Duchenne Muscular Dystrophy (DMD) is a rare disorder caused by mutations in the dystrophin gene. A recent systematic review and meta-analysis of global DMD epidemiology is not available. This study ...aimed to estimate the global overall and birth prevalence of DMD through an updated systematic review of the literature. MEDLINE and EMBASE databases were searched for original research articles on the epidemiology of DMD from inception until 1st October 2019. Studies were included if they were original observational research articles written in English, reporting DMD prevalence and/or incidence along with the number of individuals of the underlying population. The quality of the studies was assessed using a STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) checklist adapted for observational studies on rare diseases. To derive the pooled epidemiological prevalence estimates, a meta-analysis was performed using random-effects logistic models for overall and birth prevalence and within two different underlying populations (i.e. all individuals and in males only), separately. Heterogeneity was assessed using Cochran's Q-test along with its derived measure of inconsistency I.sup.2. A total of 44 studies reporting the global epidemiology of DMD were included in the systematic review and only 40 were included in the meta-analysis. The pooled global DMD prevalence was 7.1 cases (95% CI: 5.0-10.1) per 100,000 males and 2.8 cases (95% CI: 1.6-4.6) per 100,000 in the general population, while the pooled global DMD birth prevalence was 19.8 (95% CI:16.6-23.6) per 100,000 live male births. A very high between-study heterogeneity was found for each epidemiological outcome and for all underlying populations (I.sup.2 > 90%). The test for funnel plot asymmetry suggested the absence of publication bias. Of the 44 studies included in this systematic review, 36 (81.8%) were assessed as being of medium and 8 (18.2%) of low quality, while no study was assessed as being of high quality. Generating epidemiological evidence on DMD is fundamental to support public health decision-making. The high heterogeneity and the lack of high quality studies highlights the need to conduct better quality studies on rare diseases.
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Tyrosine kinase inhibitors (TKIs), the treatment of choice for chronic myeloid leukemia (CML), can be associated to cardiovascular (CV) adverse events (AEs). A case/non-case study was performed using ...AE reports registered in the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database to compare the risk of CV event reports related to TKIs indicated in the management of chronic myeloid leukemia (CML). Disproportionality of CV event-related TKIs was computed using the Reporting Odds Ratio (ROR) as a measure of potential risk increase. Nilotinib accounts for more than half of reported cases related to TKIs. Signal of Disproportionate Reporting (SDR) was found for cardiac failure, ischemic heart disease, cardiac arrhythmias,
/QT prolongation, hypertension, and pulmonary hypertension. Dasatinib and bosutinib were related to the highest disproportionality for cardiac failure. Nilotinib was associated with the highest SDR for ischemic heart disease,
/QT prolongation and cardiac arrhythmias. Only ponatinib was related to an SDR for hypertension, while dasatinib and imatinib were related to pulmonary hypertension. In the context of CML, TKIs have different safety profiles related to CV events, among which nilotinib seems particularly related to. These results claim for a revision of its CV safety profile mainly for the risk of
/QT prolongation.
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Sleepiness at the wheel is widely believed to be a cause of motor vehicle accidents. Nevertheless, a systematic review of studies investigating this relationship has not yet been published. The ...objective of this study was to quantify the relationship between sleepiness at the wheel and motor vehicle accidents.
A systematic review was performed using Medline, Scopus, and ISI Web of Science. The outcome measure of interest was motor vehicle accident defined as involving four- or two-wheeled vehicles in road traffic, professional and nonprofessional drivers, with or without objective consequences. The exposure was sleepiness at the wheel defined as self-reported sleepiness at the wheel. Studies were included if they provided adjusted risk estimates of motor vehicle accidents related to sleepiness at the wheel. Risk estimates and 95% confidence intervals (95% CIs) were extracted and pooled as odds ratios (ORs) using a random-effect model. Heterogeneity was quantified using Q statistics and the I2 index. The potential causes of heterogeneity were investigated using meta-regressions.
