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  1. Article ; Online: Principled estimation and evaluation of treatment effect heterogeneity: A case study application to dabigatran for patients with atrial fibrillation.

    Xu, Yizhe / Bechler, Katelyn / Callahan, Alison / Shah, Nigam

    Journal of biomedical informatics

    2023  Volume 143, Page(s) 104420

    Abstract: Objective: To apply the latest guidance for estimating and evaluating heterogeneous treatment effects (HTEs) in an end-to-end case study of the Long-term Anticoagulation Therapy (RE-LY) trial, and summarize the main takeaways from applying state-of-the- ... ...

    Abstract Objective: To apply the latest guidance for estimating and evaluating heterogeneous treatment effects (HTEs) in an end-to-end case study of the Long-term Anticoagulation Therapy (RE-LY) trial, and summarize the main takeaways from applying state-of-the-art metalearners and novel evaluation metrics in-depth to inform their applications to personalized care in biomedical research.
    Methods: Based on the characteristics of the RE-LY data, we selected four metalearners (S-learner with Lasso, X-learner with Lasso, R-learner with random survival forest and Lasso, and causal survival forest) to estimate the HTEs of dabigatran. For the outcomes of (1) stroke or systemic embolism and (2) major bleeding, we compared dabigatran 150 mg, dabigatran 110 mg, and warfarin. We assessed the overestimation of treatment heterogeneity by the metalearners via a global null analysis and their discrimination and calibration ability using two novel metrics: rank-weighted average treatment effects (RATE) and estimated calibration error for treatment heterogeneity. Finally, we visualized the relationships between estimated treatment effects and baseline covariates using partial dependence plots.
    Results: The RATE metric suggested that either the applied metalearners had poor performance of estimating HTEs or there was no treatment heterogeneity for either the stroke/SE or major bleeding outcome of any treatment comparison. Partial dependence plots revealed that several covariates had consistent relationships with the treatment effects estimated by multiple metalearners. The applied metalearners showed differential performance across outcomes and treatment comparisons, and the X- and R-learners yielded smaller calibration errors than the others.
    Conclusions: HTE estimation is difficult, and a principled estimation and evaluation process is necessary to provide reliable evidence and prevent false discoveries. We have demonstrated how to choose appropriate metalearners based on specific data properties, applied them using the off-the-shelf implementation tool survlearners, and evaluated their performance using recently defined formal metrics. We suggest that clinical implications should be drawn based on the common trends across the applied metalearners.
    MeSH term(s) Humans ; Anticoagulants/pharmacology ; Anticoagulants/therapeutic use ; Atrial Fibrillation/drug therapy ; Dabigatran/therapeutic use ; Hemorrhage/complications ; Hemorrhage/drug therapy ; Stroke/drug therapy ; Clinical Trials as Topic
    Chemical Substances Anticoagulants ; Dabigatran (I0VM4M70GC)
    Language English
    Publishing date 2023-06-14
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2057141-0
    ISSN 1532-0480 ; 1532-0464
    ISSN (online) 1532-0480
    ISSN 1532-0464
    DOI 10.1016/j.jbi.2023.104420
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Re: "Utilizing 3D-Printed Orbital Floor Stamps to Create Patient-Specific Implants for Orbital Floor Reconstruction".

    Callahan, Alison B / Kazim, Michael

    Ophthalmic plastic and reconstructive surgery

    2020  Volume 36, Issue 5, Page(s) 519

    MeSH term(s) Humans ; Orbit/diagnostic imaging ; Orbit/surgery ; Orbital Fractures ; Printing, Three-Dimensional ; Prostheses and Implants
    Language English
    Publishing date 2020-08-31
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 632830-1
    ISSN 1537-2677 ; 0740-9303
    ISSN (online) 1537-2677
    ISSN 0740-9303
    DOI 10.1097/IOP.0000000000001789
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: APLUS: A Python library for usefulness simulations of machine learning models in healthcare.

    Wornow, Michael / Gyang Ross, Elsie / Callahan, Alison / Shah, Nigam H

    Journal of biomedical informatics

    2023  Volume 139, Page(s) 104319

    Abstract: Despite the creation of thousands of machine learning (ML) models, the promise of improving patient care with ML remains largely unrealized. Adoption into clinical practice is lagging, in large part due to disconnects between how ML practitioners ... ...

