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Core Outcome Sets (COS) define minimum outcomes to be measured and reported in clinical effectiveness trials for a particular health condition/health area. Despite recognition as critical to clinical research design for other health areas, none have been developed for neuro-oncology. COS development projects should carefully consider: scope (how the COS should be used), stakeholders involved in development (including patients as both research partners and participants), and consensus methodologies used (typically a Delphi survey and consensus meeting), as well as dissemination plans. Developing COS for neuro-oncology is potentially challenging due to extensive tumor subclassification (including molecular stratification), different symptoms related to anatomical tumor location, and variation in treatment options. Development of a COS specific to tumor subtype, in a specific location, for a particular intervention may be too narrow and would be unlikely to be used. Equally, a COS that is applicable across a wider area of neuro-oncology may be too broad and therefore lack specificity. This review describes why and how a COS may be developed, and discusses challenges for their development, specific to neuro-oncology. The COS under development are briefly described, including: adult glioma, incidental/untreated meningioma, meningioma requiring intervention, and adverse events from surgical intervention for pediatric brain tumors.

IntroductionMeningioma is the most common primary intracranial tumour in adults. The majority are non-malignant, but a proportion behave more aggressively. Incidental/minimally symptomatic meningioma are often managed by serial imaging. Symptomatic meningioma, those that threaten neurovascular structures, or demonstrate radiological growth, are usually resected as first-line management strategy. For patients in poor clinical condition, or with inoperable, residual or recurrent disease, radiotherapy is often used as primary or adjuvant treatment. Effective pharmacotherapy treatments do not currently exist. There is heterogeneity in the outcomes measured and reported in meningioma clinical studies. Two 'Core Outcome Sets' (COS) will be developed: (COSMIC: Intervention) for use in meningioma clinical effectiveness trials and (COSMIC: Observation) for use in clinical studies of incidental/untreated meningioma.Methods and analysisTwo systematic literature reviews and trial registry searches will identify outcomes measured and reported in published and ongoing (1) meningioma clinical effectiveness trials, and (2) clinical studies of incidental/untreated meningioma. Outcomes include those that are clinician reported, patient reported, caregiver reported and based on objective tests (eg, neurocognitive tests), as well as measures of progression and survival. Outcomes will be deduplicated and categorised to generate two long lists. The two long lists will be prioritised through two, two-round, international, modified eDelphi surveys including patients with meningioma, healthcare professionals, researchers and those in caring/supporting roles. The two final COS will be ratified through two 1-day online consensus meetings, with representation from all stakeholder groups.Ethics and disseminationInstitutional review board (University of Liverpool) approval was obtained for the conduct of this study. Participant eConsent will be obtained prior to participation in the eDelphi surveys and consensus meetings. The two systematic literature reviews and two final COS will be published and freely available.Trial registration numberCOMET study ID 1508.

ObjectiveParoxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations.MethodsConfounding factors, including the heterogeneous etiology of epilepsies and medication effects, hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a genome-wide association study (GWAS) on epilepsy (n = 12 803 people with epilepsy and 24 218 controls) with that from a GWAS on background EEG (n = 8425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta, and theta. We replicated our findings in an independent epilepsy replication dataset (n = 4851 people with epilepsy and 20 428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores, and Mendelian randomization analyses.ResultsOur analyses show strong genetic correlations of genetic generalized epilepsy (GGE) with background EEG oscillations, primarily in the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations.SignificanceOur results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic workup of epilepsy.

