National Cancer Institute Biospecimen Evidence-Based Practices: Harmonizing Procedures for Nucleic Acid Extraction from Formalin-Fixed, Paraffin-Embedded Tissue

Variable and suboptimal biospecimen handling practices have been identified as impediments to biomarker discovery, including predictive biomarkers for oncology indicating a clear and present need for evidence-based, standardized practices. The United States and international efforts have been launched to better understand andmitigate variability during the preanalytical phase and decrease associated effects by promoting harmonization of procedures both within and across institutions. The Biorepositories and Biospecimen Research Branch (BBRB) of the United States National Cancer Institute (NCI) publishes best practice documents aimed at improving the quality of data generated from human biospecimens (https://biospecimens.cancer.gov/bestpractices/overview.asp) and sponsors research initiatives (https://biospecimens.cancer.gov/programs/default.asp) and the Biospecimen Research Database (BRD; http://biospecimens.cancer.gov/brd) to better understand thresholds and effects of individual preanalytical factors in biospecimen handling. The BRD allows users to query both a curated literature repository and standard operating procedure (SOP) library for a specific preservative, diagnosis, analyte, or preanalytical factor. The BRD incorporates information from international efforts, including those by the International Society for Biological and Environmental Repositories (ISBER) and the European Union-sponsored SPIDIA program (standardization and improvement of generic preanalytical tools and procedures for in vitro diagnostics; www.spidia.eu), among others

Changes in chronic medication adherence, costs, and health care use after a cancer diagnosis among low-income patients and the role of patient-centered medical homes

Background: Approximately 40% of patients with cancer also have another chronic medical condition. Patient-centered medical homes (PCMHs) have improved outcomes among patients with multiple chronic comorbidities. The authors first evaluated the impact of a cancer diagnosis on chronic medication adherence among patients with Medicaid coverage and, second, whether PCMHs influenced outcomes among patients with cancer. Methods: Using linked 2004 to 2010 North Carolina cancer registry and claims data, the authors included Medicaid enrollees who were diagnosed with breast, colorectal, or lung cancer who had hyperlipidemia, hypertension, and/or diabetes mellitus. Using difference-in-difference methods, the authors examined adherence to chronic disease medications as measured by the change in the percentage of days covered over time among patients with and without cancer. The authors then further evaluated whether PCMH enrollment modified the observed differences between those patients with and without cancer using a differences-in-differences-in-differences approach. The authors examined changes in health care expenditures and use as secondary outcomes. Results: Patients newly diagnosed with cancer who had hyperlipidemia experienced a 7-percentage point to 11-percentage point decrease in the percentage of days covered compared with patients without cancer. Patients with cancer also experienced significant increases in medical expenditures and hospitalizations compared with noncancer controls. Changes in medication adherence over time between patients with and without cancer were not determined to be statistically significantly different by PCMH status. Some PCMH patients with cancer experienced smaller increases in expenditures (diabetes) and emergency department use (hyperlipidemia) but larger increases in their inpatient hospitalization rates (hypertension) compared with non-PCMH patients with cancer relative to patients without cancer. Conclusions: PCMHs were not found to be associated with improvements in chronic disease medication adherence, but were associated with lower costs and emergency department visits among some low-income patients with cancer

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits

Dialysis initiation, modality choice, access, and prescription: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Globally, the number of patients undergoing maintenance dialysis is increasing, yet throughout the world there is significant variability in the practice of initiating dialysis. Factors such as availability of resources, reasons for starting dialysis, timing of dialysis initiation, patient education and preparedness, dialysis modality and access, as well as varied \u201ccountry-specific\u201d factors significantly affect patient experiences and outcomes. As the burden of end-stage kidney disease (ESKD) has increased globally, there has also been a growing recognition of the importance of patient involvement in determining the goals of care and decisions regarding treatment. In January 2018, KDIGO (Kidney Disease: Improving Global Outcomes) convened a Controversies Conference focused on dialysis initiation, including modality choice, access, and prescription. Here we present a summary of the conference discussions, including identified knowledge gaps, areas of controversy, and priorities for research. A major novel theme represented during the conference was the need to move away from a \u201cone-size-fits-all\u201d approach to dialysis and provide more individualized care that incorporates patient goals and preferences while still maintaining best practices for quality and safety. Identifying and including patient-centered goals that can be validated as quality indicators in the context of diverse health care systems to achieve equity of outcomes will require alignment of goals and incentives between patients, providers, regulators, and payers that will vary across health care jurisdictions

The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): Illuminating the Functional Diversity of Eukaryotic Life in the Oceans through Transcriptome Sequencing

Microbial ecology is plagued by problems of an abstract nature. Cell sizes are so small and population sizes so large that both are virtually incomprehensible. Niches are so far from our everyday experience as to make their very definition elusive. Organisms that may be abundant and critical to our survival are little understood, seldom described and/or cultured, and sometimes yet to be even seen. One way to confront these problems is to use data of an even more abstract nature: molecular sequence data. Massive environmental nucleic acid sequencing, such as metagenomics or metatranscriptomics, promises functional analysis of microbial communities as a whole, without prior knowledge of which organisms are in the environment or exactly how they are interacting. But sequence-based ecological studies nearly always use a comparative approach, and that requires relevant reference sequences, which are an extremely limited resource when it comes to microbial eukaryotes