759 research outputs found

    Maternal sex chromosome aneuploidy identified through noninvasive prenatal screening: clinical profile and patient experience

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    Objective: Non-invasive prenatal screening (NIPS) may incidentally identify maternal aneuploidies that have health implications, such as maternal monosomy X. We evaluated patients’ experience with counseling and follow-up diagnostic testing after NIPS flags a potential maternal sex chromosome aneuploidy (SCA). We hypothesized that patients were routinely offered, and completed, diagnostic follow-up genetic testing after SCA is detected on NIPS. Study Design: Patients who underwent NIPS at two reference laboratories between 2012 and 2021 and had test results that were consistent with possible or probable maternal SCA were contacted with a link to an anonymous survey. Survey topics included demographics, health history, pregnancy history, counseling, and follow-up testing. Results: 269 patients responded to the anonymous survey, and 83 of these individuals also completed one follow-up survey (Figure 1). Most (75%) received pre-test counseling. 80% were offered fetal genetic testing during the pregnancy, which was completed in 25% of respondents. Only 35% of patients completed diagnostic maternal testing (Figure 2). Patients with monosomy X-related phenotypes were more likely to have follow up testing that led to a diagnosis of monosomy X in 14 cases (6%, Figure 2). Two patients with diagnostic testing that confirmed mosaic Turner’s had no phenotypical findings. No other clinical or demographic factors were associated with an abnormal maternal karyotype on diagnostic evaluation. Conclusion: Follow up counseling and testing after a high-risk NIPS result suggestive of maternal SCA is heterogenous in this cohort and may be frequently incomplete. We observed that the presence of Turner’s phenotype increased the likelihood of diagnostic testing in this cohort. However, the incomplete penetrance of SCA phenotypes in the population could hinder the performance of this strategy. Health outcomes may be affected by SCA and an effective strategy for definitive testing could improve the provision, delivery, and quality of post-test counseling

    Rethinking non-inferiority: a practical trial design for optimising treatment duration.

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    Background Trials to identify the minimal effective treatment duration are needed in different therapeutic areas, including bacterial infections, tuberculosis and hepatitis C. However, standard non-inferiority designs have several limitations, including arbitrariness of non-inferiority margins, choice of research arms and very large sample sizes. Methods We recast the problem of finding an appropriate non-inferior treatment duration in terms of modelling the entire duration-response curve within a pre-specified range. We propose a multi-arm randomised trial design, allocating patients to different treatment durations. We use fractional polynomials and spline-based methods to flexibly model the duration-response curve. We call this a 'Durations design'. We compare different methods in terms of a scaled version of the area between true and estimated prediction curves. We evaluate sensitivity to key design parameters, including sample size, number and position of arms. Results A total sample size of ~ 500 patients divided into a moderate number of equidistant arms (5-7) is sufficient to estimate the duration-response curve within a 5% error margin in 95% of the simulations. Fractional polynomials provide similar or better results than spline-based methods in most scenarios. Conclusion Our proposed practical randomised trial 'Durations design' shows promising performance in the estimation of the duration-response curve; subject to a pending careful investigation of its inferential properties, it provides a potential alternative to standard non-inferiority designs, avoiding many of their limitations, and yet being fairly robust to different possible duration-response curves. The trial outcome is the whole duration-response curve, which may be used by clinicians and policymakers to make informed decisions, facilitating a move away from a forced binary hypothesis testing paradigm

    The DURATIONS randomised trial design: estimation targets, analysis methods and operating characteristics

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    Background. Designing trials to reduce treatment duration is important in several therapeutic areas, including TB and antibiotics. We recently proposed a new randomised trial design to overcome some of the limitations of standard two-arm non-inferiority trials. This DURATIONS design involves randomising patients to a number of duration arms, and modelling the so-called duration-response curve. This article investigates the operating characteristics (type-1 and type-2 errors) of different statistical methods of drawing inference from the estimated curve. Methods. Our first estimation target is the shortest duration non-inferior to the control (maximum) duration within a specific risk difference margin. We compare different methods of estimating this quantity, including using model confidence bands, the delta method and bootstrap. We then explore the generalisability of results to estimation targets which focus on absolute event rates, risk ratio and gradient of the curve. Results. We show through simulations that, in most scenarios and for most of the estimation targets, using the bootstrap to estimate variability around the target duration leads to good results for DURATIONS design-appropriate quantities analogous to power and type-1 error. Using model confidence bands is not recommended, while the delta method leads to inflated type-1 error in some scenarios, particularly when the optimal duration is very close to one of the randomised durations. Conclusions. Using the bootstrap to estimate the optimal duration in a DURATIONS design has good operating characteristics in a wide range of scenarios, and can be used with confidence by researchers wishing to design a DURATIONS trial to reduce treatment duration. Uncertainty around several different targets can be estimated with this bootstrap approach.Comment: 4 figures, 1 table + additional materia

