Reporting of prognostic studies of tumour markers: a review of published articles in relation to REMARK guidelines

Background: Poor reporting compromises the reliability and clinical value of prognostic tumour marker studies. We review articles to assess the reporting of patients and events using REMARK guidelines, at the time of guideline publication. Methods: We sampled 50 prognostic tumour marker studies from higher impact cancer journals between 2006 and 2007. The inclusion criteria were cancer; focus on single biological tumour marker; survival analysis; multivariable analysis; and not gene array or proteomic data. Articles were assessed for the REMARK profile and other REMARK guideline items. We propose a reporting aid, the REMARK profile, motivated by the CONSORT flowchart. Results: In 50 studies assessed for the REMARK profile, the number of eligible patients (56% of articles), excluded patients (54%) and patients in analyses (98%) was reported. Only 50% of articles reported the number of outcome events. In multivariable analyses, 54% and 30% of articles reported patient and event numbers for all variables. Of the studies, 66% used archival samples, indicating a potentially biased patient selection. Only 36% of studies reported clearly defined outcomes. Conclusions: Good reporting is critical for the interpretability and clinical applicability of prognostic studies. Current reporting of key information, such as the number of outcome events in all patients and subgroups, is poor. Use of the REMARK profile would greatly improve reporting and enhance prognostic research

Structured Variability in Purkinje Cell Activity during Locomotion

The cerebellum is a prominent vertebrate brain structure that is critically involved in sensorimotor function. During locomotion, cerebellar Purkinje cells are rhythmically active, shaping descending signals and coordinating commands from higher brain areas with the step cycle. However, the variation in this activity across steps has not been studied, and its statistical structure, afferent mechanisms, and relationship to behavior remain unknown. Here, using multi-electrode recordings in freely moving rats, we show that behavioral variables systematically influence the shape of the step-locked firing rate. This effect depends strongly on the phase of the step cycle and reveals a functional clustering of Purkinje cells. Furthermore, we find a pronounced disassociation between patterns of variability driven by the parallel and climbing fibers. These results suggest that Purkinje cell activity not only represents step phase within each cycle but also is shaped by behavior across steps, facilitating control of movement under dynamic conditions

Towards a Microscopic Model of Magnetoelectric Interactions in Ni3V2O8

We develop a microscopic magnetoelectric coupling in Ni$_3$V$_2$O$_8$ (NVO) which gives rise to the trilinear phenomenological coupling used previously to explain the phase transition in which magnetic and ferroelectric order parameters appear simultaneously. Using combined neutron scattering measurements and first-principles calculations of the phonons in NVO, we determine eleven phonons which can induce the observed spontaneous polarization. Among these eleven phonons, we find that a few of them can actually induce a significant dipole moment. Using the calculated atomic charges, we find that the required distortion to induce the observed dipole moment is very small (~0.001 \AA) and therefore it would be very difficult to observe the distortion by neutron-powder diffraction. Finally, we identify the derivatives of the exchange tensor with respect to atomic displacements which are needed for a microscopic model of a spin-phonon coupling in NVO and which we hope will be obtained from a fundamental quantum calculation such as LDA+U. We also analyze two toy models to illustrate that the Dzyaloskinskii-Moriya interaction is very important for coexisting of magnetic and ferroelectric order but it is not the only mechanism when the local site symmetry of the system is low enough.Comment: 20 pages, 10 figure

Magnetic order in GdBiPt studied by x-ray resonant magnetic scattering

Rare earth (R) half-Heusler compounds, RBiPt, exhibit a wide spectrum of novel ground states. Recently, GdBiPt has been proposed as a potential antiferromagnetic topological insulator (AFTI). We have employed x-ray resonant magnetic scattering to elucidate the microscopic details of the magnetic structure in GdBiPt below T_N = 8.5 K. Experiments at the Gd L_2 absorption edge show that the Gd moments order in an antiferromagnetic stacking along the cubic diagonal [1 1 1] direction satisfying the requirement for an AFTI, where both time-reversal symmetry and lattice translational symmetry are broken, but their product is conserved.Comment: 4 pages, 4 figure

Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example

Background Prognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI) is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches. Methods and Findings Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index. Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived. Conclusions The prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other diseases

Multivariable fractional polynomial interaction to investigate continuous effect modifiers in a meta-analysis on higher versus lower PEEP for patients with ARDS.

OBJECTIVES: A recent individual patient data (IPD) meta-analysis suggested that patients with moderate or severe acute respiratory distress syndrome (ARDS) benefit from higher positive end-expiratory pressure (PEEP) ventilation strategies. However, thresholds for continuous variables (eg, hypoxaemia) are often arbitrary and linearity assumptions in regression approaches may not hold; the multivariable fractional polynomial interaction (MFPI) approach can address both problems. The objective of this study was to apply the MFPI approach to investigate interactions between four continuous patient baseline variables and higher versus lower PEEP on clinical outcomes. SETTING: Pooled data from three randomised trials in intensive care identified by a systematic review. PARTICIPANTS: 2299 patients with acute lung injury requiring mechanical ventilation. INTERVENTIONS: Higher (N=1136) versus lower PEEP (N=1163) ventilation strategy. OUTCOME MEASURES: Prespecified outcomes included mortality, time to death and time-to-unassisted breathing. We examined the following continuous baseline characteristics as potential effect modifiers using MFPI: PaO2/FiO2 (arterial partial oxygen pressure/ fraction of inspired oxygen), oxygenation index, respiratory system compliance (tidal volume/(inspiratory plateau pressure-PEEP)) and body mass index (BMI). RESULTS: We found that for patients with PaO2/FiO2 below 150 mm Hg, but above 100 mm Hg or an oxygenation index above 12 (moderate ARDS), higher PEEP reduces hospital mortality, but the beneficial effect appears to level off for patients with very severe ARDS. Patients with mild ARDS (PaO2/FiO2 above 200 mm Hg or an oxygenation index below 10) do not seem to benefit from higher PEEP and might even be harmed. For patients with a respiratory system compliance above 40 mL/cm H2O or patients with a BMI above 35 kg/m(2), we found a trend towards reduced mortality with higher PEEP, but there is very weak statistical confidence in these findings. CONCLUSIONS: MFPI analyses suggest a nonlinear effect modification of higher PEEP ventilation by PaO2/FiO2 and oxygenation index with reduced mortality for some patients suffering from moderate ARDS. STUDY REGISTRATION NUMBER: CRD42012003129

Prognosis research strategy (PROGRESS) 1: a framework for researching clinical outcomes.

The PROGRESS series (www.progress-partnership.org) sets out a framework of four interlinked prognosis research themes and provides examples from several disease fields to show why evidence from prognosis research is crucial to inform all points in the translation of biomedical and health related research into better patient outcomes. Recommendations are made in each of the four papers to improve current research standards What is prognosis research? Prognosis research seeks to understand and improve future outcomes in people with a given disease or health condition. However, there is increasing evidence that prognosis research standards need to be improved Why is prognosis research important? More people now live with disease and conditions that impair health than at any other time in history; prognosis research provides crucial evidence for translating findings from the laboratory to humans, and from clinical research to clinical practice This first article introduces the framework of four interlinked prognosis research themes and then focuses on the first of the themes - fundamental prognosis research, studies that aim to describe and explain future outcomes in relation to current diagnostic and treatment practices, often in relation to quality of care Fundamental prognosis research provides evidence informing healthcare and public health policy, the design and interpretation of randomised trials, and the impact of diagnostic tests on future outcome. It can inform new definitions of disease, may identify unanticipated benefits or harms of interventions, and clarify where new interventions are required to improve prognosis