Predictors of tyrosine kinase inhibitor adherence trajectories in patients with newly diagnosed chronic myeloid leukemia | Zendy

Samantha Clark | Zendy; Zachary A. Marcum | Zendy; Jerald P. Radich | Zendy; Aasthaa Bansal | Zendy

Open Access

Predictors of tyrosine kinase inhibitor adherence trajectories in patients with newly diagnosed chronic myeloid leukemia

Author(s) -

Samantha Clark,

Zachary A. Marcum,

Jerald P. Radich,

Aasthaa Bansal

Publication year - 2020

Publication title -

journal of oncology pharmacy practice

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.548

H-Index - 34

eISSN - 1477-092X

pISSN - 1078-1552

DOI - 10.1177/1078155220970616

Subject(s) - medicine , myeloid leukemia , multinomial logistic regression , concomitant , logistic regression , tyrosine kinase inhibitor , population , oncology , demography , cancer , environmental health , machine learning , sociology , computer science

Although consistent use of tyrosine kinase inhibitors (TKIs) confers significant improvements in long-term survival for individuals with chronic myeloid leukemia (CML), only 70% of CML patients are adherent to TKIs. Understanding the factors that contribute to non-adherence and establishing dynamic adherence patterns in this population are essential aspects of targeted drug monitoring and intervention strategies.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research