RESUMO
Health-related quality of life is frequently included in patient-reported outcomes aimed at evaluating the effectiveness of disease-modifying drugs for multiple sclerosis, but recent data about Italian patients are missing. A multicenter observational and cross-sectional study was performed by students of hospital pharmacy to update existing data on quality of life and to correlate it with the pharmacological and medical history of patients. Quality of life (QoL) was assessed using the MS-QoL54 questionnaire, and the pharmacist collected patients' characteristics, medical and pharmacological history, and Expanded Disability Status Scale (EDSS). Three hundred and forty-nine patients with multiple sclerosis were recruited from 16 centers between May 2018 and June 2019 (median age = 44.1 years; 68.9% women). The composite indexes of physical and mental well-being showed direct correlation with each other (R = 0.826; p < 0.001), and EDSS disability was an independent negative predictor of both indexes (R2 = 35.08% p < 0.001 and R2 = 15.74% p < 0.001, respectively). A trend of association between Physical Health Composite Score and different classes of oral disease-modifying drugs (DMDs) was observed. Our study found a decrease in QoL correlated with teriflunomide, which deserves further investigation. This experience demonstrates that joint action between scientific society and students association can be successful in conducting a no-profit multicenter observational study in a real-world setting.
RESUMO
Background Cancer patients can be a human model of potential drug interactions. Usually they receive a large number of different medications, including antineoplastic agents, drugs for comorbid illness and medication for supportive care, however information about these interactions are fragmented and poor. Objective We assessed a prospective study to evaluate the prevalence of drug interaction among patients hospitalized in the Onco-Haematology department, Hospital of Piacenza. Methods Data on drugs administered for cancer, comorbidities, or supportive care were collected from different computerized prescription software in use in the department; we compared them with a database to focus on the co-administration of drugs. A literature review was performed to identify major potential drug interaction and to classify them by level of severity and by strengths of scientific evidence. Results In this study 284 cancer patients were enrolled; patients had taken an average of seven drugs on each day of therapy plus chemotherapeutic agents, we identified 67 potential drug interactions. At least 53 patients had one potential drug interaction. Of all potential drug interactions 63 were classified as moderate severity and only four as major. In 55 cases chemotherapeutic agents were involved in possible interactions with supportive care drugs, meanwhile in 12 cases the potential drug interactions were between supportive care drugs. Conclusions In our centre, thanks to a computerized prescription software, integrated with caution alarm in case of possible interaction, we had a lower rate of potential drug interactions than the one from literature. It is possible to improve the software integrating the alarm with the potential drug interactions between chemotherapy agents and supportive care drugs.
