Duration of untreated psychosis: Impact of the definition of treatment onset on its predictive value over three years of treatment.

BACKGROUND: While reduction of DUP (Duration of Untreated Psychosis) is a key goal in early intervention strategies, the predictive value of DUP on outcome has been questioned. We planned this study in order to explore the impact of three different definition of "treatment initiation" on the predictive value of DUP on outcome in an early psychosis sample. METHODS: 221 early psychosis patients aged 18-35 were followed-up prospectively over 36 months. DUP was measured using three definitions for treatment onset: Initiation of antipsychotic medication (DUP1); engagement in a specialized programme (DUP2) and combination of engagement in a specialized programme and adherence to medication (DUP3). RESULTS: 10% of patients never reached criteria for DUP3 and therefore were never adequately treated over the 36-month period of care. While DUP1 and DUP2 had a limited predictive value on outcome, DUP3, based on a more restrictive definition for treatment onset, was a better predictor of positive and negative symptoms, as well as functional outcome at 12, 24 and 36 months. Globally, DUP3 explained 2 to 5 times more of the variance than DUP1 and DUP2, with effect sizes falling in the medium range according to Cohen. CONCLUSIONS: The limited predictive value of DUP on outcome in previous studies may be linked to problems of definitions that do not take adherence to treatment into account. While they need replication, our results suggest effort to reduce DUP should continue and aim both at early detection and development of engagement strategies.

Positive predictive values of Breast Imaging Reporting and Data System (BI-RADS®) categories 3, 4 and 5 in breast lesions submitted to percutaneous biopsy

Objective To evaluate the BI-RADS as a predictive factor of suspicion for malignancy in breast lesions by correlating radiological with histological results and calculating the positive predictive value for categories 3, 4 and 5 in a breast cancer reference center in the city of São Paulo. Materials and Methods Retrospective, analytical and cross-sectional study including 725 patients with mammographic and/or sonographic findings classified as BI-RADS categories 3, 4 and 5 who were referred to the authors' institution to undergo percutaneous biopsy. The tests results were reviewed and the positive predictive value was calculated by means of a specific mathematical equation. Results Positive predictive values found for categories 3, 4 and 5 were respectively the following: 0.74%, 33.08% and 92.95%, for cases submitted to ultrasound-guided biopsy, and 0.00%, 14.90% and 100% for cases submitted to stereotactic biopsy. Conclusion The present study demonstrated high suspicion for malignancy in lesions classified as category 5 and low risk for category 3. As regards category 4, the need for systematic biopsies was observed.

[(18)F]FDG-PET/CT metabolic parameters as useful prognostic factors in cervical cancer patients treated with chemo-radiotherapy.

BACKGROUND: To compare the prognostic value of different anatomical and functional metabolic parameters determined using [(18)F]FDG-PET/CT with other clinical and pathological prognostic parameters in cervical cancer (CC). METHODS: Thirty-eight patients treated with standard curative doses of chemo-radiotherapy (CRT) underwent pre- and post-therapy [(18)F]FDG-PET/CT. [(18)F]FDG-PET/CT parameters including mean tumor standardized uptake values (SUV), metabolic tumor volume (MTV) and tumor glycolytic volume (TGV) were measured before the start of CRT. The post-treatment tumor metabolic response was evaluated. These parameters were compared to other clinical prognostic factors. Survival curves were estimated by using the Kaplan-Meier method. Cox regression analysis was performed to determine the independent contribution of each prognostic factor. RESULTS: After 37 months of median follow-up (range, 12-106), overall survival (OS) was 71 % [95 % confidence interval (CI), 54-88], disease-free survival (DFS) 61 % [95 % CI, 44-78] and loco-regional control (LRC) 76 % [95 % CI, 62-90]. In univariate analyses the [(18)F]FDG-PET/CT parameters unfavorably influencing OS, DFS and LRC were pre-treatment TGV-cutoff ≥562 (37 vs. 76 %, p = 0.01; 33 vs. 70 %, p = 0.002; and 55 vs. 83 %, p = 0.005, respectively), mean pre-treatment tumor SUV cutoff ≥5 (57 vs. 86 %, p = 0.03; 36 vs. 88 %, p = 0.004; 65 vs. 88 %, p = 0.04, respectively) and a partial tumor metabolic response after treatment (9 vs. 29 %, p = 0.0008; 0 vs. 83 %, p < 0.0001; 22 vs. 96 %, p < 0.0001, respectively). After multivariate analyses a partial tumor metabolic response after treatment remained as an independent prognostic factor unfavorably influencing DFS and LRC (RR 1:7.7, p < 0.0001, and RR 1:22.6, p = 0.0003, respectively) while the pre-treatment TGV-cutoff ≥562 negatively influenced OS and DFS (RR 1:2, p = 0.03, and RR 1:2.75, p = 0.05). CONCLUSIONS: Parameters capturing the pre-treatment glycolytic volume and metabolic activity of [(18)F]FDG-positive disease provide important prognostic information in patients with CC treated with CRT. The post-therapy [(18)F]FDG-PET/CT uptake (partial tumor metabolic response) is predictive of disease outcome.

