Anxiety characteristics in individuals with Williams syndrome

BACKGROUND: Williams syndrome anxiety research predominantly focuses on disorder prevalence and symptomatology, categorised using standardised mental health classifications. However, the use of these assessments may not fully capture the phenotypic features of anxiety in Williams syndrome. In this study, we examined characteristics of anxiety using a formulation framework. METHOD: A semi-structured interview was conducted with thirteen parents of individuals with Williams syndrome (median age: 19, age range: 12-45, 8 females). RESULTS: Various anxiety triggers were reported, including anxiety triggered by phobias, uncertainty and negative emotions in others. The range of described behaviours was diverse with both avoidant and active coping strategies for anxiety management reported. CONCLUSIONS: Many of the characteristics described were consistent with findings in the intellectual disability and typically developing literature, although novel information was identified. The study demonstrates the utility of a formulation framework to explore anxiety characteristics in atypical populations and has outlined new avenues for research

Impact of lack-of-benefit stopping rules on treatment effect estimates of two-arm multi-stage (TAMS) trials with time to event outcome

In 2011, Royston et al. described technical details of a two-arm, multi-stage (TAMS) design. The design enables a trial to be stopped part-way through recruitment if the accumulating data suggests a lack of benefit of the experimental arm. Such interim decisions can be made using data on an available 'intermediate' outcome. At the conclusion of the trial, the definitive outcome is analyzed. Typical intermediate and definitive outcomes in cancer might be progression-free and overall survival, respectively. In TAMS designs, the stopping rule applied at the interim stage(s) affects the sampling distribution of the treatment effect estimator, potentially inducing bias that needs addressing

The Profiles and Correlates of Psychopathology in Adolescents and Adults with Williams, Fragile X and Prader-Willi Syndromes

Psychopathology is prevalent in Williams (WS), fragile X (FXS) and Prader-Willi (PWS) syndromes. However, little is known about the potential correlates of psychopathology in these groups. A questionnaire study was completed by 111 caregivers of individuals with WS (n = 35); FXS (n = 50) and PWS (n = 26). Mean age was 26 years (range 12-57 years); 74 (67%) were male. Multiple regression analyses indicated that higher rates of health problems and sensory impairments predicted higher psychopathology in WS (p < .0001). In PWS, poorer adaptive ability predicted higher overall psychiatric disturbance (p = .001), generalised anxiety (p = .006) and hyperactivity (p = .003). There were no significant predictors in FXS. This study highlights dissociations in the potential risk markers of psychopathology between genetic syndromes. Implications for intervention are discussed

An approach to estimating prognosis using fractional polynomials in metastatic renal carcinoma

We present a prognostic model for metastatic renal cell carcinoma based on fractional polynomials. We retrospectively analysed 425 metastatic renal cell carcinoma patients treated with subcutaneous recombinant cytokine-based home therapies in consecutive trials. In our approach, we categorised a continuous prognostic index produced by the multivariable fractional polynomial (MFP) algorithm, using a strategy in which continuous predictors are kept continuous. The MFP algorithm selected five prognostic factors as significant at the 5% level in a multivariable model: lymph node metastases, liver metastases, bone metastases, age, C-reactive protein and neutrophils. The MFP model allowed us to divide patients into four risk groups achieving median overall survivals of 38 months (low risk), 23 months (low intermediate risk), 15 months (high intermediate risk) and 5.6 months (high risk). Our approach, based on categorising a continuous prognostic index produced by the MFP algorithm, allowed more flexibility in the determination of risk groups than traditional approaches

Investigating whether adverse prenatal and perinatal events are associated with non-clinical psychotic symptoms at age 12 years in the ALSPAC birth cohort

Background. Non-clinical psychosis-like symptoms (PLIKS) occur in about 15% of the population. It is not clear whether adverse events during early development alter the risk of developing PLIKS. We aimed to examine whether maternal infection, diabetes or pre-eclampsia during pregnancy, gestational age, perinatal cardiopulmonary resuscitation or 5-min Apgar score were associated with development of psychotic symptoms during early adolescence. Method. A longitudinal study of 6356 12-year-old adolescents who completed a semi-structured interview for psychotic symptoms in the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. Prenatal and perinatal data were obtained from obstetric records and maternal questionnaires completed during pregnancy. Results. The presence of definite psychotic symptoms was associated with maternal infection during pregnancy [adjusted odds ratio (OR) 1.44, 95% confidence interval (CI) 1.11–1.86, p=0.006], maternal diabetes (adjusted OR 3.43, 95% CI 1.14–10.36, p=0.029), need for resuscitation (adjusted OR 1.50, 95% CI 0.97–2.31, p=0.065) and 5-min Apgar score (adjusted OR per unit decrease 1.30, 95% CI 1.12–1.50, p<0.001). None of these associations were mediated by childhood IQ score. Most associations persisted, but were less strong, when including suspected symptoms as part of the outcome. There was no association between PLIKS and gestational age or pre-eclampsia. Conclusions. Adverse events during early development may lead to an increased risk of developing PLIKS. Although the status of PLIKS in relation to clinical disorders such as schizophrenia is not clear, the similarity between these results and findings reported for schizophrenia indicates that future studies of PLIKS may help us to understand how psychotic experiences and clinical disorders develop throughout the life-course