Ten cross-sectional studies (51,520 participants), six case-control studies (4904 participants), and one cohort study (13,674 participants) were included. Sleepiness at the wheel was associated with an increased risk of motor vehicle accidents (pooled OR 2.51 95% CI 1.87; 3.39). A significant heterogeneity was found between the individual risk estimates (Q = 93.21; I2 = 83%).
Sleepiness at the wheel increases the risk of motor vehicle accidents and should be considered when investigating fitness to drive. Further studies are required to explore the nature of this relationship.
PROSPERO 2015 CRD42015024805.
Objective To quantify the risk of hypoglycaemia associated with the concomitant use of dipeptidyl peptidase-4 (DPP-4) inhibitors and sulphonylureas compared with placebo and ...sulphonylureas.Design Systematic review and meta-analysis.Data sources Medline, ISI Web of Science, SCOPUS, Cochrane Central Register of Controlled Trials, and clinicaltrial.gov were searched without any language restriction.Study selection Placebo controlled randomised trials comprising at least 50 participants with type 2 diabetes treated with DPP-4 inhibitors and sulphonylureas.Review methods Risk of bias in each trial was assessed using the Cochrane Collaboration tool. The risk ratio of hypoglycaemia with 95% confidence intervals was computed for each study and then pooled using fixed effect models (Mantel Haenszel method) or random effect models, when appropriate. Subgroup analyses were also performed (eg, dose of DPP-4 inhibitors). The number needed to harm (NNH) was estimated according to treatment duration.Results 10 studies were included, representing a total of 6546 participants (4020 received DPP-4 inhibitors plus sulphonylureas, 2526 placebo plus sulphonylureas). The risk ratio of hypoglycaemia was 1.52 (95% confidence interval 1.29 to 1.80). The NNH was 17 (95% confidence interval 11 to 30) for a treatment duration of six months or less, 15 (9 to 26) for 6.1 to 12 months, and 8 (5 to 15) for more than one year. In subgroup analysis, no difference was found between full and low doses of DPP-4 inhibitors: the risk ratio related to full dose DPP-4 inhibitors was 1.66 (1.34 to 2.06), whereas the increased risk ratio related to low dose DPP-4 inhibitors did not reach statistical significance (1.33, 0.92 to 1.94).Conclusions Addition of DPP-4 inhibitors to sulphonylurea to treat people with type 2 diabetes is associated with a 50% increased risk of hypoglycaemia and to one excess case of hypoglycaemia for every 17 patients in the first six months of treatment. This highlights the need to respect recommendations for a decrease in sulphonylureas dose when initiating DPP-4 inhibitors and to assess the effectiveness of this risk minimisation strategy.
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Introduction: With increasing availability, the use of healthcare databases as complementary data source for drug safety signal detection has been explored to circumvent the limitations inherent in ...spontaneous reporting.
Areas covered: To review the methods proposed for safety signal detection in healthcare databases and their performance.
Expert opinion: Fifteen different data mining methods were identified. They are based on disproportionality analysis, traditional pharmacoepidemiological designs (e.g. self-controlled designs), sequence symmetry analysis (SSA), sequential statistical testing, temporal association rules, supervised machine learning (SML), and the tree-based scan statistic. When considering the performance of these methods, the self-controlled designs, the SSA, and the SML seemed the most interesting approaches. In the perspective of routine signal detection from healthcare databases, pragmatic aspects such as the need for stakeholders to understand the method in order to be confident in the results must be considered. From this point of view, the SSA could appear as the most suitable method for signal detection in healthcare databases owing to its simple principle and its ability to provide a risk estimate. However, further developments, such as automated prioritization, are needed to help stakeholders handle the multiplicity of signals.
