Patient population with multiple myeloma and transitions across different lines of therapy in the USA: an epidemiologic model.

Javier Cid Ruzafa; Evie Merinopoulou; Rebecca F Baggaley; Pamela Leighton; Winifred Werther; Diana Felici; Andrew Cox; (2016) Patient population with multiple myeloma and transitions across different lines of therapy in the USA: an epidemiologic model. Pharmacoepidemiology and drug safety, 25 (8). pp. 871-879. ISSN 1053-8569 DOI: 10.1002/pds.3927
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PURPOSE: Multiple myeloma (MM) is a progressive, malignant neoplasia with a worldwide, age-standardized annual incidence of 1.5 per 100 000 individuals and 5-year prevalence around 230 000 patients. Main favorable prognostic factors are younger age, low/standard cytogenetic risk, and undergoing stem cell transplantation. Our aim was to estimate the size of the patient population with MM eligible to receive a new MM therapy at different lines of therapy in the USA. METHODS: We constructed a compartmental, differential equation model representing the flow of MM patients from diagnosis to death, via two possible treatment pathways and distinguished in four groups based on prognostic factors. Parameters were obtained from published references, available statistics, and assumptions. The model was used to estimate number of diagnosed MM patients and number of patient transitions from one line of therapy to the next over 1 year. Model output included 95% credible intervals from probabilistic sensitivity analyses. RESULTS: The base-case estimates were 80 219 patients living with MM, including 70 375 on treatment, 780 symptomatic untreated patients, and 9064 asymptomatic untreated patients. Over a 1-year period, the number of MM patients on treatment line 1 was estimated at 23 629 (credible intervals 22 236-25 029), and the number of transitions from treatment line 1 to treatment line 2 was estimated at 14 423. CONCLUSIONS: The size of the patient population with MM on different lines of therapy and in patient subgroups of interest estimated from this epidemiologic model can be used to assess the number of patients who could benefit from new MM therapies and their corresponding budgetary impact. Copyright © 2016 John Wiley & Sons, Ltd.


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