AIMS: Broad molecular profiling of patients with advanced non-small cell lung cancer (NSCLC) is strongly advised to optimize genomic matching with available targeted treatment options or investigational agents. Unlike conventional molecular diagnostic testing, or smaller hotspot panels, comprehensive genomic profiling (CGP) identifies genomic alterations across hundreds of clinically relevant cancer genes from a single tissue specimen. The present study sought to estimate the budget impact of increased use of CGP using a 324-gene panel (FoundationOne) vs non-CGP (represented by a mix of conventional molecular diagnostic testing and smaller NGS hotspot panels) and the number needed to test with CGP to gain 1 life year. MATERIALS AND METHODS: A decision analytic model was developed to assess the budget impact of increased CGP in advanced NSCLC from a US private payer perspective. Model inputs were based on published literature (epidemiology and treatment outcomes), real-world data (testing and rates, medical service costs), list prices for CGP and anti-cancer drugs, and assumptions for clinical trial participation. RESULTS: Among 2 million covered lives, 532 had advanced NSCLC; 266 underwent molecular diagnostic testing. An increase in CGP among those tested, from 2% to 10%, was associated with $0.02 per member per month budget impact, of which $0.013 was attributable to costs of prolonged drug treatment and survival and $0.005 to testing cost. Approximately 12 patients would need to be tested with CGP to add 1 life year. LIMITATIONS: The model incorporated certain assumptions to account for inputs with a limited evidence profile and simplify the possible post-CGP treatments. CONCLUSIONS: An increase in CGP utilization from 2% to 10% among patients with advanced NSCLC undergoing molecular diagnostic testing was associated with a modest budget impact, most of which was attributable to increased use of more effective treatments and prolonged survival.
AIMS: Broad molecular profiling of patients with advanced non-small cell lung cancer (NSCLC) is strongly advised to optimize genomic matching with available targeted treatment options or investigational agents. Unlike conventional molecular diagnostic testing, or smaller hotspot panels, comprehensive genomic profiling (CGP) identifies genomic alterations across hundreds of clinically relevant cancer genes from a single tissue specimen. The present study sought to estimate the budget impact of increased use of CGP using a 324-gene panel (FoundationOne) vs non-CGP (represented by a mix of conventional molecular diagnostic testing and smaller NGS hotspot panels) and the number needed to test with CGP to gain 1 life year. MATERIALS AND METHODS: A decision analytic model was developed to assess the budget impact of increased CGP in advanced NSCLC from a US private payer perspective. Model inputs were based on published literature (epidemiology and treatment outcomes), real-world data (testing and rates, medical service costs), list prices for CGP and anti-cancer drugs, and assumptions for clinical trial participation. RESULTS: Among 2 million covered lives, 532 had advanced NSCLC; 266 underwent molecular diagnostic testing. An increase in CGP among those tested, from 2% to 10%, was associated with $0.02 per member per month budget impact, of which $0.013 was attributable to costs of prolonged drug treatment and survival and $0.005 to testing cost. Approximately 12 patients would need to be tested with CGP to add 1 life year. LIMITATIONS: The model incorporated certain assumptions to account for inputs with a limited evidence profile and simplify the possible post-CGP treatments. CONCLUSIONS: An increase in CGP utilization from 2% to 10% among patients with advanced NSCLC undergoing molecular diagnostic testing was associated with a modest budget impact, most of which was attributable to increased use of more effective treatments and prolonged survival.
Entities:
Keywords:
I10; I11; Non-small cell lung cancer (NSCLC); budget impact; comprehensive genomic profiling (CGP); molecular diagnostic testing; number needed to test; precision oncology
Authors: Coren A Milbury; James Creeden; Wai-Ki Yip; David L Smith; Varun Pattani; Kristi Maxwell; Bethany Sawchyn; Ole Gjoerup; Wei Meng; Joel Skoletsky; Alvin D Concepcion; Yanhua Tang; Xiaobo Bai; Ninad Dewal; Pei Ma; Shannon T Bailey; James Thornton; Dean C Pavlick; Garrett M Frampton; Daniel Lieber; Jared White; Christine Burns; Christine Vietz Journal: PLoS One Date: 2022-03-16 Impact factor: 3.240
Authors: Denis Horgan; Giuseppe Curigliano; Olaf Rieß; Paul Hofman; Reinhard Büttner; Pierfranco Conte; Tanja Cufer; William M Gallagher; Nadia Georges; Keith Kerr; Frédérique Penault-Llorca; Ken Mastris; Carla Pinto; Jan Van Meerbeeck; Elisabetta Munzone; Marlene Thomas; Sonia Ujupan; Gilad W Vainer; Janna-Lisa Velthaus; Fabrice André Journal: J Pers Med Date: 2022-01-08