Kelly Magee

RWD123 CUSTOMIZATION OF A LARGE LANGUAGE MODEL APPROACH TO CAPTURE PSA AND IMAGING DERIVED REAL-WORLD PROGRESSION EVENTS IN PROSTATE CANCER

Kelly Magee, Patrick Ward, Wanjing Chen, Eunice Hankinson et autres

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Ensuring Reliability of Curated Electronic Health Record–Derived Data: The Validation of Accuracy for Large Language Model–/Machine Learning–Extracted Information and Data (VALID) Framework

Melissa Soria Estévez, Nisha Singh, Lauren Dyson, Blythe Adamson et autres

Large language models (LLMs) are increasingly used to extract clinical data from electronic health records, offering significant improvements in scalability and efficiency for real-world data (RWD) curation in oncology. However, the adoption of LLMs introduces new challenges in ensuring the reliability, accuracy, …

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Beyond the clinical trial: Real-world treatment patterns and drivers of PD-(L)1 therapy use in first-line metastatic NSCLC

Siobhan Halloran, Salman R. Punekar, Mark Guinter, Kelly Magee et autres

BACKGROUND: Immunotherapies have improved survival in patients with metastatic non-small cell lung cancer (mNSCLC), yet a substantial fraction of eligible patients remain untreated with immunotherapy in routine clinical practice. This study examined treatment patterns and factors associated with receipt of non-immunotherapy-containing first-line …

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Abstract B006: Using large language models for scalable extraction of real-world progression events across multiple cancer types

Aaron Benjamin Cohen, Konstantin Krismer, Kelly Magee, James Gippetti et autres

Abstract Background: Accurate identification of cancer progression events from electronic health records (EHRs) can help enable promising oncology applications such as predicting disease trajectory, assessing treatment efficacy, and generating real-world evidence. These use cases require both large-scale and high-quality data but manual …

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MSR142 Performance Assessment and Validation of Real-World Response Data Generated Using a Deep Learning-Based Natural Language Processing Model Across Multiple Solid Tumors

Kelly Magee, Qianyu Yuan, Auriane Blarre, Aaron Benjamin Cohen et autres

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A retrospective real-world study of first-line PD-(L)1 inhibitor use in patients with metastatic non-small cell lung cancer (mNSCLC).

Kim R. Saverno, Siobhan Halloran, Mark A. Guinter, Kelly Magee et autres

e20563 Background: Programmed death ligand 1 (PD-[L]1) inhibitors such as retifanlimab have improved survival in patients with mNSCLC, yet these treatments may still be underutilized. This study examined treatment patterns and factors associated with selection of a PD-(L)1 inhibitor in first-line (1L) …

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Concordance of response-based clinical trial and machine learning–generated real-world end points.

Qianyi Zhang, Konstantin Krismer, Yichen Lu, Qianyu Yuan et autres

e13625 Background: Real-world evidence (RWE) is increasingly used to complement clinical trial data in oncology, providing rapid insights to inform study design and drug development. Using deep learning, natural language processing (NLP)-based machine learning models, we developed a real-world response (rwR) approach.This …

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Assessment of racial/ethnic inequities in uptake of PSMA-PET imaging among patients with metastatic prostate cancer in the United States.

Eunice Hankinson, Samantha Reiss, Patrick J. Ward, Brooke A. Jarrett et autres

e13739 Background: Prostate-Specific Membrane Antigen–Positron Emission Tomography (PSMA-PET) imaging has transformed the diagnosis and treatment of prostate cancer (PCa) since 2020 because it can detect smaller PCa lesions earlier than conventional imaging methods. Racial/ethnic inequities in PCa are well documented; yet, little …

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Analysis of Real-World Progression and Insufficient Response Variables and Related Endpoints Among Patients with Non-Hodgkin Lymphoma

Madeline Richey, Christina G. Fullerton, Qianyi Zhang, Tori Williams et autres

INTRODUCTION: Methods for assessing change in tumor burden differ between clinical trial and routine clinical care settings, presenting a unique opportunity to design novel methods to capture clinical outcomes from electronic health record (EHR) data. We adapted a previously established approach for …

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P2.11A.01 Racial/ethnic Differences in Real-World Adverse Events and Survival Among Patients on Immunotherapy for Advanced NSCLC

Gene Ho, Xiaowei Wang, K. Schwed, Aaron Dolor et autres

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MSR79 Evaluation of Real-World Response Rate in Clinical Trial-Aligned Cohorts of Patients With Lung, Colon, and Breast Cancer Using Machine Learning

Qiushi Zhang, Konstantin Krismer, Xiaofeng Wang, Cliff Fullerton et autres

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Response- and Progression-Based End Points in Trial and Observational Cohorts of Patients With NSCLC

Yichen Lu, Spencer S. Langerman, Emily McCain, Kelly Magee et autres

Importance: Response Evaluation Criteria in Solid Tumors (RECIST) are commonly used to assess therapeutic response in clinical trials but not in routine care; thus, RECIST-based end points are difficult to include in observational studies. Clinician-anchored approaches for measuring clinical response have been …

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