Cost‑effectiveness analysis of hexaminolevulinate (Hexvix®) guided cystoscopy in Non‑Muscle Invasive Bladder Cancer patients (NMIBC) in Italy

OBJECTIVE: To estimate the incremental cost‑effectiveness of hexaminolevulinate (Hexvix®) + Blue Light (H+BL) cystoscopy (compared to white light cystoscopy only) when used at initial transurethral resection of the bladder tumour (TURBT) for patients diagnosed with non‑muscle invasive bladder cancer (NMIBC) in Italy.METHODS: A cost‑effectiveness model has been developed to estimate the incremental cost‑effectiveness of introducing H+BL at initial TURBT for patients diagnosed with NMIBC in Italy. The model consists of two parts: 1) a short term decision tree which estimates the outcome of the initial diagnostic procedure, and 2) a Markov cohort model which is used to estimate long term outcomes through extrapolation based on data and assumptions about patient management, the natural history of the disease and the empirical efficacy of H+BL in improving diagnosis detection and reducing recurrence. Cost‑effectiveness results are expressed as incremental costs per QALY gained. Univariate and probabilistic sensitivity analyses are conducted to test the robustness of the model to changes in inputs and assumptions.RESULTS: Base case results suggest that Hexvix® is a dominant strategy when used in the resection of NMIBC. Hexvix® is expected to be associated with 0.070 incremental QALYs, with cost savings of € 435 per patient. Sensitivity analyses suggest that the cost of Hexvix® and the relative risk of recurrence in intermediate and low risk groups are key drivers in the model. Probabilistic analyses indicate that Hexvix® is expected to be cost‑effective in >99% of iterations, assuming a willingness to pay threshold of € 25,000 per QALY.CONCLUSION: In conclusion, Hexvix® is expected to be a cost‑effective strategy when used in the resection of NMIBC in Italy.

Diagnostic imaging to detect and evaluate response to therapy in bone metastases from prostate cancer: current modalities and new horizons

Different therapeutic options for the management of prostate cancer (PC) have been developed, and some are successful in providing crucial improvement in both survival and quality of life, especially in patients with metastatic castration-resistant PC. In this scenario, diverse combinations of radiopharmaceuticals (for targeting bone, cancer cells and receptors) and nuclear medicine modalities (e.g. bone scan, SPECT, SPECT/CT, PET and PET/CT) are now available for imaging bone metastases. Some radiopharmaceuticals are approved, currently available and used in the routine clinical setting, while others are not registered and are still under evaluation, and should therefore be considered experimental. On the other hand, radiologists have other tools, in addition to CT, that can better visualize bone localization and medullary involvement, such as multimodal MRI. In this review, the authors provide an overview of current management of advanced PC and discuss the choice of diagnostic modality for the detection of metastatic skeletal lesions in different phases of the disease. In addition to detection of bone metastases, the evaluation of response to therapy is another critical issue, since it remains one of the most important open questions that a multidisciplinary team faces when optimizing the management of PC. The authors emphasize the role of nuclear modalities that can presently be used in clinical practice, and also look at future perspectives based on relevant clinical data with novel radiopharmaceuticals

U-CHANGE Project: a multidimensional consensus on how clinicians, patients and caregivers may approach together the new urothelial cancer scenario

IntroductionAdvanced urothelial carcinoma remains aggressive and very hard to cure, while new treatments will pose a challenge for clinicians and healthcare funding policymakers alike. The U-CHANGE Project aimed to redesign the current model of care for advanced urothelial carcinoma patients to identify limitations (“as is” scenario) and recommend future actions (“to be” scenario).MethodsTwenty-three subject-matter experts, divided into three groups, analyzed the two scenarios as part of a multidimensional consensus process, developing statements for specific domains of the disease, and a simplified Delphi methodology was used to establish consensus among the experts.ResultsRecommended actions included increasing awareness of the disease, increased training of healthcare professionals, improvement of screening strategies and care pathways, increased support for patients and caregivers and relevant recommendations from molecular tumor boards when comprehensive genomic profiling has to be provided for appropriate patient selection to ad hoc targeted therapies.DiscussionWhile the innovative new targeted agents have the potential to significantly alter the clinical approach to this highly aggressive disease, the U-CHANGE Project experience shows that the use of these new agents will require a radical shift in the entire model of care, implementing sustainable changes which anticipate the benefits of future treatments, capable of targeting the right patient with the right agent at different stages of the disease

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions

Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS (N = 142,392) with gene expression measured in 45 tissues (N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are region

Genome-wide association study of classical Hodgkin lymphoma identifies key regulators of disease susceptibility

Several susceptibility loci for classical Hodgkin lymphoma (cHL) have been reported, however much of the heritable risk is unknown. Here, we perform a meta-analysis of two existing genome-wide association studies (GWAS), a new GWAS, and replication totalling 5,314 cases and 16,749 controls. We identify risk loci for all cHL at 6q22.33 (rs9482849, P=1.52 × 10-8) and for nodular sclerosis HL (NSHL) at 3q28 (rs4459895, P=9.43 × 10-17), 6q23.3 (rs6928977, P=4.62 × 10-55 11), 10p14 (rs3781093, P=9.49 × 10-13), 13q34 (rs112998813, P=4.58 × 10-8) and 16p13.13 (rs34972832, P=2.12 × 10-8). Additionally, independent loci within the HLA region are observed for NSHL (rs9269081, HLA-DPB1*03:01, Val86 in HLA-DRB1) and mixed cellularity HL (rs1633096, rs13196329, Val86 in HLA-DRB1). The new and established risk loci localise to areas of active chromatin and show an over-representation of transcription factor binding for determinants of B-cell development and immune response.In the United Kingdom, Bloodwise (LLR; 10021) provided principal funding for the study. Support from Cancer Research UK (C1298/A8362 supported by the Bobby Moore Fund) and the Lymphoma Research Trust is also acknowledged. A.S. is supported by a clinical fellowship from Cancer Research UK. For the UK-GWAS, sample and data acquisition were supported by Breast Cancer Now, the European Union and the Lymphoma Research Trust. The UK-GWAS made use of control genotyping data generated by the WTCCC. For further information, please visit the publishr's website

Partitioning the Heritability of Tourette Syndrome and Obsessive Compulsive Disorder Reveals Differences in Genetic Architecture

The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained