130 research outputs found

    Evaluating a multicomponent survivorship programme for men with prostate cancer in Australia: A single cohort study

    Get PDF
    Objective: To evaluate the implementation of a multicomponent survivorship programme for men with prostate cancer and their carers. Design: A single cohort study, guided by the RE-AIM framework. Setting: Multiple health services in Australia. Participants: Men with prostate cancer and their carers, and health professionals. Intervention: A 12-month telehealth programme that provided centralised and coordinated decision and information support, exercise and nutrition management, specialised clinical support and practical support to men and their carers. Data collection: Multiple sources of data including participant-reported health outcomes and experience of care, qualitative interviews, records of the programme were collected at different time points. Results: Reach: Of 394 eligible men at various stages of survivorship, 142 consented (36% consent rate) and 136 (96%) completed the programme. Adoption: All men participated in general care coordination and more than half participated in exercise and/or nutrition management interventions. Participation in the specialised support component (ie, psychosocial and sexual health support, continence management) was low despite the high level of need reported by men. Effectiveness: Overall, the men reported improvements in their experience of care. Implementation: Factors such as addressing service gaps, provision of specialised services, care coordination, adoption of needs-based and telehealth-based approaches were identified as enablers to the successful implementation of the programme. Issues such as insufficient integration with existing services, lack of resources and high caseload of the intervention team, men\u27s reluctance to discuss needs and lack of confidence with technology were barriers in implementing the programme. Conclusion: Survivorship interventions are relevant to men regardless of the stage of their disease and treatments undertaken. It is possible to provide access to a comprehensive model of survivorship care to promote the health and quality of life for men with prostate cancer. Trial registration number: This study was registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12617000174381)

    An integrated multicomponent care model for men affected by prostate cancer: A feasibility study of TrueNTH Australia

    Get PDF
    Objective: To evaluate the feasibility of implementing an integrated multicomponent survivorship care model for men affected by prostate cancer. Methods: Using a single arm prospective cohort study design, men with prostate cancer were recruited from two regional public hospitals in Australia for a 6-months program that provided information and decision support, exercise and nutrition management, specialised clinical support, and practical support through localised and central care coordination. Carers of the men were also invited to the program. Data were collected from multiple sources to evaluate: (1) recruitment capability and participant characteristics; (2) appropriateness and feasibility of delivering the specific intervention components using an electronic care management tool; and (3) suitability of data collection procedures and proposed outcome measures. Results: Of the 105 eligible men, 51 (consent rate 49%) participated in the program. Of the 31 carers nominated by the men, 13 consented (consent rate 42%). All carers and 50 (98%) men completed the program. Most (92%) men were newly diagnosed with localised prostate cancer. All men attended initial screening and assessment for supportive care needs; a total of 838 episodes of contact/consultation were made by the intervention team either in person (9%) or remotely (91%). The intervention was implemented as proposed with no adverse events. The proposed outcome measures and evaluation procedures were found to be appropriate. Conclusions: Our results support the feasibility of implementing this integrated multicomponent care model for men affected by prostate cancer

    Can chemical and molecular biomarkers help discriminate between industrial, rural and urban environments?

    Get PDF
    Abstract Air samples from four contrasting outdoor environments including a park, an arable farm, a waste water treatment plant and a composting facility were analysed during the summer and winter months. The aim of the research was to study the feasibility of differentiating microbial communities from urban, rural and industrial areas between seasons with chemical and molecular markers such as microbial volatile organic compounds (MVOCs) and phospholipid fatty acids (PLFAs). Air samples (3 l) were collected every 2 h for a total of 6 h in order to assess the temporal variations of MVOCs and PLFAs along the day. MVOCs and VOCs concentrations varied over the day, especially in the composting facility which was the site where more human activities were carried out. At this site, total VOC concentration varied between 80 and 170 μg m−3 in summer and 20–250 μg m−3 in winter. The composition of MVOCs varied between sites due to the different biological substrates including crops, waste water, green waste or grass. MVOCs composition also differed between seasons as in summer they are more likely to get modified by oxidation processes in the atmosphere and in winter by reduction processes. The composition of microbial communities identified by the analysis of PLFAs also varied among the different locations and between seasons. The location with higher concentrations of PLFAs in summer was the farm (7297 ng m−3) and in winter the park (11,724 ng m−3). A specific set of MVOCs and PLFAs that most represent each one of the locations was identified by principal component analyses (PCA) and canonical analyses. Further to this, concentrations of both total VOCs and PLFAs were at least three times higher in winter than in summer. The difference in concentrations between summer and winter suggest that seasonal variations should be considered when assessing the risk of exposure to these compounds

    Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

    Get PDF
    Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

    Germline variation at 8q24 and prostate cancer risk in men of European ancestry

    Get PDF
    Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

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

    Get PDF
    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 expert-curated database for benchmarking document similarity detection in biomedical literature search

    Get PDF
    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
    corecore