BackgroundRetesting for HIV is critical to identifying newly-infected persons and reinforcing prevention efforts among at-risk adults. Incentives can increase one-time HIV testing, but their role in promoting retesting is unknown. We sought to test feasibility and acceptability of incentive strategies, including commitment contracts, to promote HIV retesting among at-risk adults in rural Uganda.MethodsAt-risk HIV-negative adults were enrolled in a pilot trial assessing feasibility and acceptability of incentive strategies to promote HIV retesting three months after enrollment. Participants were randomized (1:1:3) to: 1) no incentive; 2) standard cash incentive (~US$4); and 3) commitment contract: participants could voluntarily make a low- or high-value deposit that would be returned with added interest (totaling ~US$4 including the deposit) upon retesting or lost if participants failed to retest. Contracts sought to promote retesting by leveraging loss aversion and addressing present bias via pre-commitment. Outcomes included acceptability of trial enrollment, contract feasibility (proportion of participants making deposits), and HIV retesting uptake.ResultsOf 130 HIV-negative eligible adults, 123 (95%) enrolled and were randomized: 74 (60%) to commitment contracts, 25 (20%) to standard incentives, and 24 (20%) to no incentive. Of contract participants, 69 (93%) made deposits. Overall, 93 (76%) participants retested for HIV: uptake was highest in the standard incentive group (22/25 [88%]) and lowest in high-value contract (26/36 [72%]) and no incentive (17/24 [71%]) groups.ConclusionIn a randomized trial of strategies to promote HIV retesting among at-risk adults in Uganda, incentive strategies, including commitment contracts, were feasible and had high acceptability. Our findings suggest use of incentives for HIV retesting merits further comparison in a larger trial.Trial registrationClinicalTrials.gov identifier: NCT:02890459.

ObjectiveClassification of epilepsy into types and subtypes is important for both clinical care and research into underlying disease mechanisms. A quantitative, data-driven approach may augment traditional electroclinical classification and shed new light on existing classification frameworks.MethodsWe used latent class analysis, a statistical method that assigns subjects into groups called latent classes based on phenotypic elements, to classify individuals with common familial epilepsies from the Epi4K Multiplex Families study. Phenotypic elements included seizure types, seizure symptoms, and other elements of the medical history. We compared class assignments to traditional electroclinical classifications and assessed familial aggregation of latent classes.ResultsA total of 1120 subjects with epilepsy were assigned to five latent classes. Classes 1 and 2 contained subjects with generalized epilepsy, largely reflecting the distinction between absence epilepsies and younger onset (class 1) versus myoclonic epilepsies and older onset (class 2). Classes 3 and 4 contained subjects with focal epilepsies, and in contrast to classes 1 and 2, these did not adhere as closely to clinically defined focal epilepsy subtypes. Class 5 contained nearly all subjects with febrile seizures plus or unknown epilepsy type, as well as a few subjects with generalized epilepsy and a few with focal epilepsy. Family concordance of latent classes was similar to or greater than concordance of clinically defined epilepsy types.SignificanceQuantitative classification of epilepsy has the potential to augment traditional electroclinical classification by (1) combining some syndromes into a single class, (2) splitting some syndromes into different classes, (3) helping to classify subjects who could not be classified clinically, and (4) defining the boundaries of clinically defined classifications. This approach can guide future research, including molecular genetic studies, by identifying homogeneous sets of individuals that may share underlying disease mechanisms.

Sequencing-based studies have identified novel risk genes associated with severe epilepsies and revealed an excess of rare deleterious variation in less-severe forms of epilepsy. To identify the shared and distinct ultra-rare genetic risk factors for different types of epilepsies, we performed a whole-exome sequencing (WES) analysis of 9,170 epilepsy-affected individuals and 8,436 controls of European ancestry. We focused on three phenotypic groups: severe developmental and epileptic encephalopathies (DEEs), genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We observed that compared to controls, individuals with any type of epilepsy carried an excess of ultra-rare, deleterious variants in constrained genes and in genes previously associated with epilepsy; we saw the strongest enrichment in individuals with DEEs and the least strong in individuals with NAFE. Moreover, we found that inhibitory GABAA receptor genes were enriched for missense variants across all three classes of epilepsy, whereas no enrichment was seen in excitatory receptor genes. The larger gene groups for the GABAergic pathway or cation channels also showed a significant mutational burden in DEEs and GGE. Although no single gene surpassed exome-wide significance among individuals with GGE or NAFE, highly constrained genes and genes encoding ion channels were among the lead associations; such genes included CACNA1G, EEF1A2, and GABRG2 for GGE and LGI1, TRIM3, and GABRG2 for NAFE. Our study, the largest epilepsy WES study to date, confirms a convergence in the genetics of severe and less-severe epilepsies associated with ultra-rare coding variation, and it highlights a ubiquitous role for GABAergic inhibition in epilepsy etiology.

