Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
360 participants
INTERVENTIONAL
2023-06-15
2026-01-31
Brief Summary
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Detailed Description
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The overarching goal of this current trial is to expand the application of the BE informed nudges, which includes a Best Practice Advisory (BPA) and Electronic Decision Support Tool (e-CDS) approach, which has been operationalized within Epic, the EHR used at UPHS, to six satellite hospitals. Our central hypothesis is that this approach will dramatically increase adoption of comprehensive molecular testing and enhance the delivery of molecularly informed 1L therapy in patients with newly diagnosed mNSq NSCLC.
Intervention: A multicomponent BE-informed EHR-based nudge designed to facilitate comprehensive molecular testing by embedding a default P-NGS order into the EHR at the time of the NPV. If ordered, test results are incorporated into provider workflows and conveyed through electronic clinical decision support (e-CDS) notifications. This support program will notify clinicians of targetable mutations, potential clinical trials, as well as absence of mutations detected on plasma testing as a means of improving the timely delivery of molecularly informed therapy.
Study Design
Objective 1: In a stepped wedge cluster randomized trial of newly diagnosed patients with mNSq NSCLC, evaluate the effectiveness of a multicomponent BE-informed EHR-based nudge intervention at increasing timely receipt of comprehensive molecular test results prior to 1L therapy by incorporating P-NGS into the standard clinical workup.
The design of this trial will include 3 clusters, representing 6 community hospitals. There will be an initial period in which no clusters are exposed to the intervention. Subsequently, at regular intervals (the "steps") one cluster (or a group of clusters) will be randomized to cross from the control to the intervention under evaluation. This process will continue until all clusters have crossed over to be exposed to the intervention. At the end of the study there will be a period when all clusters are exposed. Data collection will continue throughout the study, so that each cluster will contribute observations under both control and intervention observation periods. Two years of baseline data will be obtained from all study sites for comparison.
Objective 2: Assess the contextual mechanisms influencing the adoption, reach, and effectiveness of EHR-based nudge interventions, with a lens for health equity in molecular testing using mixed-methods.
Using rigorous approaches proven successful in our prior work, we will recruit patient and clinician participants from each site to complete semi-structured interviews and structured questionnaires. The goal of this objective is to understand contextual mechanisms (e.g., patient, clinician, clinic, structural factors) shaping adoption, reach, and effectiveness of each intervention and identify how response may differ by key characteristics. These data will be analyzed using convergent mixed methods analysis, which employs the simultaneous collection and analysis of both quantitative and qualitative data to gain a comprehensive understanding of the multi-level factors shaping trial outcomes.
Conditions
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Study Design
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RANDOMIZED
SEQUENTIAL
HEALTH_SERVICES_RESEARCH
NONE
Study Groups
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Penn Medicine New Jersey
All sites with be randomized to implement the nudge at different points in time. Prospective data with be compared with each site's respective baseline numbers over a two-year period.
iNUDGE
Electronic health record nudge which prompts physicians to order plasma-based NGS testing for eligible patients with newly diagnosed lung cancer.
Penn Medicine Lancaster General Health
All sites with be randomized to implement the nudge at different points in time. Prospective data with be compared with each site's respective baseline numbers over a two-year period.
iNUDGE
Electronic health record nudge which prompts physicians to order plasma-based NGS testing for eligible patients with newly diagnosed lung cancer.
Penn Presbyterian Medical Center
All sites with be randomized to implement the nudge at different points in time. Prospective data with be compared with each site's respective baseline numbers over a two-year period.
iNUDGE
Electronic health record nudge which prompts physicians to order plasma-based NGS testing for eligible patients with newly diagnosed lung cancer.
Interventions
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iNUDGE
Electronic health record nudge which prompts physicians to order plasma-based NGS testing for eligible patients with newly diagnosed lung cancer.
Eligibility Criteria
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Inclusion Criteria
* Participants must be seen at Lancaster General Health (LGH), Penn Presbyterian Medical Center (PPMC), Penn Medicine Cherry Hill (PMCH), Penn Medicine Princeton Health (PMPH), Penn Medicine Voorhees (PMV) or Penn Medicine Washington Township (PMWT) for mNSq NSCLC.
Exclusion Criteria
* Children, pregnant women, fetuses, neonates, or prisoners are not included in this research study.
ALL
No
Sponsors
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Eli Lilly and Company
INDUSTRY
Charu Aggarwal
OTHER
Responsible Party
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Charu Aggarwal
Leslye M. Heisler Associate Professor of Lung Cancer Excellence and Associate Director, Penn Center for Precision Medicine
Principal Investigators
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Charu Aggarwal, MD, MPH
Role: PRINCIPAL_INVESTIGATOR
Penn Medicine
Locations
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Penn Medicine Cherry Hill
Cherry Hill, New Jersey, United States
Penn Medicine Princeton Health
Plainsboro, New Jersey, United States
Penn Medicine Washington Township
Sewell, New Jersey, United States
Penn Medicine Voorhees
Voorhees Township, New Jersey, United States
Penn Medicine Lancaster General Health
Lancaster, Pennsylvania, United States
Penn Presbyterian Medical Center
Philadelphia, Pennsylvania, United States
Countries
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Central Contacts
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Facility Contacts
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Shayma Kazmi, MD
Role: primary
Ramy Sedhom, MD
Role: primary
Shayma Kazmi, MD
Role: primary
Shayma Kazmi, MD
Role: primary
Samuel J Kerr, MD
Role: primary
Christopher A D'Avella, MD
Role: primary
Christine Ciunci, MD
Role: backup
References
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Aggarwal C, Rolfo CD, Oxnard GR, Gray JE, Sholl LM, Gandara DR. Strategies for the successful implementation of plasma-based NSCLC genotyping in clinical practice. Nat Rev Clin Oncol. 2021 Jan;18(1):56-62. doi: 10.1038/s41571-020-0423-x. Epub 2020 Sep 11.
