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Background Immune checkpoint inhibitors (ICIs) can cause serious immune-related adverse events (irAEs). This study aimed to identify risk factors for all types of irAEs induced by ICIs in patients with non-small-cell lung cancer (NSCLC), by systematic review and meta-analyses. Methods A systematic search was performed in Pubmed, Embase and Web of Science by two independent reviewers. Studies were selected that included patients with NSCLC and evaluated characteristics of patients with and without irAEs induced by ICIs. Quality and risk of bias of the selected studies were assessed. Random effects meta-analyses were conducted to estimate pooled odds ratios (ORs) for risk factors of developing all type of irAEs, and separately for pneumonitis, interstitial lung disease and severe irAEs. With the objective of exploring sources of heterogeneity, stratified analyses were performed by quality and region. Results 25 studies met the inclusion criteria. In total, the data of 6696 patients were pooled. 33 different risk factors for irAEs were reported. irAEs of interest were reported for 1653 (25%) of the patients. Risk factors related to the development of irAEs were: C-reactive protein, neutrophil lymphocyte ratio (NLR), use of PD-1 inhibitor, high PD-L1 expression, an active or former smoking status, ground glass attenuation, and a better treatment response. Conclusion The identified risk factors for the development of these irAEs are mostly related to the alteration of the immune system, proinflammatory states and loss of immunological self-tolerance. Patients identified as having a higher risk for irAEs should be monitored more closely.

Purpose: Signal detection is a crucial step in the discovery of post-marketing adverse drug reactions. There is a growing interest in using routinely collected data to complement established spontaneous report analyses. This work aims to systematically review the methods for drug safety signal detection using routinely collected healthcare data and their performance, both in general and for specific types of drugs and outcomes.Methods: We conducted a systematic review following the PRISMA guidelines, and registered a protocol in PROSPERO. MEDLINE, EMBASE, PubMed, Web of Science, Scopus, and the Cochrane Library were searched until July 13, 2021. Results:The review included 101 articles, among which there were 39 methodological works, 25 performance assessment papers, and 24 observational studies.Methods included adaptations from those used with spontaneous reports, traditional epidemiological designs, methods specific to signal detection with real-world data.More recently, implementations of machine learning have been studied in the literature. Twenty-five studies evaluated method performances, 16 of them using the area under the curve (AUC) for a range of positive and negative controls as their main measure. Despite the likelihood that performance measurement could vary by drugevent pair, only 10 studies reported performance stratified by drugs and outcomes, in a heterogeneous manner. The replicability of the performance assessment results was limited due to lack of transparency in reporting and the lack of a gold standard reference set.Conclusions: A variety of methods have been described in the literature for signal detection with routinely collected data. No method showed superior performance in all papers and across all drugs and outcomes, performance assessment and reporting were heterogeneous. However, there is limited evidence that self-controlled designs, high dimensional propensity scores, and machine learning can achieve higher performances than other methods.

BackgroundConflicting literature exists regarding the risk factors for exacerbations among pregnant women with asthma. This systematic review and meta-analysis aimed to determine risk factors for asthma exacerbations during pregnancy.MethodsElectronic databases were searched for the following terms: (asthma or wheeze) and (pregnan* or perinat* or obstet*) and (exacerb* or flare up or morbidit* or attack*).All studies published between 2000 and 24 August 2021 were considered for inclusion if they reported at least one potential risk factor of asthma exacerbations in pregnant women with asthma. Of the 3337 references considered, 35 publications involving 429 583 pregnant women with asthma were included. Meta-analyses were conducted to determine mean difference in risk factor between exacerbation groups, or the relative risks of exacerbation with certain risk factors. Good study quality was found through the Newcastle-Ottawa Scale (median score 8, interquartile range 7–9).ResultsIncreased maternal age (mean difference 0.62, 95% CI 0.11–1.13), obesity (relative risk 1.25, 95% CI 1.15–1.37), smoking (relative risk 1.35, 95% CI 1.04–1.75), black ethnicity (relative risk 1.62, 95% CI 1.52–1.73), multiparity (relative risk 1.31, 95% CI 1.01–1.68), depression/anxiety (relative risk 1.42, 95% CI 1.27–1.59), moderate–severe asthma (relative risk 3.44, 95% CI 2.03–5.83, versus mild) and severe asthma (relative risk 2.70, 95% CI 1.85–3.95, versus mild–moderate) were associated with an increased risk of asthma exacerbations during pregnancy.ConclusionsFuture interventions aimed at reducing exacerbations in pregnancy could address the modifiable factors, such as smoking and depression/anxiety, and introduce more regular monitoring for those with nonmodifiable risk factors such as obesity and more severe asthma.

PurposePrevalent new user (PNU) designs extend the active comparator new user design by allowing for the inclusion of initiators of the study drug who were previously on a comparator treatment. We performed a literature review summarising current practice.MethodsPubMed was searched for studies applying the PNU design since its proposal in 2017. The review focused on three components. First, we extracted information on the overall study design, including the database used. We summarised information on implementation of the PNU design, including key decisions relating to exposure set definition and estimation of time‐conditional propensity scores. Finally, we reviewed the analysis strategy of the matched cohort.ResultsNineteen studies met the criteria for inclusion. Most studies (73%) implemented the PNU design in electronic health record or registry databases, with the remaining using insurance claims databases. Of 15 studies including a class of prevalent users, 40% deviated from the original exposure set definition proposals in favour of a more complex definition. Four studies did not include prevalent new users but used other aspects of the PNU framework. Several studies lacked details on exposure set definition (n = 2), time‐conditional propensity score model (n = 2) or integration of complex analytical techniques, such as the high‐dimensional propensity score algorithm (n = 3).ConclusionPNU designs have been applied in a range of therapeutic and disease areas. However, to encourage more widespread use of this design and help shape best practice, there is a need for improved accessibility, specifically through the provision of analytical code alongside guidance to support implementation and transparent reporting.

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Background Asthma is the most common medical condition to affect pregnancy. Asthma exacerbations occur in up to 45% of pregnant women and have been associated with adverse perinatal and infant outcomes. Conflicting literature exists regarding the risk factors for exacerbations, and no synthesis of the literature currently exists. Therefore, this systematic review and meta-analysis aims to determine risk factors for asthma exacerbations during pregnancy among pregnant women with asthma. Methods This protocol has been reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis protocols checklist. A systematic search will be conducted in the electronic MEDLINE, Embase, CINAHL and Cochrane Clinical Trials Register databases (from January 2000 onwards). Eligibility of each publication will be determined based on predefined selection criteria. Prospective cohort studies, retrospective cohort studies, case-control studies and randomised controlled trials (RCTs) will be included. Quality of included studies will be determined using the Newcastle Ottawa Scale and the Cochrane Risk of Bias tool. Pooled relative risk will be computed using random-effects meta-analyses. Heterogeneity will be assessed using the chi-squared test and the I2 parameter. Publication bias will be assessed by inspecting a funnel plot for asymmetry and with the Egger’s test of analyses including ten studies or more. Discussion The results of this systematic review and meta-analysis will discuss the potential risk factors for asthma exacerbations during pregnancy. This may aid healthcare professionals in early identification of pregnant women with asthma at risk of poor outcomes, providing the opportunity to implement early interventions in order to avoid deterioration of asthma symptoms during pregnancy. Systematic review registration PROSPERO CRD42020196190