When no treatment is the best treatment: Active surveillance strategies for low risk prostate cancers

Although the incidence of prostate cancer is rising due to PSA screening and increased life expectancy, the metastatic potential of low-grade, organ-confined disease remains low. An increasing number of studies suggest that radical treatment in such cases confers little or no survival benefit at a significant cost to morbidity. Active surveillance is a promising management approach of such low-risk cancers: eligible patients are selected based on clinical and pathological findings at diagnosis and are regularly monitored with digital rectal examinations, PSA testing and biopsies. Treatment, however, is deferred until and unless there is evidence of disease progression. This is a key difference from watchful waiting, where treatment is avoided until and unless there are symptoms. The purpose of this work is to review the rationale and evidence behind active surveillance and to offer an overview of current active surveillance strategies and outcomes

Analysis of independent cohorts of outbred CFW mice reveals novel loci for behavioral and physiological traits and identifies factors determining reproducibility

Combining samples for genetic association is standard practice in human genetic analysis of complex traits, but is rarely undertaken in rodent genetics. Here, using 23 phenotypes and genotypes from two independent laboratories, we obtained a sample size of 3,076 commercially available outbred mice and identified 70 loci, more than double the number of loci identified in the component studies. Fine-mapping in the combined sample reduced the number of likely causal variants, with a median reduction in set size of 51%, and indicated novel gene associations, including Pnpo, Ttll6 and GM11545 with bone mineral density, and Psmb9 with weight. However replication at a nominal threshold of 0.05 between the two component studies was low, with less than a third of loci identified in one study replicated in the second. In addition to overestimates in the effect size in the discovery sample (Winner's Curse), we also found that heterogeneity between studies explained the poor replication, but the contribution of these two factors varied among traits. Leveraging these observations we integrated information about replication rates, study-specific heterogeneity, and Winner's Curse corrected estimates of power to assign variants to one of four confidence levels. Our approach addresses concerns about reproducibility, and demonstrates how to obtain robust results from mapping complex traits in any genome-wide association study

Origin of Cosmic Magnetic Fields

We propose that the overlapping shock fronts from young supernova remnants produce a locally unsteady, but globally steady large scale spiral shock front in spiral galaxies, where star formation and therefore massive star explosions correlate geometrically with spiral structure. This global shock front with its steep gradients in temperature, pressure and associated electric fields will produce drifts, which in turn give rise to a strong sheet-like electric current, we propose. This sheet current then produces a large scale magnetic field, which is regular, and connected to the overall spiral structure. This rejuvenates the overall magnetic field continuously, and also allows to understand that there is a regular field at all in disk galaxies. This proposal connects the existence of magnetic fields to accretion in disks. We not yet address all the symmetries of the magnetic field here; the picture proposed here is not complete. X-ray observations may be able to test it already.Comment: 18 pages, no figures; to be published in Proc. Palermo Meeting Sept. 2002, Eds. N. G. Sanchez et al., The Early Universe and the Cosmic Microwave Background: Theory and Observation

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

A Perspective of Preconception Health Activities in the United States

Objectives: Information regarding the type and scope of preconception care programs in the United States is scant. We evaluated State Title V measurement and indicator data and abstracts presented at the National Summit on Preconception Care (June 2005) in order to identify existing programs and innovative strategies for preconception health promotion. Methods: We used the web-based Title V Information System to identify state Performance Measures and Priority Needs pertaining to preconception health as reported for the 2005–2010 Needs Assessment Cycle. We also present a detailed summary of the abstracts presented at the National Summit on Preconception Care. Results: A total of 23 states reported a Priority Need that focused on preconception health and health care. Forty-two states and jurisdictions identified a Performance Measure associated with preconception health or a related indicator (e.g., folic acid, birth spacing, family planning, unintended pregnancy, and healthy weight). Nearly 60 abstracts pertaining to preconception care were presented at the National Summit and included topics such as research, programs, patient or provider toolkits, clinical practice strategies, and public policy. Conclusions: Strategies for improving preconception health have been incorporated into numerous programs throughout the United States. Widespread recognition of the benefits of preconception health promotion is evidenced by the number of states identifying related indicators