    General practice and the Medical Licensing Assessment

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    From 2024/2025, all UK medical students will sit the Medical Licensing Assessment (MLA),1 a mandated national exam comprising: a written applied knowledge test (AKT) in single best answer (SBA) format; and a clinical and professional skills assessment (CPSA). Here we consider the implications for primary care, and for those involved in teaching primary care to medical undergraduates, including GPs and other primary care professionals

    Comparison of aggregate and individual participant data approaches to meta-analysis of randomised trials : An observational study

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    BACKGROUND: It remains unclear when standard systematic reviews and meta-analyses that rely on published aggregate data (AD) can provide robust clinical conclusions. We aimed to compare the results from a large cohort of systematic reviews and meta-analyses based on individual participant data (IPD) with meta-analyses of published AD, to establish when the latter are most likely to be reliable and when the IPD approach might be required. METHODS AND FINDINGS: We used 18 cancer systematic reviews that included IPD meta-analyses: all of those completed and published by the Meta-analysis Group of the MRC Clinical Trials Unit from 1991 to 2010. We extracted or estimated hazard ratios (HRs) and standard errors (SEs) for survival from trial reports and compared these with IPD equivalents at both the trial and meta-analysis level. We also extracted or estimated the number of events. We used paired t tests to assess whether HRs and SEs from published AD differed on average from those from IPD. We assessed agreement, and whether this was associated with trial or meta-analysis characteristics, using the approach of Bland and Altman. The 18 systematic reviews comprised 238 unique trials or trial comparisons, including 37,082 participants. A HR and SE could be generated for 127 trials, representing 53% of the trials and approximately 79% of eligible participants. On average, trial HRs derived from published AD were slightly more in favour of the research interventions than those from IPD (HRAD to HRIPD ratio = 0.95, p = 0.007), but the limits of agreement show that for individual trials, the HRs could deviate substantially. These limits narrowed with an increasing number of participants (p < 0.001) or a greater number (p < 0.001) or proportion (p < 0.001) of events in the AD. On average, meta-analysis HRs from published AD slightly tended to favour the research interventions whether based on fixed-effect (HRAD to HRIPD ratio = 0.97, p = 0.088) or random-effects (HRAD to HRIPD ratio = 0.96, p = 0.044) models, but the limits of agreement show that for individual meta-analyses, agreement was much more variable. These limits tended to narrow with an increasing number (p = 0.077) or proportion of events (p = 0.11) in the AD. However, even when the information size of the AD was large, individual meta-analysis HRs could still differ from their IPD equivalents by a relative 10% in favour of the research intervention to 5% in favour of control. We utilised the results to construct a decision tree for assessing whether an AD meta-analysis includes sufficient information, and when estimates of effects are most likely to be reliable. A lack of power at the meta-analysis level may have prevented us identifying additional factors associated with the reliability of AD meta-analyses, and we cannot be sure that our results are generalisable to all outcomes and effect measures. CONCLUSIONS: In this study we found that HRs from published AD were most likely to agree with those from IPD when the information size was large. Based on these findings, we provide guidance for determining systematically when standard AD meta-analysis will likely generate robust clinical conclusions, and when the IPD approach will add considerable value

    Dysregulation of ErbB4 Signaling Pathway in the Dorsal Hippocampus after Neonatal Hypoxia-Ischemia and Late Deficits in PV+ Interneurons, Synaptic Plasticity and Working Memory

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    Neonatal hypoxic-ischemic (HI) injury leads to deficits in hippocampal parvalbumin (PV)+ interneurons (INs) and working memory. Therapeutic hypothermia (TH) does not prevent these deficits. ErbB4 supports maturation and maintenance of PV+ IN. Thus, we hypothesized that neonatal HI leads to persistent deficits in PV+ INs, working memory and synaptic plasticity associated with ErbB4 dysregulation despite TH. P10 HI-injured mice were randomized to normothermia (NT, 36 °C) or TH (31 °C) for 4 h and compared to sham. Hippocampi were studied for α-fodrin, glial fibrillary acidic protein (GFAP), and neuroregulin (Nrg) 1 levels; erb-b2 receptor tyrosine kinase 4 (ErbB4)/ Ak strain transforming (Akt) activation; and PV, synaptotagmin (Syt) 2, vesicular-glutamate transporter (VGlut) 2, Nrg1, and ErbB4 expression in coronal sections. Extracellular field potentials and behavioral testing were performed. At P40, deficits in PV+ INs correlated with impaired memory and coincided with blunted long-term depression (LTD), heightened long-term potentiation (LTP) and increased Vglut2/Syt2 ratio, supporting excitatory-inhibitory (E/I) imbalance. Hippocampal Nrg1 levels were increased in the hippocampus 24 h after neonatal HI, delaying the decline documented in shams. Paradoxically ErbB4 activation decreased 24 h and again 30 days after HI. Neonatal HI leads to persistent deficits in hippocampal PV+ INs, memory, and synaptic plasticity. While acute decreased ErbB4 activation supports impaired maturation and survival after HI, late deficit reemergence may impair PV+ INs maintenance after HI
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