Story 1-2 Orlo Miller Interview

Sir Adam Beck was both one of the most respected—and one of the most hated—figures of his time, as this story about his funeral procession shows

Story 7-2 Frazer Davidson Interview

A small pane of leaded glass finds its way home

Comparative Effectiveness Research: Challenges for Medical Journals

Editors from a number of medical journals lay out principles for journals considering publication of Comparative Effectiveness Research (CER). In order to encourage dissemination of this editorial, this article is freely available in PLoS Medicine and will be also published in Medical Decision Making, Croatian Medical Journal, The Cochrane Library, Trials, The American Journal of Managed Care, and Journal of Clinical Epidemiology

Advancing the field of health systems research synthesis.

Those planning, managing and working in health systems worldwide routinely need to make decisions regarding strategies to improve health care and promote equity. Systematic reviews of different kinds can be of great help to these decision-makers, providing actionable evidence at every step in the decision-making process. Although there is growing recognition of the importance of systematic reviews to inform both policy decisions and produce guidance for health systems, a number of important methodological and evidence uptake challenges remain and better coordination of existing initiatives is needed. The Alliance for Health Policy and Systems Research, housed within the World Health Organization, convened an Advisory Group on Health Systems Research (HSR) Synthesis to bring together different stakeholders interested in HSR synthesis and its use in decision-making processes. We describe the rationale of the Advisory Group and the six areas of its work and reflects on its role in advancing the field of HSR synthesis. We argue in favour of greater cross-institutional collaborations, as well as capacity strengthening in low- and middle-income countries, to advance the science and practice of health systems research synthesis. We advocate for the integration of quasi-experimental study designs in reviews of effectiveness of health systems intervention and reforms. The Advisory Group also recommends adopting priority-setting approaches for HSR synthesis and increasing the use of findings from systematic reviews in health policy and decision-making

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer

BACKGROUND: Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs. METHODS: All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki672wk). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. FINDINGS: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki672wk (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki672wk. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. INTERPRETATION: Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse