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PharmacoEconomics

, Volume 25, Issue 6, pp 481–496 | Cite as

Treatment Interruptions and Non-Adherence with Imatinib and Associated Healthcare Costs

A Retrospective Analysis among Managed Care Patients with Chronic Myelogenous Leukaemia
  • Theodore Darkow
  • Henry J. Henk
  • Simu K. Thomas
  • Weiwei Feng
  • Jean-Francois Baladi
  • George A. Goldberg
  • Alan Hatfield
  • Jorge Cortes
Original Research Article

Abstract

Objectives

Identify treatment interruptions and non-adherence with imatinib; examine the clinical and patient characteristics related to treatment interruptions and non-adherence; and estimate the association between treatment interruptions and non-adherence with imatinib and healthcare costs for US managed care patients with chronic myeloid leukaemia (CML).

Methods

This retrospective analysis utilised electronic healthcare claims data from a US managed care provider. Adult patients with CML (as determined by International Classification of Diseases, ninth revision, Clinical Modification [ICD-9-CM] diagnosis code) were identified who began treatment with imatinib from 1 June 2001 through 31 March 2004. Treatment interruptions (i.e. failure to refill imatinib within 30 days from the run-out date of the prior prescription) were identified during the 12-month follow-up period. Medication possession ratio (MPR), calculated as total days’ supply of imatinib divided by 365, was also examined. Healthcare costs (i.e. paid amounts for all prescription medications and medical services received, including health plan and patient liability) were examined in three ways: (i) total healthcare costs; (ii) total healthcare costs exclusive of imatinib costs; and (iii) total medical costs. All costs were converted to $US (2004 values) using the medical component of the Consumer Price Index.

MPR was modelled using ordinary least squares regression. Presence of treatment interruptions was modelled using logistic regression. The association between MPR and healthcare costs was estimated using a generalised linear model specified with a gamma error distribution and a log link. All models included adjustment for age, gender, number of concomitant medications, starting dose of imatinib and cancer complexity.

Results

A total of 267 patients were identified. Average age was approximately 50 years, and 43% were women. Mean MPR was 77.7%, with 31% of patients having a treatment interruption. However, all of these patients resumed imatinib within the study period. In this population, MPR decreased as the number of concomitant medications increased (p = 0.002), and was lower among women (p = 0.003), patients with high cancer complexity (p = 0.003) and patients with a higher starting dose of imatinib (p = 0.04). Women were approximately twice as likely as men to have a treatment interruption (p = 0.009), as were patients with a high cancer complexity (p = 0.03). After adjusting for the aforementioned covariates, MPR was found to be inversely associated with healthcare costs excluding imatinib (p < 0.001) and medical costs (p < 0.001). A 10% point difference in MPR was associated with a 14% difference in healthcare costs excluding imatinib and a 15% difference in medical costs. For example, patients with an MPR of 75% incur an additional $US4072 in medical costs annually compared with patients with an MPR of 85%.

Conclusions

Treatment interruptions and non-adherence with imatinib, both of which could lead to undesired clinical and economic outcomes, appear to be prevalent. Physicians and pharmacists should educate patients and closely monitor adherence to therapy, as improving adherence and limiting treatment interruptions may not only optimise clinical outcomes but also reduce the economic burden of CML.

Keywords

Imatinib Chronic Myeloid Leukaemia Healthcare Cost Treatment Interruption Chronic Myeloid Leukaemia Patient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors would like to acknowledge Dr Yiyu Fang for her assistance during data analysis. Support for this study was provided by Novartis Pharmaceuticals Corporation.

Simu Thomas, Weiwei Feng, Jean-Francois Baladi and Alan Hatfield are employees of Novartis and potentially hold stock options in the company. Jorge Cortes has received research funding from Novartis.

Supplementary material

40273_2012_25060481_MOESM1_ESM.pdf (138 kb)
Supplementary material, approximately 142 KB.

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Copyright information

© Adis Data Information BV 2007

Authors and Affiliations

  • Theodore Darkow
    • 1
  • Henry J. Henk
    • 1
  • Simu K. Thomas
    • 2
  • Weiwei Feng
    • 3
  • Jean-Francois Baladi
    • 3
  • George A. Goldberg
    • 4
  • Alan Hatfield
    • 3
  • Jorge Cortes
    • 5
  1. 1.i3 InnovusEden PrairieUSA
  2. 2.Novartis Pharmaceuticals CorporationEast HanoverUSA
  3. 3.Novartis Pharmaceuticals CorporationFlorham ParkUSA
  4. 4.i3 InnovusSanta MonicaUSA
  5. 5.MD Anderson Cancer CenterHoustonUSA

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