    Abstract Despite the creation of thousands of machine learning (ML) models, the promise of improving patient care with ML remains largely unrealized. Adoption into clinical practice is lagging, in large part due to disconnects between how ML practitioners evaluate models and what is required for their successful integration into care delivery. Models are just one component of care delivery workflows whose constraints determine clinicians' abilities to act on models' outputs. However, methods to evaluate the usefulness of models in the context of their corresponding workflows are currently limited. To bridge this gap we developed APLUS, a reusable framework for quantitatively assessing via simulation the utility gained from integrating a model into a clinical workflow. We describe the APLUS simulation engine and workflow specification language, and apply it to evaluate a novel ML-based screening pathway for detecting peripheral artery disease at Stanford Health Care.
    MeSH term(s) Humans ; Computer Simulation ; Delivery of Health Care ; Workflow ; Machine Learning ; Language
    Language English
    Publishing date 2023-02-13
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
    ZDB-ID 2057141-0
    ISSN 1532-0480 ; 1532-0464
    ISSN (online) 1532-0480
    ISSN 1532-0464
    DOI 10.1016/j.jbi.2023.104319
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Selumetinib in the Treatment of Orbital Plexiform Neurofibroma: A Case Report.

    Dai, Yi Ling / Choi, Catherine S / Wiltsie, Laura / Callahan, Alison B

    Ophthalmic plastic and reconstructive surgery

    2023  Volume 39, Issue 3, Page(s) e75–e78

    Abstract: A 4-year-old boy with a known diagnosis of neurofibromatosis 1 (NF1) and a diffusely infiltrative plexiform neurofibroma (PN) of the left orbit was started on selumetinib treatment for progressively worsening amblyopia. The patient first presented with ... ...

    Abstract A 4-year-old boy with a known diagnosis of neurofibromatosis 1 (NF1) and a diffusely infiltrative plexiform neurofibroma (PN) of the left orbit was started on selumetinib treatment for progressively worsening amblyopia. The patient first presented with new-onset left ptosis at 11 months old. He subsequently developed refractory anisometropic amblyopia of the left eye, in addition to clinically significant left proptosis and hypoglobus that interfered with glasses wear for his amblyopia treatment. The plexiform neurofibroma was not amenable to surgical resection and selumetinib treatment was initiated 3 years after the initial diagnosis. The patient showed remarkable clinical and radiographic improvement in tumor burden after treatment. Best corrected visual acuity improved from 20/50 to 20/20- in his amblyopic eye. Relative proptosis of the affected eye also improved from 4mm to 2mm on Hertel measurements, which allowed for consistent glasses wear. Adverse effects from the treatment were limited to an acneiform rash, which resolved following dose reduction according to the FDA dosing guidelines.
    MeSH term(s) Male ; Humans ; Child, Preschool ; Infant ; Amblyopia ; Neurofibroma, Plexiform/complications ; Neurofibroma, Plexiform/diagnosis ; Neurofibroma, Plexiform/drug therapy ; Neurofibromatosis 1/complications ; Neurofibromatosis 1/diagnosis ; Neurofibromatosis 1/drug therapy ; Exophthalmos
    Chemical Substances AZD 6244
    Language English
    Publishing date 2023-02-21
    Publishing country United States
    Document type Case Reports ; Journal Article
    ZDB-ID 632830-1
    ISSN 1537-2677 ; 0740-9303
    ISSN (online) 1537-2677
    ISSN 0740-9303
    DOI 10.1097/IOP.0000000000002330
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: A Second Opinion From Observational Data on Second-line Diabetes Drugs.

    Callahan, Alison / Shah, Nigam H

    JAMA network open

    2018  Volume 1, Issue 8, Page(s) e186119

    MeSH term(s) Adult ; Cardiovascular Diseases ; Diabetes Mellitus, Type 2 ; Humans ; Hypoglycemic Agents ; Referral and Consultation
    Chemical Substances Hypoglycemic Agents
    Language English
    Publishing date 2018-12-07
    Publishing country United States
    Document type Journal Article ; Comment
    ISSN 2574-3805
    ISSN (online) 2574-3805
    DOI 10.1001/jamanetworkopen.2018.6119
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Research and Reporting Considerations for Observational Studies Using Electronic Health Record Data.

