iNUDGE: INtegration of liqUiD Biopsy Based Next Generation Gene sEquencing in Newly Diagnosed NSCLC - A Stepped Wedge Cluster Randomized Clinical Trial
Phase: NA
Conditions: Non Small Cell Lung Cancer Metastatic, Newly Diagnosed NSCLC, Non-Squamous Non-Small Cell Neoplasm of Lung
Sponsor: Charu Aggarwal

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iNUDGE: INtegration of liqUiD biopsy based next generation Gene sEquencing in newly diagnosed 
NSCLC – A stepped wedge cluster randomized clinical trial  
Principal Investigator  
Co-investigators 
Funding Agency: 
IRB Protocol Number: 
UPCC Protocol Number: 
Version Date:  
Charu Aggarwal, MD, MPH 
10-137, South Pavilion 
3400 Civic Center Boulevard 
Philadelphia, PA 19104 
Tel: 215-662-6318 | Fax: 215-349-5326 
Penn Medicine 
Christopher D’ Avella, MD 
E. Paul Wileyto, PhD 
Katharine Rendle, PhD, MPH 
Melina Marmarelis, MD, MSCE 
Ramy Sedhom, MD 
Samuel Kerr, MD  
Shayma Kazmi, MD 
Eli Lilly 
27522 
852795 
4/8/2025  
 
 
 

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Table of Contents 
1. 
BACKGROUND AND RATIONALE ............................................................................. 3 
2. 
OBJECTIVES ................................................................................................................... 4 
2.1 
Primary Objectives ...................................................................................................... 4 
2.2 
Primary Outcomes ...................................................................................................... 4 
2.3 
Secondary Outcomes ................................................................................................. 4 
3. STUDY POPULATION ........................................................................................................... 4 
3.1 
Target Population ........................................................................................................ 4 
3.2 
Inclusion Criteria ......................................................................................................... 5 
3.3 Exclusion Criteria ............................................................................................................ 5 
3.4 Vulnerable Populations ................................................................................................. 5 
4. 
STUDY DESIGN............................................................................................................... 5 
4.1 
Preliminary Studies..................................................................................................... 5 
4.2 
Overview ........................................................................................................................ 5 
4.3 
Study Duration and Timeline .................................................................................... 9 
4.4 
Study Setting .............................................................................................................. 10 
5. 
STUDY PROCEDURES ................................................................................................ 10 
5.1 
Recruitment and Retention ..................................................................................... 10 
5.2 
Informed Consent ...................................................................................................... 11 
5.3 
Sources of Materials ................................................................................................. 12 
6. 
STATISTICAL DESIGN AND POWER ...................................................................... 12 
6.1 
Sample Size................................................................................................................. 12 
6.2 
Analysis Plan .............................................................................................................. 13 
7. 
RESOURCES NECESSARY FOR HUMAN RESEARCH PROTECTION ........... 14 
8. 
STUDY TEAM................................................................................................................. 15 
9. 
REFERENCES ............................................................................................................... 16 
10. 
APPENDICES................................................................................................................. 18 
 
 

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1. BACKGROUND AND RATIONALE 
The development of targeted therapies has changed the treatment paradigm for non–small cell 
lung cancer (NSCLC). With the growing number of FDA approved targeted therapies, current 
NCCN guidelines recommend comprehensive molecular genotyping, defined as detection of 
mutations in seven genes (EGFR, ALK, BRAF, ROS1, MET, RET, and NTRK) prior to first line 
(1L) therapy for all newly diagnosed patients with metastatic non-squamous (mNSq) NSCLC to 
enable the delivery of personalized therapy.1, 2 Furthermore, the emergence of immune-
checkpoint inhibitors has amplified the importance of molecular genotyping in the care of these 
patients because patients with actionable genomic alterations rarely respond to immunotherapy, 
even in the presence of high PD-L1 expression and should be preferentially treated with 
targeted therapy.3 In addition, there is a growing body of evidence that introduction of targeted 
tyrosine kinase inhibitors after immunotherapy may be associated with higher rates of immune 
related adverse events, even after discontinuation of immunotherapy.4 Additionally, in previous 
studies, amongst patients with a mutation in a NCCN-listed gene, exposure to targeted therapy 
has been shown to be associated with improved overall survival.5 Given these considerations, 
upfront tumor genotyping is now considered an essential step in guiding treatment decisions for 
all patients with mNSq NSCLC, prior to 1L therapy.  
Despite the critical importance of molecular testing in patients with advanced NSCLC, numerous 
barriers impede timely completion of testing prior to initiation of 1L systemic therapy.6-8 Common 
issues include insufficient tissue for testing, lack of infrastructure for obtaining and sending 
biopsy samples for testing, and unacceptably long turnaround times for results.9 These issues 
have created a critical need for additional convenient, and minimally invasive options for tumor 
genotyping.10, 11 We and others have previously demonstrated that the incorporation of 
concurrent plasma based next-generation gene sequencing (NGS), ordered at the same time as 
tissue NGS, improves detection of clinically actionable mutations in patients with advanced 
NSCLC.11  
At our institution, we piloted a behavioral economics (BE) informed “nudge” strategy to guide 
physicians’ clinical practice to include concurrent use of plasma and tissue-based NGS at initial 
diagnosis. This real-world cohort study was conducted at the Abramson Cancer Center and 2 
community sites within UPHS. Across the 3 practice sites, a provider team-focused Electronic 
Health Record (EHR) -based “nudge intervention” was designed to order plasma-based NGS at 
the time of new patient consultation. Eligible patients for the nudge were identified using an 
EHR based checklist, that included 3 criteria: i. new diagnosis, ii. treatment naïve, iii. mNSq 
NSCLC. Results from the intervention period (4/2021-12/2021) were compared to baseline data 
from similar patients treated at our institution between 01/2019 and 03/2021. Of the 526 patients 
with mNSq NSCLC that were included in the analysis: 381 were included in the pre-intervention 
cohort and 145 in the post-intervention cohort. After implementation of the EHR-based nudge, 
we observed that a higher proportion of patients underwent concurrent tissue + plasma testing 
in the post intervention cohort compared to pre-intervention 90.3% (131/145) vs. 68.8% 
(262/381), p<0.00001. Additionally, by virtue of having robust tissue + plasma testing 
performed, there were improved rates of comprehensive molecular genotyping in the post-
intervention cohort compared to pre-intervention, 98.6% (143/145) vs. 87.1% (332/381), 
p=0.00007. A greater proportion of patients had comprehensive genotyping available prior to 
1st-line therapy in the post-intervention vs. pre-intervention cohort (86.2% vs. 76.3%, p=0.013).  
These findings demonstrated that behavioral, 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 the BE informed nudges, which includes a 
Best Practice Advisory (BPA) and Electronic Decision Support Tool (e-CDS) approach, which 

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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 first-line therapy in patients 
with newly diagnosed metastatic non-squamous NSCLC. Molecular testing will be defined as i) 
comprehensive: EGFR, ALK, BRAF, ROS1, MET, RET, KRAS, Her2 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. 
 
