Using mammographic density to predict breast cancer risk: dense area or percentage dense area.

INTRODUCTION: Mammographic density (MD) is one of the strongest risk factors for breast cancer. It is not clear whether this association is best expressed in terms of absolute dense area or percentage dense area (PDA). METHODS: We measured MD, including nondense area (here a surrogate for weight), in the mediolateral oblique (MLO) mammogram using a computer-assisted thresholding technique for 634 cases and 1,880 age-matched controls from the Cambridge and Norwich Breast Screening programs. Conditional logistic regression was used to estimate the risk of breast cancer, and fits of the models were compared using likelihood ratio tests and the Bayesian information criteria (BIC). All P values were two-sided. RESULTS: Square-root dense area was the best single predictor (for example, χ₁² = 53.2 versus 44.4 for PDA). Addition of PDA and/or square-root nondense area did not improve the fit (both P > 0.3). Addition of nondense area improved the fit of the model with PDA (χ₁² = 11.6; P < 0.001). According to the BIC, the PDA and nondense area model did not provide a better fit than the dense area alone model. The fitted values of the two models were highly correlated (r = 0.97). When a measure of body size is included with PDA, the predicted risk is almost identical to that from fitting dense area alone. CONCLUSIONS: As a single parameter, dense area provides more information than PDA on breast cancer risk

Can Reproductive Health Voucher Programs Improve Quality of Postnatal Care? A Quasi-Experimental Evaluation of Kenya’s Safe Motherhood Voucher Scheme

This study tests the group-level causal relationship between the expansion of Kenya’s Safe Motherhood voucher program and changes in quality of postnatal care (PNC) provided at voucher-contracted facilities. We compare facilities accredited since program inception in 2006 (phase I) and facilities accredited since 2010-2011 (phase II) relative to comparable non-voucher facilities. PNC quality is assessed using observed clinical content processes, as well as client-reported outcome measures. Two-tailed unpaired t-tests are used to identify differences in mean process quality scores and client-reported outcome measures, comparing changes between intervention and comparison groups at the 2010 and 2012 data collection periods. Difference-in-differences analysis is used to estimate the reproductive health (RH) voucher program’s causal effect on quality of care by exploiting group-level differences between voucher-accredited and non-accredited facilities in 2010 and 2012. Participation in the voucher scheme since 2006 significantly improves overall quality of postnatal care by 39% (p=0.02), where quality is defined as the observable processes or components of service provision that occur during a PNC consultation. Program participation since phase I is estimated to improve the quality of observed maternal postnatal care by 86% (p=0.02), with the largest quality improvements in counselling on family planning methods (IRR 5.0; p=0.01) and return to fertility (IRR 2.6; p=0.01). Despite improvements in maternal aspects of PNC, we find a high proportion of mothers who seek PNC are not being checked by any provider after delivery. Additional strategies will be necessary to standardize provision of packaged postnatal interventions to both mother and new-born. This study addresses an important gap in the existing RH literature by using a strong evaluation design to assess RH voucher program effectiveness on quality improvement

The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study.

We evaluated the association between short-term change in body mass index (BMI) and breast density during a 1 year weight-loss intervention (Manchester, UK). We included 65 premenopausal women (35-45 years, ≥7 kg adult weight gain, family history of breast cancer). BMI and breast density (semi-automated area-based, automated volume-based) were measured at baseline, 1 year, and 2 years after study entry (1 year post intervention). Cross-sectional (between-women) and short-term change (within-women) associations between BMI and breast density were measured using repeated-measures correlation coefficients and multivariable linear mixed models. BMI was positively correlated with dense volume between-women (r = 0.41, 95%CI: 0.17, 0.61), but less so within-women (r = 0.08, 95%CI: -0.16, 0.28). There was little association with dense area (between-women r = -0.12, 95%CI: -0.38, 0.16; within-women r = 0.01, 95%CI: -0.24, 0.25). BMI and breast fat were positively correlated (volume: between r = 0.77, 95%CI: 0.69, 0.84, within r = 0.58, 95%CI: 0.36, 0.75; area: between r = 0.74, 95%CI: 0.63, 0.82, within r = 0.45, 95%CI: 0.23, 0.63). Multivariable models reported similar associations. Exploratory analysis suggested associations between BMI gain from 20 years and density measures (standard deviation change per +5 kg/m2 BMI: dense area: +0.61 (95%CI: 0.12, 1.09); fat volume: -0.31 (95%CI: -0.62, 0.00)). Short-term BMI change is likely to be positively associated with breast fat, but we found little association with dense tissue, although power was limited by small sample size

