N
Nathan C. Nussbaum
Researcher at New York University
Publications - 24
Citations - 929
Nathan C. Nussbaum is an academic researcher from New York University. The author has contributed to research in topics: Cancer & Lung cancer. The author has an hindex of 7, co-authored 23 publications receiving 454 citations. Previous affiliations of Nathan C. Nussbaum include Duke University.
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Journal ArticleDOI
Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a Clinicogenomic Database
Gaurav Singal,Gaurav Singal,Peter Miller,Vineeta Agarwala,Gerald Li,Gaurav Kaushik,Daniel Backenroth,Anala Gossai,Garrett M. Frampton,Aracelis Z. Torres,Erik M. Lehnert,David Bourque,Claire O'Connell,Bryan Bowser,Thomas Caron,Ezra Baydur,Kathi Seidl-Rathkopf,Ivan Ivanov,Garrett Alpha-Cobb,Ameet Guria,Jie He,Shannon Frank,Allen C. Nunnally,Mark Bailey,Ann Jaskiw,Dana Feuchtbaum,Nathan C. Nussbaum,Amy P. Abernethy,Vincent A. Miller +28 more
TL;DR: Whether a database that combines EHR-derived clinical data with CGP can identify and extend associations in non–small cell lung cancer (NSCLC) can be identified and extended, and how this approach may accelerate precision medicine.
Journal ArticleDOI
Association of Broad-Based Genomic Sequencing With Survival Among Patients With Advanced Non-Small Cell Lung Cancer in the Community Oncology Setting.
Carolyn J Presley,Daiwei Tang,Pamela R. Soulos,Anne C. Chiang,Janina A. Longtine,Kerin B. Adelson,Roy S. Herbst,Weiwei Zhu,Nathan C. Nussbaum,Rachael Sorg,Vineeta Agarwala,Amy P. Abernethy,Cary P. Gross +12 more
TL;DR: Among patients with advanced non–small cell lung cancer receiving care in the community oncology setting, broad-based genomic sequencing directly informed treatment in a minority of patients and was not independently associated with better survival.
Posted Content
Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research.
Benjamin Birnbaum,Nathan C. Nussbaum,Katharina Nicola Seidl-Rathkopf,Monica Agrawal,Melissa Estevez,Evan Estola,Haimson Joshua D,He Lucy Dao-Ke,Peter Larson,Paul Richardson +9 more
TL;DR: Model-Ass Cohort Selection with bias analysis can significantly improve the efficiency of cohort selection on EHR data while instilling confidence that outcomes research performed on the resulting cohort will not be biased.
Journal ArticleDOI
Speed of Adoption of Immune Checkpoint Inhibitors of Programmed Cell Death 1 Protein and Comparison of Patient Ages in Clinical Practice vs Pivotal Clinical Trials.
Jeremy M. O’Connor,Kristen L Fessele,Jean Steiner,Kathi Seidl-Rathkopf,Kenneth R. Carson,Nathan C. Nussbaum,Emily S. Yin,Kerin B. Adelson,Carolyn J Presley,Anne C. Chiang,Joseph S. Ross,Amy P. Abernethy,Cary P. Gross +12 more
TL;DR: Overall, similar proportions of older and younger patients received anti–PD-1 agents treatment during the first 9 months after FDA approval, however, there were significant differences in age between clinical trial participants and patients receiving anti-PD- 1 agents treatment in clinical practice.
Journal ArticleDOI
Validation analysis of a composite real-world mortality endpoint for patients with cancer in the United States.
TL;DR: Across all cancer types analyzed, this composite mortality variable showed high sensitivity, specificity, PPV, NPV, and ±15‐day agreement, and yielded median rwOS values modestly overestimated when compared to NDI‐based results.