iNUDGE: Liquid Biopsy Based NGS in Newly Diagnosed NSCLC
Study Details
Study Description
Brief Summary
This study expands the application of an electronic health record (EHR) "nudge" used to prompt physicians' clinical practice to order molecular testing at the time of initial diagnosis for patients with specific types of advanced lung cancer. The primary goal is to have these test results available prior to starting treatment so that physicians can make molecularly-informed treatment decisions. The second goal is to better understand factors that contribute to whether or not the EHR-nudge implementation is successful.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
N/A |
Detailed Description
At the University of Pennsylvania Health System (UPHS), a behavioral economics (BE) informed "nudge" strategy was piloted to guide physicians' clinical practice to include concurrent use of plasma and tissue-based next generation sequencing (NGS) testing at the time of initial diagnosis for patients with newly diagnosed metastatic non-squamous (mNSq) non-small cell lung cancer (NSCLC). These findings have demonstrated that behavioral, electronic health record (EHR)-based nudges are feasible and can promote guideline concordant diagnostic testing at both community and academic sites. The overarching goal of this current trial is to expand the application of this BE informed nudge 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.
Molecular testing will be defined as i) comprehensive: EGFR, ALK, BRAF, ROS1, MET, RET, and NTRK testing, ii) incomplete: <6 genes tested, and iii) no testing performed. Clinically actionable mutations will be defined as an alteration in one of the seven genes on the comprehensive gene list with an FDA approved targeted therapy in the 1L setting, plus KRAS G12C, EGFR exon 20 insertion, and ErbB2 mutations. Molecularly informed first line therapy will be defined as one that is informed by results of NGS, obtained by plasma, tissue or both.
Intervention
An EHR-based nudge intervention that allows for default placement of a plasma based molecular genotyping order at time of the first new patient visit will be implemented. Subsequently, results detected on the default plasma NGS order will be conveyed to providers in the form of an electronic clinical decision support notification.
As part of the downstream EHR-based nudge intervention workflow, an electronic clinical decision support (e-CDS) system for alterations detected on plasma genotyping will be created and implemented into the EHR as a "Research (non-chargeable) Encounter" to alert the provider team caring for the patient. This support program will be created to notify clinicians of targetable mutations, 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 patients with newly diagnosed mNSq NSCLC, test the effectiveness of a behavioral economics (BE) informed EHR nudge intervention to increase timely receipt of comprehensive molecular test results before 1L therapy by integration of concurrent tissue and plasma molecular testing.
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: Evaluate contextual mechanisms contributing to the adoption, reach, and effectiveness of EHR nudge interventions with a lens for health equity.
Using rigorous approaches proven successful in our prior work, the investigators will recruit 10-15 patient and clinician participants from each site (estimated 40-60 participants total) to complete semi-structured interviews following the active trial period. 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 race and ethnicity, socioeconomic status, and other key social determinants of health. These data will be analyzed using qualitative comparative analysis, a mixed method approach well suited to identify mechanisms in pragmatic trials with smaller sample sizes.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Other: 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. |
Behavioral: iNUDGE
Electronic health record nudge which prompts physicians to order plasma-based NGS testing for eligible patients with newly diagnosed lung cancer.
|
| Other: 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. |
Behavioral: iNUDGE
Electronic health record nudge which prompts physicians to order plasma-based NGS testing for eligible patients with newly diagnosed lung cancer.
|
| Other: 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. |
Behavioral: iNUDGE
Electronic health record nudge which prompts physicians to order plasma-based NGS testing for eligible patients with newly diagnosed lung cancer.
|
Outcome Measures
Primary Outcome Measures
- Availability of comprehensive molecular test results prior to first line therapy for patients with newly diagnosed mNSq NSCLC [Measured up to 6 weeks from initial diagnosis]
Were comprehensive molecular test results available prior to initiation of 1L therapy? (Yes/No)
Secondary Outcome Measures
- Successful EHR based nudge delivery [Measured up to 6 weeks from randomization]
Amongst eligible patients, calculate the proportion of patients for whom the EHR nudge fired successfully (Yes/No). Applicable for the patients enrolled in the time periods following randomization.
- Turnaround time of delivery of provider focused alerts [Measured up to 6 weeks from randomization]
Reported as number of days, median. Applicable for the patients enrolled in the time periods following randomization.
- Completion of comprehensive molecular testing & modality used [Measured up to 3 months from initial diagnosis]
Relative and absolute change in completion of comprehensive testing by tissue and plasma, plasma alone, or tissue alone will be tabulated.
- Reasons for failure to complete comprehensive molecular testing: [Measured up to 3 months from initial diagnosis]
Summarize reasons for failure of completion of testing i. Tissue related (QNS) ii. Patient related factors (unable to biopsy, patient declined biopsy etc.) iii. Assay related factors (plasma assay does not detect mutations) iv. Other
- Time to molecularly informed treatment initiation [Measured up to 6 weeks from initial diagnosis]
i. Calculated as time to therapy from the date of diagnosis of Stage IV disease (date of biopsy) ii. Calculated as time to therapy from the date of first new patient visit with medical oncology
- Type of therapy received [Measured up to 3 months from initial diagnosis]
i. Targeted therapy ii. Chemo-immunotherapy iii. Immunotherapy iv. Clinical trial or n v. None
- Overall survival [Measured up to 1 year from the time of randomization to death from any cause]
i. Time from initial diagnosis to date of death or last follow up. ii. 1 year and 2-year overall survival rates will be calculated for the intervention group, and compared to baseline.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Participants with a histological, or cytological diagnosis of metastatic non-squamous (mNSq) non-small cell lung cancer (NSCLC) who have not yet received systemic treatment for metastatic disease.
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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:
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Participants with incomplete staging information.
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Children, pregnant women, fetuses, neonates, or prisoners are not included in this research study.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Penn Medicine Cherry Hill | Cherry Hill | New Jersey | United States | 08003 |
| 2 | Penn Medicine Princeton Health | Plainsboro | New Jersey | United States | 08536 |
| 3 | Penn Medicine Washington Township | Sewell | New Jersey | United States | 08080 |
| 4 | Penn Medicine Voorhees | Voorhees | New Jersey | United States | 08043 |
| 5 | Penn Medicine Lancaster General Health | Lancaster | Pennsylvania | United States | 17602 |
| 6 | Penn Presbyterian Medical Center | Philadelphia | Pennsylvania | United States | 19104 |
Sponsors and Collaborators
- Charu Aggarwal
- Loxo Oncology, Inc.
Investigators
- Principal Investigator: Charu Aggarwal, MD, MPH, Penn Medicine
Study Documents (Full-Text)
More Information
Publications
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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. Erratum In: JAMA. 2020 Feb 4;323(5):480.
- 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.
- 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. Erratum In: Implement Sci. 2021 Jan 12;16(1):11.
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