Evaluation of person-level heterogeneity of treatment effects in published multiperson N-of-1 studies: systematic review and reanalysis.

OBJECTIVE:Individual patients with the same condition may respond differently to similar treatments. Our aim is to summarise the reporting of person-level heterogeneity of treatment effects (HTE) in multiperson N-of-1 studies and to examine the evidence for person-level HTE through reanalysis. STUDY DESIGN:Systematic review and reanalysis of multiperson N-of-1 studies. DATA SOURCES:Medline, Cochrane Controlled Trials, EMBASE, Web of Science and review of references through August 2017 for N-of-1 studies published in English. STUDY SELECTION:N-of-1 studies of pharmacological interventions with at least two subjects. DATA SYNTHESIS:Citation screening and data extractions were performed in duplicate. We performed statistical reanalysis testing for person-level HTE on all studies presenting person-level data. RESULTS:We identified 62 multiperson N-of-1 studies with at least two subjects. Statistical tests examining HTE were described in only 13 (21%), of which only two (3%) tested person-level HTE. Only 25 studies (40%) provided person-level data sufficient to reanalyse person-level HTE. Reanalysis using a fixed effect linear model identified statistically significant person-level HTE in 8 of the 13 studies (62%) reporting person-level treatment effects and in 8 of the 14 studies (57%) reporting person-level outcomes. CONCLUSIONS:Our analysis suggests that person-level HTE is common and often substantial. Reviewed studies had incomplete information on person-level treatment effects and their variation. Improved assessment and reporting of person-level treatment effects in multiperson N-of-1 studies are needed

The Validity of Peer Review in a General Medicine Journal

All the opinions in this article are those of the authors and should not be construed to reflect, in any way, those of the Department of Veterans Affairs

Serotonin and Depression: A Disconnect between the Advertisements and the Scientific Literature

Many ads for SSRI antidepressants claim that the drugs boost brain serotonin levels. Lacasse and Leo argue there is little scientific evidence to support this claim

Levitated micro-accelerometer.

The objective is a significant advancement in the state-of-the-art of accelerometer design for tactical grade (or better) applications. The design goals are <1 milli-G bias stability across environments and $200 cost. This quantum leap in performance improvement and cost reduction can only be achieved by a radical new approach, not incremental improvements to existing concepts. This novel levitated closed-loop accelerometer is implemented as a hybrid micromachine. The hybrid approach frees the designer from the limitations of any given monolithic process and dramatically expands the available design space. The design can be tailored to the dynamic range, resolution, bandwidth, and environmental requirements of the application while still preserving all of the benefits of monolithic MEMS fabrication - extreme precision, small size, low cost, and low power. An accelerometer was designed and prototype hardware was built, driving the successful development and refinement of several 'never been done before' fabrication processes. Many of these process developments are commercially valuable and are key enablers for the realization of a wide variety of useful micro-devices. While controlled levitation of a proof mass has yet to be realized, the overall design concept remains sound. This was clearly demonstrated by the stable and reliable closed-loop control of a proof mass at the test structure level. Furthermore, the hybrid MEMS implementation is the most promising approach for achieving the ambitious cost and performance targets. It is strongly recommended that Sandia remain committed to the original goal

Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer

PURPOSE: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS: The American Association of Physicists in Medicine\u27s Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders\u27 collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS: We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS: O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive real-world data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets

The Diploid Genome Sequence of an Individual Human

Presented here is a genome sequence of an individual human. It was produced from ∼32 million random DNA fragments, sequenced by Sanger dideoxy technology and assembled into 4,528 scaffolds, comprising 2,810 million bases (Mb) of contiguous sequence with approximately 7.5-fold coverage for any given region. We developed a modified version of the Celera assembler to facilitate the identification and comparison of alternate alleles within this individual diploid genome. Comparison of this genome and the National Center for Biotechnology Information human reference assembly revealed more than 4.1 million DNA variants, encompassing 12.3 Mb. These variants (of which 1,288,319 were novel) included 3,213,401 single nucleotide polymorphisms (SNPs), 53,823 block substitutions (2–206 bp), 292,102 heterozygous insertion/deletion events (indels)(1–571 bp), 559,473 homozygous indels (1–82,711 bp), 90 inversions, as well as numerous segmental duplications and copy number variation regions. Non-SNP DNA variation accounts for 22% of all events identified in the donor, however they involve 74% of all variant bases. This suggests an important role for non-SNP genetic alterations in defining the diploid genome structure. Moreover, 44% of genes were heterozygous for one or more variants. Using a novel haplotype assembly strategy, we were able to span 1.5 Gb of genome sequence in segments >200 kb, providing further precision to the diploid nature of the genome. These data depict a definitive molecular portrait of a diploid human genome that provides a starting point for future genome comparisons and enables an era of individualized genomic information