Nicole Fusco

The symptoms experienced by people with narcolepsy and idiopathic hypersomnia (IH) have profound effects on individuals’ lives, affecting daily functioning, relationships and mental health, and can impair performance at work or school. Although numerous studies have evaluated the impact of narcolepsy and IH on work-related outcomes, the evidence base is highly fragmented and difficult to meaningfully summarize. We conducted a systematic literature review of published evidence to better understand the impact of these disorders on employment, work productivity, work satisfaction, and related outcomes. We identified 54 publications representing 51 unique studies that met the study inclusion criteria and were included in the review. Although most people with narcolepsy or IH were employed, fewer were in paid work than control populations, and absenteeism and presenteeism were high. Having narcolepsy and IH resulted in lower wages and missed work time, leading to unfavorable impacts on career progression, promotion, job satisfaction, and income. The most frequently reported work-related problems were sleepiness at work, reduced performance, work accidents, and lateness. More severe excessive daytime sleepiness was associated with greater work impairment. Narcolepsy-specific medications that improved excessive daytime sleepiness were reported to improve work productivity in clinical trials; however, many people are left with substantial residual impairment despite treatment. These findings indicate that narcolepsy and IH impose a substantial burden on work functioning and employment, and there is a need for more research to inform interventions and policies aimed at mitigating the impact of these debilitating conditions on individuals’ professional lives.

Aim: Next-generation sequencing (NGS) of solid tumors can inform treatment decisions; however, uptake remains low. This objective of this systematic review was to identify barriers to and facilitators of NGS in US oncology settings.

Data for individual trials included in systematic reviews may be available in multiple sources. For example, a single trial might be reported in 2 journal articles and 3 conference abstracts. Because of differences across sources, source selection can influence the results of systematic reviews. We used our experience in the Multiple Data Sources in Systematic Reviews (MUDS) study, and evidence from previous studies, to develop practical guidance for using multiple data sources in systematic reviews.We recommend the following: (1) Specify which sources you will use. Before beginning a systematic review, consider which sources are likely to contain the most useful data. Try to identify all relevant reports and to extract information from the most reliable sources. (2) Link individual trials with multiple sources. Write to authors to determine which sources are likely related to the same trials. Use a modified Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) flowchart to document both the selection of trials and the selection of sources. (3) Follow a prespecified protocol for extracting trial characteristics from multiple sources. Identify differences among sources, and contact study authors to resolve differences if possible. (4) Prespecify outcomes and results to examine in the review and meta‐analysis. In your protocol, describe how you will handle multiple outcomes within each domain of interest. Look for outcomes using all eligible sources. (5) Identify which data sources were included in the review. Consider whether the results might have been influenced by data sources used. (6) To reduce bias, and to reduce research waste, share the data used in your review.