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Primary and secondary prevention can highly benefit a personalized medicine approach through the accurate discrimination of individuals at high risk of developing a specific disease from those at moderate and low risk. To this end precise risk prediction models need to be built. This endeavor requires a precise characterization of the individual exposome, genome, and phenome. Massive molecular omics data representing the different layers of the biological processes of the host and the nonhost will enable to build more accurate risk prediction models. Epidemiologists aim to integrate omics data along with important information coming from other sources (questionnaires, candidate markers) that has been proved to be relevant in the discrimination risk assessment of complex diseases. However, the integrative models in large-scale epidemiologic research are still in their infancy and they face numerous challenges, some of them at the analytical stage. So far, there are a small number of studies that have integrated more than two omics data sets, and the inclusion of non-omics data in the same models is still missing in most of studies. In this contribution, we aim at approaching the omics and non-omics data integration from the epidemiology scope by considering the “massive” inclusion of variables in the risk assessment and predictive models. We also provide already available examples of integrative contributions in the field, propose analytical strategies that allow considering both omics and non-omics data in the models, and finally review the challenges imbedding this type of research., Fondo de Investigaciones Sanitarias (FIS), Instituto de Salud Carlos III, Spain, Red Temática de Investigación Cooperativa en Cáncer, ISCIII, Spain, European Cooperation in Science and Technology, World Cancer Research, Obra Social Fundación la Caixa, Depto. de Estadística y Ciencia de los Datos, Fac. de Estudios Estadísticos, TRUE, pub

01 juli 2023, Item does not contain fulltext, BACKGROUND: Genomic regions identified by genome-wide association studies (GWAS) for bladder cancer risk provide new insights into etiology. OBJECTIVE: To identify new susceptibility variants for bladder cancer in a meta-analysis of new and existing genome-wide genotype data. DESIGN, SETTING, AND PARTICIPANTS: Data from 32 studies that includes 13,790 bladder cancer cases and 343,502 controls of European ancestry were used for meta-analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES: Log-additive associations of genetic variants were assessed using logistic regression models. A fixed-effects model was used for meta-analysis of the results. Stratified analyses were conducted to evaluate effect modification by sex and smoking status. A polygenic risk score (PRS) was generated on the basis of known and novel susceptibility variants and tested for interaction with smoking. RESULTS AND LIMITATIONS: Multiple novel bladder cancer susceptibility loci (6p.22.3, 7q36.3, 8q21.13, 9p21.3, 10q22.1, 19q13.33) as well as improved signals in three known regions (4p16.3, 5p15.33, 11p15.5) were identified, bringing the number of independent markers at genome-wide significance (p < 5 × 10(-8)) to 24. The 4p16.3 (FGFR3/TACC3) locus was associated with a stronger risk for women than for men (p-interaction = 0.002). Bladder cancer risk was increased by interactions between smoking status and genetic variants at 8p22 (NAT2; multiplicative p value for interaction [p(M-I)] = 0.004), 8q21.13 (PAG1; p(M-I) = 0.01), and 9p21.3 (LOC107987026/MTAP/CDKN2A; p(M-I) = 0.02). The PRS based on the 24 independent GWAS markers (odds ratio per standard deviation increase 1.49, 95% confidence interval 1.44-1.53), which also showed comparable results in two prospective cohorts (UK Biobank, PLCO trial), revealed an approximately fourfold difference in the lifetime risk of bladder cancer according to the PRS (e.g., 1st vs 10th decile) for both smokers and nonsmokers. CONCLUSIONS: We report novel loci ass

Background This study investigates sex disparities in clinical outcomes and tumour immune profiles in patients with pancreatic ductal adenocarcinoma (PDAC) who underwent upfront resection or resection preceded by gemcitabine-based neoadjuvant chemoradiotherapy (nCRT). Methods Patients originated from the PREOPANC randomised controlled trial. Upfront surgery was performed in 82 patients, and 66 received nCRT before resection. The impact of sex on overall survival (OS) was investigated using Cox proportional hazards models. The immunological landscape within the tumour microenvironment (TME) was mapped using transcriptomic and spatial proteomic profiling. Results The 5-year OS rate differed between the sexes following resection preceded by nCRT, with 43% for women compared with 22% for men. In multivariate analysis, the female sex was a favourable independent prognostic factor for OS only in the nCRT group (HR 0.19; 95% CI 0.07 to 0.52). Multivariate heterogeneous treatment effects analysis revealed a significant interaction between sex and treatment, implying increased nCRT efficacy among women with resected PDAC. The TME of women contained fewer protumoural CD163+MRC1+M2 macrophages than that of men after nCRT, as indicated by transcriptomic and validated using spatial proteomic profiling. Conclusion PDAC tumours of women are more sensitive to gemcitabine-based nCRT, resulting in longer OS after resection compared with men. This may be due to enhanced immunity impeding the infiltration of protumoral M2 macrophages into the TME. Our findings highlight the importance of considering sex disparities and mitigating immunosuppressive macrophage polarisation for personalised PDAC treatment.

