Elevating the Patient Perspective: Quantifying First-Line Preferences in Locally Advanced Metastatic Non-Small Cell Lung Cancer (NSCLC) Using the Threshold Technique
Author(s)
Pratyusha Vadagam, MS1, Matthew Reiss, MSE, PhD2, Hatim Hussian, MD3, Ellen M. Janssen, BA, PhD4, Iris Lin, PhD5, Divya Mohan, PhD6, Debdeep Chattopadhyay, PhD7, Marco Boeri, BSc, MSc, PhD6.
1Johnson & Johnson, Warrington, PA, USA, 2Go2 for Lung Cancer, Washington, DC, USA, 3University of California San Diego, San Diego, CA, USA, 4Janssen Research & Development, LLC, Baltimore, MD, USA, 5Johnson & Johnson, Philadelphia, PA, USA, 6OPEN Health, London, United Kingdom, 7Patient Centered Outcomes, OPEN Health, Rotterdam, Netherlands.
1Johnson & Johnson, Warrington, PA, USA, 2Go2 for Lung Cancer, Washington, DC, USA, 3University of California San Diego, San Diego, CA, USA, 4Janssen Research & Development, LLC, Baltimore, MD, USA, 5Johnson & Johnson, Philadelphia, PA, USA, 6OPEN Health, London, United Kingdom, 7Patient Centered Outcomes, OPEN Health, Rotterdam, Netherlands.
OBJECTIVES: To understand how treatment type and side effects (SEs) influence first-line treatment preferences among individuals with locally advanced/metastatic (LA/met) non-small cell lung cancer (NSCLC).
METHODS: US respondents with clinician-confirmed LA/met NSCLC completed a threshold technique (TT) survey. Initially, a direct elicitation (DE) question was asked comparing two hypothetical 1L regimens, with and without chemotherapy, given as intravenous + oral and subcutaneous + oral combinations. Respondents were then presented with a series of TT questions that varied the risks of specific SEs (hematological, dermatological, gastrointestinal, venous thromboembolism, and fatigue) to determine the maximum acceptable risk (MAR) for each SE based on their initial preference. Interval regression analysis was conducted to understand how patient and clinical characteristics influenced MAR. Finally, a follow-up DE question incorporated all SEs at risk levels representative of real-world regimens with and without chemotherapy. An additional TT also assessed the influence of progression-free survival (PFS) on preferences.
RESULTS: Among 150 respondents (median age: 64; 46% female; 58% white; 43% stage 3b; 67% EGFR-positive, 23% chemotherapy- naïve), 25% initially preferred a chemotherapy-containing regimen and demonstrated the highest MAR for fatigue (14.39%) before switching to a non-chemotherapy regimen; while, 75% initially preferred a non-chemotherapy regimen, with the highest MAR observed for hematological SE (22.82%) before switching to a chemotherapy-containing regimen. In the follow-up DE question that incorporated SEs, 90% chose the treatment set without chemotherapy. Respondents’ preferences were generally less sensitive to variations in PFS, and few switched from their initial stated preferences. Subgroup analysis of EGFR-positive individuals and those with prior chemotherapy exposure showed similar patterns.
CONCLUSIONS: While preferences for chemotherapy versus non-chemotherapy regimens vary, SE risks are important factors in their decision-making. These insights highlight the importance of integrating patient-defined benefit-risk trade-offs into personalized, patient-centered treatment strategies in the evolving 1L LA/met NSCLC landscape.
METHODS: US respondents with clinician-confirmed LA/met NSCLC completed a threshold technique (TT) survey. Initially, a direct elicitation (DE) question was asked comparing two hypothetical 1L regimens, with and without chemotherapy, given as intravenous + oral and subcutaneous + oral combinations. Respondents were then presented with a series of TT questions that varied the risks of specific SEs (hematological, dermatological, gastrointestinal, venous thromboembolism, and fatigue) to determine the maximum acceptable risk (MAR) for each SE based on their initial preference. Interval regression analysis was conducted to understand how patient and clinical characteristics influenced MAR. Finally, a follow-up DE question incorporated all SEs at risk levels representative of real-world regimens with and without chemotherapy. An additional TT also assessed the influence of progression-free survival (PFS) on preferences.
RESULTS: Among 150 respondents (median age: 64; 46% female; 58% white; 43% stage 3b; 67% EGFR-positive, 23% chemotherapy- naïve), 25% initially preferred a chemotherapy-containing regimen and demonstrated the highest MAR for fatigue (14.39%) before switching to a non-chemotherapy regimen; while, 75% initially preferred a non-chemotherapy regimen, with the highest MAR observed for hematological SE (22.82%) before switching to a chemotherapy-containing regimen. In the follow-up DE question that incorporated SEs, 90% chose the treatment set without chemotherapy. Respondents’ preferences were generally less sensitive to variations in PFS, and few switched from their initial stated preferences. Subgroup analysis of EGFR-positive individuals and those with prior chemotherapy exposure showed similar patterns.
CONCLUSIONS: While preferences for chemotherapy versus non-chemotherapy regimens vary, SE risks are important factors in their decision-making. These insights highlight the importance of integrating patient-defined benefit-risk trade-offs into personalized, patient-centered treatment strategies in the evolving 1L LA/met NSCLC landscape.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
PCR68
Topic
Patient-Centered Research
Disease
Oncology, Respiratory-Related Disorders (Allergy, Asthma, Smoking, Other Respiratory)