The growing amount of data in operational electronic health record (EHR) systems provides unprecedented opportunity for its re-use for many tasks, including comparative effectiveness research (CER). However, there are many caveats to the use of such data. EHR data from clinical settings may be inaccurate, incomplete, transformed in ways that undermine their meaning, unrecoverable for research, of unknown provenance, of insufficient granularity, and incompatible with research protocols. However, the quantity and real-world nature of these data provide impetus for their use, and we develop a list of caveats to inform would-be users of such data as well as provide an informatics roadmap that aims to insure this opportunity to augment CER can be best leveraged.

Purpose To describe social support for weight loss shared by members of a large Internet weight loss community. Methods We conducted a mixed-methods study with surveys (n = 193) and interviews (n = 13) of community members along with a content analysis of discussion forum messages (n = 1924 messages). Qualitative data were analyzed for social support themes. Results Survey respondents were primarily white (91.4%) and female (93.8%) with mean age 37.3 years and mean body mass index 30.9. They used forums frequently, with 56.8% reading messages, 36.1% replying to messages, and 18.5% posting messages to start a discussion related to weight loss on a daily or more frequent basis. Major social support themes were encouragement and motivation, mentioned at least once by 87.6% of survey respondents, followed by information (58.5%) and shared experiences (42.5%). Subthemes included testimonies, recognition for success, accountability, friendly competition, and humor. Members valued convenience, anonymity, and the non-judgmental interactions as unique characteristics of Internet-mediated support. Conclusion This Internet weight loss community plays a prominent role in participants’ weight loss efforts. Social support within Internet weight loss communities merits further evaluation as a weight loss resource for clinicians to recommend to patients. Understanding these communities could improve how health professionals evaluate, build, harness, and manipulate social support for weight loss.

Summary Whereas countless highly penetrant variants have been associated with Mendelian disorders, the genetic etiologies underlying complex diseases remain largely unresolved. Here, we examine the extent to which Mendelian variation contributes to complex disease risk by mining the medical records of over 110 million patients. We detect thousands of associations between Mendelian and complex diseases, revealing a non-degenerate, phenotypic code that links each complex disorder to a unique collection of Mendelian loci. Using genome-wide association results, we demonstrate that common variants associated with complex diseases are enriched in the genes indicated by this “Mendelian code.” Finally, we detect hundreds of comorbidity associations among Mendelian disorders, and we use probabilistic genetic modeling to demonstrate that Mendelian variants likely contribute non-additively to the risk for a subset of complex diseases. Overall, this study illustrates a complementary approach for mapping complex disease loci and provides unique predictions concerning the etiologies of specific diseases.

Objectives To determine the characteristics of popular breast cancer related websites and whether more popular sites are of higher quality. Design The search engine Google was used to generate a list of websites about breast cancer. Google ranks search results by measures of link popularity-the number of links to a site from other sites. The top 200 sites returned in response to the query "breast cancer" were divided into "more popular" and "less popular" subgroups by three different measures of link popularity: Google rank and number of links reported independently by Google and by AltaVista (another search engine). Main outcome measures Type and quality of content. Results More popular sites according to Google rank were more likely than less popular ones to contain information on ongoing clinical trials (27% v 12%, P = 0.01 ), results of trials (12% v 3%, P = 0.02), and opportunities for psychosocial adjustment (48% v 23%, P < 0.01). These characteristics were also associated with higher number of links as reported by Google and AltaVista. More popular sites by number of linking sites were also more likely to provide updates on other breast cancer research, information on legislation and advocacy, and a message board service. Measures of quality such as display of authorship, attribution or references, currency of information, and disclosure did not differ between groups. Conclusions Popularity of websites is associated with type rather than quality of content. Sites that include content correlated with popularity may best meet the public's desire for information about breast cancer.

Rapidly improving understanding of molecular oncology, emerging novel therapeutics, and increasingly available and affordable next-generation sequencing have created an opportunity for delivering genomically informed personalized cancer therapy. However, to implement genomically informed therapy requires that a clinician interpret the patient's molecular profile, including molecular characterization of the tumor and the patient's germline DNA. In this Commentary, we review existing data and tools for precision oncology and present a framework for reviewing the available biomedical literature on therapeutic implications of genomic alterations. Genomic alterations, including mutations, insertions/deletions, fusions, and copy number changes, need to be curated in terms of the likelihood that they alter the function of a "cancer gene" at the level of a specific variant in order to discriminate so-called "drivers" from "passengers." Alterations that are targetable either directly or indirectly with approved or investigational therapies are potentially "actionable." At this time, evidence linking predictive biomarkers to therapies is strong for only a few genomic markers in the context of specific cancer types. For these genomic alterations in other diseases and for other genomic alterations, the clinical data are either absent or insufficient to support routine clinical implementation of biomarker-based therapy. However, there is great interest in optimally matching patients to early-phase clinical trials. Thus, we need accessible, comprehensive, and frequently updated knowledge bases that describe genomic changes and their clinical implications, as well as continued education of clinicians and patients.

No abstract

different proportions of high risk pregnancies and parity, but using standard populations of primiparous women at low risk identified by the criteria described here could enable valid international comparisons of spontaneous preterm delivery rates to be made.Contributors: JL-R conceived the study in collaboration with UK. SR retrieved register data and performed the initial analyses. UK performed additional statistical analyses. All authors contributed to the data interpretation. JL-R wrote the first draft of the manuscript and all authors contributed to the revision. AbstractObjectives To determine the prevalence of false or misleading statements in messages posted by internet cancer support groups and whether these statements were identified as false or misleading and corrected by other participants in subsequent postings.

PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.