A Flexible Parametric Modelling Framework for Survival Analysis

We introduce a general, flexible, parametric survival modelling framework which encompasses key shapes of hazard function (constant, increasing, decreasing, up-then-down, down-then-up), various common survival distributions (log-logistic, Burr type XII, Weibull, Gompertz), and includes defective distributions (cure models). This generality is achieved using four distributional parameters: two scale-type parameters – which, respectively, relate to accelerated failure time (AFT) and proportional hazards (PH) modelling – and two shape parameters. Furthermore, we advocate “multi-parameter regression” whereby more than one distributional parameter depends on covariates – rather than the usual convention of having a single covariate-dependent (scale) parameter. This general formulation unifies the most popular survival models, allowing us to consider the practical value of possible modelling choices. In particular, we suggest introducing covariates through just one or other of the two scale parameters (covering AFT and PH models), and through a “power” shape parameter (covering more complex non-AFT/non-PH effects); the other shape parameter remains covariate-independent, and handles automatic selection of the baseline distribution. We explore inferential issues and compare with alternative models through various simulation studies, with particular focus on evidence concerning the need, or otherwise, to include both AFT and PH parameters. We illustrate the efficacy of our modelling framework using data from lung cancer, melanoma, and kidney function studies. Censoring is accommodated throughout

Metabolic responses of eukaryotic microalgae to environmental stress limit the ability of FT-IR spectroscopy for species identification

AbstractFourier Transform Infrared (FT-IR) spectroscopy is a robust method for macromolecular analysis and differentiation of microorganisms. However, most studies are performed in controlled conditions and it is unclear whether this tool is appropriate for the identification of eukaryotic microalgae species from variable environments. In order to address this, nine closely-related species of marine and freshwater microalgae were grown under controlled (non-stressed) and variable (non-stressed and stressed) conditions, including nutrient-stressed and wastewater-stressed conditions. Following optimization of data processing methods, FT-IR spectra from all species and conditions were compared. The substantial metabolic changes that were caused by nutrient starvation restricted the ability of FT-IR spectroscopy to differentiate the microalgal species grown under variable conditions efficiently. Comparison of unsupervised and supervised multivariate data analysis methods found that principal component-discriminant function analysis was able best to differentiate between some species under controlled conditions but still gave poor differentiation under variable environmental conditions

A Comparison of the Ovulation Method With the CUE Ovulation Predictor in Determining the Fertile Period

The purpose of this study was to compare the CUE Ovulation Predictor with the ovulation method in determining the fertile period. Eleven regularly ovulating women measured their salivary and vaginal electrical resistance (ER) with the CUE, observed their cervical-vaginal mucus, and measured their urine for a luteinizing hormone (LH) surge on a daily basis. Data from 21 menstrual cycles showed no statistical difference (T= 0.33, p= 0.63) between the CUE fertile period, which ranged from 5 to 10 days (mean = 6.7 days, SD = 1.6), and the fertile period of the ovulation method, which ranged from 4 to 9 days (mean = 6.5 days, SD = 2.0). The CUE has potential as an adjunctive device in the learning and use of natural family planning methods

Gestational age at delivery and special educational need: retrospective cohort study of 407,503 schoolchildren

&lt;STRONG&gt;Background&lt;/STRONG&gt; Previous studies have demonstrated an association between preterm delivery and increased risk of special educational need (SEN). The aim of our study was to examine the risk of SEN across the full range of gestation. &lt;STRONG&gt;Methods and Findings&lt;/STRONG&gt; We conducted a population-based, retrospective study by linking school census data on the 407,503 eligible school-aged children resident in 19 Scottish Local Authority areas (total population 3.8 million) to their routine birth data. SEN was recorded in 17,784 (4.9%) children; 1,565 (8.4%) of those born preterm and 16,219 (4.7%) of those born at term. The risk of SEN increased across the whole range of gestation from 40 to 24 wk: 37–39 wk adjusted odds ratio (OR) 1.16, 95% confidence interval (CI) 1.12–1.20; 33–36 wk adjusted OR 1.53, 95% CI 1.43–1.63; 28–32 wk adjusted OR 2.66, 95% CI 2.38–2.97; 24–27 wk adjusted OR 6.92, 95% CI 5.58–8.58. There was no interaction between elective versus spontaneous delivery. Overall, gestation at delivery accounted for 10% of the adjusted population attributable fraction of SEN. Because of their high frequency, early term deliveries (37–39 wk) accounted for 5.5% of cases of SEN compared with preterm deliveries (&lt;37 wk), which accounted for only 3.6% of cases. &lt;STRONG&gt;Conclusions&lt;/STRONG&gt; Gestation at delivery had a strong, dose-dependent relationship with SEN that was apparent across the whole range of gestation. Because early term delivery is more common than preterm delivery, the former accounts for a higher percentage of SEN cases. Our findings have important implications for clinical practice in relation to the timing of elective delivery