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Ruxolitinib Adherence in Myelofibrosis and Polycythemia Vera: the "RAMP" Italian multicenter prospective study.

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Summary

Low adherence to ruxolitinib is common in myelofibrosis and polycythemia vera patients, often due to supply issues. Addressing adherence challenges is crucial for optimizing treatment outcomes.

Keywords:
AdherenceAdherence to medicationDistressMyelofibrosisPolycythemia VeraRuxolitinib

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Area of Science:

  • Hematology
  • Pharmacology
  • Patient Adherence Research

Background:

  • Ruxolitinib is a key treatment for myelofibrosis (MF) and polycythemia vera (PV).
  • Limited data exists on patient adherence to ruxolitinib therapy.
  • Understanding adherence barriers is vital for effective MF and PV management.

Purpose of the Study:

  • To evaluate ruxolitinib adherence rates and associated factors in MF and PV patients.
  • To identify predictors of low adherence and high distress.
  • To explore the relationship between adherence and treatment response.

Main Methods:

  • Prospective, multicenter RAMP study (NCT06078319) enrolled 189 ruxolitinib-treated patients.
  • Adherence was assessed using the Adherence to Refills and Medications Scale (ARMS).
  • Distress was measured using the Distress Thermometer and Problem List (DTPL).

Main Results:

  • Nearly 50% of patients exhibited low adherence (ARMS > 14) and over 40% reported high distress (DT ≥ 4) at baseline.
  • Difficult ruxolitinib supply was the primary reason for low adherence (49%).
  • Low adherence correlated with male sex, high distress, and longer treatment duration (≥ 1 year).
  • Unintentional non-adherence decreased significantly by week 48.
  • Stable high adherence and low distress were linked to spleen response at week 24 in MF patients.

Conclusions:

  • Low ruxolitinib adherence is a significant unmet need in MF and PV.
  • A multifaceted approach, considering patient characteristics and treatment duration, is required.
  • Identifying non-adherent patients can help differentiate refractory disease from those needing therapy optimization.