title: Health Care Resource Utilization and Costs in Patients with Chronic Myeloid Leukemia with Better Adherence to Tyrosine Kinase Inhibitors and Increased Molecular Monitoring Frequency.
abstract: BACKGROUND
  Frequent molecular monitoring (qPCR tests), as recommended by evidence-based monitoring guidelines, is associated with higher adherence to tyrosine kinase inhibitors (TKIs) in the management of chronic myeloid leukemia (CML); both factors have been associated with better clinical and economic outcomes.
  
  
  OBJECTIVE
  To (a) estimate the effect of more frequent qPCR tests on health care resource utilization (HRU) and associated costs, including direct (effect of qPCR test frequency on HRU) and indirect (through TKI adherence) effects, and (b) develop an economic model applicable to multiple clinical practice scenarios.
  
  
  METHODS
  Adult patients newly diagnosed with CML who started TKI firstline therapy were identified from U.S. administrative claims data (2010-2015). TKI adherence (medication possession ratio [MPR]), number of inpatient days, emergency room (ER) visits, outpatient service days, and mean costs per HRU event were measured during the first year of CML treatment. Direct and indirect effects of qPCR test frequency were estimated using multivariate regression models. Subsequently, an economic model was developed to assess the overall effect of varying qPCR test frequency on HRU and associated costs during the first year of CML treatment under different clinical practice scenarios; the scenario reported is the increase from 1 to 2 qPCR tests.
  
  
  RESULTS
  Of the 1,431 patients included, 36% had no qPCR tests, the average qPCR test frequency was 1.6, and the average MPR was 0.86 during the first year of CML treatment. The direct effect of increasing qPCR test frequency by 1 was associated with 13.0% fewer inpatient days (adjusted incidence rate ratio [adjusted IRR] = 0.87; P = 0.010); 8.3% fewer ER visits (adjusted IRR = 0.92; P = 0.043); and 3.0% more outpatient service days (adjusted IRR = 1.03; P = 0.002). Each increase of 1 test was associated with an increase in TKI adherence by 2.2 percentage points (adjusted MPR difference = 0.022; P < 0.001). When considering the indirect effect of qPCR test frequency through TKI adherence, an increase of 1 qPCR test combined with an increase in TKI adherence by 2.2 percentage points was associated with a greater reduction of inpatient days from 13.0% to 15.2%, ER visits from 8.3% to 8.6%, and a smaller increase of outpatient service days from 3.0% to 2.6%. Based on the economic model, an increase from 1 to 2 qPCR tests, considering the increase in TKI adherence, was associated with a reduction of 0.87 (95% CI = -1.49, -0.18) inpatient days and 0.06 (95% CI = -0.12, 0.05) ER visits, an increase of 0.98 (95% CI = 0.25, 1.60) outpatient service days and a cost savings of $2,918 (95% CI = -5,213, -349) per patient per year.
  
  
  CONCLUSIONS
  Closer alignment with the monitoring guidelines' recommended qPCR test frequency and better adherence to TKIs were associated with lower HRU and medical service costs. Managed care initiatives to increase qPCR test frequency and TKI adherence might benefit from an enhanced reduction because of the interaction between both factors.
  
  
  BACKGROUND
  This study was funded by Novartis Pharmaceuticals, which was involved in all stages of the study and in the decision to submit the report for publication. Latremouille-Viau, Guerin, Gagnon-Sanschagrin, and Dea are employees of Analysis Group, which received consulting fees from Novartis Pharmaceuticals for work on this study. Joseph is an employee of Novartis Pharmaceuticals and owns stock in Amgen and Pfizer. Cohen was an employee of Novartis Pharmaceuticals at the time of this study. Portions of this study were presented online (beginning May 20, 2016) as part of the American Society of Clinical Oncology (ASCO) Annual Meeting in Chicago, Illinois, on June 3-7, 2016, and as a poster at the American Society of Hematology (ASH) Annual Meeting in San Diego, California, on December 3-6, 2016. Study concept and design were contributed by Latremouille-Viau and Guerin, along with the other authors. Gagnon-Sanschagrin and Dea took the lead in data collection, assisted by the other authors, and data interpretation was performed by Cohen and Joseph, along with the other authors. The manuscript was written by Latremouille-Viau, along with the other authors, and revised by Joseph, along with the other authors.
authors.affiliation: 1 Analysis Group, Montreal, Canada.
authors.forename: Dominick
authors.initials: D
authors.lastname: Latremouille-Viau
authors.affiliation: 1 Analysis Group, Montreal, Canada.
authors.forename: Annie
authors.initials: A
authors.lastname: Guerin
authors.affiliation: 1 Analysis Group, Montreal, Canada.
authors.forename: Patrick
authors.initials: P
authors.lastname: Gagnon-Sanschagrin
authors.affiliation: 1 Analysis Group, Montreal, Canada.
authors.forename: Katherine
authors.initials: K
authors.lastname: Dea
authors.affiliation: 2 Novartis Pharmaceuticals, East Hanover, New Jersey.
authors.forename: Benjamin G
authors.initials: BG
authors.lastname: Cohen
authors.affiliation: 2 Novartis Pharmaceuticals, East Hanover, New Jersey.
authors.forename: George J
authors.initials: GJ
authors.lastname: Joseph
mesh_terms: D000368:Aged; D000553:Ambulatory Care / Q000706:statistics & numerical data; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006801:Humans; D015464:Leukemia, Myelogenous, Chronic, BCR-ABL Positive / Q000188:drug therapy*; D008297:Male; D008875:Middle Aged; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data*; D047428:Protein Kinase Inhibitors / Q000627:therapeutic use*; D011505:Protein-Tyrosine Kinases / Q000037:antagonists & inhibitors*; D012189:Retrospective Studies; D014481:United States; D016903:Drug Monitoring
chemical_list: D047428:Protein Kinase Inhibitors; D011505:Protein-Tyrosine Kinases