Genomic profiling using the UltraSEEK panel identifies discordancy between paired primary and breast cancer brain metastases and an association with brain metastasis-free survival.

PURPOSE: Brain metastases (BM) are an increasing clinical problem. This study aimed to assess paired primary breast cancers (BC) and BM for aberrations within TP53, PIK3CA, ESR1, ERBB2 and AKT utilising the MassARRAY® UltraSEEK® technology (Agena Bioscience, San Diego, USA). METHODS: DNA isolated from 32 paired primary BCs and BMs was screened using the custom UltraSEEK® Breast Cancer Panel. Data acquisition and analysis was performed by the Agena Bioscience Typer software v4.0.26.74. RESULTS: Mutations were identified in 91% primary BCs and 88% BM cases. TP53, AKT1, ESR1, PIK3CA and ERBB2 genes were mutated in 68.8%, 37.5%, 31.3%, 28.1% and 3.1% respectively of primary BCs and in 59.4%, 37.5%, 28.1%, 28.1% and 3.1% respectively of BMs. Differences in the mutations within the 5 genes between BC and paired BM were identified in 62.5% of paired cases. In primary BCs, ER-positive/HER2-negative cases harboured the most mutations (70%), followed by ER-positive/HER2-positive (15%) and triple-negatives (13.4%), whereas in BMs, the highest number of mutations was observed in triple-negative (52.5%), followed by ER-positive/HER2-negative (35.6%) and ER-negative/HER2-positive (12%). There was a significant association between the number of mutations in the primary BC and breast-to-brain metastasis-free survival (p = 0.0001) but not with overall survival (p = 0.056). CONCLUSION: These data demonstrate the discordancy between primary BC and BM, as well as the presence of clinically important, actionable mutations in BCBM. The UltraSEEK® Breast Cancer Panel provides a tool for BCBM that can be utilised to direct more tailored treatment decisions and for clinical studies investigating targeted agents.

Multilevel growth curve models that incorporate a random coefficient model for the level 1 variance function.

Aim To present a flexible model for repeated measures longitudinal growth data within individuals that allows trends over time to incorporate individual-specific random effects. These may reflect the timing of growth events and characterise within-individual variability which can be modelled as a function of age. Subjects and methods A Bayesian model is developed that includes random effects for the mean growth function, an individual age-alignment random effect and random effects for the within-individual variance function. This model is applied to data on boys' heights from the Edinburgh longitudinal growth study and to repeated weight measurements of a sample of pregnant women in the Avon Longitudinal Study of Parents and Children cohort. Results The mean age at which the growth curves for individual boys are aligned is 11.4 years, corresponding to the mean 'take off' age for pubertal growth. The within-individual variance (standard deviation) is found to decrease from 0.24 cm2 (0.50 cm) at 9 years for the 'average' boy to 0.07 cm2 (0.25 cm) at 16 years. Change in weight during pregnancy can be characterised by regression splines with random effects that include a large woman-specific random effect for the within-individual variation, which is also correlated with overall weight and weight gain. Conclusions The proposed model provides a useful extension to existing approaches, allowing considerable flexibility in describing within- and between-individual differences in growth patterns.

Impact and cost-effectiveness of a universal strategy to promote physical activity in primary care: population-based cohort study and Markov model.

BACKGROUND: This study aimed to estimate the cost-effectiveness of a universal strategy to promote physical activity in primary care. METHODS: Data were analysed for a cohort of participants from the general practice research database. Empirical estimates informed a Markov model that included five long-term conditions (diabetes, coronary heart disease, stroke, colorectal cancer and depression). Simulations compared an intervention promoting physical activity in healthy adults with standard care. The intervention effect on physical activity was from a meta-analysis of randomised trials. The annual cost of intervention, in the base case, was one family practice consultation per participant year. The primary outcome was net health benefit in quality adjusted life years (QALYs). RESULTS: A cohort of 262,704 healthy participants entered the model. Intervention was associated with an increase in life years lived free from physical disease. With 5 years intervention the increase was 52 (95 % interval -11 to 115) per 1,000 participants entering the model (probability increased 91.9 %); with 10 years intervention the increase was 102 (42-164) per 1,000 (probability 99.7 %). Net health benefits at a threshold of £30,000 per QALY were 3.2 (-11.1 to 16.9) QALYs per 1,000 participants with 5 years intervention (probability cost-effective 64.7 %) and 5.0 (-9.5 to 19.3) with 10 years intervention (probability cost-effective 72.4 %). CONCLUSIONS: A universal strategy to promote physical activity in primary care has the potential to increase life years lived free from physical disease. There is only weak evidence that a universal intervention strategy might prove cost-effective.