2. OBJECTIVES 
2.1 Primary Objectives 
Objective 1: In a stepped wedge cluster randomized trial of patients with newly diagnosed 
metastatic NSCLC, test the effectiveness multicomponent BE informed EHR nudge intervention 
to increase timely receipt of comprehensive molecular test results before 1L therapy by 
integrating concurrent tissue and plasma-based molecular testing into the workup of newly 
diagnosed patients. Molecular testing will be defined as i) comprehensive: EGFR, ALK, BRAF, 
ROS1, MET, RET, KRAS, Her2 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. 
 
Objective 2: Evaluate contextual mechanisms contributing to the adoption, reach, and 
effectiveness of EHR nudge interventions with a lens for health equity. 
2.2 Primary Outcomes 
Objective 1: Availability of comprehensive molecular test results (as defined above) prior to first 
line therapy for patients with mNSq NSCLC. 
 
2.3 Secondary Outcomes 
Objective 1: 1) successful EHR-based nudge and e-CDS delivery, 2) turnaround time of delivery 
of provider focused alerts after receipt of plasma genotyping results, 3) completion of 
comprehensive molecular testing (tissue and/or plasma testing), 4) reasons for failure to 
complete comprehensive molecular testing (QNS or other), 5) time to molecularly-informed 
treatment initiation, 6) type of therapy received (targeted therapy, chemo-immunotherapy, 
immunotherapy, clinical trial or none) and 7) overall survival. 
Objective 2: Individual and contextual factors shaping adoption (provider-level ordering of 
molecular testing), reach (patient-level completion of molecular testing), and effectiveness 
(receipt of molecular testing), of interventions, guided by RE-AIM with Equity Extension 
Framework12. 
 
3. STUDY POPULATION 
3.1 Target Population 
This stepped wedge cluster randomized trial will be conducted across newly diagnosed patients 
with mNSq NSCLC treated at Penn Medicine that comprise 3 clusters (sites): 1) Lancaster 
General Health(LGH), 2) Penn – New Jersey (Princeton Medical Center (PMPH), Penn 

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Medicine at Cherry Hill (PMCH), Penn Medicine at Washington Township (PMWT), and Penn 
Medicine Voorhees (PMV)), and 3) Penn Presbyterian Medical Center (PPMC). 
 
3.2 Inclusion Criteria 
Objective 1 and Objective 2 - Patients 
a) Patients with histological, or cytological diagnosis of mNSq NSCLC who have not yet 
received systemic treatment for metastatic disease.  
b) Patients must have completed at least one medical oncology visit at one of the 
participating sites: LGH, PMPH, PMCH, PMWT, PMV, PPMC for mNSq NSCLC.  
 
Objective 2 – Clinicians 
a) All study site personnel involved in molecular testing, including but not limited to medical 
oncologists, advanced practice providers, registered nurses, phlebotomy and laboratory 
technician staff, and front desk staff  
3.3 Exclusion Criteria 
a) Incomplete staging information. 
 
3.4 Vulnerable Populations 
a) Children, pregnant women, fetuses, neonates, or prisoners are not included in this 
research study. 
 
4. STUDY DESIGN 
4.1 Preliminary Studies 
We have conducted two prior studies that inform the design of this trial. In the first, we evaluated 
the impact of plasma-based molecular testing in addition to tissue testing on the detection of 
actionable mutations in patients with metastatic NSCLC. In 229 patients who underwent 
concurrent plasma and tissue molecular testing, tissue alone detected targetable mutations in 
21% of patients, whereas addition of plasma testing increased targetable mutation detection to 
36%.11 Thus, plasma-based testing increased the rate of detection of therapeutically targetable 
alterations in metastatic NSCLC when used concurrently with tissue testing. In a second study, 
initiation of plasma-based testing, based on a BE informed EHR based nudge at time of new 
patient evaluation increased the proportion of patients undergoing concurrent tissue + plasma 
NGS testing to 90.3% (131/145) vs. 68.8% (262/381), p<0.00001(Aggarwal C et al, ASCO 
Quality Care Symposium, 2022). Thus, the proposed stepped wedge cluster randomized trial 
will examine effectiveness of this approach in a larger proportion of patients, reduce disparities 
in molecular testing, and target testing more optimally. 
 
4.2 Overview 
Objective 1: In a stepped wedge cluster randomized trial of patients with newly diagnosed 
mNSq NSCLC, test the effectiveness of a multicomponent BE informed EHR nudge intervention 
(as defined below)  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 the 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 

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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. 
 
Interventions: 
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 (Figure 1). 
Additionally, results detected on the default plasma NGS order will be conveyed to providers in 
the form of an electronic clinical decision support (e-CDS) notification (Figure 3). These 
interventions will be considered the multicomponent nudge intervention and will be tailored to 
the organizational needs of each cluster.  
 
Figure 1. EHR based nudge intervention workflow. 
1. The EHR-based nudge intervention will fire at the time of the first telephone encounter 
with a new patient coordinator (NPC) based on a set of pre-populated molecular 
questions (Supplemental eFigure 1) for all patients with a new diagnosis of mNSq 
NSCLC.  
2. The EHR-based nudge intervention will appear when the visit is opened within the 
electronic medical record by a provider and will allow default placement of a plasma-
based NGS order. Thoracic oncology providers can opt out of this order if they feel it is 
not appropriate for the patient or because other molecular testing has already been 
initiated/completed. Large gene panel (>50 genes) based plasma will be used, and be 
based on site preference.  
Standardization of the process will include availability of plasma kits at each of the sites LGH, 
PMPH, PMCH, PMWT, PMV, PPMC and clinical labs, and communication of the ordering 
process will be conveyed with the respective medical support teams (APP, RN) (Figure 2). 
Sites will be encouraged to choose one plasma-based assay to be used at their site in order to 
streamline order design.  
Figure 2. Current and proposed future workflow for plasma-NGS ordering. 

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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 (Supplemental eFigure 2). 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 and 
alerting providers to available clinical trials. 
 
Figure 3: Screening of plasma NGS reports and creation of e-CDS.  
 
