Population-Level Projections for Multiple Myeloma Patients By Line of Therapy in the USA

Abstract

Introduction: Treatment for multiple myeloma (MM) has evolved over time, leading to improved survival outcomes for patients. However, information on real world clinical practice, such as the proportion of patients receiving each treatment regimen or the number of patients eligible for a given line of therapy (LOT), is limited. The purpose of this analysis is to report the results of a patient epidemiology model for MM treatment by LOT in the USA. Methods: This study was a retrospective, population-based, secondary data analysis of MM in the USA combining data from the Surveillance, Epidemiology, and End Results (SEER) registry and physician survey results from the CancerMPact® (CMP) database. Age- and gender-specific incidence rates were obtained from SEER for all available years through 2016 using the ICD-O-3 histology codes of 9731 (solitary plasmacytoma of bone), 9732 (plasma cell myeloma), and 9734 (extraosseous plasmacytoma). Based on the observed trend in the historical incidence rates through 2016, the incidence rates were projected to 2025. These projected rates were multiplied by the respective age- and gender-specific USA population from the 2010 U.S. Census, moderate projection to calculate the estimated number of incident MM patients between 2020-2025. Complete prevalence was calculated using the National Cancer Institute's Complete Prevalence (ComPrev) software. Annual prevalent patients by LOT were defined as the number of MM patients who received a line therapy at any point in the given year, and who had not yet progressed to the next LOT. To calculate the number of unique patients during a given year who were on a specific LOT, the mean progression-free survival (PFS) of the LOT in months was calculated based on data from the 2018-2019 CMP Treatment Architecture (TA) physician surveys. The total estimate of MM patients on a LOT among prevalent patients was calculated using the annual estimate of patients initiating a line by year, divided by total months per year, then multiplied by the average PFS in months for that line. Results: Projected complete MM prevalence in the USA in 2020 was estimated at 144,922, further increasing to 162,339 by 2025. Projected unique MM patients by LOT in 2020 was estimated as 53,176 (1st LOT), 19,407 (2nd LOT), 6,481 (3rd LOT), 1,649 (4th LOT), and 426 (5th LOT) (refer to Table 1 for ranges). It is estimated the number of unique prevalent patients will increase over time for each line (total of 13% across 5 years). Conclusions: With different treatment options available, the choice of therapeutic approach for MM patients is an increasingly complex process. As more new anti-neoplastic agents are introduced and survival duration for patients with MM continues to increase with longer intervals between disease progression, patients are potentially able to receive multiple lines of therapy. In this study, the proportion of prevalent cases by line decreased with each additional LOT. The current study estimated overall lower proportions than previous studies for third line and beyond (Ruzafa 2016, Raab 2018). These differences can be attributed to the underlying assumptions and different methodologies used. The physicians responding to the TA survey are basing their responses on their own recall and clinical experience across all the multiple myeloma patients they treated over the past 6 months. Few published studies have reported on contemporary proportions of treated MM patients by LOT combining data from both registry sources and physician surveys in an epidemiology model. The results of this study show that incidence and prevalence by LOT for MM patients in the USA are estimated to increase between 2020-2025. While several factors can contribute to the increase of MM incidence and treated patients projected into the future, a key consideration is the underlying aging of the population (Vespa 2020). Between 2020-2025, the total incidence as well as the total unique patients treated by line increased substantially and the assumption is that this trend will continue. Funding: GSK (study: 213443). Disclosures Kanas: Kantar: Consultancy. Clark:Kantar: Consultancy, Current Employment, Honoraria. Keeven:Kantar: Consultancy, Current Employment. Nersesyan:Kantar: Consultancy, Current Employment. Sansbury:GSK: Current Employment, Current equity holder in publicly-traded company. Hoggea:GSK: Current Employment, Current equity holder in publicly-traded company.