Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected.

Prediction of 1-year mortality in patients with acute coronary syndromes undergoing percutaneous coronary intervention: validation of the logistic clinical SYNTAX (Synergy Between Percutaneous Coronary Interventions With Taxus and Cardiac Surgery) score

OBJECTIVES This study sought to validate the Logistic Clinical SYNTAX (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery) score in patients with non-ST-segment elevation acute coronary syndromes (ACS), in order to further legitimize its clinical application. BACKGROUND The Logistic Clinical SYNTAX score allows for an individualized prediction of 1-year mortality in patients undergoing contemporary percutaneous coronary intervention. It is composed of a "Core" Model (anatomical SYNTAX score, age, creatinine clearance, and left ventricular ejection fraction), and "Extended" Model (composed of an additional 6 clinical variables), and has previously been cross validated in 7 contemporary stent trials (>6,000 patients). METHODS One-year all-cause death was analyzed in 2,627 patients undergoing percutaneous coronary intervention from the ACUITY (Acute Catheterization and Urgent Intervention Triage Strategy) trial. Mortality predictions from the Core and Extended Models were studied with respect to discrimination, that is, separation of those with and without 1-year all-cause death (assessed by the concordance [C] statistic), and calibration, that is, agreement between observed and predicted outcomes (assessed with validation plots). Decision curve analyses, which weight the harms (false positives) against benefits (true positives) of using a risk score to make mortality predictions, were undertaken to assess clinical usefulness. RESULTS In the ACUITY trial, the median SYNTAX score was 9.0 (interquartile range 5.0 to 16.0); approximately 40% of patients had 3-vessel disease, 29% diabetes, and 85% underwent drug-eluting stent implantation. Validation plots confirmed agreement between observed and predicted mortality. The Core and Extended Models demonstrated substantial improvements in the discriminative ability for 1-year all-cause death compared with the anatomical SYNTAX score in isolation (C-statistics: SYNTAX score: 0.64, 95% confidence interval [CI]: 0.56 to 0.71; Core Model: 0.74, 95% CI: 0.66 to 0.79; Extended Model: 0.77, 95% CI: 0.70 to 0.83). Decision curve analyses confirmed the increasing ability to correctly identify patients who would die at 1 year with the Extended Model versus the Core Model versus the anatomical SYNTAX score, over a wide range of thresholds for mortality risk predictions. CONCLUSIONS Compared to the anatomical SYNTAX score alone, the Core and Extended Models of the Logistic Clinical SYNTAX score more accurately predicted individual 1-year mortality in patients presenting with non-ST-segment elevation acute coronary syndromes undergoing percutaneous coronary intervention. These findings support the clinical application of the Logistic Clinical SYNTAX score.

Complex visual hallucinations and attentional performance in eye disease and dementia: a test of the Perception and Attention Deficit model

OBJECTIVE This study aimed to test the prediction from the Perception and Attention Deficit model of complex visual hallucinations (CVH) that impairments in visual attention and perception are key risk factors for complex hallucinations in eye disease and dementia. METHODS Two studies ran concurrently to investigate the relationship between CVH and impairments in perception (picture naming using the Graded Naming Test) and attention (Stroop task plus a novel Imagery task). The studies were in two populations-older patients with dementia (n = 28) and older people with eye disease (n = 50) with a shared control group (n = 37). The same methodology was used in both studies, and the North East Visual Hallucinations Inventory was used to identify CVH. RESULTS A reliable relationship was found for older patients with dementia between impaired perceptual and attentional performance and CVH. A reliable relationship was not found in the population of people with eye disease. CONCLUSIONS The results add to previous research that object perception and attentional deficits are associated with CVH in dementia, but that risk factors for CVH in eye disease are inconsistent, suggesting that dynamic rather than static impairments in attentional processes may be key in this population.

Improving the clinical prediction of psychosis by combining ultra-high risk criteria and cognitive basic symptoms

OBJECTIVE Cognitive impairments are regarded as a core component of schizophrenia. However, the cognitive dimension of psychosis is hardly considered by ultra-high risk (UHR) criteria. Therefore, we studied whether the combination of symptomatic UHR criteria and the basic symptom criterion "cognitive disturbances" (COGDIS) is superior in predicting first-episode psychosis. METHOD In a naturalistic 48-month follow-up study, the conversion rate to first-episode psychosis was studied in 246 outpatients of an early detection of psychosis service (FETZ); thereby, the association between conversion, and the combined and singular use of UHR criteria and COGDIS was compared. RESULTS Patients that met UHR criteria and COGDIS (n=127) at baseline had a significantly higher risk of conversion (hr=0.66 at month 48) and a shorter time to conversion than patients that met only UHR criteria (n=37; hr=0.28) or only COGDIS (n=30; hr=0.23). Furthermore, the risk of conversion was higher for the combined criteria than for UHR criteria (n=164; hr=0.56 at month 48) and COGDIS (n=158; hr=0.56 at month 48) when considered irrespective of each other. CONCLUSIONS Our findings support the merits of considering both COGDIS and UHR criteria in the early detection of persons who are at high risk of developing a first psychotic episode within 48months. Applying both sets of criteria improves sensitivity and individual risk estimation, and may thereby support the development of stage-targeted interventions. Moreover, since the combined approach enables the identification of considerably more homogeneous at-risk samples, it should support both preventive and basic research.