1. The study team will review plasma NGS reports for therapeutically targetable alterations 
(based on NCCN recommended biomarkers including EGFR, ALK, ROS1, RET, MET, 
BRAF, KRAS, ErbB2 and NTRK) (Table 1). When identified, the research coordinator(s) 
will alert the internal review team (Drs. Aggarwal and Marmarelis).  
2. If deemed appropriate the research coordinator(s) will assemble and send an EHR-
based reflex alert with the information included in Figure 3 to the patient’s oncologist 
and associated APP. This alert will be created by the internal review team and will 
include information about the possible therapeutic options for this alteration including 
available clinical trials. 
3. To ensure that providers are reaching the most appropriate molecularly informed 
treatment decision, e-CDS alerts will be sent to providers even for mutations deemed not 
“therapeutically targetable” (i.e., STK11, TP53, etc.). 
4. Provider response to the e-CDS program, plan to prescribe targeted therapy as well as 
prescription of targeted therapy in response to a molecular alteration will be monitored to 

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determine provider engagement. Reasons for not prescribing targeted therapy will also 
be recorded, if available.  
Table 1. 
Gene 
Mutations 
Targeted Therapies 
EGFR 
Exon 19 del/ Exon 21 L858R 
Osimertinib 
EGFR 
Exon 18del/ins, E709A, G719A, G719C, 
G719R, G719S, Exon19del, Exon20Ins, 
T790M, S768I, C797S, L858R, L861Q 
Afatinib, Erlotinib, Gefitinib, Osimertinib, 
Dacomitinib, Amivantamab 
ALK 
EML-ALK fusion, F1174L, G1123S, G1202R, 
I1171S, I1171T, L1196Q 
Alectinib, Brigatinib, Ceritinib, Crizotinib, 
Lorlatinib 
ROS1 
Fusions 
Brigatinib, Ceritinib, Crizotinib, Entrectinib, 
Lorlatinib 
RET 
RET-KIF5B Fusion 
RET fusions with CCDC6, NCOA, TRIM33, 
CUX1, KIAA1217, FRMD4A, KIAA1468  
Pralsetinib, Selpercatinib  
MET 
Exon 14 skipping mutation 
Crizotinib, Capmatinib, Cabozantinib 
BRAF 
V600E, V600 
Dabrafenib, Dabrafenib/Trametinib, 
Vemurafenib 
KRAS 
G12C 
Clinical Trials 
ErbB2 
Exon20Ins 
Trastuzumab-deruxtecan, Ado-trastuzumab, 
emtansine, Afatinib, Lapatinib, Neratinib 
NTRK 
NTRK 1,2,3 fusions 
Larotrectinib, Entrectinib 
 
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 work13, we will recruit patient and 
clinician participants from each site to complete semi-structured interviews and structured 
questionnaires (Supplemental eFigure 3). 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 
patient characteristics. These data will be analyzed using convergent mixed methods analysis, 
which is 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. 
 
 
 

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4.3 Study Duration and Timeline 
The study duration will be approximately 34 months.  
 
 
 
Objective 1: Following an observation period, in month 6, we will initiate the stepped wedge 
cluster randomized trial. Each cluster will include a 5-month observation period, and a 1-month 
washout. The active enrollment period will be 24 months, with a 6-month lookback for baseline 
period observation. Longitudinal data capture to collect secondary outcome information for 
patients will be completed up to 90 days after study completion. Thus, collection and verification 
of all study endpoints will be completed by the end of year 3.  
 
 
 
 
 
Trial Timeline 
Project Timeline 
Year 1 
Year 2 
Year 3 
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 
Protocol Development, IRB  
• 
 
 
 
 
Objective1: Deliver 
intervention 
 
 
• 
• 
• 
• 
• 
• 
• 
• 
 
 
Objective 1: Endpoint 
ascertainment 
 
 
• 
• 
• 
• 
• 
• 
• 
• 
 
 
Objective 1: Endpoint analysis 
 
 
• 
• 
Objective 2: Recruit & conduct 
patient interviews 
• 
• 
• 
• 
• 
• 
• 
• 
 
Objective 2: Recruit & conduct 
clinician interviews 
 
 
 
 
 
 
 
 
 
• 
• 
• 
Objective 2: Mixed methods 
coding & analysis 
 
• 
• 
• 
Baseline Analysis and 
disseminate results 
 
 
• 
 
• 
 
• 
 
• 
 
 
 
Submit manuscripts & 
disseminate overall results 
 
 
 
 
 
 
 
 
• 
• 
• 
• 

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Objective 2: For patient interviews, we will use rolling enrollment to capture variation in 
processes and effectiveness over time. Patient interview recruitment and data collection is 
estimated to begin during the first month of intervention observation (i.e., second month of after 
implementation to account for washout period) and continue until saturation if reached. Clinician 
recruitment and data collection will start after active trial observation is completed at the specific 
site. Mixed methods analysis (including transcription and coding) will run throughout year 3. 
 
4.4 Study Setting 
This study will occur within the University of Pennsylvania Health System. 
 
5. STUDY PROCEDURES 
5.1 Recruitment and Retention 
Objective 1: A waiver of informed consent is requested for the stepped wedge cluster 
randomized trial. The study evaluates molecular testing rates before and after intervention at 
each site. Molecular testing at the initial diagnosis of mNSq NSCLC is standard, therefore, 
physicians and their patients will not be consented as this is the standard of practice.  
Objective 2: This portion of the study will utilize prospective consent with waiver of written 
documentation. An estimated 30-40 patients and 10-20 clinicians will be interviewed (sample 
size dependent upon when data saturation is reached). Interview participants will also complete 
a structured questionnaire at the time of the interview.  
Patients: A sample of patients will be invited to participate in the semi-structured interview and 
survey via email, phone call, and/or letter within approximately six weeks after their first medical 
oncology visit with a Penn Medicine provider. Participants who have completed molecular 
testing will be invited in purposively selected batches of approximately 5 per month (to enhance 
capture over time) until we reach saturation, which we estimate to be approximately 30-40 
patients. We will oversample for Black patients (at least 50% of the sample at each site) to 
understand effectiveness by race. We will stratify by study site (5 -10 patients at each site) as 
well as the presence of mutations (including actionable mutations, non-clinically actionable 
mutations, and absence of mutations) in order to understand how molecular testing influences 
treatment pathways for each group.  
 
Clinicians: Recruitment outreach of clinicians (i.e., procedures to invite for participation) will be 
similar to that of patients, except we will wait until end of active observation at each site to avoid 
potential contamination. Clinicians will be purposively sampled by adoption (e.g., low or high 
levels of ordering for molecular testing) and clinical role (e.g., oncologists, nurses, clinical leads, 
new patient coordinators) to enhance variation. Recruitment will continue until we reach 

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saturation, which we estimate to be approximately 2-3 clinicians per site, and approximately 10-
20 clinicians total.  
 
 
Data Collection: For patients, email and letter invitations will be followed by phone calls from 
research staff to assess interest and schedule interviews with all interested participants. 
Clinician interviews will also be contacted for invitation and scheduling by letter, email and/or 
phone.  Interviews will be conducted by a trained member of the research team and overseen 
by Dr. Rendle (Co-I), who has extensive experience in qualitative research. Interviews will be 
conducted in-person, by phone or using a HIPAA-compliant video platform, depending on 
participant preference. Structured questionnaire data will be collected via REDCap, a HIPAA 
compliant survey platform, or verbally administered if the participant cannot access this 
platform. 
 