Contains fulltext : 248271.pdf (Publisher’s version ) (Open Access), BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) is characterized by frequent recurrences and a risk of progression in stage and grade. Increased knowledge of underlying biological mechanisms is needed. OBJECTIVE: To identify single nucleotide polymorphisms (SNPs) associated with recurrence-free (RFS) and progression-free (PFS) survival in NMIBC. DESIGN, SETTING, AND PARTICIPANTS: We analyzed outcome data from 3400 newly diagnosed NMIBC patients from the Netherlands, the UK, Canada, and Spain. We generated genome-wide germline SNP data using Illumina OmniExpress and Infinium Global Screening Array in combination with genotype imputation. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Cohort-specific genome-wide association studies (GWASs) for RFS and PFS were performed using a Cox proportional hazard model. Results were combined in a fixed-effect inverse-variance weighted meta-analysis. Candidate genes for the identified SNP associations were prioritized using functional annotation, gene-based analysis, expression quantitative trait locus analysis, and transcription factor binding site databases. Tumor expression levels of prioritized genes were tested for association with RFS and PFS in an independent NMIBC cohort. RESULTS AND LIMITATIONS: This meta-analysis revealed a genome-wide significant locus for RFS on chromosome 14 (lead SNP rs12885353, hazard ratio [HR] C vs T allele 1.55, 95% confidence interval [CI] 1.33-1.82, p = 4.0 × 10(-8)), containing genes G2E3 and SCFD1. Higher expression of SCFD1 was associated with increased RFS (HR 0.70, 95% CI 0.59-0.84, p(FDR) = 0.003). Twelve other loci were suggestively associated with RFS (p < 10(-5)), pointing toward 18 additional candidate genes. For PFS, ten loci showed suggestive evidence of association, indicating 36 candidate genes. Expression levels of ten of these genes were statistically significantly associated with PFS, of which four (IFT140, UBE2I, FAHD1, and NME3) showed directional consistency with our

Rapid and continuing advances in biomarker testing are not being matched by uptake in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre‐eminently in many cancers, but also in an ever‐wider range of conditions— notably BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, the implementation of genetic testing in clinical routine setting is still challenging. Development is impeded by country‐related heterogeneity, data deficiencies, and lack of policy alignment on standards, approval—and the role of real‐world evidence in the process—and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe’s industrial competitiveness and innovation require an appropriate policy framework—starting with an update to outdated recommendations. We show herein the main issues and proposals that emerged during the previous advisory boards organised by the European Alliance for Personalized Medicine which mainly focus on possible scenarios of harmonisation of both oncogenetic testing and management of cancer patients.

Background: Whether circulating polyunsaturated fatty acid (PUFA) levels are associated with pancreatic cancer risk is uncertain. Mendelian randomization (MR) represents a study design using genetic instruments to better characterize the relationship between exposure and outcome. Method(s): We utilized data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium, involving approximately 9,269 cases and 12,530 controls of European descent, to evaluate associations between pancreatic cancer risk and genetically predicted plasma n-6 PUFA levels. Conventional MR analyses were performed using individual-level and summary-level data. Result(s): Using genetic instruments, we did not find evidence of associations between genetically predicted plasma n-6 PUFA levels and pancreatic cancer risk [estimates per one SD increase in each PUFA-specific weighted genetic score using summary statistics: Linoleic acid odds ratio (OR)1.00, 95% confidence interval (CI) 0.98-1.02; arachidonic acid OR 1.00, 95% CI 0.99-1.01; and dihomo-gamma-linolenic acid OR 0.95, 95% CI 0.87-1.02]. The OR estimates remained virtually unchanged after adjustment for covariates, using individual-level data or summary statistics, or stratification by age and sex. Conclusion(s): Our results suggest that variations of genetically determined plasma n-6 PUFA levels are not associated with pancreatic cancer risk. Impact: These results suggest that modifying n-6 PUFA levels through food sources or supplementation may not influence risk of pancreatic cancer.Copyright © 2020 American Association for Cancer Research Inc.. All rights reserved.

Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Method(s): We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index >=30 kg/m2) and diabetes (duration >=3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency >=0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Result(s): No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 106) was observed in the meta-analysis (PGxE 1/4 1.2 106, PJoint 1/4 4.2 107). Conclusion(s): This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, Pinteraction 1/4 3.08 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r2 1/4 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings.Copyright © 2021 American Association for Cancer Research.

BACKGROUND: Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. OBJECTIVE(S): The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. METHOD(S): We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (+/-20 kb) for a total of 412 SNPs. RESULT(S): The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. CONCLUSION(S): Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association.Copyright Published by Oxford University Press on behalf of the American Society for Nutrition 2021.

