http://hdl.handle.net/10854/4376 2026-04-17T10:27:11Z 2026-04-17T10:27:11Z López de Maturana, Evangelina Chanock, Stephen Picornell, A.C. Rothman, Nathaniel Herranz, J. Calle, M. Luz García-Closas, Montserrat Marenne, Gaëlle Brand, A. Tardón, Adonina Carrato, Alfredo Silverman, Debra T. Kogevinas, Manolis Gianola, D. Real, Francisco X. Malats i Riera, Núria http://hdl.handle.net/10854/3226 2025-11-28T11:28:53Z 2014-01-01T00:00:00Z

Whole Genome Prediction of Bladder Cancer Risk With the Bayesian LASSO López de Maturana, Evangelina; Chanock, Stephen; Picornell, A.C.; Rothman, Nathaniel; Herranz, J.; Calle, M. Luz; García-Closas, Montserrat; Marenne, Gaëlle; Brand, A.; Tardón, Adonina; Carrato, Alfredo; Silverman, Debra T.; Kogevinas, Manolis; Gianola, D.; Real, Francisco X.; Malats i Riera, Núria To build a predictive model for urothelial carcinoma of the bladder (UCB) risk combining both genomic and nongenomic data, 1,127 cases and 1,090 controls from the Spanish Bladder Cancer/EPICURO study were genotyped using the HumanHap 1M SNP array. After quality control filters, genotypes from 475,290 variants were available. Nongenomic information comprised age, gender, region, and smoking status. Three Bayesian threshold models were implemented including: (1) only genomic information, (2) only nongenomic data, and (3) both sources of information. The three models were applied to the whole population, to only nonsmokers, to male smokers, and to extreme phenotypes to potentiate the UCB genetic component. The area under the ROC curve allowed evaluating the predictive ability of each model in a 10-fold cross-validation scenario. Smoking status showed the highest predictive ability of UCB risk (AUCtest = 0.62). On the other hand, the AUC of all genetic variants was poorer (0.53). When the extreme phenotype approach was applied, the predictive ability of the genomic model improved 15%. This study represents a first attempt to build a predictive model for UCB risk combining both genomic and nongenomic data and applying state-of-the-art statistical approaches. However, the lack of genetic relatedness among individuals, the complexity of UCB etiology, as well as a relatively small statistical power, may explain the low predictive ability for UCB risk. The study confirms the difficulty of predicting complex diseases using genetic data, and suggests the limited translational potential of findings from this type of data into public health interventions. © 2014 WILEY PERIODICALS, INC.

2014-01-01T00:00:00Z Vedder, M.M. Márquez, M. Bekker-Grob de, E.W. Calle, M. Luz Dyrskjot, L. Kogevinas, Manolis Segersten, U. Malmström, P.U. Algaba, F. Beukers, W. Orntoft, T.F. Zwarthoff, E. Real, Francisco X. Malats i Riera, Núria Steyerberg, E.W. http://hdl.handle.net/10854/3223 2025-11-28T11:29:46Z 2014-01-01T00:00:00Z

Risk Prediction Scores for Recurrence and Progression of Non-Muscle Invasive Bladder Cancer: An International Validation in Primary Tumours Vedder, M.M.; Márquez, M.; Bekker-Grob de, E.W.; Calle, M. Luz; Dyrskjot, L.; Kogevinas, Manolis; Segersten, U.; Malmström, P.U.; Algaba, F.; Beukers, W.; Orntoft, T.F.; Zwarthoff, E.; Real, Francisco X.; Malats i Riera, Núria; Steyerberg, E.W. Abstract Objective: We aimed to determine the validity of two risk scores for patients with non-muscle invasive bladder cancer in different European settings, in patients with primary tumours. Methods: We included 1,892 patients with primary stage Ta or T1 non-muscle invasive bladder cancer who underwent a transurethral resection in Spain (n = 973), the Netherlands (n = 639), or Denmark (n = 280). We evaluated recurrence-free survival and progression-free survival according to the European Organisation for Research and Treatment of Cancer (EORTC) and the Spanish Urological Club for Oncological Treatment (CUETO) risk scores for each patient and used the concordance index (c-index) to indicate discriminative ability. Results: The 3 cohorts were comparable according to age and sex, but patients from Denmark had a larger proportion of patients with the high stage and grade at diagnosis (p,0.01). At least one recurrence occurred in 839 (44%) patients and 258 (14%) patients had a progression during a median follow-up of 74 months. Patients from Denmark had the highest 10- year recurrence and progression rates (75% and 24%, respectively), whereas patients from Spain had the lowest rates (34% and 10%, respectively). The EORTC and CUETO risk scores both predicted progression better than recurrence with c-indices ranging from 0.72 to 0.82 while for recurrence, those ranged from 0.55 to 0.61. Conclusion: The EORTC and CUETO risk scores can reasonably predict progression, while prediction of recurrence is more difficult. New prognostic markers are needed to better predict recurrence of tumours in primary non-muscle invasive bladder cancer patients.

