Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420).

BACKGROUND: Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a sub-sample, a Polygenic Risk Score (PRS). METHODS: Risk prediction was estimated primarily from self-reported questionnaires and mammographic density using the Tyrer-Cuzick risk model. Women eligible for NHSBSP were recruited. BC-Predict produced risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5-<8% 10-year) to have appointments to discuss prevention and additional screening. RESULTS: Overall uptake of BC-Predict in screening attendees was 16.9% with 2472 consenting to the study; 76.8% of those received risk feedback within the 8-week timeframe. Recruitment was 63.2% with an onsite recruiter and paper questionnaire compared to <10% with BC-Predict only (P < 0.0001). Risk appointment attendance was highest for those at high risk (40.6%); 77.5% of those opted for preventive medication. DISCUSSION: We have shown that a real-time offer of breast cancer risk information (including both mammographic density and PRS) is feasible and can be delivered in reasonable time, although uptake requires personal contact. Preventive medication uptake in women newly identified at high risk is high and could improve the cost-effectiveness of risk stratification. TRIAL REGISTRATION: Retrospectively registered with clinicaltrials.gov (NCT04359420).

What are the benefits and harms of risk stratified screening as part of the NHS breast screening Programme? Study protocol for a multi-site non-randomised comparison of BC-predict versus usual screening (NCT04359420).

BACKGROUND: In principle, risk-stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) should produce a better balance of benefits and harms. The main benefit is the offer of NICE-approved more frequent screening and/ or chemoprevention for women who are at increased risk, but are unaware of this. We have developed BC-Predict, to be offered to women when invited to NHSBSP which collects information on risk factors (self-reported information on family history and hormone-related factors via questionnaire; mammographic density; and in a sub-sample, Single Nucleotide Polymorphisms). BC-Predict produces risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5 to < 8% 10-year) to have discussion of prevention and early detection options at Family History, Risk and Prevention Clinics. Despite the promise of systems such as BC-Predict, there are still too many uncertainties for a fully-powered definitive trial to be appropriate or ethical. The present research aims to identify these key uncertainties regarding the feasibility of integrating BC-Predict into the NHSBSP. Key objectives of the present research are to quantify important potential benefits and harms, and identify key drivers of the relative cost-effectiveness of embedding BC-Predict into NHSBSP. METHODS: A non-randomised fully counterbalanced study design will be used, to include approximately equal numbers of women offered NHSBSP (n = 18,700) and BC-Predict (n = 18,700) from selected screening sites (n = 7). In the initial 8-month time period, women eligible for NHSBSP will be offered BC-Predict in four screening sites. Three screening sites will offer women usual NHSBSP. In the following 8-months the study sites offering usual NHSBSP switch to BC-Predict and vice versa. Key potential benefits including uptake of risk consultations, chemoprevention and additional screening will be obtained for both groups. Key potential harms such as increased anxiety will be obtained via self-report questionnaires, with embedded qualitative process analysis. A decision-analytic model-based cost-effectiveness analysis will identify the key uncertainties underpinning the relative cost-effectiveness of embedding BC-Predict into NHSBSP. DISCUSSION: We will assess the feasibility of integrating BC-Predict into the NHSBSP, and identify the main uncertainties for a definitive evaluation of the clinical and cost-effectiveness of BC-Predict. TRIAL REGISTRATION: Retrospectively registered with clinicaltrials.gov (NCT04359420).

Uncertainty quantification in modeling HIV viral mechanics.

We consider an in-host model for HIV-1 infection dynamics developed and validated with patient data in earlier work [7]. We revisit the earlier model in light of progress over the last several years in understanding HIV-1 progression in humans. We then consider statistical models to describe the data and use these with residual plots in generalized least squares problems to develop accurate descriptions of the proper weights for the data. We use recent parameter subset selection techniques [5,6] to investigate the impact of estimated parameters on the corresponding selection scores. Bootstrapping and asymptotic theory are compared in the context of confidence intervals for the resulting parameter estimates.

amoA Gene abundances and nitrification potential rates suggest that benthic ammonia-oxidizing bacteria and not Archaea dominate N cycling in the Colne Estuary, United Kingdom.

Nitrification, mediated by ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA), is important in global nitrogen cycling. In estuaries where gradients of salinity and ammonia concentrations occur, there may be differential selections for ammonia-oxidizer populations. The aim of this study was to examine the activity, abundance, and diversity of AOA and AOB in surface oxic sediments of a highly nutrified estuary that exhibits gradients of salinity and ammonium. AOB and AOA communities were investigated by measuring ammonia monooxygenase (amoA) gene abundance and nitrification potentials both spatially and temporally. Nitrification potentials differed along the estuary and over time, with the greatest nitrification potentials occurring mid-estuary (8.2 µmol N grams dry weight [gdw](-1) day(-1) in June, increasing to 37.4 µmol N gdw(-1) day(-1) in January). At the estuary head, the nitrification potential was 4.3 µmol N gdw(-1) day(-1) in June, increasing to 11.7 µmol N gdw(-1) day(-1) in January. At the estuary head and mouth, nitrification potentials fluctuated throughout the year. AOB amoA gene abundances were significantly greater (by 100-fold) than those of AOA both spatially and temporally. Nitrosomonas spp. were detected along the estuary by denaturing gradient gel electrophoresis (DGGE) band sequence analysis. In conclusion, AOB dominated over AOA in the estuarine sediments, with the ratio of AOB/AOA amoA gene abundance increasing from the upper (freshwater) to lower (marine) regions of the Colne estuary. These findings suggest that in this nutrified estuary, AOB (possibly Nitrosomonas spp.) were of major significance in nitrification.

Oncostatin M induced alpha1-antitrypsin (AAT) gene expression in Hep G2 cells is mediated by a 3' enhancer.

alpha(1)-Antitrypsin (AAT) is the major serine proteinase inhibitor (SERPIN A1) in human plasma. Its target proteinase is neutrophil elastase and its main physiological function is protection of the lower respiratory tract from the destructive effects of neutrophil elastase during an inflammatory response. Circulating levels of AAT rise 2-3-fold during inflammation and the liver produces most of this increase. The cytokines oncostatin M (OSM) and interleukin-6 have been shown to be mainly responsible for this effect, which is mediated via the interaction of cytokine-inducible transcription factors with regulatory elements within the gene. In the present study, we report for the first time that OSM stimulation of hepatocyte AAT occurs via an interaction between the hepatocyte promoter and an OSM-responsive element at the 3'-end of the AAT gene. This effect is mediated by the transcription factor signal transducer and activator of transcription 3 ('STAT 3') binding to an OSM-responsive element (sequence TTCTCTTAA), and this site is distinct from, but close to, a previously reported interleukin-6-responsive element.