Aromatase Inhibitor-Induced Arthralgia: A Proposed Management Algorithm
Aromatase Inhibitor-Induced Arthralgia: A Proposed Management Algorithm
Aromatase inhibitors are the most effective adjuvant anti-hormonal therapy for estrogen receptor positive (ER+) post-menopausal breast cancer patients, with proven superiority over tamoxifen in terms of disease-free survival, time to recurrence, and contralateral breast cancer. However, approximately half of the women who take this drug will develop significant joint pains, termed Aromatase Inhibitor-Induced Arthralgia (AIA). Though this medicine should be taken for 5 years, the joint pain can be so troublesome that up to 13% may prematurely discontinue it because of the arthralgia, thus sacrificing their best chance of recurrence-free survival. Nonetheless, neither the etiology nor optimal management of AIA is clearly understood, leaving both doctor and patient rather frustrated.
The investigators therefore propose to test the hypothesis that AIA can be effectively treated by a new clinical algorithm, and that effective treatment of the problem will lead to improved compliance with Aromatase Inhibitor (AI) therapy. The algorithm is a clinical pathway for treating AIA which incorporates, in a rational and step-wise manner, a series of interventions based on the available evidence. Interventions include acupuncture, pain medication, weight bearing exercise, and other commonly used therapies for AIA.
The investigators will enroll 100 women who are beginning adjuvant AI therapy and assess each woman's baseline joint pains via a questionnaire as well as grip strength measurement. The investigators will then periodically repeat these tests during AI therapy in order to systematically quantify and characterize AIA. Those women who develop AIA during the course of the study will be placed on the clinical algorithm, and the investigators will observe whether their joint pains significantly improve (as measured by questionnaire and grip strength measurement) after institution of the algorithm. The investigators will also determine whether their compliance is improved compared to historical controls, and at least non-inferior to the women in the study who do not develop AIA. Finally, the investigators will measure serum estrogen level at baseline and then periodically during AI therapy to investigate whether more dramatic decline in estrogen level after initiation of an AI leads to significant AIA and earlier time to onset.
This study targets a very common cause of pain among breast cancer survivors and aims to offer an effective treatment strategy to alleviate pain and improve quality of life as well as medication compliance.
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