Joint pain severity predicts premature discontinuation of aromatase inhibitors in breast cancer survivors

Third-generation aromatase inhibitors (AIs) are commonly prescribed as standard adjuvant therapy for postmenopausal breast cancer survivors with hormone-receptor positive disease and are associated with improved disease-free survival compared with the previous standard of tamoxifen therapy [1‐4]. The recommended duration of initial adjuvant endocrine therapy is five years though some patients have benefitted from extended therapy. Current American Society of Clinical Oncology guidelines recommend incorporating an AI either as primary, sequential (following 2–3 years of tamoxifen), or extended therapy (following 5 years of tamoxifen) [5].

Despite the survival benefits of AIs, many women demonstrate some degree of non-adherence with their use. Non-adherence, a term which comprises both non-compliance with dosing, timing, and instruction of medication and non-persistence, or early discontinuation of medication, represents an emergent area to intervene for treatment benefit. Indeed, non-adherence of adjuvant endocrine therapy has been associated with increased mortality in breast cancer patients [6]. In the emerging literature, premature discontinuation of AI therapy ranges from 13-35% [7‐9].

Despite the prevalence of early medication discontinuation and its deleterious effects, little is understood about risk factors for premature discontinuation of AI therapy. The available adherence research largely consists of medical claims-based epidemiological studies in which younger age, increased cormorbidities, and higher medication co-payments have been noted as risk factors for nonadherence to adjuvant therapy [10‐12]. While these studies are useful in quantifying the magnitude of medication nonadherence, they often lack clinical insights into patient perspectives such as the reasons for premature discontinuation. AI-associated arthralgia, or joint pain, has been recognized as a particularly debilitating side effect which develops in nearly half of women treated with AIs [13, 14]. In online breast cancer message board discussions, joint pain is the most commonly mentioned side effect of AIs and often leads to AI discontinuation [15]. Although joint pain was the most cited reason for premature discontinuation of AIs in a recently published clinical trial, little is known about how levels of joint pain may predict early discontinuation of therapy [9]. Appropriate identification of patients most at risk for discontinuing therapy may provide an opportunity for early interventions to alleviate the adverse effects of joint pain and improve medication adherence. We conducted a retrospective cohort study to determine whether patient-reported joint pain severity predicts premature discontinuation of AIs. As a secondary aim, we examined provider-documented pain and practice behaviors among those with clinically important pain.

In this retrospective analysis we evaluated whether patient-reported joint pain severity is predictive of premature discontinuation of AIs. After controlling for demographic and clinical characteristics, patients who reported worst joint pain severity of 4 or greater on the BPI were significantly more likely to prematurely discontinue AI therapy. However, patient-reported AIAA did not predict premature discontinuation. Although clinicians often documented the presence of joint pain in the EMR of patients with clinically important pain, no quantitative assessment was used, and only half offered a plan to further evaluate or treat pain. These findings warrant future clinical improvements in both pain diagnosis and management for breast cancer survivors receiving AI therapy.

Premature discontinuation specific to AI therapy has been reported to range from 13-35% in the emerging literature [7‐9]. These variations may be due to population characteristics (clinical trial vs. community), time to follow-up, and different definitions of premature discontinuation. In our study 11% of women who were on AI therapy at cohort entry stopped medication during a follow-up period of 29–45 months. This rate is predictably lower than the total premature discontinuation rate of the entire cohort given that nearly half of our study population was still taking an AI at the time of the study and remain at risk for prematurely discontinuing therapy. Additionally, 40 individuals were excluded from analysis for not taking AIs at the time of recruitment. Among those, 29 patients had prematurely discontinued AI therapy; in sum, 16% of the sample which falls in the range of reported premature discontinuation rates in the literature.

