An Epidemiology Model for Estimating the Numbers of US Patients With Multiple Myeloma by Line of Therapy and Treatment Exposure

Dec 1, 2022, 00:00
10.1016/j.jval.2022.05.011
https://www.valueinhealthjournal.com/article/S1098-3015(22)01999-4/fulltext
Title : An Epidemiology Model for Estimating the Numbers of US Patients With Multiple Myeloma by Line of Therapy and Treatment Exposure
Citation : https://www.valueinhealthjournal.com/action/showCitFormats?pii=S1098-3015(22)01999-4&doi=10.1016/j.jval.2022.05.011
First page : 1977
Section Title : METHODOLOGY
Open access? : No
Section Order : 1977

Objectives

Estimates on the distribution of patients with multiple myeloma (MM) by line of therapy (LOT) are scarce and get outdated quickly as new treatments become available. The objective of this study was to estimate the number of patients with MM by LOT and the number of patients who have received at least 4 previous LOTs including proteasome inhibitors, immunomodulatory agents, and anti-CD38 monoclonal antibodies (mAbs).

Methods

A compartmental model was developed to calculate the number of patients by LOT. Two pathways were considered based on stem cell transplant eligibility, and at each pathway, treatments were stratified in 2 types: anti-CD38 mAbs or other. The model population was stratified into 4 subgroups based on age and cytogenetic risk. Model inputs were informed from real-world evidence.

Results

The model estimated that, in 2020, 126 869 patients were living with MM in the United States. Of these, 105 701 received treatment in any LOT, with 56 959, 27 252, 11 258, and 5217 in lines 1 to 4, respectively, and 5015 in line 5 or beyond. The model estimated that 3497 patients received at least 4 previous LOTs including proteasome inhibitors, immunomodulatory agents, and anti-CD38 mAbs. The model overall prevalence predictions aligned well with publicly available estimates.

Conclusions

This study proposes a novel framework to estimate MM prevalence. It can assist clinicians to understand future trends in MM epidemiology, healthcare systems to plan for future resource use allocation, and payers to quantify the budget impact of new treatments.

Categories :
  • Decision Modeling & Simulation
  • Oncology
  • Specific Diseases & Conditions
  • Study Approaches
Tags :
  • differential equations
  • epidemiology
  • line of therapy
  • modeling
  • multiple myeloma
  • prevalence
Regions :
  • North America
ViH Article Tags :