Prediction of dynamic strains on a monopile offshore wind turbine using virtual sensors

The monitoring of the condition of the offshore wind turbine during its operational states offers the possibility of performing accurate assessments of the remaining life-time as well as supporting maintenance decisions during its entire life. The efficacy of structural monitoring in the case of the offshore wind turbine, though, is undermined by the practical limitations connected to the measurement system in terms of cost, weight and feasibility of sensor mounting (e.g. at muddline level 30m below the water level). This limitation is overcome by reconstructing the full-field response of the structure based on the limited number of measured accelerations and a calibrated Finite Element Model of the system. A modal decomposition and expansion approach is used for reconstructing the responses at all degrees of freedom of the finite element model. The paper will demonstrate the possibility to predict dynamic strains from acceleration measurements based on the aforementioned methodology. These virtual dynamic strains will then be evaluated and validated based on actual strain measurements obtained from a monitoring campaign on an offshore Vestas V90 3 MW wind turbine on a monopile foundation

A first step towards a global nomogram to predict disease progression for men on active surveillance

Background: Signs of disease progression (28%) and conversion to active treatment without evidence of disease progression (13%) are the main reasons for discontinuation of active surveillance (AS) in men with localised prostate cancer (PCa). We aimed to develop a nomogram to predict disease progression in these patients. Methods: As a first step in the development of a nomogram, using data from Movembers' GAP3 Consortium (n=14,380), we assessed heterogeneity between centres in terms of risk of disease progression. We started with assessment of baseline hazards for disease progression based on grouping of centres according to follow-up protocols [high: yearly; intermediate: similar to 2 yearly; and low: at year 1, 4 & 7 (i.e., PRIAS)]. We conducted cause-specific random effect Cox proportional hazards regression to estimate risk of disease progression by centre in each group. Results: Disease progression rates varied substantially between centres [median hazard ratio (MHR): 2.5]. After adjustment for various clinical factors (age, year of diagnosis, Gleason grade group, number of positive cores and PSA), substantial heterogeneity in disease progression remained between centres. Conclusions: When combining worldwide data on AS, we noted unexplained differences of disease progression rate even after adjustment for various clinical factors. This suggests that when developing a global nomogram, local adjustments for differences in risk of disease progression and competing outcomes such as conversion to active treatment need to be considered.Peer reviewe

Serum Calcium and the Risk of Breast Cancer: Findings from the Swedish AMORIS Study and a Meta-Analysis of Prospective Studies

To investigate the association between serum calcium and risk of breast cancer using a large cohort and a systematic review with meta-analysis. From the Swedish Apolipoprotein Mortality Risk (AMORIS) Study we included 229,674 women who had baseline measurements of serum total calcium and albumin. Multivariable Cox regression was used to assess the association between total and albumin-corrected calcium and breast cancer risk. For the systematic review, an electronic search of MEDLINE and EMBASE databases was performed to identify other prospective cohorts assessing the relationship between serum calcium and breast cancer risk. We pooled the results of our AMORIS cohort with other eligible studies in a meta-analysis using a random effects model. I² test was used to assess heterogeneity. In the AMORIS study, 10,863 women were diagnosed with breast cancer (mean follow-up: 19 years). We found an inverse association between total serum calcium and breast cancer when comparing the fourth quartile to the first quartile (HR: 0.94, 95% CI: 0.88-0.99, p value for trend 0.04) and similar results using albumin-corrected calcium. In the systematic review, we identified another two prospective cohorts evaluating pre-diagnostic serum total calcium and breast cancer. Combining these studies and our findings in AMORIS in a meta-analysis showed a protective effect of serum calcium against breast cancer, with a summary RR of 0.80 (95% CI: 0.66-0.97). No substantial heterogeneity was observed. Our findings in AMORIS and the meta-analysis support an inverse association between serum calcium and breast cancer risk, which warrants mechanistic investigations

Toward an MRI-based nomogram for the prediction of transperineal prostate biopsy outcome: A physician and patient decision tool