Premature discontinuation, as one aspect of non-adherence, has substantial negative effects by the very meaning of its definition – the complete cessation of therapy. Hershman et al. demonstrated an absolute increase in mortality of more than 7% in women who prematurely discontinued hormonal therapy with either an AI or tamoxifen compared to those who continued therapy over a 4.5 year period. Even with adjustment for relevant clinical and demographic variables, early discontinuation was associated with a relative 26% increase in all-cause mortality [6]. These results emphasize the importance of identifying patients most at risk for stopping AIs and targeting interventions toward this group.

We found patient-reported worst joint pain severity of 4 or greater to be predictive of premature AI discontinuation. Interestingly, patient-reported AI-associated arthralgia was not a significant predictor, suggesting that it is the severity of joint pain, rather than its assumed origins, that may lead women to stop therapy. The finding of joint pain severity as a predictor of premature discontinuation is consistent with a recently published study in a clinical trial setting in which higher baseline pain is a positive predictor of early discontinuation of AI therapy [9]. These findings suggest that although patients may function reasonably well at low pain levels, a threshold may exist beyond which pain is difficult to ignore and may impact adherence behavior. Our results suggest a BPI worst pain rating of 4 or greater may be a threshold for predicting premature discontinuation to AI therapy, a finding warranting validation in independent datasets.

In contrast to research suggesting physicians' failure to routinely assess patient pain [20], it is encouraging that joint pain was documented in the majority of provider notes for patients reporting pain ratings of 4 or greater. Despite the high percentage of symptom reporting, the lack of specific pain quantification warrants improvement. Quantitative pain assessments provide a reliable and valid measure of pain intensity and are recommended by the National Comprehensive Cancer Network (NCCN) Practice Guidelines for cancer pain [21]. A simple measure such as a 10-point numerical rating scale of pain can be easily and reliably incorporated into an outpatient visit [20]. With the emergence of health technology, electronic patient-report assessments can be utilized to provide quantitative assessments of patient pain and facilitate patient-provider communication regarding symptom distress [22]. Ultimately, with targeted therapies currently under investigation to alleviate joint pain related to AIs [23‐25], patients and their providers will have increasingly effective options to manage joint pain rather than discontinuing AI therapy.

In multivariate modeling, we found that controlling for joint pain severity strengthened the association between prior tamoxifen use and premature discontinuation of AIs. This suggests that for patients who experience the same level of pain severity, they are more likely to discontinue AIs if they had prior use of tamoxifen. Based on clinical experience, it is possible that prior tamoxifen users who perceived that they had adequate hormonal therapy were therefore less tolerant of side effects of AIs. Another possible explanation is that prior tamoxifen users have gotten used to the side effects of tamoxifen over time and when they experience new side effects related to AIs, they prefer to switch back to tamoxifen rather than staying on AIs.

Our study has several potential limitations. First, in our retrospective cohort study design, we assessed joint pain one time to predict premature discontinuation of AIs. As pain may change over time, our data does not provide an absolute cut-off pain level necessary to discontinue AIs and requires validation in independent datasets. Additionally, our retrospective design did not include patients who prematurely discontinued AIs prior to enrollment which may bias our results towards null. Thus, the strength of association between joint pain severity and premature discontinuation may in fact be even stronger. Third, our outcome focused on premature discontinuation based on chart-abstraction. Theoretically, patients may discontinue therapy without informing their providers; however, if that is the case, it should bias our results towards null. Lastly, our research was conducted in a large academic medical center which may limit the ability to generalize findings to community hospital settings.

Despite these limitations, our study had a number of strengths including a large clinical population, incorporation of patient-reported outcome, and examination of provider pain diagnosis and management behaviors. We found that patient-reported joint pain severity of 4 or greater was significantly associated with early discontinuation of therapy. These results highlight the importance of medical providers performing quantitative assessments of pain and inquiring about other medication adverse effects in order to appropriately identify patients who may be at risk for stopping therapy. Targeting interventions for these patients will ultimately optimize adherence to AIs and improve both quality of life and survival outcomes for women with breast cancer.

Written informed consent was obtained from each participant.