Valproate is the most effective treatment for idiopathic generalised epilepsy. Currently, its use is restricted in women of childbearing potential owing to high teratogenicity. Recent evidence extended this risk to men's offspring, prompting recommendations to restrict use in everybody aged <55 years. This study will evaluate mortality and morbidity risks associated with valproate withdrawal by emulating a hypothetical randomised-controlled trial (called a "target trial") using retrospective observational data. The data will be drawn from ~250m mainly US patients in the TriNetX repository and ~60m UK patients in Clinical Practice Research Datalink (CPRD). These will be scanned for individuals aged 16–54 years with epilepsy and on valproate who either continued, switched to lamotrigine or levetiracetam, or discontinued valproate between 2014–2024, creating four groups. Randomisation to these groups will be emulated by baseline confounder adjustment using g-methods. Mortality and morbidity outcomes will be assessed and compared between groups over 1–10 years, employing time-to-first-event and recurrent events analyses. A causal prediction model will be developed from these data to aid in predicting the safest alternative antiseizure medications. Together, these findings will optimise informed decision-making about valproate withdrawal and alternative treatment selection, providing immediate and vital information for patients, clinicians and regulators. [ABSTRACT FROM AUTHOR]

Study Design: This was a systematic review of surgically managed Cauda Equina Syndrome (CES) Outcome Measurement Instruments (OMI). Objective: A core outcome set (COS) defines agreed outcomes which should be reported as a minimum in any research study for a specific condition. This study identified OMIs used in the wider CES literature and compare these to the established CESCOS. Methods: To identify measurement methods and instruments in the CES surgical outcome evidence base, a systematic review was performed. Medline, Embase and CINAHL plus databases were queried. In addition, a secondary search for validation studies of measurement instruments in CES was undertaken. Identified studies from this search were subject to the COSMIN risk of bias assessment. Results: In total, 112 studies were identified investigating surgical outcomes for CES. The majority (80%, n = 90) of these OMI studies were retrospective in nature and only 55% (n = 62) utilised a measurement method or instrument. The remaining 50 studies used study specific definitions for surgical outcomes defined within their methods. Of the 59 measurement instruments identified, 60% (n = 38 instruments) were patient reported outcome measures. Only one validated instrument was identified, which was a patient reported outcome measure. The validated instrument was not used in any study identified in the initial search (to identify measurement instruments). Conclusions: This review highlights the wide heterogeneity of measurement instruments used in surgically managed CES research. Subsequently, there is need for consensus agreement on which instrument or instruments should be used to measure each core outcome for CES surgical outcomes. [ABSTRACT FROM AUTHOR]

Many randomized trials evaluate an intervention effect on time-to-event outcomes. Individual participant data (IPD) from such trials can be obtained and combined in a so-called IPD meta-analysis (IPD-MA), to summarize the overall intervention effect. We performed a narrative literature review to provide an overview of methods for conducting an IPD-MA of randomized intervention studies with a time-to-event outcome. We focused on identifying good methodological practice for modeling frailty of trial participants across trials, modeling heterogeneity of intervention effects, choosing appropriate association measures, dealing with (trial differences in) censoring and follow-up times, and addressing time-varying intervention effects and effect modification (interactions).We discuss how to achieve this using parametric and semi-parametric methods, and describe how to implement these in a one-stage or two-stage IPD-MA framework. We recommend exploring heterogeneity of the effect(s) through interaction and non-linear effects. Random effects should be applied to account for residual heterogeneity of the intervention effect. We provide further recommendations, many of which specific to IPD-MA of time-to-event data from randomized trials examining an intervention effect.We illustrate several key methods in a real IPD-MA, where IPD of 1225 participants from 5 randomized clinical trials were combined to compare the effects of Carbamazepine and Valproate on the incidence of epileptic seizures.

