title: A cost-effectiveness analysis of real-world treatment for elderly patients with multiple myeloma using a full disease model.
abstract: OBJECTIVE
  To study the impact of novel treatments for elderly (≥66 yr) patients with multiple myeloma (MM) in daily practice by comparing real-world effects [overall survival (OS) and quality-adjusted life years (QALYs)] and costs over time. Also, we calculate cost-effectiveness of treatment sequences commonly prescribed to predict effects and costs if patients had received a different treatment sequence.
  
  
  METHODS
  Real-world data including patient and disease characteristics, treatment information and resource use were collected from 1054 elderly patients with MM. Patients received first-line treatment during 2004-2007 (cohort 1) and 2008-2013 (cohort 2). The two cohorts were compared using a patient-level simulation (PLS) model comprising regression models which used patient and disease characteristics to estimate time to next treatment and death. Effects and costs from cohort 2 were compared to 4 commonly prescribed real-world sequences.
  
  
  RESULTS
  Utilisation of novel agents was higher for cohort 2 compared to cohort 1. Modelled average OS for cohort 1 was 38 months (median 25) and total costs €44,200. OS for cohort 2 was 42 months (median 28) and total costs €69,017. The model identified potential OS gains if all patients were to be treated using combinations containing thalidomide, lenalidomide and bortezomib in that particular order. This sequence had, compared to real-world treatment, the most favourable incremental cost-effectiveness ratio, €24,618 per life year gained and €34,875 per QALY.
  
  
  CONCLUSIONS
  Our patient-level model enabled to study the effects and costs of entire treatment sequences and to compare real-world treatment patterns over time. Increased utilisation of novel agents improved survival and increased costs for real-world patients with MM in the Netherlands.
authors.affiliation: Department of Health Policy & Management/institute for Medical Technology Assessment, Erasmus University, Rotterdam, The Netherlands.|Comprehensive Cancer Organisation, Utrecht, The Netherlands.
authors.forename: Hedwig M
authors.initials: HM
authors.lastname: Blommestein
authors.affiliation: Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands.
authors.forename: Silvia G R
authors.initials: SG
authors.lastname: Verelst
authors.affiliation: Department of Health Policy & Management/institute for Medical Technology Assessment, Erasmus University, Rotterdam, The Netherlands.
authors.forename: Saskia
authors.initials: S
authors.lastname: de Groot
authors.affiliation: Comprehensive Cancer Organisation, Utrecht, The Netherlands.|VU Medical Center Amsterdam, Amsterdam, The Netherlands.
authors.forename: Peter C
authors.initials: PC
authors.lastname: Huijgens
authors.affiliation: Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands.
authors.forename: Pieter
authors.initials: P
authors.lastname: Sonneveld
authors.affiliation: Department of Health Policy & Management/institute for Medical Technology Assessment, Erasmus University, Rotterdam, The Netherlands.|Comprehensive Cancer Organisation, Utrecht, The Netherlands.
authors.forename: Carin A
authors.initials: CA
authors.lastname: Uyl-de Groot
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000191:economics / Q000627:therapeutic use*; D000069286:Bortezomib / Q000191:economics / Q000627:therapeutic use*; D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D005260:Female; D006801:Humans; D000077269:Lenalidomide; D008297:Male; D009101:Multiple Myeloma / Q000188:drug therapy* / Q000191:economics / Q000401:mortality / Q000473:pathology; D009426:Netherlands; D019057:Quality-Adjusted Life Years; D016019:Survival Analysis; D013792:Thalidomide / Q000031:analogs & derivatives* / Q000191:economics / Q000627:therapeutic use*
chemical_list: D013792:Thalidomide; D000069286:Bortezomib; D000077269:Lenalidomide
keywords: bortezomib; cost-effectiveness analysis; lenalidomide; multiple myeloma; real-world data; registries; thalidomide