Overview of data-synthesis in systematic reviews of studies on outcome prediction models

Background: Many prognostic models have been developed. Different types of models, i.e. prognostic factor and outcome prediction studies, serve different purposes, which should be reflected in how the results are summarized in reviews. Therefore we set out to investigate how authors of reviews synthesize and report the results of primary outcome prediction studies. Methods: Outcome prediction reviews published in MEDLINE between October 2005 and March 2011 were eligible and 127 Systematic reviews with the aim to summarize outcome prediction studies written in English were identified for inclusion. Characteristics of the reviews and the primary studies that were included were independently assessed by 2 review authors, using standardized forms. Results: After consensus meetings a total of 50 systematic reviews that met the inclusion criteria were included. The type of primary studies included (prognostic factor or outcome prediction) was unclear in two-thirds of the reviews. A minority of the reviews reported univariable or multivariable point estimates and measures of dispersion from the primary studies. Moreover, the variables considered for outcome prediction model development were often not reported, or were unclear. In most reviews there was no information about model performance. Quantitative analysis was performed in 10 reviews, and 49 reviews assessed the primary studies qualitatively. In both analyses types a range of different methods was used to present the results of the outcome prediction studies. Conclusions: Different methods are applied to synthesize primary study results but quantitative analysis is rarely performed. The description of its objectives and of the primary studies is suboptimal and performance parameters of the outcome prediction models are rarely mentioned. The poor reporting and the wide variety of data synthesis strategies are prone to influence the conclusions of outcome prediction reviews. Therefore, there is much room for improvement in reviews of outcome prediction studies. (aut.ref.

Managing sedentary behavior to reduce the risk of diabetes and cardiovascular disease

Modern human environments are vastly different from those of our forebears. Rapidly advancing technology in transportation, communications, workplaces, and home entertainment confer a wealth of benefits, but increasingly come with costs to human health. Sedentary behavior—too much sitting as distinct from too little physical activity—contributes adversely to cardiometabolic health outcomes and premature mortality. Findings from observational epidemiology have been synthesized in meta-analyses, and evidence is now shifting into the realm of experimental trials with the aim of identifying novel mechanisms and potential causal relationships. We discuss recent observational and experimental evidence that makes a compelling case for reducing and breaking up prolonged sitting time in both the primary prevention and disease management contexts. We also highlight future research needs, the opportunities for developing targeted interventions, and the potential of population-wide initiatives designed to address too much sitting as a health risk

Quantile forecast combination using stochastic dominance

This paper derives optimal forecast combinations based on stochastic dominance efficiency (SDE) analysis with differential forecast weights for different quantiles of forecast error distribution. For the optimal forecast combination, SDE will minimize the cumulative density functions of the levels of loss at different quantiles of the forecast error distribution by combining different time-series model-based forecasts. Using two exchange rate series on weekly data for the Japanese yen/US dollar and US dollar/Great Britain pound, we find that the optimal forecast combinations with SDE weights perform better than different forecast selection and combination methods for the majority of the cases at different quantiles of the error distribution. However, there are also some very few cases where some other forecast selection and combination model performs equally well at some quantiles of the forecast error distribution. Different forecasting period and quadratic loss function are used to obtain optimal forecast combinations, and results are robust to these choices. The out-of sample performance of the SDE forecast combinations is also better than that of the other forecast selection and combination models we considered

Survival in dialysis patients is not different between patients with diabetes as primary renal disease and patients with diabetes as a co-morbid condition

On dialysis, survival among patients with diabetes mellitus is inferior to survival of non-diabetic patients. We hypothesized that patients with diabetes as primary renal disease have worse survival compared to patients with diabetes as a co-morbid condition and aimed to compare all-cause mortality between these patient groups. Data were collected from the Netherlands Cooperative Study on the Adequacy of Dialysis (NECOSAD), a multicenter, prospective cohort study in which new patients with end stage renal disease (ESRD) were monitored until transplantation or death. Patients with diabetes as primary cause of ESRD were compared with patients with diabetes as co-morbid condition and both of these patient groups were compared to patients without diabetes. Analysis was performed using Kaplan-Meier and Cox regression. Fifteen % of the patients had diabetic nephropathy as primary renal disease (N = 281); 6% had diabetes as co-morbid condition (N = 107) and 79% had no diabetes (N = 1465). During follow-up 42% of patients (N = 787) died. Compared to non-diabetic patients, mortality risk was increased for both patients with diabetes as primary renal disease HR: 1.9 (95% CI 1.6, 2.3) and for patients with diabetes as co-morbid condition HR: 1.7 (95% CI 1.3, 2.2). Mortality was not significantly higher in patients with diabetes as primary renal disease compared to patients with diabetes as co-morbid condition (HR 1.06; 95% CI 0.79, 1.43). This study in patients with ESRD showed no survival difference between patients with diabetes as primary renal disease and patients with diabetes as a co-morbid condition. Both conditions were associated with increased mortality risk compared to non-diabetic patient

Estimation of Activity Related Energy Expenditure and Resting Metabolic Rate in Freely Moving Mice from Indirect Calorimetry Data

