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Treatment Patterns, Adherence, Persistence, and Health Care Resource Utilization in Acromegaly: A Real-World Analysis
Maria Fleseriu1, Ariel Barkan2, Thierry Brue3
1Pituitary Center, Departments of Medicine and Neurological Surgery, Oregon Health & Science University, Portland, OR 97239, USA.
Context:
Treatment of acromegaly is multimodal for many patients, and medical treatments include somatostatin receptor ligands (SRLs), dopamine agonists (DAs), and growth hormone receptor antagonists (GHRAs). However, recent real-world evidence on treatment patterns for patients with acromegaly is limited.
Objective:
This study evaluated medication usage, treatment changes, adherence, persistence, comorbidities, and health care resource utilization using deidentified data from MarketScan, a US claims database.
Methods:
Eligible patients (n = 882) were those receiving monotherapy or combination therapy for ≥90 days without treatment gaps.
Results:
Mean age at diagnosis was 48.6 years; 50.1% of patients were female. Over half (59.4%) had 1 line of treatment (LOT); 23.1% had 2 LOTs; 17.5% had at least 3 LOTs. Most patients (94.6%) initiated treatment with monotherapies. The most common first-line monotherapy treatments were cabergoline (DA, 36.8%), octreotide long-acting release (first-generation SRL, 29.5%), and lanreotide depot (first-generation SRL, 22.5%). Adherence for first-line treatments (proportion of days covered) was higher for first-generation SRLs (lanreotide depot: 0.8) compared with DAs (0.7). Treatment persistence (time between the first treatment record and a change in LOT/censoring) in LOT 1 was higher for GHRAs (24.8 months) and first-generation SRLs (20.0 months) compared with DAs (14.4 months). Female patients and those diagnosed at a younger age were more likely to have shorter treatment persistence. The most prevalent comorbidities were hyperlipidemia, essential hypertension, and sleep apnea.
Conclusion:
Patients with more comorbidities had more health care visits during the first year after diagnosis, suggesting increased disease burden. Real-world evidence on treatment patterns provides insights into recommendations for individualized therapy.
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