Gene identification in epilepsy has mainly been limited to large families segregating genes of major effect and de novo mutations in epileptic encephalopathies. Many families that present with common non-acquired focal epilepsies and genetic generalized epilepsies remain unexplained. We assembled a cohort of 'genetically enriched' common epilepsies by collecting and phenotyping families containing multiple individuals with unprovoked seizures. We aimed to determine if specific clinical epilepsy features aggregate within families, and whether this segregation of phenotypes may constitute distinct 'familial syndromes' that could inform genomic analyses. Families with three or more individuals with unprovoked seizures were studied across multiple international centres. Affected individuals were phenotyped and classified according to specific electroclinical syndromes. Families were categorized based on syndromic groupings of affected family members, examined for pedigree structure and phenotypic patterns and, where possible, assigned specific familial epilepsy syndromes. A total of 303 families were assembled and analysed, comprising 1120 affected phenotyped individuals. Of the 303 families, 117 exclusively segregated generalized epilepsy, 62 focal epilepsy, and 22 were classified as genetic epilepsy with febrile seizures plus. Over one-third (102 families) were observed to have mixed epilepsy phenotypes: 78 had both generalized and focal epilepsy features within the same individual (n = 39), or within first or second degree relatives (n = 39). Among the genetic generalized epilepsy families, absence epilepsies were found to cluster within families independently of juvenile myoclonic epilepsy, and significantly more females were affected than males. Of the 62 familial focal epilepsy families, two previously undescribed familial focal syndrome patterns were evident: 15 families had posterior quadrant epilepsies, including seven with occipito-temporal localization and seven with temporo-parietal foci, and four families displayed familial focal epilepsy of childhood with multiple affected siblings that was suggestive of recessive inheritance. The findings suggest (i) specific patterns of syndromic familial aggregation occur, including newly recognized forms of familial focal epilepsy; (ii) although syndrome-specificity usually occurs in multiplex families, the one-third of families with features of both focal and generalized epilepsy is suggestive of shared genetic determinants; and (iii) patterns of features observed across families including pedigree structure, sex, and age of onset may hold clues for future gene identification. Such detailed phenotypic information will be invaluable in the conditioning and interpretation of forthcoming sequencing data to understand the genetic architecture and inter-relationships of the common epilepsy syndromes.

BackgroundOur medical center laboratory recently adapted its 24/7, two-hourly testing program to use an ARCHITECT-Multispot-viral load (AR-MS-VL) algorithm in place of a previous rapid test-immunofluorescence (RT-IF) algorithm.ObjectivesWe evaluated screening test performance, acute case detection, turnaround time and ability to resolve HIV status under the new algorithm.Study designWe considered consecutive HIV tests from January to November 2015. AR-MS-VL results at Zuckerberg San Francisco General Hospital and Trauma Center (ZSFG) were compared with RT-IF results at ZSFG and also with AR-MS-VL results in the recently completed CDC Screening Targeted Populations to Interrupt On-going Chains of HIV Transmission with Enhanced Partner Notification (STOP) Study for targeted testing of MSM at publicly funded testing sites in San Francisco.ResultsAmong 21,985 HIV tests performed at ZSFG, 16,467 were tested by RT-IF and 5518 by AR-MS-VL. There were 321 HIV infections detected, of which 274 (84%) were known HIV+ cases, and 47 were newly identified HIV infections. Considering only patients of HIV-negative or -unknown status, prevalence was 0.22%. Under the AR-MS-VL algorithm, turnaround times for screening results and full algorithm results were 3 and 21h; status-unresolved cases were reduced (from 47% to 22%) compared with the RT-IF algorithm. The positive predictive value (PPV) of a new-positive AR screening test was low (0.44) at ZSFG, where no acute infections were detected. At STOP Study sites where HIV prevalence was higher and acute infection was more common, the AR PPV was higher (0.93). All 24 false-positive AR screening tests at ZSFG had a signal/cutoff (S/CO) ratio of 15. Of 62 acute infections in the STOP Study, 23 (37%) had an S/CO