Can quantitative EEG measures predict clinical outcome in subjects at Clinical High Risk for psychosis? A prospective multicenter study

BACKGROUND Prediction studies in subjects at Clinical High Risk (CHR) for psychosis are hampered by a high proportion of uncertain outcomes. We therefore investigated whether quantitative EEG (QEEG) parameters can contribute to an improved identification of CHR subjects with a later conversion to psychosis. METHODS This investigation was a project within the European Prediction of Psychosis Study (EPOS), a prospective multicenter, naturalistic field study with an 18-month follow-up period. QEEG spectral power and alpha peak frequencies (APF) were determined in 113 CHR subjects. The primary outcome measure was conversion to psychosis. RESULTS Cox regression yielded a model including frontal theta (HR=1.82; [95% CI 1.00-3.32]) and delta (HR=2.60; [95% CI 1.30-5.20]) power, and occipital-parietal APF (HR=.52; [95% CI .35-.80]) as predictors of conversion to psychosis. The resulting equation enabled the development of a prognostic index with three risk classes (hazard rate 0.057 to 0.81). CONCLUSIONS Power in theta and delta ranges and APF contribute to the short-term prediction of psychosis and enable a further stratification of risk in CHR samples. Combined with (other) clinical ratings, EEG parameters may therefore be a useful tool for individualized risk estimation and, consequently, targeted prevention.

Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center

Therapeutic resistance remains the principal problem in acute myeloid leukemia (AML). We used area under receiver-operating characteristic curves (AUCs) to quantify our ability to predict therapeutic resistance in individual patients, where AUC=1.0 denotes perfect prediction and AUC=0.5 denotes a coin flip, using data from 4601 patients with newly diagnosed AML given induction therapy with 3+7 or more intense standard regimens in UK Medical Research Council/National Cancer Research Institute, Dutch–Belgian Cooperative Trial Group for Hematology/Oncology/Swiss Group for Clinical Cancer Research, US cooperative group SWOG and MD Anderson Cancer Center studies. Age, performance status, white blood cell count, secondary disease, cytogenetic risk and FLT3-ITD/NPM1 mutation status were each independently associated with failure to achieve complete remission despite no early death (‘primary refractoriness’). However, the AUC of a bootstrap-corrected multivariable model predicting this outcome was only 0.78, indicating only fair predictive ability. Removal of FLT3-ITD and NPM1 information only slightly decreased the AUC (0.76). Prediction of resistance, defined as primary refractoriness or short relapse-free survival, was even more difficult. Our limited ability to forecast resistance based on routinely available pretreatment covariates provides a rationale for continued randomization between standard and new therapies and supports further examination of genetic and posttreatment data to optimize resistance prediction in AML.

Clinical importance of risk variants in the dihydropyrimidine dehydrogenase gene for the prediction of early-onset fluoropyrimidine toxicity.

We investigated the clinical relevance of dihydropyrimidine dehydrogenase gene (DPYD) variants to predict severe early-onset fluoropyrimidine (FP) toxicity, in particular of a recently discovered haplotype hapB3 and a linked deep intronic splice site mutation c.1129-5923C>G. Selected regions of DPYD were sequenced in prospectively collected germline DNA of 500 patients receiving FP-based chemotherapy. Associations of DPYD variants and haplotypes with hematologic, gastrointestinal, infectious, and dermatologic toxicity in therapy cycles 1-2 and resulting FP-dose interventions (dose reduction, therapy delay or cessation) were analyzed accounting for clinical and demographic covariates. Fifteen additional cases with toxicity-related therapy delay or cessation were retrospectively examined for risk variants. The association of c.1129-5923C>G/hapB3 (4.6% carrier frequency) with severe toxicity was replicated in an independent prospective cohort. Overall, c.1129-5923G/hapB3 carriers showed a relative risk of 3.74 (RR, 95% CI = 2.30-6.09, p = 2 × 10(-5)) for severe toxicity (grades 3-5). Of 31 risk variant carriers (c.1129-5923C>G/hapB3, c.1679T>G, c.1905+1G>A or c.2846A>T), 11 (all with c.1129-5923C>G/hapB3) experienced severe toxicity (15% of 72 cases, RR = 2.73, 95% CI = 1.61-4.63, p = 5 × 10(-6)), and 16 carriers (55%) required FP-dose interventions. Seven of the 15 (47%) retrospective cases carried a risk variant. The c.1129-5923C>G/hapB3 variant is a major contributor to severe early-onset FP toxicity in Caucasian patients. This variant may substantially improve the identification of patients at risk of FP toxicity compared to established DPYD risk variants (c.1905+1G>A, c.1679T>G and c.2846A>T). Pre-therapeutic DPYD testing may prevent 20-30% of life-threatening or lethal episodes of FP toxicity in Caucasian patients.

DNA Methylation-Guided Prediction of Clinical Failure in High-Risk Prostate Cancer.