PURPOSE: To develop and internally validate a nomogram using biparametric magnetic resonance imaging (B-MRI)-derived variables for the prediction of prostate cancer at transperineal sector-guided prostate biopsy (TPSB). SUBJECTS/PATIENTS AND METHODS: Consecutive patients referred to our institution with raised prostate-specific antigen (PSA), abnormal prostate examination, or persistent suspicion of prostate cancer after previous transrectal biopsy between July 2012 and November 2015 were reviewed from a prospective database. All patients underwent prebiopsy B-MRI with T2-weighted and diffusion-weighted imaging sequences, followed by 24 to 40 core TPSB with additional targeted cores using cognitive registration. Univariable and multivariable logistic regression analysis was used to determine predictors of prostate cancer outcomes. Multivariable coefficients were used to construct 2 MRI-based nomograms to predict any and significant (Gleason 4 or maximum cancer core length ≥6mm) prostate cancer at TPSB. Bootstrap resamples were used for internal validation. Accuracy was assessed by calculating the concordance index. RESULTS: In total, 615 men were included in the study. Prostate cancer was diagnosed in 317 (51.5%) men with significant cancer diagnosed in 237 (38.5%) men. Age, Prostate Imaging Reporting and Data System (PI-RADS) score, PSA, PSA density, and primary biopsy were predictors of prostate cancer at TPSB on univariable analysis (P<0.0001). PSA showed strong correlation with PSA density and was excluded. The remaining variables were all independent predictors of prostate cancer on multivariable analysis (P<0.0001) and used to generate the nomograms. Both nomograms showed good discrimination for prostate cancer, with a concordance index of 87% for any cancer and 92% for significant disease. Using a nomogram-derived probability threshold of<15%, 111 (18.0%) biopsies can be saved, at the expense of 3 missed significant prostate cancers. CONCLUSIONS: These internally validated MR-based nomograms were able to accurately predict TPSB outcomes for prostate cancer, especially significant disease. Our findings support the combination of prebiopsy MRI results and clinical factors as part of the biopsy decision-making process

PCASTt/SPCG-17-a randomised trial of active surveillance in prostate cancer : rationale and design

Introduction Overtreatment of localised prostate cancer is substantial despite increased use of active surveillance. No randomised trials help define how to monitor patients or when to initiate treatment with curative intent. Methods and analysis A randomised, multicentre, intervention trial designed to evaluate the safety of an MRI-based active surveillance protocol, with standardised triggers for repeated biopsies and radical treatment. The aim is to reduce overtreatment of prostate cancer. 2000 men will be randomly allocated to either surveillance according to current practice or to standardised triggers at centres in Sweden, Norway, Finland and the UK. Men diagnosed in the past 12 months with prostate cancer, 0.2ng/mL/cc, any International Society of Urological Pathology (ISUP) grade 1 are eligible. Men with ISUP grade 2 in Ethics and dissemination Ethical approval was obtained in each participating country. Results for the primary and secondary outcome measures will be submitted for publication in peer-reviewed journals. Trial registration number NCT02914873.Peer reviewe

A latent class model for competing risks

Survival data analysis becomes complex when the proportional hazards assumption is violated at population level or when crude hazard rates are no longer estimators of marginal ones. We develop a Bayesian survival analysis method to deal with these situations, on the basis of assuming that the complexities are induced by latent cohort or disease heterogeneity that is not captured by covariates and that proportional hazards hold at the level of individuals. This leads to a description from which risk-specific marginal hazard rates and survival functions are fully accessible, 'decontaminated' of the effects of informative censoring, and which includes Cox, random effects and latent class models as special cases. Simulated data confirm that our approach can map a cohort's substructure and remove heterogeneity-induced informative censoring effects. Application to data from the Uppsala Longitudinal Study of Adult Men cohort leads to plausible alternative explanations for previous counter-intuitive inferences on prostate cancer. The importance of managing cardiovascular disease as a comorbidity in women diagnosed with breast cancer is suggested on application to data from the Swedish Apolipoprotein Mortality Risk Study. Copyright © 2017 John Wiley & Sons, Ltd