5.2 Informed Consent 
Objective 1: This study will employ a waiver of consent mechanism. 
 
Objective 2: Potential interview participants will be initially contacted by study team members by 
patient portal, email, phone, and/or letter (depending on what is available for a specific 
participant) and given the option to decline further contact from the team. If the participant has 
not opted out within two weeks, they will be contacted by phone to assess interest in 
participating in the study. If the participant agrees to participate, they will be scheduled to have 
an interview via telephone or in person (based on preference and study procedures at the time). 
For this portion of the study, a waiver of documentation of written informed consent will be used 
because the risk to the individual is minimal, a signed informed consent form (ICF) could identify 
that an individual participated in the study and obtaining a signed paper form would significantly 
decrease the likelihood of proceeding towards an interview. Prior to the start of the interview, 
research staff will review study purpose, procedures, and the rights of the participant. They will 
also provide an information statement to participants via email prior to the scheduled interview. 
Research staff will state that participation is voluntary and ask the participant’s permission to 
record their interview. They will describe the transcription and de-identification process, and 
they will ask permission to proceed with the interview. All participants will be free to withdraw 
participation at any time, and study enrollment will not impact employment or care at Penn 
Medicine. An amended patient full interview guide and questionnaire are available in the 
appendices. The full interview guide for clinicians will be submitted for IRB review prior to 
commencement of interviews. 
Measures and Outcomes 
Primary outcome: The primary endpoint is receipt of comprehensive molecular test results prior 
to 1L therapy for patients with mNSq NSCLC. This outcome encompasses successful 
completion of concurrent tissue and plasma based molecular testing and the ability of the 
patient and oncology care team to have all necessary information to collaboratively arrive at the 
optimal treatment approach. We anticipate that approximately 80% of patients in the 
interventional arm will have molecular test results available prior to initiation of first line therapy. 
The primary outcome will be assessed by review of clinician documentation (e.g., progress 
notes) within the electronic medical record (EHR). Baseline data will be collected from all 3 
clusters.. Molecular testing rates will be assessed, proportion of patients that undergo complete 
molecular genotyping prior to start of 1L therapy for mNSq NSCLC will be tabulated 
(Comprehensive testing will be defined as testing of all NCCN recommended biomarkers). 
Proportion of patients receiving targeted therapies when therapeutically targetable alterations 
are detected (Table 1) will be tabulated on a quarterly basis.  

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Secondary outcomes include: 1) successful EHR based nudge delivery, 2) turnaround time of 
delivery of provider focused alerts after receipt of plasma genotyping results, 3) completion of 
comprehensive molecular testing (tissue and/or plasma testing), 4) reasons for failure to 
complete comprehensive molecular testing (QNS or other), 5) time to molecularly-informed 
treatment initiation, 6) type of therapy received (targeted therapy, chemo-immunotherapy, 
immunotherapy, clinical trial or none) and 7) overall survival at 1 year, and 2 years. We will also 
compare our primary and secondary outcomes from our enrollment sites to baseline data 
collected from a non-study site (i.e., PCAM), to explore contemporaneous academic benchmark 
for molecular testing outside of the study. 
 
Objective 2: We will use structured and validated measures and develop a semi-structured 
interview guide. The interview guide will be developed using RE-AIM with Equity Extension 
Framework, a widely used implementation science framework that measures key 
implementation outcomes (reach, effectiveness, adoption, implementation, and maintenance) 
and monitors how these outcomes vary by key determinants of health (equity). We will also 
draw upon the Consolidated Framework for Implementation Research (CFIR) to assess 
multilevel determinants that may shape implementation success. For patients, we will also 
assess factors that we hypothesize will impact completion of patient testing (e.g., patient 
knowledge of molecular testing, perceived importance of molecular testing, barriers to testing) 
and sociodemographics (e.g., self-reported race/ethnicity, health literacy, insurance, medical 
mistrust) using structured and validated items when available. An amended patient full interview 
guide and questionnaire are available in the appendices. The full interview guide for clinicians 
will be submitted for IRB review prior to commencement of interviews. 
 
5.3 Sources of Materials 
Objective 1: Electronic health record (EHR) data will be used to collect the primary endpoint as 
well as covariates required for statistical analysis, including any data received from FlatIron, 
Guardant360, and Care Everywhere related to treatment and/or testing that has been integrated 
as clinical data into the PennEHR. 
 
Objective 2: Semi-structured interviews and structured questionnaire data will be collected and 
analyzed in conjunction with quantitative measures conducted. 
 
6. STATISTICAL DESIGN AND POWER 
6.1 Sample Size 
Objective 1: We have calculated sample size based on estimates of completion of 
comprehensive molecular testing prior to initiation of first line therapy. Based on our prior 
studies, we anticipate that the baseline rate of comprehensive molecular testing prior to first line 
therapy is 60%. In this stepped wedge cluster randomized trial, we wish to detect an absolute 
increase of 20% in our primary outcome for patients in the intervention arm.  
 
A sample of 3 clusters in a complete stepped-wedge cluster-randomized design with 4 time 
periods (including the baseline), 3 steps, 1 cluster(s) switching from control to treatment at each 
step, and an average of 120 subjects per cluster with an average of 30 subjects per cluster per 
time period (for a total sample size of 360 subjects) achieves 80% power to detect a difference 
between proportions of 0.21701. The treatment proportion is assumed to be 0.81701 under the 
alternative hypothesis. The control proportion is 0.6. The test statistic used is the two-sided 
Wald Z-Test. The ICC is 0, and the significance level of the test is 0.05. 
 
 

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Objective 2: Proposed sample size (30-40 patients and 10-20 clinicians) is based on the 
estimated number of interviews needed to reach data saturation (within each group, by site,  
and by presence of mutations) to support mixed methods evaluation. However, interviews will 
continue until saturation is achieved. 
 
6.2 Analysis Plan 
 
Objective 1 Primary Analyses Outcome Measures: Relative and absolute change in 
availability of molecular testing prior to IL therapy. The change will be calculated from baseline 
pre-intervention period to intervention periods in all the intervention arms. Comprehensive 
molecular testing will be defined as comprehensive if results for EGFR, ALK, BRAF, ROS1, 
MET, RET, and NTRK testing are available from plasma, tissue, or both.  
 
Primary Analyses Statistical Plan 
The primary outcome is binary and will be analyzed using logistic regression, fitted using 
Generalized Estimating Equations (GEE). The model will include a time varying covariate to 
represent pre-treatment, washout, and treatment, within each randomized cluster, and an 
ordinal categorical variable to represent time. The GEE model will adjust variances for 
correlation within institution (cluster). The primary hypothesis will be tested using the z-score 
corresponding to the difference between treatment and pretreatment proportions (after 
adjustment for time effects).    
Objective 1 Secondary Analyses Outcome Measures: 
1. Successful EHR based nudge delivery:  
a. Amongst eligible patients (see eligibility above), calculate the proportion of 
patients who received any part of the multicomponent intervention  (yes/no). 
Applicable for the patients enrolled in the time periods following randomization. 
b. We will also explore the proportion of patients that received the full intervention 
(BPA + e-CDS) in contrast to a portion of the intervention to assess fidelity. 
 
2. Turnaround time of delivery of provider focused alerts: 
a. Reported as number of days, median. Applicable for the patients enrolled in the 
time periods following randomization. 
 
3. Completion of comprehensive molecular testing: 
a. Amongst eligible patients, relative and absolute change in completion of 
comprehensive molecular testing will be tabulated, regardless of timing of 1L 
therapy.  
b. Relative and absolute change in completion of comprehensive testing by tissue 
and plasma, plasma alone, or tissue alone will be tabulated. 
 
