Abstract PD12-03: Predictors of pain reduction in trials of interventions for aromatase inhibitor (AI)-associated musculoskeletal symptoms (AIMSS)

Abstract

Abstract Background: Up to half of AI-treated breast cancer patients experience AIMSS, and 20-30% have severe symptoms that lead to treatment discontinuation. Multiple interventions have been examined in randomized clinical trials, including in SWOG S0927 (omega-3 fatty acids vs placebo), S1202 (duloxetine vs placebo), and S1200 (true acupuncture vs sham acupuncture vs wait list control). We hypothesized that we could identify predictors of pain reduction in AIMSS intervention trials by combining data from these trials. Methods: The S0927, S1200, and S1202 clinical trials had similar eligibility criteria, and all used the same patient-reported outcomes measures to assess arthralgias and endocrine symptoms. The Brief Pain Inventory (BPI) examines average pain, worst pain, and pain interference; higher numbers reflect more symptoms. Endocrine symptoms were assessed with the Functional Assessment of Cancer Therapy-Endocrine Subscale (FACT-ES), which includes subscales for functional and physical well-being; higher scores reflect better function. We also used validated measures to assess joint symptoms in the knees/hips (WOMAC) and hands (M-SACRAH), where higher scores indicate greater symptom severity. We analyzed the subset of patients enrolled on these three trials who had a baseline BPI average pain score of at least 4/10 (S0927, n=185; S1200, n=158; S1202, n=240). The primary outcome was 50% reduction in BPI average pain from baseline to week 12. Variable cut-point selection was performed on each continuous variable to identify a binary cut-point that optimally distinguished high versus low levels of pain reduction. Logistic regression was performed for each variable. A risk model was built by summing the number of statistically significant baseline predictors and categorizing patients by low vs. medium vs. high likelihood of pain reduction. All analyses were stratified by study and adjusted for treatment arm. Results: Of the 583 analyzed patients, median age was 60 years (range 27-84), median body mass index was 30 kg/m2 (range 18-84), and 208 patients (35.7%) had at least a 50% reduction in BPI average pain. Factors significantly associated with at least a 50% reduction in pain included lower pain and pain interference and better physical and functional status at study enrollment (Table). Patients with 2-4 of the 7 statistically significant factors were twice as likely to experience pain reduction compared to those with fewer than 2 factors (37.8% vs. 22.5%; odds ratio [OR] 2.08, 95% CI 1.38-3.13, p<.001). Those with 5-7 factors were more than 5 times more likely to experience pain reduction (61.2% vs. 22.5%; OR 5.66, 95% CI 3.21-9.98, p<.001). Conclusions: Patients with AIMSS who have lower pain and better functional status are more likely to experience meaningful pain reduction in intervention trials for AIMSS. These findings suggest early intervention for treating AIMSS may be important. Baseline pain and functional status should be considered as stratification factors in future interventional trials. Funding: NIH/NCI Grant Award CA189974; and in part by the Hope Foundation for Cancer Research. Association of baseline characteristics with 50% reduction in average pain from baseline to 12 weeksFactorRates of pain reductionOdds Ratio (95% CI)P valueAge: <70 vs ≥70 years37.1% vs. 26.3%1.66 (0.96-2.86)0.07BMI: <30 vs. ≥30 kg/m237.9% vs. 33.6%1.27 (0.90-1.79)0.17BPI average pain: 4 vs. ≥548.6% vs. 31.7%1.93 (1.30-2.86)0.001BPI worst pain: <6 vs. ≥649.0% vs. 32.8%1.95 (1.26-3.02)0.003BPI pain interference: <3 vs. ≥347.8% vs. 31.9%2.21 (1.47-3.32)0.0001FACT-ES Functional Well-Being: ≥24 vs. <2449.3% vs. 33.9%1.97 (1.18-3.30)0.01FACT-ES Physical Well-Being: ≥12 vs. <1238.6% vs. 21.1%2.45 (1.44-4.18)0.001FACT-ES Endocrine Subscale: ≥42 vs. <4236.7% vs. 29.7%1.44 (0.84-2.47)0.19WOMAC: <50 vs. ≥5049.0% vs. 26.0%2.63 (1.85-3.74)<.001M-SACRAH: <33 vs. ≥3345.6% vs. 27.4%2.18 (1.54-3.10)<.001 Citation Format: N. Lynn Henry, Joseph M Unger, Cathee Till, Katherine D Crew, Michael J Fisch, Dawn L Hershman. Predictors of pain reduction in trials of interventions for aromatase inhibitor (AI)-associated musculoskeletal symptoms (AIMSS) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD12-03.