Assessment of potential drug interactions in rheumatology: a comparative study o...

연구 요약

Assessment of potential drug interactions in rheumatology: a comparative study of decision support software.

Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences 학술지에 발표된 이 연구는 Şahin Y, Yildirim HB, Okumuş H 외 연구팀이 수행하였습니다.

이 연구는 'Assessment of potential drug interactions in rheumatology: a comparative study of decision support software.'에 대한 과학적 분석을 제공합니다.

핵심 내용

BACKGROUND: Rheumatologic diseases often require long-term, complex pharmacotherapy involving immunosuppressive and anti-inflammatory agents. This complexity leads to a high prevalence of polypharmacy and increases the risk of potential drug–drug interactions (pDDIs), which may reduce efficacy, cause adverse effects, prolong hospitalization, and increase costs. Clinical decision support systems (CDSSs) are used to detect pDDIs, but inconsistencies in knowledge bases, severity classification, and evidence sources challenge their reliability. OBJECTIVES: To identify pDDIs in rheumatology patients and compare different CDSSs used in their evaluation. METHODS: This prospective cross-sectional study was conducted between January–July 2022 in a rheumatology outpatient clinic in Ağrı, Türkiye. Adult patients (≥ 18 years) using ≥ 2 systemic drugs (including one rheumatologic agent) were included. Data were collected by a rheumatologist, clinical pharmacist, and pharmacy student. pDDIs were identified using Lexidrug® and Micromedex®, with D/major and X/contraindicated levels considered clinically significant. Statistical analyses were performed using SPSS v29; concordance between systems was assessed via Kendall’s W test. RESULTS: Among 147 patients (64.6% female; mean age 45 ± 13.58 years), rheumatoid arthritis (46.3%), ankylosing spondylitis (27.9%), and Behçet’s disease (7.5%) were most common. Median disease duration was 4 years (IQR: 1–10); median drug count was 3 (IQR: 2–4). Hypertension (18.4%) and diabetes (11.6%) were frequent comorbidities. No concordance was found between CDSSs for contraindicated/major pDDIs; weak concordance was observed for total pDDIs (Kendall’s W: 0.006; 0.001; 0.286). Clinically significant interactions were identified in 87% (Lexidrug) and 84% (Micromedex) of differing pDDI pairs. Most frequent pDDIs were leflunomide–prednisolone (Lexidrug, 17.3%) and folic acid–methotrexate (Micromedex, 15.1%). CONCLUSION: Clinically significant pDDIs are common in rheumatology patients, with notable discrepancies between CDSSs. Clinical pharmacists play a vital role in interpreting interaction alerts and supporting safe prescribing. Using multiple CDSSs and fostering interdisciplinary collaboration may enhance patient safety and treatment outcomes.

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