4. Reasons for failure to complete comprehensive molecular testing: 
a. 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 
5.  Time to molecularly informed treatment initiation: 
a. Amongst eligible patients, relative and absolute change in time to start 1L 
therapy.  

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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 
 
6.  Type of therapy received: 
a. Targeted therapy 
b. Chemo-immunotherapy 
c. Immunotherapy 
d. Clinical trial or n 
e. None 
 
7. Overall Survival: 
a. Time from initial diagnosis to date of death or last follow up. 
b. 1 year and 2-year overall survival rates will be calculated for the intervention 
group and compared to baseline. 
 
Secondary Analyses Statistical Plan 
Secondary outcomes will be summarized by time and treatment condition, as proportions, 
means, medians, as appropriate with two-sided 95% CIs. Successful nudge delivery, completion 
of testing, reasons for failure to complete testing, and type of therapy received will be tabulated 
and summarized as proportions. Turnaround time of delivery for provider focused alerts will be 
treated as time to event and summarized as median time with 95% CI. Time to treatment 
initiation and Overall Survival will be summarized as time to event using Kaplan Meier methods, 
with the effect of intervention estimated as the hazard ratio (with two-sided 95% CI). 
For a complete list of clinical and interventional related variables that will be collected 
throughout the course of this study please refer to Supplemental eTable 1 below.  
 
Objective 2 Analyses Plan 
We will use convergent mixed-methods analysis to explore the multilevel factors shaping the 
effectiveness of our EHR-based nudge intervention. The constant comparative method, guided 
by grounded theory, will be used to inductively explore emergent themes and deductively 
identify a priori domains of interest within and across interviews, guided by the RE-AIM with 
Equity Extension Framework and the Consolidated Framework for Implementation Research 
(CFIR). Two trained coders will first independently read each transcript to identify themes within 
each domain. We then will use this list to develop a coding dictionary and apply it to subset of 
the data. We will measure inter-rater reliability to document and improve coding consistency. 
Once high reliability is achieved (e.g., kappa > 0.8), we will apply the full coding dictionary to the 
interview data using Atlas.ti (computer-assisted qualitative analytic software) and produce 
thematic reports summarizing our findings by each domain and sub-theme. Data from structured 
questionnaires will be analyzed descriptively. Qualitative and quantitative data will be analyzed 
and triangulated using a convergent mixed-methods approach (QUAL + QUAN). 
 
7. RESOURCES NECESSARY FOR HUMAN RESEARCH PROTECTION 
Adequate facilities are available within Penn Medicine’s Clinical Practice Network. Members of 
the research team, listed in HSERA, will be overseen by the PI and include appropriate 
personnel to successfully implement this pilot project. All personnel will complete required 
training before being granted access to any identifying information. Training includes information 
on confidentiality through the Collaborative IRB Training Initiative (CITI) courses. All personnel 

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will also be trained in procedures for reporting unintentional breaches in confidentiality to the PI. 
All personnel will be aware that violations of participant’s confidentiality, either unintentional or 
deliberate, may result in termination of hire.  
 
Protection of Human Subjects 
Computer-based files will only be made available to personnel involved in the study through the 
use of access privileges and passwords. Wherever feasible, identifiers will be removed from 
study-related information. Precautions are already in place to ensure the data are secure by 
using passwords and HIPAA-compliant encryption. Data on physicians and patients will be 
obtained from EHR and Penn Data Store. Any information that is obtained will be used only for 
research purposes and to inform the interventions described above. Information on individual 
patients will only be disclosed within the study team. All study staff will be reminded of the 
confidential nature of the data collected and contained in these databases. Data will be stored, 
managed, and analyzed on a secure, encrypted server behind the University of Pennsylvania 
Health System (UPHS) firewall. Data access will be password protected. Whenever possible, 
data will be de-identified for analysis. 
 
 
8. STUDY TEAM 
Our interdisciplinary team includes investigators with world known experts in thoracic oncology, 
and clinical implementation of molecular testing, implementation science, behavioral economics, 
EHR-based strategies, and mixed-methods research. At the University of Pennsylvania, the 
work will be led by Charu Aggarwal, MD, MPH, Leslye M. Heisler Associate Professor of Lung 
Cancer Excellence and Associate Director, Penn Center for Precision Medicine . Other key 
investigators include Melina E. Marmarelis, MD, a medical oncologist with clinical and research 
expertise in lung cancer. Other co-investigators include E. Paul Wilyeto, PhD (biostatistician), 
and Katharine Rendle, PhD, MSW, MPH who bring statistical and implementation science 
expertise to the team. Local team leaders will be Chris D. Avella, MD at Penn Presbyterian 
Medical Center, Ramy Sedhom, MD at Penn-Princeton, Shayma Kazmi, MD at Penn-Cherry 
Hill and Penn-Washington Township, and Penn Voorhees, and Samuel Kerr, MD at Penn-LGH.  
The study team will include Peter Gabriel, MD, Chief Oncology Informatics Officer at the 
Abramson Cancer Center, Meagan Hume, MDP, MPH, Senior Innovation Manager at PC3I, 
Anthony Martella, BA, Innovation Manager at PC3I, , , and, Clinical Research Coordinator B, 
Clinical Research Unit. Weilu Song, MS, MPH, Statistical Analyst, Dept. of Family Medicine and 
Community Health, Chelsea Saia, MPH, Senior Health Data Manager, Dept. of Family Medicine & 
Community Health, Jocelyn Wainwright, MS, Associate Director of Research Operations, PC3I, Alex 
Watts, MS, Statistical Analyst at Penn CCEB, Jillian Kalman, BA, Clinical Research Coordinator, 
Dept. of Family Medicine and Community Health, Anne Montgomery, PhD, MSc, Qualitative Research 
Investigator, Dept. of Family Medicine and Community Health, Xiaoke Wang, MD, Clinical Research 
Coordinator B, Willdragon Wang, Clinical Research Coordinator B, Busra Karatas, Clinical Research 
Unit, Penn Medicine, and Naomi Yu, Research Assistant.  
 