The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

DNA Topoisomerase I Gene Copy Number and mRNA Expression Assessed as Predictive Biomarkers for Adjuvant Irinotecan in Stage II/III Colon Cancer.

PURPOSE: Prospective-retrospective assessment of theTOP1gene copy number andTOP1mRNA expression as predictive biomarkers for adjuvant irinotecan in stage II/III colon cancer. EXPERIMENTAL DESIGN: Formalin-fixed, paraffin-embedded tissue microarrays were obtained from an adjuvant colon cancer trial (PETACC3) where patients were randomized to 5-fluorouracil/folinic acid with or without additional irinotecan.TOP1copy number status was analyzed by fluorescencein situhybridization (FISH) using aTOP1/CEN20 dual-probe combination.TOP1mRNA data were available from previous analyses. RESULTS: TOP1FISH and follow-up data were obtained from 534 patients.TOP1gain was identified in 27% using a single-probe enumeration strategy (≥4TOP1signals per cell) and in 31% when defined by aTOP1/CEN20 ratio ≥ 1.5. The effect of additional irinotecan was not dependent onTOP1FISH status.TOP1mRNA data were available from 580 patients with stage III disease. Benefit of irinotecan was restricted to patients characterized byTOP1mRNA expression ≥ third quartile (RFS: HRadjusted, 0.59;P= 0.09; OS: HRadjusted, 0.44;P= 0.03). The treatment byTOP1mRNA interaction was not statistically significant, but in exploratory multivariable fractional polynomial interaction analysis, increasingTOP1mRNA values appeared to be associated with increasing benefit of irinotecan. CONCLUSIONS: In contrast to theTOP1copy number, a trend was demonstrated for a predictive property ofTOP1mRNA expression. On the basis ofTOP1mRNA, it might be possible to identify a subgroup of patients where an irinotecan doublet is a clinically relevant option in the adjuvant setting of colon cancer.Clin Cancer Res; 22(7); 1621-31. ©2015 AACR.

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Regression analysis of compositional data when both the dependent variable and independent variable are components

It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features

The causal factors of international inequality in CO2 emissions per capita: a regression-based inequality decomposition analysis

This paper uses the possibilities provided by the regression-based inequality decomposition (Fields, 2003) to explore the contribution of different explanatory factors to international inequality in CO2 emissions per capita. In contrast to previous emissions inequality decompositions, which were based on identity relationships (Duro and Padilla, 2006), this methodology does not impose any a priori specific relationship. Thus, it allows an assessment of the contribution to inequality of different relevant variables. In short, the paper appraises the relative contributions of affluence, sectoral composition, demographic factors and climate. The analysis is applied to selected years of the period 1993–2007. The results show the important (though decreasing) share of the contribution of demographic factors, as well as a significant contribution of affluence and sectoral composition.

Determinação de misturas de sulfametoxazol e trimetoprima por espectroscopia eletrônica multivariada

In this work a multivariate spectroscopic methodology is proposed for quantitative determination of sulfamethoxazole and trimethoprim in pharmaceutical associations. The multivariate model was developed by partial least-squares regression, using twenty synthetic mixtures and the spectral region between 190 and 350 nm. In the validation stage, which involved the analysis of five synthetic mixtures, prediction errors lower that 3% were observed. The predictive capacity of the multivariate models is seriously affected by spectral changes induced by pH variations, a fact that acquires a great significance in the analysis of real samples (pharmaceuticals) that contain chemical additives.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Estudos de QSAR 3D para um conjunto de inibidores de butirilcolinesterase humana

Alzheimer's disease (AD) is considered the main cause of cognitive decline in adults. The available therapies for AD treatment seek to maintain the activity of cholinergic system through the inhibition of the enzyme acetylcholinesterase. However, butyrylcholinesterase (BuChE) can be considered an alternative target for AD treatment. Aiming at developing new BuChE inhibitors, robust QSAR 3D models with high predictive power were developed. The best model presents a good fit (r²=0.82, q²=0.76, with two PCs) and high predictive power (r²predict=0.88). Analysis of regression vector shows that steric properties have considerable importance to the inhibition of the BuChE.