Rationality versus reality: the challenges of evidence-based decision making for health policy makers

<p>Abstract</p> <p>Background</p> <p>Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process.</p> <p>Discussion</p> <p>We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence.</p> <p>Summary</p> <p>In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved.</p

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

The bioenergetics of inflammation: insights into obesity and type 2 diabetes

Diabetes mellitus is one of the most common chronic metabolic disorders worldwide, and its incidence in Asian countries is alarmingly high. Type 2 diabetes (T2DM) is closely associated with obesity, and the staggering rise in obesity is one of the primary factors related to the increased frequency of T2DM. Low-grade chronic inflammation is also accepted as an integral metabolic adaption in obesity and T2DM, and is believed to be a major player in the onset of insulin resistance. However, the exact mechanism(s) that cause a persistent chronic low-grade infiltration of leukocytes into insulin-target tissues such as adipose, skeletal muscle and liver are not entirely known. Recent developments in the understanding of leukocyte metabolism have revealed that the inflammatory polarization of immune cells, and consequently their immunological function, are strongly connected to their metabolic profile. Therefore, it is hypothesized that dysfunctional immune cell metabolism is a central cellular mechanism that prevents the resolution of inflammation in chronic metabolic conditions such as that observed in obesity and T2DM. The purpose of this review is to explore the metabolic demands of different immune cell types, and identify the molecular switches that control immune cell metabolism and ultimately function. Understanding of these concepts may allow the development of interventions that can correct immune function and may possibly decrease chronic low-grade inflammation in humans suffering from obesity and T2DM. We also review the latest clinical techniques used to measure metabolic flux in primary leukocytes isolated from obese and T2DM patients.European Journal of Clinical Nutrition advance online publication, 12 April 2017; doi:10.1038/ejcn.2017.45