Epileptic encephalopathies (EEs) are the most clinically important group of severe early-onset epilepsies. Next-generation sequencing has highlighted the crucial contribution of de novo mutations to the genetic architecture of EEs as well as to their underlying genetic heterogeneity. Our previous whole-exome sequencing study of 264 parent-child trios revealed more than 290 candidate genes in which only a single individual had a de novo variant. We sought to identify additional pathogenic variants in a subset (n = 27) of these genes via targeted sequencing in an unsolved cohort of 531 individuals with a diverse range of EEs. We report 17 individuals with pathogenic variants in seven of the 27 genes, defining a genetic etiology in 3.2% of this unsolved cohort. Our results provide definitive evidence that de novo mutations in SLC1A2 and CACNA1A cause specific EEs and expand the compendium of clinically relevant genotypes for GABRB3. We also identified EEs caused by genetic variants in ALG13, DNM1, and GNAO1 and report a mutation in IQSEC2. Notably, recurrent mutations accounted for 7/17 of the pathogenic variants identified. As a result of high-depth coverage, parental mosaicism was identified in two out of 14 cases tested with mutant allelic fractions of 5%-6% in the unaffected parents, carrying significant reproductive counseling implications. These results confirm that dysregulation in diverse cellular neuronal pathways causes EEs, and they will inform the diagnosis and management of individuals with these devastating disorders.

Infantile spasms (IS) and Lennox-Gastaut syndrome (LGS) are epileptic encephalopathies characterized by early onset, intractable seizures, and poor developmental outcomes. De novo sequence mutations and copy number variants (CNVs) are causative in a subset of cases. We used exome sequence data in 349 trios with IS or LGS to identify putative de novo CNVs. We confirm 18 de novo CNVs in 17 patients (4.8%), 10 of which are likely pathogenic, giving a firm genetic diagnosis for 2.9% of patients. Confirmation of exome-predicted CNVs by array-based methods is still required due to false-positive rates of prediction algorithms. Our exome-based results are consistent with recent array-based studies in similar cohorts and highlight novel candidate genes for IS and LGS.

Objective: Guidelines suggest considering antiseizure medication (ASM) discontinuation in seizure‐free patients with epilepsy. Past work has poorly explored how discontinuation effects vary between patients. We evaluated (1) what factors modify the influence of discontinuation on seizure risk; and (2) the range of seizure risk increase due to discontinuation across low‐ versus high‐risk patients. Methods: We pooled three datasets including seizure‐free patients who did and did not discontinue ASMs. We conducted time‐to‐first‐seizure analyses. First, we evaluated what individual patient factors modified the relative effect of ASM discontinuation on seizure risk via interaction terms. Then, we assessed the distribution of 2‐year risk increase as predicted by our adjusted logistic regressions. Results: We included 1626 patients, of whom 678 (42%) planned to discontinue all ASMs. The mean predicted 2‐year seizure risk was 43% [95% confidence interval (CI) 39%–46%] for discontinuation versus 21% (95% CI 19%–24%) for continuation. The mean 2‐year absolute seizure risk increase was 21% (95% CI 18%–26%). No individual interaction term was significant after correcting for multiple comparisons. The median [interquartile range (IQR)] risk increase across patients was 19% (IQR 14%–24%; range 7%–37%). Results were unchanged when restricting analyses to only the two RCTs. Significance: No single patient factor significantly modified the influence of discontinuation on seizure risk, although we captured how absolute risk increases change for patients that are at low versus high risk. Patients should likely continue ASMs if even a 7% 2‐year increase in the chance of any more seizures would be too much and should likely discontinue ASMs if even a 37% risk increase would be too little. In between these extremes, individualized risk calculation and a careful understanding of patient preferences are critical. Future work will further develop a two‐armed individualized seizure risk calculator and contextualize seizure risk thresholds below which to consider discontinuation. Plain Language Summary: Understanding how much antiseizure medications (ASMs) decrease seizure risk is an important part of determining which patients with epilepsy should be treated, especially for patients who have not had a seizure in a while. We found that there was a wide range in the amount that ASM discontinuation increases seizure risk—between 7% and 37%. We found that no single patient factor modified that amount. Understanding what a patient's seizure risk might be if they discontinued versus continued ASM treatment is critical to making informed decisions about whether the benefit of treatment outweighs the downsides. [ABSTRACT FROM AUTHOR]