    Callahan, Alison / Shah, Nigam H / Chen, Jonathan H

    Annals of internal medicine

    2020  Volume 172, Issue 11 Suppl, Page(s) S79–S84

    Abstract: Electronic health records (EHRs) are an increasingly important source of real-world health care data for observational research. Analyses of data collected for purposes other than research require careful consideration of data quality as well as the ... ...

    Abstract Electronic health records (EHRs) are an increasingly important source of real-world health care data for observational research. Analyses of data collected for purposes other than research require careful consideration of data quality as well as the general research and reporting principles relevant to observational studies. The core principles for observational research in general also apply to observational research using EHR data, and these are well addressed in prior literature and guidelines. This article provides additional recommendations for EHR-based research. Considerations unique to EHR-based studies include assessment of the accuracy of computer-executable cohort definitions that can incorporate unstructured data from clinical notes and management of data challenges, such as irregular sampling, missingness, and variation across time and place. Principled application of existing research and reporting guidelines alongside these additional considerations will improve the quality of EHR-based observational studies.
    MeSH term(s) Data Collection ; Electronic Health Records/standards ; Humans ; Observational Studies as Topic/statistics & numerical data ; Primary Health Care/statistics & numerical data
    Language English
    Publishing date 2020-06-01
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Review
    ZDB-ID 336-0
    ISSN 1539-3704 ; 0003-4819
    ISSN (online) 1539-3704
    ISSN 0003-4819
    DOI 10.7326/M19-0873
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Underestimated Recurrence Rates after Ablation for Wolff-Parkinson-White Syndrome and Impact on Follow-up Practices.

    Burke, Brendan J / El Assaad, Iqbal / Liu, Wei / Kanj, Mohamed / Wazni, Oussama M / Callahan, Thomas D / Baranowski, Bryan / Saarel, Elizabeth V / Heilbronner, Alison / Aziz, Peter F

    Heart rhythm

    2024  

    Language English
    Publishing date 2024-04-23
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2229357-7
    ISSN 1556-3871 ; 1547-5271
    ISSN (online) 1556-3871
    ISSN 1547-5271
    DOI 10.1016/j.hrthm.2024.04.071
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: A Nationwide Network of Health AI Assurance Laboratories.

    Shah, Nigam H / Halamka, John D / Saria, Suchi / Pencina, Michael / Tazbaz, Troy / Tripathi, Micky / Callahan, Alison / Hildahl, Hailey / Anderson, Brian

    JAMA

    2023  Volume 331, Issue 3, Page(s) 245–249

    Abstract: Importance: Given the importance of rigorous development and evaluation standards needed of artificial intelligence (AI) models used in health care, nationwide accepted procedures to provide assurance that the use of AI is fair, appropriate, valid, ... ...

    Abstract Importance: Given the importance of rigorous development and evaluation standards needed of artificial intelligence (AI) models used in health care, nationwide accepted procedures to provide assurance that the use of AI is fair, appropriate, valid, effective, and safe are urgently needed.
    Observations: While there are several efforts to develop standards and best practices to evaluate AI, there is a gap between having such guidance and the application of such guidance to both existing and new AI models being developed. As of now, there is no publicly available, nationwide mechanism that enables objective evaluation and ongoing assessment of the consequences of using health AI models in clinical care settings.
    Conclusion and relevance: The need to create a public-private partnership to support a nationwide health AI assurance labs network is outlined here. In this network, community best practices could be applied for testing health AI models to produce reports on their performance that can be widely shared for managing the lifecycle of AI models over time and across populations and sites where these models are deployed.
    MeSH term(s) Artificial Intelligence/standards ; Health Facilities/standards ; Laboratories/standards ; Public-Private Sector Partnerships ; Quality Assurance, Health Care/standards ; Delivery of Health Care/standards ; Quality of Health Care/standards ; United States
    Language English
    Publishing date 2023-12-20
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2958-0
    ISSN 1538-3598 ; 0254-9077 ; 0002-9955 ; 0098-7484
    ISSN (online) 1538-3598
    ISSN 0254-9077 ; 0002-9955 ; 0098-7484
    DOI 10.1001/jama.2023.26930
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Exploring the potential utility of AI large language models for medical ethics: an expert panel evaluation of GPT-4.

