSN (online) 2504-110X
    DOI 10.1159/000525080
    Database MEDical Literature Analysis and Retrieval System OnLINE

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