 
 
 
 

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9. REFERENCES 
1. 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 2020. 
2. Rolfo C, Mack P, Scagliotti GV, et al. Liquid Biopsy for Advanced NSCLC: A Consensus 
Statement From the International Association for the Study of Lung Cancer. J Thorac Oncol 
2021;16(10): 1647-62. 
3. Lisberg A, Cummings A, Goldman JW, et al. A Phase II Study of Pembrolizumab in EGFR-
Mutant, PD-L1+, Tyrosine Kinase Inhibitor Naive Patients With Advanced NSCLC. J Thorac 
Oncol 2018;13(8): 1138-45. 
4. Schoenfeld AJ, Arbour KC, Rizvi H, et al. Severe immune-related adverse events are 
common with sequential PD-(L)1 blockade and osimertinib. Ann Oncol 2019;30(5): 839-44. 
5. Singal G, Miller PG, Agarwala V, et al. Association of Patient Characteristics and Tumor 
Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a 
Clinicogenomic Database. JAMA 2019;321(14): 1391-99. 
6. Robert NJ, Espirito JL, Chen L, et al. 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;166: 197-204. 
7. Bruno DS, et al. Racial disparities in biomarker testing and clinical trial enrollment in non-
small cell lung cancer (NSCLC). . Journal of Clinical Oncology 2021;39(no. 15_suppl (May 20, 
2021) ): 9005-05. 
8. Presley CJ, Tang D, Soulos PR, et al. Association of Broad-Based Genomic Sequencing With 
Survival Among Patients With Advanced Non-Small Cell Lung Cancer in the Community 
Oncology Setting. JAMA 2018;320(5): 469-77. 
9. Thompson JC, Yee SS, Troxel AB, et al. 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;22(23): 5772-82. 
10. Leighl NB, Page RD, Raymond VM, et al. 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;25(15): 4691-700. 
11. Aggarwal C, Thompson JC, Black TA, et al. Clinical Implications of Plasma-Based 
Genotyping With the Delivery of Personalized Therapy in Metastatic Non-Small Cell Lung 
Cancer. JAMA Oncol 2019;5(2): 173-80. 

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12. 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;8: 134. 
13. 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;9(8): 
e030123. 
14. Glaser BG, Strauss AL. The Discovery of Grounded Theory: Strategies for Qualitative 
Research. Aldine Pub Co; 1967. 
15. Creswell JW, Plano Clark VL. Designing and Conducting Mixed Methods Research. 3rd ed. 
SAGE Publications, Inc; 2018. 
16. Rihoux B, Ragin C. Configurational Comparative Methods. SAGE Publications; 2008. 
17. Kane H, Lewis MA, Williams PA, Kahwati LC. Using qualitative comparative analysis to 
understand and quantify translation and implementation. Transl Behav Med. 2014;4(2):201-208. 
doi:10.1007/s13142-014-0251-6 
18. Weiner BJ, Jacobs SR, Minasian LM, Good MJ. Organizational designs for achieving high 
treatment trial enrollment: a fuzzy-set analysis of the community clinical oncology program. J 
Oncol Pract. 2012;8(5):287-291. doi:10.1200/JOP.2011.000507 
19. Baumgartner M, Ambühl M. Causal modeling with multi-value and fuzzy-set Coincidence 
Analysis. Polit Sci Res Methods. 2020;8(3). doi:10.1017/psrm.2018.45 
20. Ragin CC. Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago; 
2008. 
21. Whitaker RG, Sperber N, Baumgartner M, et al. Coincidence analysis: a new method for 
causal inference in implementation science. Implement Sci. 2020;15(1):108-108. 
doi:10.1186/s13012-020-01070-3 
22. Thiem A. Using Qualitative Comparative Analysis for Identifying Causal Chains in 
Configurational Data: A Methodological Commentary on Baumgartner and Epple (2014). Sociol 
Methods Res. 2015;44(4):723-736. doi:10.1177/0049124115589032 
23. Baumgartner M, Thiem A. Often Trusted but Never (Properly) Tested: Evaluating Qualitative 
Comparative Analysis. Sociol Methods Res. 2020;49(2). doi:10.1177/0049124117701487 
24. Baumgartner M, Ambühl M. Cna: An R Package for Configurational Causal Inference and 
Modeling. 
 
 

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10. APPENDICES 
Supplemental eTable 1: Clinical variables and tumor characteristics 
Variable 
Description 
Demographics  
Study Patient ID 
Unique identifier generated by study team 
Name 
First Last 
MRN 
Medical record number 
DOB 
date of birth, MM/DD/YYYY 
DOD  
date of death, MM/DD/YYYY 
 
Vital status 
Alive, deceased 
 
ECOG date (@ time of 1st MedOnc visit) 
MM/DD/YYYY 
 
ECOG value 
0-1, >2 
 
Days difference (ECOG date – Dx date) 
# (days) 
 
Race 
American Indian or Alaskan Native, Asian, Black or 
African American, Native Hawaiian or Other Pacific 
Islander, White, Other, Declined, Unknown 
Ethnic group 
Hispanic or Latino, Non-Hispanic or Latino, Declined 
 
Sex 
Female, male, other (if available)  
Date of Diagnosis 
date of clinical or pathologic diagnosis, MM/DD/YYYY 
Age at Diagnosis 
# (year) 
 
Histology 
i.e. adenocarcinoma, poorly differentiated etc. 
TNM Stage 
Stage IV (T4, N0, M0 or any T, N1, M0 or any T, any 
N, M1) 
 
Primary site of treatment 
PPMC, PMC, LGH, PMCH, PMWT, OHCI 
Medical Oncologist 
MD name (First Last)  
Date of 1st MedOnc encounter 
MM/DD/YYYY 
 
Smoking status 
Current, former, never 
 
Molecular testing 
Date of Tissue Testing 
MM/DD/YYYY 
Type of Tissue Testing 
Spot, NGS, FISH, IHC, etc. 
Tissue testing successful? 
yes/no (QNS – quality/quantity not sufficient, 
cancelled, etc.)  
 
Tissue Testing Platform 
CPD NGS/FTP, CARIS, GenPath OnkoSight, etc.  
 
Gene panel size  
>50 vs. <50 genes 
 
Tissue NCCN markers* 
EGFR, ALK, BRAF, ROS1, MET, RET, ErbB2, 
NTRK. 
 
Tissue additional markers 
KRAS, ErbB2, BRCA1 (yes/no and specific 
alteration)  
Date of Plasma Testing 
MM/DD/YYYY 
Plasma Testing Platform 
Guardant360®, Foundation etc.  
Type of Plasma Testing 
Spot, NGS, FISH, IHC, etc. 

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Plasma testing successful?  
yes/no (QNS – quality/quantity not sufficient, 
cancelled, etc.) 
 
Plasma NCCN markers* 
EGFR, ALK, BRAF, ROS1, MET, RET, ErbB2, 
NTRK.  
 
Plasma additional markers  
KRAS, ErbB2, BRCA1 (yes/no and specific 
alteration)  
Gene panel size 
>50 vs. <50 genes 
 
Testing modality  
T, P, or T+P 
 
Treatment 
First line start date 
MM/DD/YYYY 
First line treatment regimen 
systemic therapy regimen (IO, chemo-IO, TKI, etc.) 
First line last treatment date 
MM/DD/YYYY 
Second line treatment start date 
MM/DD/YYYY 
Second line treatment regimen 
systemic therapy regimen (IO, chemo-IO, TKI, etc.)  
Second line last treatment date 
MM/DD/YYYY 
Radiation prior to first line? 
yes/no 
Type of radiation prior to first line 
curative, palliative etc. 
Date of completion of radiation 
MM/DD/YYYY 
Assessment 
NCCN markers tested prior to 1L start? 
yes/no 
Targeted Tx prescribed if targetable mutation 
detected? (If no, will record reasons why) 
yes/no  
Line of targeted TX prescribed? 
1L, 2L, subsequent lines 
 
Response to Reflex Alert Notification 
Alteration detected 
yes/no 
Alteration gene 
EGFR L858R, KRAS G12C, KIF5B-RET Fusion, etc.  
 
