Bayesian model comparison with un-normalised likelihoods

Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalizing constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and network analysis. However, Bayesian analysis of these models using standard Monte Carlo methods is not possible due to the intractability of their likelihood functions. Several methods that permit exact, or close to exact, simulation from the posterior distribution have recently been developed. However, estimating the evidence and Bayes’ factors for these models remains challenging in general. This paper describes new random weight importance sampling and sequential Monte Carlo methods for estimating BFs that use simulation to circumvent the evaluation of the intractable likelihood, and compares them to existing methods. In some cases we observe an advantage in the use of biased weight estimates. An initial investigation into the theoretical and empirical properties of this class of methods is presented. Some support for the use of biased estimates is presented, but we advocate caution in the use of such estimates

Efficient importance sampling in low dimensions using affine arithmetic

Despite the development of sophisticated techniques such as sequential Monte Carlo, importance sampling (IS) remains an important Monte Carlo method for low dimensional target distributions. This paper describes a new technique for constructing proposal distributions for IS, using affine arithmetic. This work builds on the Moore rejection sampler to which we provide a comparison

ESR1 gene promoter region methylation in free circulating DNA and its correlation with estrogen receptor protein expression in tumor tissue in breast cancer patients

[Background] Tumor expression of estrogen receptor (ER) is an important marker of prognosis, and is predictive of response to endocrine therapy in breast cancer. Several studies have observed that epigenetic events, such methylation of cytosines and deacetylation of histones, are involved in the complex mechanisms that regulate promoter transcription. However, the exact interplay of these factors in transcription activity is not well understood. In this study, we explored the relationship between ER expression status in tumor tissue samples and the methylation of the 5′ CpG promoter region of the estrogen receptor gene (ESR1) isolated from free circulating DNA (fcDNA) in plasma samples from breast cancer patients. [Methods] Patients (n = 110) with non-metastatic breast cancer had analyses performed of ER expression (luminal phenotype in tumor tissue, by immunohistochemistry method), and the ESR1-DNA methylation status (fcDNA in plasma, by quantitative methylation specific PCR technique). [Results] Our results showed a significant association between presence of methylated ESR1 in patients with breast cancer and ER negative status in the tumor tissue (p = 0.0179). There was a trend towards a higher probability of ESR1-methylation in those phenotypes with poor prognosis i.e. 80% of triple negative patients, 60% of HER2 patients, compared to 28% and 5.9% of patients with better prognosis such as luminal A and luminal B, respectively. [Conclusion] Silencing, by methylation, of the promoter region of the ESR1 affects the expression of the estrogen receptor protein in tumors of breast cancer patients; high methylation of ESR1-DNA is associated with estrogen receptor negative status which, in turn, may be implicated in the patient’s resistance to hormonal treatment in breast cancer. As such, epigenetic markers in plasma may be of interest as new targets for anticancer therapy, especially with respect to endocrine treatment.The study was funded, in part, by a grant from the Ministerio de Educación y Ciencia (CICYT: SAF 2004–00889)

Bayesian Computation with Intractable Likelihoods

This article surveys computational methods for posterior inference with intractable likelihoods, that is where the likelihood function is unavailable in closed form, or where evaluation of the likelihood is infeasible. We review recent developments in pseudo-marginal methods, approximate Bayesian computation (ABC), the exchange algorithm, thermodynamic integration, and composite likelihood, paying particular attention to advancements in scalability for large datasets. We also mention R and MATLAB source code for implementations of these algorithms, where they are available.Comment: arXiv admin note: text overlap with arXiv:1503.0806

Trends in incidence, mortality and survival in women with breast cancer from 1985 to 2012 in Granada, Spain: a population-based study