BACKGROUND Prostate cancer (PCa) is a very heterogeneous disease with respect to clinical outcome. This study explored differential DNA methylation in a priori selected genes to diagnose PCa and predict clinical failure (CF) in high-risk patients. METHODS A quantitative multiplex, methylation-specific PCR assay was developed to assess promoter methylation of the APC, CCND2, GSTP1, PTGS2 and RARB genes in formalin-fixed, paraffin-embedded tissue samples from 42 patients with benign prostatic hyperplasia and radical prostatectomy specimens of patients with high-risk PCa, encompassing training and validation cohorts of 147 and 71 patients, respectively. Log-rank tests, univariate and multivariate Cox models were used to investigate the prognostic value of the DNA methylation. RESULTS Hypermethylation of APC, CCND2, GSTP1, PTGS2 and RARB was highly cancer-specific. However, only GSTP1 methylation was significantly associated with CF in both independent high-risk PCa cohorts. Importantly, trichotomization into low, moderate and high GSTP1 methylation level subgroups was highly predictive for CF. Patients with either a low or high GSTP1 methylation level, as compared to the moderate methylation groups, were at a higher risk for CF in both the training (Hazard ratio [HR], 3.65; 95% CI, 1.65 to 8.07) and validation sets (HR, 4.27; 95% CI, 1.03 to 17.72) as well as in the combined cohort (HR, 2.74; 95% CI, 1.42 to 5.27) in multivariate analysis. CONCLUSIONS Classification of primary high-risk tumors into three subtypes based on DNA methylation can be combined with clinico-pathological parameters for a more informative risk-stratification of these PCa patients.

Model for ranking freshwater fish farms according to their risk of infection and illustration for viral haemorrhagic septicaemia

We developed a model to calculate a quantitative risk score for individual aquaculture sites. The score indicates the risk of the site being infected with a specific fish pathogen (viral haemorrhagic septicaemia virus (VHSV); infectious haematopoietic necrosis virus, Koi herpes virus), and is intended to be used for risk ranking sites to support surveillance for demonstration of zone or member state freedom from these pathogens. The inputs to the model include a range of quantitative and qualitative estimates of risk factors organised into five risk themes (1) Live fish and egg movements; (2) Exposure via water; (3) On-site processing; (4) Short-distance mechanical transmission; (5) Distance-independent mechanical transmission. The calculated risk score for an individual aquaculture site is a value between zero and one and is intended to indicate the risk of a site relative to the risk of other sites (thereby allowing ranking). The model was applied to evaluate 76 rainbow trout farms in 3 countries (42 from England, 32 from Italy and 2 from Switzerland) with the aim to establish their risk of being infected with VHSV. Risk scores for farms in England and Italy showed great variation, clearly enabling ranking. Scores ranged from 0.002 to 0.254 (mean score 0.080) in England and 0.011 to 0.778 (mean of 0.130) for Italy, reflecting the diversity of infection status of farms in these countries. Requirements for broader application of the model are discussed. Cost efficient farm data collection is important to realise the benefits from a risk-based approach.

At risk or not at risk? A meta-analysis of the prognostic accuracy of psychometric interviews for psychosis prediction

An accurate detection of individuals at clinical high risk (CHR) for psychosis is a prerequisite for effective preventive interventions. Several psychometric interviews are available, but their prognostic accuracy is unknown. We conducted a prognostic accuracy meta-analysis of psychometric interviews used to examine referrals to high risk services. The index test was an established CHR psychometric instrument used to identify subjects with and without CHR (CHR+ and CHR-). The reference index was psychosis onset over time in both CHR+ and CHR- subjects. Data were analyzed with MIDAS (STATA13). Area under the curve (AUC), summary receiver operating characteristic curves, quality assessment, likelihood ratios, Fagan's nomogram and probability modified plots were computed. Eleven independent studies were included, with a total of 2,519 help-seeking, predominately adult subjects (CHR+: N=1,359; CHR-: N=1,160) referred to high risk services. The mean follow-up duration was 38 months. The AUC was excellent (0.90; 95% CI: 0.87-0.93), and comparable to other tests in preventive medicine, suggesting clinical utility in subjects referred to high risk services. Meta-regression analyses revealed an effect for exposure to antipsychotics and no effects for type of instrument, age, gender, follow-up time, sample size, quality assessment, proportion of CHR+ subjects in the total sample. Fagan's nomogram indicated a low positive predictive value (5.74%) in the general non-help-seeking population. Albeit the clear need to further improve prediction of psychosis, these findings support the use of psychometric prognostic interviews for CHR as clinical tools for an indicated prevention in subjects seeking help at high risk services worldwide.

Directional DBS improves therapeutic window: from model prediction to human use

Deep brain stimulation of different targets has been shown to drastically improve symptoms of a variety of neurological conditions. However, the occurrence of disabling side effects may limit the ability to deliver adequate amounts of current necessary to reach the maximal benefit. Computed models have suggested that reduction in electrode size and the ability to provide directional stimulation could increase the efficacy of such therapies. This has never been demonstrated in humans. In the present study, we assess the effect of directional stimulation compared to omnidirectional stimulation.