Date of plasma report 
MM/DD/YYYY 
Date reflex alert sent 
MM/DD/YYYY 
Turnaround time (TAT) of alert 
# (days) 
 
Name of MD receiving alert 
First Last 
Tx naïve at time of alert? 
yes/no 
 
Tx pre-reflex alert 
systemic therapy regimen (IO, chemo-IO, TKI, etc.) 
 
Tx post-reflex alert 
systemic therapy regimen (IO, chemo-IO, TKI, etc.) 
 
Change in Tx pre-vs. post reflex alert? 
yes/no 
 
Plan to prescribe a targeted Tx? 
yes/no 
Receipt of targeted Tx? 
yes/no 
Clinical team review requested 
yes/no 

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Supplemental eFigure 1: Pre-populated molecular questions 
 
 

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Supplemental eFigure 2: e-CDS alert template 

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Supplemental eFigure 3: Patient Interview Semi-Structured Questions 
Supplemental eFigure 3: Patient Interview Semi-Structured Questions 
iNUDGE Patient Interview Guide (Version Date: 2.7.2025): Semi-Structured Questions 
 
OPENING SCRIPT  
Hello, thank you again for agreeing to this interview today and for taking time out of your day to 
speak with me. The objective of this study is to better understand your experience receiving 
cancer treatment at [SITE] and in particular your thoughts and experiences related to biomarker 
testing as part of your lung cancer care. Our future goal is to try to identify ways we can better 
support patients like you and improve how we deliver care. As a patient who has been diagnosed 
with cancer, we consider you an expert in this project and value your input and experiences. 
There are no right or wrong answers.  
Participation in this study is completely voluntary and you can withdraw at any time. Please 
know that everything you say today is confidential. We request that you allow us to audio-record 
the conversation as it will ensure we capture your thoughts and views completely. The things you 
share will not be connected to your name, and the recording will be destroyed after it is 
transcribed. Any identifying information, for example your name, will be removed from the 
transcript.  
Do you have any questions about the study or what is required to participate? (Answer all 
questions).  
1. Are you comfortable with me recording this conversation? (Pause for confirmation).   
2. Do you agree to participate in this study? (Pause for confirmation)  
If you need a break or want to stop at any point, please let me know.   
  
TURN TAPE ON NOW  
State Interviewer Name, Date, Participant ID into recorder  
 
 

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1. To help me understand a bit more about your experiences, I would like to start by asking you 
to tell me about where you are currently in your cancer treatment journey and how the 
journey has been thus far?   
a. Are they any specific things that have helped you through this process, either from 
your care team, your family, friends, or any other sources of support? 
 
Thank you for sharing your experiences – I recognize that this can be hard to describe and 
talk about. Now, I am going to shift to more specific questions about your care experiences. 
 
2. Do you recall approximately which month/year you had your first visit with your medical oncologist 
for your lung cancer care? It is okay if you don’t remember – I know this time is challenging and 
overwhelming for most patients. 
 
3. During your first visit (or first visits), can you describe to me how challenging (or not) it was to 
understand your diagnosis and treatment options? 
a. What, if anything, helped you to understand? 
b. What, if anything, helped you to remember information that was given to you during these 
first appointments? 
c. What might have helped you better understand and remember information during these first 
appointments? 
 
As part of lung cancer care, some patients are recommended to do molecular testing 
(sometimes called biomarker testing) to identify which treatments might be best for their 
specific cancer. Sometimes molecular testing is done even before you know you have cancer 
for sure. Molecular testing often involves giving your blood or another type of sample at a lab 
or in the clinic when you see your care team.   
 
4.  How familiar are you, if at all, with molecular testing or biomarker testing related to lung cancer 
care? 
a. IF FAMILIAR (AT ALL), what are some things you’ve heard about it?  Where and when did 
you learn those things? 
b. IF NOT AT ALL [GO TO NEXT QUESTION BUT PREFACE WITH I KNOW I JUST 
ASKED THIS GENERALLY BUT TO CONFIRM, DO YOU RECALL IF YOU…]. 
 
5. How, if at all, did your cancer care team talk with you about molecular testing in relation to your lung 
cancer care? [IF NO DISCUSSION, SKIP TO Q6]  
a. How, if at all, did your care team discuss how molecular testing might change what 
treatment options would be best for you?  
b. Do you recall if they recommended that you complete molecular testing, at any point in 
your care?  
c. Do you recall if you asked questions related to molecular testing?  
a. [IF YES] How comfortable did you feel asking questions about molecular testing 
with your care team?  
b. [IF YES] How well did your care team answer your questions? Did you leave 
with any unanswered questions or concerns?  
 
Now I want to ask you a few more questions about your experience with molecular testing.  
 

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6. At any point in your lung cancer care, did you complete molecular testing [IF NO RECALL, SKIP 
TO Q9]  
a. [IF YES]: Can you tell me a bit more about when and where you completed 
molecular testing?   
b. How, if at all, were your results discussed with you? By whom? 
c. Do you recall if your care team informed you that you had molecular changes 
(potentially called mutations) that could shape your care or cancer? If you feel 
comfortable, would you mind sharing what they told you? 
 
7. Barriers/Facilitators: What, if anything, made it easier for you to complete (or not complete) 
molecular testing? What, if anything, made it harder for you to complete (or not complete) molecular 
testing?   
a. How, if it all, did insurance coverage impact your decision to be tested?  Did you have any 
problems with coverage or reimbursement? 
 
8. How, if at all, has your decision to complete testing negatively impacted you?  For example, 
unexpected costs, time away from work, anxiety, or other experiences. 
Now I’d like to ask you specifically about discussions and decisions you had about your 
cancer treatment options. Depending on your experience and the type of cancer, your doctor 
may have presented different options – or not. I understand you may not remember specific 
details so it’s absolutely okay to say, ‘I do not remember’.  
9. First, I want to ask you a general question about your preferences for how much you like to be 
involved in decisions about treatment, because every person is different. In general, do you prefer to 
make decisions about treatment yourself, or share decision-making with your care team, or leave all 
decisions to your care team?  
a. Can you tell me why?  Are there situations when you prefer your clinicians to be more 
involved? Less involved?  
b. What things, if anything, make it easier for you to be involved? Harder? 
 
10. What, if anything, do you recall about the early conversations you had with your care team about your 
treatment options, shortly after you were diagnosed?  
a. How and what treatment options were presented to you?  
b. What information did you receive about the benefits and risks of each option? 
c. How, if at all, did your care team incorporate your preferences during the decision-making 
process? 
d. Did your care team provide a treatment recommendation? If so, how was it presented? 
e. How, if at all, did your care team discuss the possibility of participating in clinical trials?  
f. [IF MT RECALL] How, if at all, did your care team incorporate your molecular testing into these 
discussions of treatment options? 
g. In general, how do you feel about your oncology care team’s role in your decisions about 
treatment? Too involved, not involved enough, or just right?    
 
Now I’d like to ask you about your experience with treatment.  
 
11. If you feel comfortable, can you tell me what types of treatment, if any, you have started for your 
lung cancer care? 
 