2014-01-01T00:00:00Z Pineda, S. Milne, R.L. Calle, M. Luz Rothman, Nathaniel López de Maturana, Evangelina Herranz, J. Kogevinas, Manolis Chanock, Stephen Tardón, Adonina Márquez, M. Guey, Lin T. García-Closas, Montserrat Lloreta, Josep Baum, E. González-Neira, Anna Carrato, Alfredo Navarro, Arcadi Silverman, Debra T. Real, Francisco X. Malats i Riera, Núria http://hdl.handle.net/10854/3130 2025-11-28T11:29:06Z 2014-01-01T00:00:00Z

Genetic Variation in the TP53 Pathway and Bladder Cancer Risk. A Comprehensive Analysis Pineda, S.; Milne, R.L.; Calle, M. Luz; Rothman, Nathaniel; López de Maturana, Evangelina; Herranz, J.; Kogevinas, Manolis; Chanock, Stephen; Tardón, Adonina; Márquez, M.; Guey, Lin T.; García-Closas, Montserrat; Lloreta, Josep; Baum, E.; González-Neira, Anna; Carrato, Alfredo; Navarro, Arcadi; Silverman, Debra T.; Real, Francisco X.; Malats i Riera, Núria Introduction: Germline variants in TP63 have been consistently associated with several tumors, including bladder cancer, indicating the importance of TP53 pathway in cancer genetic susceptibility. However, variants in other related genes, including TP53 rs1042522 (Arg72Pro), still present controversial results. We carried out an in depth assessment of associations between common germline variants in the TP53 pathway and bladder cancer risk. Material and Methods: We investigated 184 tagSNPs from 18 genes in 1,058 cases and 1,138 controls from the Spanish Bladder Cancer/EPICURO Study. Cases were newly-diagnosed bladder cancer patients during 1998–2001. Hospital controls were age-gender, and area matched to cases. SNPs were genotyped in blood DNA using Illumina Golden Gate and TaqMan assays. Cases were subphenotyped according to stage/grade and tumor p53 expression. We applied classical tests to assess individual SNP associations and the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized logistic regression analysis to assess multiple SNPs simultaneously. Results: Based on classical analyses, SNPs in BAK1 (1), IGF1R (5), P53AIP1 (1), PMAIP1 (2), SERINPB5 (3), TP63 (3), and TP73 (1) showed significant associations at p-value#0.05. However, no evidence of association, either with overall risk or with specific disease subtypes, was observed after correction for multiple testing (p-value$0.8). LASSO selected the SNP rs6567355 in SERPINB5 with 83% of reproducibility. This SNP provided an OR = 1.21, 95%CI 1.05–1.38, p-value = 0.006, and a corrected p-value = 0.5 when controlling for over-estimation. Discussion: We found no strong evidence that common variants in the TP53 pathway are associated with bladder cancer susceptibility. Our study suggests that it is unlikely that TP53 Arg72Pro is implicated in the UCB in white Europeans. SERPINB5 and TP63 variation deserve further exploration in extended studies.

2014-01-01T00:00:00Z Porta, Núria Calle, M. Luz Malats i Riera, Núria Gómez, Guadalupe http://hdl.handle.net/10854/2717 2025-11-28T11:29:19Z 2012-01-01T00:00:00Z

A dynamic model for the risk of bladder cancer progression Porta, Núria; Calle, M. Luz; Malats i Riera, Núria; Gómez, Guadalupe We propose a multistate modeling approach to describe the observed evolution of patients diagnosed with nonmuscle- invasive bladder cancer. On the basis of data from the Spanish Bladder Cancer/EPICURO study, we adjust a multistate model taking into account the disease-related events of interest (recurrence, progression, and disease-related deaths) as well as competing deaths due to other causes. We then develop a dynamic predictive process for bladder cancer progression, which allows the risk of a patient to be updated whenever new information of his or her evolution is available. By using specific measures of prospective accuracy in the presence of competing risks, the proposed dynamic model has shown to improve prediction accuracy and provides a more personalized management of bladder patients. Copyright © 2011 John Wiley & Sons, Ltd.

2012-01-01T00:00:00Z