Design of a combinatorial DNA microarray for protein-DNA interaction studies

BACKGROUND: Discovery of precise specificity of transcription factors is an important step on the way to understanding the complex mechanisms of gene regulation in eukaryotes. Recently, double-stranded protein-binding microarrays were developed as a potentially scalable approach to tackle transcription factor binding site identification. RESULTS: Here we present an algorithmic approach to experimental design of a microarray that allows for testing full specificity of a transcription factor binding to all possible DNA binding sites of a given length, with optimally efficient use of the array. This design is universal, works for any factor that binds a sequence motif and is not species-specific. Furthermore, simulation results show that data produced with the designed arrays is easier to analyze and would result in more precise identification of binding sites. CONCLUSION: In this study, we present a design of a double stranded DNA microarray for protein-DNA interaction studies and show that our algorithm allows optimally efficient use of the arrays for this purpose. We believe such a design will prove useful for transcription factor binding site identification and other biological problems

Cost of care for cancer patients in England: evidence from population-based patient-level data

background: Health systems are facing the challenge of providing care to an increasing population of patients with cancer. However, evidence on costs is limited due to the lack of large longitudinal databases. methods: We matched cost of care data to population-based, patient-level data on cancer patients in England. We conducted a retrospective cohort study including all patients age 18 and over with a diagnosis of colorectal (275 985 patients), breast (359 771), prostate (286 426) and lung cancer (283 940) in England between 2001 and 2010. Incidence costs, prevalence costs, and phase of care costs were estimated separately for patients age 18–64 and greater than or equal to65. Costs of care were compared by patients staging, before and after diagnosis, and with a comparison population without cancer. results: Incidence costs in the first year of diagnosis are noticeably higher in patients age 18–64 than age greater than or equal to65 across all examined cancers. A lower stage diagnosis is associated with larger cost savings for colorectal and breast cancer in both age groups. The additional costs of care because of the main four cancers amounts to £1.5 billion in 2010, namely 3.0% of the total cost of hospital care. conclusions: Population-based, patient-level data can be used to provide new evidence on the cost of cancer in England. Early diagnosis and cancer prevention have scope for achieving large cost savings for the health system

Vestibular Facilitation of Optic Flow Parsing

Simultaneous object motion and self-motion give rise to complex patterns of retinal image motion. In order to estimate object motion accurately, the brain must parse this complex retinal motion into self-motion and object motion components. Although this computational problem can be solved, in principle, through purely visual mechanisms, extra-retinal information that arises from the vestibular system during self-motion may also play an important role. Here we investigate whether combining vestibular and visual self-motion information improves the precision of object motion estimates. Subjects were asked to discriminate the direction of object motion in the presence of simultaneous self-motion, depicted either by visual cues alone (i.e. optic flow) or by combined visual/vestibular stimuli. We report a small but significant improvement in object motion discrimination thresholds with the addition of vestibular cues. This improvement was greatest for eccentric heading directions and negligible for forward movement, a finding that could reflect increased relative reliability of vestibular versus visual cues for eccentric heading directions. Overall, these results are consistent with the hypothesis that vestibular inputs can help parse retinal image motion into self-motion and object motion components

Neonatal-onset multisystem inflammatory disease responsive to interleukin-1 beta inhibition