12. [IF MT RECALL] Have you been prescribed any medications related to the results of your molecular 
testing?  
a. If yes, have you started taking your medications? How has your experience been so far?  

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b. How challenging is it to take your medication as prescribed?  
c. How important is it to you to take your medication as prescribed? Why? 
 
13. Barriers/facilitators: What things have made receiving treatment harder? What things have made 
receiving treatment easier?  
 
14. How does it feel to be on this treatment? 
a. Have you experienced side-effects on treatment? How have you coped with these side 
effects? 
b. What concerns or worries have you had during your treatment? What are your coping 
strategies? 
c. How, if at all, has this treatment changed your daily life and quality of life?  
 
Now I’d like to ask how you could be better supported. I recognize that some things are likely 
outside the scope of Penn Medicine, please answer these questions as if anything is possible. 
 
15. What things, if any, would help to improve your quality of life today? Support your emotional or 
mental well-being? Make you feel better health-wise? 
 
16. What can be done to improve your experience with your cancer care team?  
 
Wrap up 
17. Is there anything else that you would like to tell us about your experience with molecular testing 
specifically or your lung care experience in general?  
 
18. To help me understand a bit more about your experiences, I would like to start by asking you 
to tell me about where you are currently in your cancer treatment journey and how the 
journey has been thus far?   
b. Are they any specific things that have helped you through this process, either from 
your care team, your family, friends, or any other sources of support? 
 
Thank you for sharing your experiences – I recognize that this can be hard to describe and 
talk about. Now, I am going to shift to more specific questions about your care experiences. 
 
19. Do you recall approximately which month/year you had your first visit with your medical oncologist 
for your lung cancer care? It is okay if you don’t remember – I know this time is challenging and 
overwhelming for most patients. 
 
20. During your first visit (or first visits), can you describe to me how challenging (or not) it was to 
understand your diagnosis and treatment options? 
d. What, if anything, helped you to understand? 
e. What, if anything, helped you to remember information that was given to you during these 
first appointments? 
f. 
What might have helped you better understand and remember information during these 
first appointments? 
 

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As part of lung cancer care, some patients are recommended to do molecular testing 
(sometimes called biomarker testing) to identify which treatments might be best for their 
specific cancer. Sometimes molecular testing is done even before you know you have cancer 
for sure. Molecular testing often involves giving your blood or another type of sample at a lab 
or in the clinic when you see your care team.   
 
21.  How familiar are you, if at all, with molecular testing or biomarker testing related to lung cancer 
care? 
a. IF FAMILIAR (AT ALL), what are some things you’ve heard about it?  Where and when did 
you learn those things? 
b. IF NOT AT ALL [GO TO NEXT QUESTION BUT PREFACE WITH I KNOW I JUST ASKED THIS 
GENERALLY BUT TO CONFIRM, DO YOU RECALL IF YOU…]. 
 
22. How, if at all, did your cancer care team talk with you about molecular testing in relation to your 
lung cancer care? [IF NO DISCUSSION, SKIP TO Q6]  
b. How, if at all, did your care team discuss how molecular testing might change what 
treatment options would be best for you?  
c. Do you recall if they recommended that you complete molecular testing, at any point in 
your care?  
d. Do you recall if you asked questions related to molecular testing?  
a. [IF YES] How comfortable did you feel asking questions about molecular testing 
with your care team?  
b. [IF YES] How well did your care team answer your questions? Did you leave 
with any unanswered questions or concerns?  
 
Now I want to ask you a few more questions about your experience with molecular testing.  
 
23. At any point in your lung cancer care, did you complete molecular testing [IF NO RECALL, SKIP TO 
Q9]  
a. [IF YES]: Can you tell me a bit more about when and where you completed 
molecular testing?   
b. How, if at all, were your results discussed with you? By whom? 
c. Do you recall if your care team informed you that you had molecular changes 
(potentially called mutations) that could shape your care or cancer? If you feel 
comfortable, would you mind sharing what they told you? 
 
24. Barriers/Facilitators: What, if anything, made it easier for you to complete (or not complete) 
molecular testing? What, if anything, made it harder for you to complete (or not complete) 
molecular testing?   
a. How, if it all, did insurance coverage impact your decision to be tested?  Did you have any 
problems with coverage or reimbursement? 
 
25. How, if at all, has your decision to complete testing negatively impacted you?  For example, 
unexpected costs, time away from work, anxiety, or other experiences. 
Now I’d like to ask you specifically about discussions and decisions you had about your 
cancer treatment options. Depending on your experience and the type of cancer, your doctor 

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may have presented different options –  or not. I understand you may not remember specific 
details so it’s absolutely okay to say ‘I do not remember’.  
26. First, I want to ask you a general question about your preferences for how much you like to be 
involved in decisions about treatment, because every person is different. In general, do you prefer 
to make decisions about treatment yourself, or share decision-making with your care team, or leave 
all decisions to your care team?  
a. Can you tell me why?  Are there situations when you prefer your clinicians to be more 
involved? Less involved?  
b. What things, if anything, make it easier for you to be involved? Harder? 
 
27. What, if anything, do you recall about the early conversations you had with your care team about 
your treatment options, shortly after you were diagnosed?  
h. How and what treatment options were presented to you?  
i. 
What information did you receive about the benefits and risks of each option? 
j. 
How, if at all, did your care team incorporate your preferences during the decision-making 
process? 
k. Did your care team provide a treatment recommendation? If so, how was it presented? 
l. 
How, if at all, did your care team discuss the possibility of participating in clinical trials?  
m. [IF MT RECALL] How, if at all, did your care team incorporate your molecular testing into these 
discussions of treatment options? 
n. In general, how do you feel about your oncology care team’s role in your decisions about 
treatment? Too involved, not involved enough, or just right?    
 
Now I’d like to ask you about your experience with treatment.  
 
28. If you feel comfortable, can you tell me what types of treatment, if any, you have started for your 
lung cancer care? 
 
29. [IF MT RECALL] Have you been prescribed any medications related to the results of your molecular 
testing?  
a. If yes, have you started taking your medications? How has your experience been so far?  
b. How challenging is it to take your medication as prescribed?  
c. How important is it to you to take your medication as prescribed? Why? 
 
30. Barriers/facilitators: What things have made receiving treatment harder? What things have made 
receiving treatment easier?  
 
31. How does it feel to be on this treatment? 
a. Have you experienced side-effects on treatment? How have you coped with these side 
effects? 
b. What concerns or worries have you had during your treatment? What are your coping 
strategies? 
c. How, if at all, has this treatment changed your daily life and quality of life?  
 
Now I’d like to ask how you could be better supported. I recognize that some things are likely 
outside the scope of Penn Medicine, please answer these questions as if anything is possible. 

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32. What things, if any, would help to improve your quality of life today? Support your emotional or 
mental well-being? Make you feel better health-wise? 
 
33. What can be done to improve your experience with your cancer care team?  
 
Wrap up 
34. Is there anything else that you would like to tell us about your experience with molecular testing 
specifically or your lung care experience in general?