Publications (4)15.76 Total impact
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Article: Genetic predisposition to early recurrence in clinically localized prostate cancer.
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ABSTRACT: Study Type - Prognosis inception (cohort) Level of Evidence 2 What's known on the subject? and What does the study add? Currently available nomograms to predict preoperative risk of early biochemical recurrence (EBCR) after radical prostatectomy are solely based on classic clinicopathological variables. Despite providing useful predictions, these models are not perfect. Indeed, most researchers agree that nomograms can be improved by incorporating novel biomarkers. In the last few years, several single nucleotide polymorphisms (SNPs) have been associated with prostate cancer, but little is known about their impact on disease recurrence. We have identified four SNPs associated with EBCR. The addition of SNPs to classic nomograms resulted in a significant improvement in terms of discrimination and calibration. The new nomogram, which combines clinicopathological and genetic variables, will help to improve prediction of prostate cancer recurrence. OBJECTIVES: • To evaluate genetic susceptibility to early biochemical recurrence (EBCR) after radical prostatectomy (RP), as a prognostic factor for early systemic dissemination. • To build a preoperative nomogram to predict EBCR combining genetic and clinicopathological factors. PATIENTS AND METHODS: • We evaluated 670 patients from six University Hospitals who underwent RP for clinically localized prostate cancer (PCa), and were followed-up for at least 5 years or until biochemical recurrence. • EBCR was defined as a level prostate-specific antigen >0.4 ng/mL within 1 year of RP; preoperative variables studied were: age, prostate-specific antigen, clinical stage, biopsy Gleason score, and the genotype of 83 PCa-related single nucleotide polymorphisms (SNPs). • Univariate allele association tests and multivariate logistic regression were used to generate predictive models for EBCR, with clinicopathological factors and adding SNPs. • We internally validated the models by bootstrapping and compared their accuracy using the area under the curve (AUC), net reclassification improvement, integrated discrimination improvement, calibration plots and Vickers' decision curves. RESULTS: • Four common SNPs at KLK3, KLK2, SULT1A1 and BGLAP genes were independently associated with EBCR. • A significant increase in AUC was observed when SNPs were added to the model: AUC (95% confidence interval) 0.728 (0.674-0.784) vs 0.763 (0.708-0.817). • Net reclassification improvement showed a significant increase in probability for events of 60.7% and a decrease for non-events of 63.5%. • Integrated discrimination improvement and decision curves confirmed the superiority of the new model. CONCLUSIONS: • Four SNPs associated with EBCR significantly improved the accuracy of clinicopathological factors. • We present a nomogram for preoperative prediction of EBCR after RP.BJU International 07/2012; · 2.84 Impact Factor -
Article: Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.
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ABSTRACT: Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information.The Journal of urology 08/2010; 184(2):506-11. · 4.02 Impact Factor -
Article: Prediction of functional impairment and remission in rheumatoid arthritis patients by biochemical variables and genetic polymorphisms.
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ABSTRACT: To develop a model to predict RA outcome based on biochemical variables and single nucleotide polymorphisms (SNPs). We collected baseline data from RA patients. SNP genotyping was performed using an oligonucleotide microarray. Remission and severe disability were investigated as outcomes of the study. Logistic regression models and receiver operating characteristic (ROC) curves were used to determine sensitivity (S), specificity (Sp) and likelihood ratio (LR). Six hundred and thirty-two patients (375 in the study and 257 in the validation) were included. Twenty-two out of 152, and 19 out of 208 patients had an HAQ > 2. The model obtained to predict disability included levels of the anti-cyclic citrullinated peptide (anti-CCP) antibodies, ESR and SNP rs2070874 in the IL-4 gene. Homozygous and heterozygous carriers of the IL-4 33T allele had a decreased risk of severe disability. The discriminative power had an area under the curve (AUC) of 0.792 (95% CI 0.694, 0.889), with S 41%, Sp 95% and LR +7.6. Twenty-one out of 268 and 17 out of 211 patients were in remission in the study and validation cohorts, respectively. The model included absence of anti-CCP antibodies and the SNP rs2476601 on the PTPN22 gene. Homozygous and heterozygous carriers of the PTPN22 1858T allele had a decreased probability of remission. The discriminative power had an AUC of 0.842 (95% CI 0.756, 0.928), with S 76%, Sp 86% and LR + 5.4. Predictive ability was confirmed on the validation cohort. We have developed two models based on laboratory variables that are associated with relevant outcomes for RA patients at disease onset.Rheumatology (Oxford, England) 03/2010; 49(3):458-66. · 4.24 Impact Factor -
Article: Identification of chitotriosidase isoforms in plasma of Gaucher disease patients by two dimensional gel electrophoresis.
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ABSTRACT: Chitotriosidase protein (ChT) is the most important biochemical marker described for Gaucher disease (GD). ChT activity is increased several hundred-fold in plasma of GD patients and shows a strong positive correlation with the severity of the disease. However, a recessively inherited enzyme deficiency, with an incidence of about 6% in the Caucasian population, means that not all patients with GD can be monitored by measuring ChT activity. Applying two-dimensional gel electrophoresis (2-DE) technology this study describes the localization and identification of five ChT isoforms in 2-DE images obtained from plasma of GD patients. All these isoforms were unequivocally identified using MALDI-TOF mass spectrometry (MS) and validated by western blot analysis. The features of each ChT isoform separated by 2-DE in plasma from GD patients homozygous for the wild-type ChT allele, carriers of one defective allele and patients homozygous for the mutant allele are presented. We also show the correlation between each ChT isoform and the plasma ChT enzymatic activity of the GD patients sampled in this study.Biochimica et Biophysica Acta 08/2006; 1764(7):1292-8. · 4.66 Impact Factor
