Background: Several drugs are available for the treatment of autoimmune rheumatic diseases; however, their effectiveness may be negatively influenced by inappropriate adherence. Low adherence and persistence rates have a significant impact on patient quality of life and are associated with health-related expenses. Purpose: To provide an up-to-date narrative review on treatment adherence and persistence rates, and discuss the factors that influence them, in patients with autoimmune rheumatic diseases. Materials and methods: We searched the PubMed database for studies among patients with a diagnosis of rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), or psoriatic arthritis (PsA), published from January 2015 to February 2017. Only studies with a well-defined measurement of adherence/persistence and those that carried out an evaluation of the influencing factors were included. Results: Fifteen relevant studies that evaluated adherence and/or persistence were included. Adherence rates varied between 9.3% and 94%, and persistence rates between 23% and 80%. Most of the studies used one method to evaluate adherence or persistence (different questionnaire scores, proportion of days covered, and mean treatment duration). A high concordance was found between the adherence measurements of the Medication Event Monitoring System and Visual Analog Scale. Factors of economic, demographic, and clinical nature were only moderately linked to treatment adherence or persistence. However, patient-related factors – such as positive and increased beliefs in medication necessity, strong views of the chronic nature of the diseases, and increased knowledge of the disease – were related to better treatment adherence. Conclusion: Owing to the heterogeneity of the study results, we consider that the use of more than one method to assess adherence/persistence should yield more comprehensive and accurate data about patient adherence behavior. Patient-related factors should be included and analyzed more often in adherence studies as the former may be modified to improve patient adherence.

Oxidative stress plays a key role in the development of chronic diabetes-related complications. Previous metabolomic studies showed a positive association of diabetes and insulin resistance with branched-chain amino acids (AAs) and aromatic AAs. The purpose of this research is to identify distinct metabolic changes associated with increased oxidative stress, as assessed by nitrotyrosine levels, in type 2 diabetes (T2DM). Serum samples of 80 patients with insulin-treated T2DM are analyzed by AA-targeted metabolomics using ultrahigh-performance liquid chromatography/mass spectrometry. Patients are divided into two groups based on their nitrotyrosine levels: the highest level of oxidative stress (Q4 nitrotyrosine) and lower levels (Q1–Q3 nitrotyrosine). The identification of biomarkers is performed in MetaboAnalyst version 5.0 using a t-test corrected for false discovery rate, unsupervised principal component analysis and supervised partial least-squares discriminant analysis (PLS-DA). Four AAs have significantly different levels between the groups for highest and lower oxidative stress. Cysteine, phenylalanine and tyrosine are substantially increased while citrulline is decreased (p-value 1). Corresponding pathways that might be disrupted in patients with high oxidative stress are phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, phenylalanine metabolism, cysteine and methionine metabolism and tyrosine metabolism.

Statins are included in the category of high-frequency prescription drugs, and their use is on an upward trend worldwide. In 2012, the FDA issued a warning about possible cognitive adverse drug reactions (ADRs) related to statins, some of which are listed in the Summary of Product Characteristics, but there are still concerns about their potential risk of psychiatric events. The aim of this research was to investigate spontaneous reports containing psychiatric ADRs associated with statins by analyzing the EudraVigilance (EV) database. From January 2004 to July 2021, a total of 8965 ADRs were reported for the Systems Organ Class (SOC) “psychiatric disorders”, of which 88.64% were registered for atorvastatin (3659), simvastatin (2326) and rosuvastatin (1962). Out of a total of 7947 individual case safety reports (ICSRs) of the 3 statins mentioned above, in 36.3% (2885) of them, statins were considered the only suspected drug, and in 42% (3338), no other co-administered drugs were mentioned. Moreover, insomnia has been reported in 19.3% (1536) of cases, being the most frequent adverse reaction. A disproportionality analysis of psychiatric ADRs was performed. The Reporting Odds Ratio (ROR) and 95% confidence interval (95% CI) were calculated for simvastatin, atorvastatin and rosuvastatin compared with antiplatelets and antihypertensive drugs. The reporting probability for most ADRs of these statins compared to antiplatelets was higher. The reporting probability for insomnia, nightmares and depression produced by statins compared to antihypertensive drugs was also higher. The results of this analysis augment the existing data about a possible correlation between the administration of statins and the occurrence of psychiatric side effects.

Background: Safety monitoring of all drugs throughout their entire life cycle is mandatory in order to protect the public health. Our objective was to describe all new safety signals assessed at EU level by the Pharmacovigilance Risk Assessment Committee (PRAC). Methods: Publicly available data on signals assessment from PRAC meeting minutes for the period January 2014–November 2017 were analyzed and classified. Results: A total of 239 new signals for 194 drugs/drug combinations/therapeutic classes were evaluated by PRAC. A total of 154 signals were triggered by spontaneous reporting, 31 by literature case reports, and 26 by observational studies. In 188 signals, the drugs involved were authorized for more than 5 years. The drug classes for which most signals were detected were antineoplastic/immunomodulators (n = 75), anti-infectives (n = 34), and drugs acting on the nervous system (n = 27). Signals were triggered for drug interactions (n = 15), in utero exposure (n = 7), medication errors (n = 6), and for different disorders, among which the skin/subcutaneous tissue disorders were more common. PRAC recommendations consisted in label updates (n = 86), in Direct Healthcare Professional Communications (n = 17), and in eight recommendations for a more complex evaluation through referral procedures. Conclusions: Most new signals assessed were triggered by spontaneous reporting and led to routine risk minimization measures, such as updating the product information.