Registry-based epidemiologic studies suggest associations between chronic inflammatory intestinal diseases and pancreatic ductal adenocarcinoma (PDAC). As genetic susceptibility contributes to a large proportion of chronic inflammatory intestinal diseases, we hypothesize that the genomic regions surrounding established genome-wide associated variants for these chronic inflammatory diseases are associated with PDAC. We examined the association between PDAC and genomic regions (+500 kb) surrounding established common susceptibility variants for ulcerative colitis, Crohn's disease, inflammatory bowel disease, celiac disease, chronic pancreatitis, and primary sclerosing cholangitis. We analyzed summary statistics from genome-wide association studies data for 8,384 cases and 11,955 controls of European descent from two large consortium studies using the summary data-based adaptive rank truncated product method to examine the overall association of combined genomic regions for each inflammatory disease group. Combined genomic susceptibility regions for ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis were associated with PDAC at P values < 0.05 (0.0040, 0.0057, 0.011, and 3.4 x 10-6, respectively). After excluding the 20 PDAC susceptibility regions (+500 kb) previously identified by GWAS, the genomic regions for ulcerative colitis, Crohn disease, and inflammatory bowel disease remained associated with PDAC (P 1/4 0.0029, 0.0057, and 0.0098, respectively). Genomic regions for celiac disease (P 1/4 0.22) and primary sclerosing cholangitis (P 1/4 0.078) were not associated with PDAC. Our results support the hypothesis that genomic regions surrounding variants associated with inflammatory intestinal diseases, particularly, ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis are associated with PDAC.Copyright © 2020 American Association for Cancer Research.

Background: Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Method(s): To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples). Result(s): We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate <.05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22:RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusion(s): By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.Copyright © 2020 Oxford University Press. All rights reserved.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with few known risk factors and biomarkers. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of biomarkers, usually in small samples. In this study, we evaluated associations of circulating protein levels and PDAC risk using genetic instruments. Method(s): To identify novel circulating protein biomarkers of PDAC, we studied 8,280 cases and 6,728 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium, using genetic instruments of protein quantitative trait loci. Result(s): We observed associations between predicted concentrations of 38 proteins and PDAC risk at an FDR of < 0.05, including 23 of those proteins that showed an association even after Bonferroni correction. These include the protein encoded by ABO, which has been implicated as a potential target gene of PDAC risk variant. Eight of the identified proteins (LMA2L, TM11D, IP-10, ADH1B, STOM, TENC1, DOCK9, and CRBB2) were associated with PDAC risk after adjusting for previously reported PDAC risk variants (OR ranged from 0.79 to 1.52). Pathway enrichment analysis showed that the encoding genes for implicated proteins were significantly enriched in cancer-related pathways, such as STAT3 and IL15 production. Conclusion(s): We identified 38 candidates of protein biomarkers for PDAC risk. Impact: This study identifies novel protein biomarker candidates for PDAC, which if validated by additional studies, may contribute to the etiologic understanding of PDAC development.Copyright © 2020 American Association for Cancer Research.

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

BACKGROUND: Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. OBJECTIVES: The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. METHODS: We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. RESULTS: The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. CONCLUSIONS: Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association.

INTRODUCTION AND OBJECTIVES: The goals of transurethral resection of a bladder tumor (TUR) are to completely resect the lesions and to make a correct diagnosis in order to adequately stage the patient. It is well known that the presence of detrusor muscle in the specimen is a prerequisite to minimize the risk of under staging. Persistent disease after resection of bladder tumors is not uncommon and is the reason why the European Guidelines recommended a re-TUR for all T1 tumors. It was recently published that when there is muscle in the specimen, re-TUR does not influence progression or cancer specific survival. We present here the patient and tumor factors that may influence the presence of residual disease at re-TUR. MATERIAL AND METHODS: In our retrospective cohort of 2451 primary T1G3 patients initially treated with BCG, pathology results for 934 patients (38.1%) who underwent re-TUR are available. 74% had multifocal tumors, 20% of tumors were more than 3 cm in diameter and 26% had concomitant CIS. In this subgroup of patients who underwent re-TUR, there was no residual disease in 267 patients (29%) and residual disease in 667 patients (71%): Ta in 378 (40%) and T1 in 289 (31%) patients. Age, gender, tumor status (primary/recurrent), previous intravesical therapy, tumor size, tumor multi-focality, presence of concomitant CIS, and muscle in the specimen were analyzed in order to evaluate risk factors of residual disease at re-TUR, both in univariate analyses and multivariate logistic regressions. RESULTS: The following were not risk factors for residual disease: age, gender, tumor status and previous intravesical chemotherapy. The following were univariate risk factors for presence of residual disease: no muscle in TUR, multiple tumors, tumors > 3 cm, and presence of concomitant CIS. Due to the correlation between tumor multi-focality and tumor size, the multivariate model retained either the number of tumors or the tumor diameter (but not both), p < 0.001.