Rolfo C, Mack P, Scagliotti GV, Aggarwal C, Arcila ME, Barlesi F, Bivona T, Diehn M, Dive C, Dziadziuszko R, Leighl N, Malapelle U, Mok T, Peled N, Raez LE, Sequist L, Sholl L, Swanton C, Abbosh C, Tan D, Wakelee H, Wistuba I, Bunn R, Freeman-Daily J, Wynes M, Belani C, Mitsudomi T, Gandara D. Liquid Biopsy for Advanced NSCLC: A Consensus Statement From the International Association for the Study of Lung Cancer. J Thorac Oncol. 2021 Oct;16(10):1647-1662. doi: 10.1016/j.jtho.2021.06.017. Epub 2021 Jul 8.
Robert NJ, Espirito JL, Chen L, Nwokeji E, Karhade M, Evangelist M, Spira A, Neubauer M, Bullock S, Walberg J, Cheng SK, Coleman RL. Biomarker testing and tissue journey among patients with metastatic non-small cell lung cancer receiving first-line therapy in The US Oncology Network. Lung Cancer. 2022 Apr;166:197-204. doi: 10.1016/j.lungcan.2022.03.004. Epub 2022 Mar 10.
Singal G, Miller PG, Agarwala V, Li G, Kaushik G, Backenroth D, Gossai A, Frampton GM, Torres AZ, Lehnert EM, Bourque D, O'Connell C, Bowser B, Caron T, Baydur E, Seidl-Rathkopf K, Ivanov I, Alpha-Cobb G, Guria A, He J, Frank S, Nunnally AC, Bailey M, Jaskiw A, Feuchtbaum D, Nussbaum N, Abernethy AP, Miller VA. Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a Clinicogenomic Database. JAMA. 2019 Apr 9;321(14):1391-1399. doi: 10.1001/jama.2019.3241.
Thompson JC, Yee SS, Troxel AB, Savitch SL, Fan R, Balli D, Lieberman DB, Morrissette JD, Evans TL, Bauml J, Aggarwal C, Kosteva JA, Alley E, Ciunci C, Cohen RB, Bagley S, Stonehouse-Lee S, Sherry VE, Gilbert E, Langer C, Vachani A, Carpenter EL. Detection of Therapeutically Targetable Driver and Resistance Mutations in Lung Cancer Patients by Next-Generation Sequencing of Cell-Free Circulating Tumor DNA. Clin Cancer Res. 2016 Dec 1;22(23):5772-5782. doi: 10.1158/1078-0432.CCR-16-1231. Epub 2016 Sep 6.
Leighl NB, Page RD, Raymond VM, Daniel DB, Divers SG, Reckamp KL, Villalona-Calero MA, Dix D, Odegaard JI, Lanman RB, Papadimitrakopoulou VA. Clinical Utility of Comprehensive Cell-free DNA Analysis to Identify Genomic Biomarkers in Patients with Newly Diagnosed Metastatic Non-small Cell Lung Cancer. Clin Cancer Res. 2019 Aug 1;25(15):4691-4700. doi: 10.1158/1078-0432.CCR-19-0624. Epub 2019 Apr 15.
Whitaker RG, Sperber N, Baumgartner M, Thiem A, Cragun D, Damschroder L, Miech EJ, Slade A, Birken S. Coincidence analysis: a new method for causal inference in implementation science. Implement Sci. 2020 Dec 11;15(1):108. doi: 10.1186/s13012-020-01070-3.
Aggarwal C, Thompson JC, Black TA, Katz SI, Fan R, Yee SS, Chien AL, Evans TL, Bauml JM, Alley EW, Ciunci CA, Berman AT, Cohen RB, Lieberman DB, Majmundar KS, Savitch SL, Morrissette JJD, Hwang WT, Elenitoba-Johnson KSJ, Langer CJ, Carpenter EL. Clinical Implications of Plasma-Based Genotyping With the Delivery of Personalized Therapy in Metastatic Non-Small Cell Lung Cancer. JAMA Oncol. 2019 Feb 1;5(2):173-180. doi: 10.1001/jamaoncol.2018.4305.
Shelton RC, Chambers DA, Glasgow RE. An Extension of RE-AIM to Enhance Sustainability: Addressing Dynamic Context and Promoting Health Equity Over Time. Front Public Health. 2020 May 12;8:134. doi: 10.3389/fpubh.2020.00134. eCollection 2020.
Rendle KA, Abramson CM, Garrett SB, Halley MC, Dohan D. Beyond exploratory: a tailored framework for designing and assessing qualitative health research. BMJ Open. 2019 Aug 27;9(8):e030123. doi: 10.1136/bmjopen-2019-030123.
Kane H, Lewis MA, Williams PA, Kahwati LC. Using qualitative comparative analysis to understand and quantify translation and implementation. Transl Behav Med. 2014 Jun;4(2):201-8. doi: 10.1007/s13142-014-0251-6.
Provided Documents
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Document Type: Study Protocol: Revised iNUDGE Protocol 04.08.2025
Document Type: Study Protocol and Statistical Analysis Plan: Original Protocol 03.24.2023
Document Type: Statistical Analysis Plan: iNUDGE Statistical Analysis Plan 04.30.2025
Other Identifiers
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852795
Identifier Type: OTHER
Identifier Source: secondary_id
UPCC 27522
Identifier Type: -
Identifier Source: org_study_id
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