    Balas, Michael / Wadden, Jordan Joseph / Hébert, Philip C / Mathison, Eric / Warren, Marika D / Seavilleklein, Victoria / Wyzynski, Daniel / Callahan, Alison / Crawford, Sean A / Arjmand, Parnian / Ing, Edsel B

    Journal of medical ethics

    2024  Volume 50, Issue 2, Page(s) 90–96

    Abstract: Integrating large language models (LLMs) like GPT-4 into medical ethics is a novel concept, and understanding the effectiveness of these models in aiding ethicists with decision-making can have significant implications for the healthcare sector. Thus, ... ...

    Abstract Integrating large language models (LLMs) like GPT-4 into medical ethics is a novel concept, and understanding the effectiveness of these models in aiding ethicists with decision-making can have significant implications for the healthcare sector. Thus, the objective of this study was to evaluate the performance of GPT-4 in responding to complex medical ethical vignettes and to gauge its utility and limitations for aiding medical ethicists. Using a mixed-methods, cross-sectional survey approach, a panel of six ethicists assessed LLM-generated responses to eight ethical vignettes.The main outcomes measured were relevance, reasoning, depth, technical and non-technical clarity, as well as acceptability of GPT-4's responses. The readability of the responses was also assessed. Of the six metrics evaluating the effectiveness of GPT-4's responses, the overall mean score was 4.1/5. GPT-4 was rated highest in providing technical (4.7/5) and non-technical clarity (4.4/5), whereas the lowest rated metrics were depth (3.8/5) and acceptability (3.8/5). There was poor-to-moderate inter-rater reliability characterised by an intraclass coefficient of 0.54 (95% CI: 0.30 to 0.71). Based on panellist feedback, GPT-4 was able to identify and articulate key ethical issues but struggled to appreciate the nuanced aspects of ethical dilemmas and misapplied certain moral principles.This study reveals limitations in the ability of GPT-4 to appreciate the depth and nuanced acceptability of real-world ethical dilemmas, particularly those that require a thorough understanding of relational complexities and context-specific values. Ongoing evaluation of LLM capabilities within medical ethics remains paramount, and further refinement is needed before it can be used effectively in clinical settings.
    MeSH term(s) Humans ; Cross-Sectional Studies ; Reproducibility of Results ; Ethics, Medical ; Ethicists ; Problem Solving
    Language English
    Publishing date 2024-01-23
    Publishing country England
    Document type Journal Article
    ZDB-ID 194927-5
    ISSN 1473-4257 ; 0306-6800
    ISSN (online) 1473-4257
    ISSN 0306-6800
    DOI 10.1136/jme-2023-109549
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Lessons Learned from a Multi-Site, Team-Based Serious Illness Care Program Implementation at an Academic Medical Center.

    Seevaratnam, Briththa / Wang, Samantha / Fong, Rebecca / Hui, Felicia / Callahan, Alison / Chobot, Sarah / Gensheimer, Michael F / Li, Ron C / Nguyen, Duy / Ramchandran, Kavitha / Shah, Nigam H / Shieh, Lisa / Zeng, Jack Guo-Qing / Teuteberg, Winifred

    Journal of palliative medicine

    2023  Volume 27, Issue 1, Page(s) 83–89

    Abstract: Background: ...

    Abstract Background:
    MeSH term(s) Humans ; Critical Care ; Critical Illness/therapy ; Communication ; Physician-Patient Relations ; Academic Medical Centers
    Language English
    Publishing date 2023-11-08
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1427361-5
    ISSN 1557-7740 ; 1096-6218
    ISSN (online) 1557-7740
    ISSN 1096-6218
    DOI 10.1089/jpm.2023.0254
    Database MEDical Literature Analysis and Retrieval System OnLINE

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