Cannabidiol is the first cannabis-derived drug approved for the treatment of Lennox–Gastaut syndrome, Dravet syndrome, and Tuberous Sclerosis Complex. In the current study, we performed a descriptive ...analysis followed by a disproportionality analysis of potential adverse events caused by CBD extracted from the VigiBase® database. Furthermore, the biological plausibility of the association between CBD and the serotonin 5-HT1A receptor as a possible cause of adverse events was analyzed and discussed. Data were extracted from the VigiBase® database using the VigiLyze® signal detection and signal management tool. Adverse events in VigiBase® reports were coded using MedDRA, version 19 of Preferred Terms (PTs). Data were uploaded into SPSS software and analyzed via a disproportionality analysis. Statistically significant disproportionality signals for CBD were found for “weight decreased” (5.19 (95% CI: 4.54–5.70)), “hypophagia” (3.68 (95% CI: 3.22–5.27)), and “insomnia” (1.6 (95% CI: 1.40–1.83)). Positive IC025 values were found for “weight decreased” (2.2), “hypophagia” (1.3), and “insomnia” (0.5), indicating a surplus of reported cases. CBD’s interactions with 5-HT1A serotonin receptors may offer a potential biological explanation for the occurrence of insomnia in patients. It is noteworthy that the risk profiles mentioned in the information for prescribing CBD as an antiepileptic agent by regulatory agencies showed disparities specifically related to the adverse event “insomnia”.
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To develop and validate a case-finding algorithm for the identification of Non-Small Cell Lung Cancer (NSCLC) cases in a region-wide Italian pathology registry (PR).
Data collected between 2009 and ...2017 in the PR and the Pharmacy Database of the University Hospital of Siena and the PR of Tuscany region were used. A NSCLC-identification algorithm based on free-text keywords and SNOMED morphology and topography codes was designed and tested on data from Siena: indication for drug use (i.e. NSCLC) was the reference standard for sensitivity (SE); positive predictive value (PPV) was estimated through manual review. Algorithm modifications were then tested to improve algorithm performance: PPV was calculated against validated dataset from PR of Siena; a range of SE min-max was estimated in PR of Tuscany using analytical formulae that assumed NSCLC incidence equal either to 80% or 90% of overall lung cancer incidence recorded in Tuscany. The algorithm modification with the best performance was chosen as the final version of the algorithm. A random sample of 200 cases was extracted from the PR of Tuscany for manual review.
The first version of the algorithm showed a PPV of 74.7% and SE of 79% in PR of Siena. The final version of the algorithm had a SE in PR of Tuscany that grew with calendar time (2009 = 24.7%-28%; 2017 = 57.9%-65.1%) and a PPV of 93%.
The final NSCLC-finding algorithm showed with very high PPV. SE was in line with the expected contribution of PR to overall cases captured in the regional Cancer Registry, with a trend of increase over calendar time. Given the promising algorithm validity and the wide use of SNOMED terminology in electronic pathology records, the proposed algorithm is expected to be easily adapted to other electronic databases for (pharmaco)epidemiology purposes.
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Daridorexant (dari), as the first dual orexin receptor antagonist (DORA) marketed in Europe, offers a novel therapeutic approach to insomnia. However, data regarding its real-world safety are scarce. ...Thus, this study was aimed at assessing its safety profile using a large-scale pharmacovigilance database. Dari-related adverse drug reaction (ADR) reports from the Food and Drug Administration Adverse Event Reporting System were scrutinized, and ADRs were selected using reporting odds ratio (ROR) as a measure of disproportionality. Frequencies of events related to dari were compared to all other drugs (reference group, RG1) and only to other DORAs (RG2). Only significant disproportionalities to both RGs were evaluated in-depth. A total of 845 dari-related reports were selected; nightmares (
= 146; dari vs. RG1: ROR = 113.74; 95%CI 95.13, 136; dari vs. RG2: ROR = 2.35; 95 CI% 1.93, 2.85), depression (
= 22; dari vs. RG1: 2.13; 1.39, 3.25; dari vs. RG2: ROR = 2.31; 95 CI% 1.45, 3.67), and hangover (
= 20; dari vs. RG1: ROR = 127.92; 95 CI% 81.98, 199.62; and dari vs. RG2: 3.38; 2.04, 5.61) were considered as safety signals. These data provide valuable insights into the real-world safety profile of daridorexant, supporting the existence of safety signals related to nightmares, depression, and hangovers.
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