BACKGROUND:Neonatal-onset multisystem inflammatory disease is characterized by fever, urticarial rash, aseptic meningitis, deforming arthropathy, hearing loss, and mental retardation. Many patients have mutations in the cold-induced autoinflammatory syndrome 1 (CIAS1) gene, encoding cryopyrin, a protein that regulates inflammation.METHODS:We selected 18 patients with neonatal-onset multisystem inflammatory disease (12 with identifiable CIAS1 mutations) to receive anakinra, an interleukin-1-receptor antagonist (1 to 2 mg per kilogram of body weight per day subcutaneously). In 11 patients, anakinra was withdrawn at three months until a flare occurred. The primary end points included changes in scores in a daily diary of symptoms, serum levels of amyloid A and C-reactive protein, and the erythrocyte sedimentation rate from baseline to month 3 and from month 3 until a disease flare.RESULTS:All 18 patients had a rapid response to anakinra, with disappearance of rash. Diary scores improved (P<0.001) and serum amyloid A (from a median of 174 mg to 8 mg per liter), C-reactive protein (from a median of 5.29 mg to 0.34 mg per deciliter), and the erythrocyte sedimentation rate decreased at month 3 (all P<0.001), and remained low at month 6. Magnetic resonance imaging showed improvement in cochlear and leptomeningeal lesions as compared with baseline. Withdrawal of anakinra uniformly resulted in relapse within days; retreatment led to rapid improvement. There were no drug-related serious adverse events.CONCLUSIONS:Daily injections of anakinra markedly improved clinical and laboratory manifestations in patients with neonatal-onset multisystem inflammatory disease, with or without CIAS1 mutations

Background risk of breast cancer and the association between physical activity and mammographic density

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Phase 2 Study of Pomalidomide (CC-4047) Monotherapy for Children and Young Adults With Recurrent or Progressive Primary Brain Tumors

INTRODUCTION: Treatment of recurrent primary pediatric brain tumors remains a major challenge, with most children succumbing to their disease. We conducted a prospective phase 2 study investigating the safety and efficacy of pomalidomide (POM) in children and young adults with recurrent and progressive primary brain tumors. BACKGROUND: METHODS: Patients with recurrent and progressive high-grade glioma (HGG), diffuse intrinsic pontine glioma (DIPG), ependymoma, or medulloblastoma received POM 2.6 mg/m2/day (the recommended phase 2 dose [RP2D]) on days 1-21 of a 28-day cycle. A Simon’s Optimal 2-stage design was used to determine efficacy. Primary endpoints included objective response (OR) and long-term stable disease (LTSD) rates. Secondary endpoints included duration of response, progression-free survival (PFS), overall survival (OS), and safety. RESULTS: 46 patients were evaluable for response (HGG, n = 19; DIPG, ependymoma, and medulloblastoma, n = 9 each). Two patients with HGG achieved OR or LTSD (10.5% [95% CI, 1.3%-33.1%]; 1 partial response and 1 LTSD) and 1 patient with ependymoma had LTSD (11.1% [95% CI, 0.3%-48.2%]). There were no ORs or LTSD in the DIPG or medulloblastoma cohorts. The median PFS for patients with HGG, DIPG, ependymoma, and medulloblastoma was 7.86, 11.29, 8.43, and 8.43 weeks, respectively. Median OS was 5.06, 3.78, 12.02, and 11.60 months, respectively. Neutropenia was the most common grade 3/4 adverse event. CONCLUSIONS: Treatment with POM monotherapy did not meet the primary measure of success in any cohort. Future studies are needed to evaluate if POM would show efficacy in tumors with specific molecular signatures or in combination with other anticancer agents. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier NCT03257631; EudraCT, identifier 2016-002903-25

Bridging Time Scales in Cellular Decision Making with a Stochastic Bistable Switch

Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.Comment: 14 pages, 4 figure