The incidence of breast cancer has increased since the 1970s. Despite favorable trends in prognosis, the role of changes in clinical practice and the introduction of screening remain controversial. We examined breast cancer trends to shed light on their determinants Overall, age-adjusted (European Standard Population) incidence rates increased from 48.0 cases × 100,000 women in 1985–1989 to 83.4 in 2008–2012, with an annual percentage change (APC) of 2.5% (95%CI, 2.1–2.9) for 1985–2012. The greatest increase was in women younger than 40 years (APC 3.5, 95%CI, 2.4–4.8). For 2000–2012 the incidence trend increased only for stage I tumors (APC 3.8, 95%CI, 1.9–5.8). Overall age-adjusted breast cancer mortality decreased (APC − 1, 95%CI, − 1.4 – − 0.5), as did mortality in the 50–69 year age group (APC − 1.3, 95%CI, − 2.2 – − 0.4). Age-standardized net survival increased from 67.5% at 5 years in 1985–1989 to 83.7% in 2010–2012. All age groups younger than 70 years showed a similar evolution. Five-year net survival rates were 96.6% for patients with tumors diagnosed in stage I, 88.2% for stage II, 62.5% for stage III and 23.3% for stage IV. Breast cancer incidence is increasing – a reflection of the evolution of risk factors and increasing diagnostic pressure. After screening was introduced, the incidence of stage I tumors increased, with no decrease in the incidence of more advanced stages. Reductions were seen for overall mortality and mortality in the 50–69 year age group, but no changes were found after screening implementation. Survival trends have evolved favorably except for the 70–84 year age group and for metastatic tumors.This study was supported by a grant from the Acción Estratégica en Salud plan for the High Resolution Project on Prognosis and Care of Cancer Patients (No. AC14/00036) awarded by the Spanish Ministry of Economy and Competitiveness and co-funded by the European Regional Development Fund (ERDF)

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

20-Year Risks of Breast-Cancer Recurrence after Stopping Endocrine Therapy at 5 Years

The administration of endocrine therapy for 5 years substantially reduces recurrence rates during and after treatment in women with early-stage, estrogen-receptor (ER)-positive breast cancer. Extending such therapy beyond 5 years offers further protection but has additional side effects. Obtaining data on the absolute risk of subsequent distant recurrence if therapy stops at 5 years could help determine whether to extend treatment

Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials

Background Neoadjuvant chemotherapy (NACT) for early breast cancer can make breast-conserving surgery more feasible and might be more likely to eradicate micrometastatic disease than might the same chemotherapy given after surgery. We investigated the long-term benefits and risks of NACT and the influence of tumour characteristics on outcome with a collaborative meta-analysis of individual patient data from relevant randomised trials. Methods We obtained information about prerandomisation tumour characteristics, clinical tumour response, surgery, recurrence, and mortality for 4756 women in ten randomised trials in early breast cancer that began before 2005 and compared NACT with the same chemotherapy given postoperatively. Primary outcomes were tumour response, extent of local therapy, local and distant recurrence, breast cancer death, and overall mortality. Analyses by intention-to-treat used standard regression (for response and frequency of breast-conserving therapy) and log-rank methods (for recurrence and mortality). Findings Patients entered the trials from 1983 to 2002 and median follow-up was 9 years (IQR 5–14), with the last follow-up in 2013. Most chemotherapy was anthracycline based (3838 [81%] of 4756 women). More than two thirds (1349 [69%] of 1947) of women allocated NACT had a complete or partial clinical response. Patients allocated NACT had an increased frequency of breast-conserving therapy (1504 [65%] of 2320 treated with NACT vs 1135 [49%] of 2318 treated with adjuvant chemotherapy). NACT was associated with more frequent local recurrence than was adjuvant chemotherapy: the 15 year local recurrence was 21·4% for NACT versus 15·9% for adjuvant chemotherapy (5·5% increase [95% CI 2·4–8·6]; rate ratio 1·37 [95% CI 1·17–1·61]; p=0·0001). No significant difference between NACT and adjuvant chemotherapy was noted for distant recurrence (15 year risk 38·2% for NACT vs 38·0% for adjuvant chemotherapy; rate ratio 1·02 [95% CI 0·92–1·14]; p=0·66), breast cancer mortality (34·4% vs 33·7%; 1·06 [0·95–1·18]; p=0·31), or death from any cause (40·9% vs 41·2%; 1·04 [0·94–1·15]; p=0·45). Interpretation Tumours downsized by NACT might have higher local recurrence after breast-conserving therapy than might tumours of the same dimensions in women who have not received NACT. Strategies to mitigate the increased local recurrence after breast-conserving therapy in tumours downsized by NACT should be considered—eg, careful tumour localisation, detailed pathological assessment, and appropriate radiotherapy