Physical activity (PA) is a main determinant of total energy expenditure (TEE) and has been suggested to play a key role in body weight regulation. However, thus far it has been challenging to determine what part of the expended energy is due to activity in freely moving subjects. We developed a computational method to estimate activity related energy expenditure (AEE) and resting metabolic rate (RMR) in mice from activity and indirect calorimetry data. The method is based on penalised spline regression and takes the time dependency of the RMR into account. In addition, estimates of AEE and RMR are corrected for the regression dilution bias that results from inaccurate PA measurements. We evaluated the performance of our method based on 500 simulated metabolic chamber datasets and compared it to that of conventional methods. It was found that for a sample time of 10 minutes the penalised spline model estimated the time-dependent RMR with 1.7 times higher accuracy than the Kalman filter and with 2.7 times higher accuracy than linear regression. We assessed the applicability of our method on experimental data in a case study involving high fat diet fed male and female C57Bl/6J mice. We found that TEE in male mice was higher due to a difference in RMR while AEE levels were similar in both groups, even though female mice were more active. Interestingly, the higher activity did not result in a difference in AEE because female mice had a lower caloric cost of activity, which was likely due to their lower body weight. In conclusion, TEE decomposition by means of penalised spline regression provides robust estimates of the time-dependent AEE and RMR and can be applied to data generated with generic metabolic chamber and indirect calorimetry set-ups

Lower Ipsilateral Hippocampal Integrity after Ischemic Stroke in Young Adults: A Long-Term Follow-Up Study.

BACKGROUND AND PURPOSE: Memory impairment after stroke is poorly understood as stroke rarely occurs in the hippocampus. Previous studies have observed smaller ipsilateral hippocampal volumes after stroke compared with controls. Possibly, these findings on macroscopic level are not the first occurrence of structural damage and are preceded by microscopic changes that may already be associated with a worse memory function. We therefore examined the relationship between hippocampal integrity, volume, and memory performance long after first-ever ischemic stroke in young adults. METHODS: We included all consecutive first-ever ischemic stroke patients, without hippocampal strokes or recurrent stroke/TIA, aged 18-50 years, admitted to our academic hospital between 1980 and 2010. One hundred and forty-six patients underwent T1 MPRAGE, DTI scanning and completed the Rey Auditory Verbal Learning Test and were compared with 84 stroke-free controls. After manual correction of hippocampal automatic segmentation, we calculated mean hippocampal fractional anisotropy (FA) and diffusivity (MD). RESULTS: On average 10 years after ischemic stroke, lesion volume was associated with lower ipsilateral hippocampal integrity (p0.05). CONCLUSIONS: Patients with average ipsilateral hippocampal volume could already have lower ipsilateral hippocampal integrity, although at present with no attendant worse memory performance compared with patients with high hippocampal integrity. Longitudinal studies are needed to investigate whether a low hippocampal integrity after stroke might lead to exacerbated memory decline with increasing age.This study was funded by the Dutch Epilepsy Fund (grant 10–18)

Activating mutations of the GNAQ gene: a frequent event in primary melanocytic neoplasms of the central nervous system

Primary melanocytic neoplasms of the central nervous system (CNS) are uncommon neoplasms derived from melanocytes that normally can be found in the leptomeninges. They cover a spectrum of malignancy grades ranging from low-grade melanocytomas to lesions of intermediate malignancy and overtly malignant melanomas. Characteristic genetic alterations in this group of neoplasms have not yet been identified. Using direct sequencing, we investigated 19 primary melanocytic lesions of the CNS (12 melanocytomas, 3 intermediate-grade melanocytomas, and 4 melanomas) for hotspot oncogenic mutations commonly found in melanocytic tumors of the skin (BRAF, NRAS, and HRAS genes) and uvea (GNAQ gene). Somatic mutations in the GNAQ gene at codon 209, resulting in constitutive activation of GNAQ, were detected in 7/19 (37%) tumors, including 6/12 melanocytomas, 0/3 intermediate-grade melanocytomas, and 1/4 melanomas. These GNAQ-mutated tumors were predominantly located around the spinal cord (6/7). One melanoma carried a BRAF point mutation that is frequently found in cutaneous melanomas (c.1799 T>A, p.V600E), raising the question whether this is a metastatic rather than a primary tumor. No HRAS or NRAS mutations were detected. We conclude that somatic mutations in the GNAQ gene at codon 209 are a frequent event in primary melanocytic neoplasms of the CNS. This finding provides new insight in the pathogenesis of these lesions and suggests that GNAQ-dependent mitogen-activated kinase signaling is a promising therapeutic target in these tumors. The prognostic and predictive value of GNAQ mutations in primary melanocytic lesions of the CNS needs to be determined in future studies

Appraisal patterns of envy and related emotions

Envy is a frustrating emotion that arises from upward social comparison. Two studies investigated the appraisals that distinguish benign envy (aimed at improving one’s own situation) from malicious envy (aimed at pulling down the superior other). Study 1 found that appraisals of deservingness and control potential differentiated both types of envy. We manipulated these appraisals in Study 2 and found that while both did not influence the intensity of envy, they did determine the type of envy that resulted. The more a situation was appraised as undeserved, the more participants experienced malicious envy. Benign envy was experienced more when the situation was not undeserved, and the most when the situation was appraised as both deserved and controllable. The current research also clarifies how the types of envy differ from the related emotions admiration and resentment