Reporting and Guidelines in Propensity Score Analysis: A Systematic Review of Cancer and Cancer Surgical Studies

Background: Propensity score (PS) analysis is increasingly being used in observational studies, especially in some cancer studies where random assignment is not feasible. This systematic review evaluates the use and reporting quality of PS analysis in oncology studies. Methods: We searched PubMed to identify the use of PS methods in cancer studies (CS) and cancer surgical studies (CSS) in major medical, cancer, and surgical journals over time and critically evaluated 33 CS published in top medical and cancer journals in 2014 and 2015 and 306 CSS published up to November 26, 2015, without earlier date limits. The quality of reporting in PS analysis was evaluated. It was also compared over time and among journals with differing impact factors. All statistical tests were two-sided. Results: More than 50% of the publications with PS analysis from the past decade occurred within the past two years. Of the studies critically evaluated, a considerable proportion did not clearly provide the variables used to estimate PS (CS 12.1%, CSS 8.8%), incorrectly included non baseline variables (CS 3.4%, CSS 9.3%), neglected the comparison of baseline characteristics (CS 21.9%, CSS 15.6%), or did not report the matching algorithm utilized (CS 19.0%, CSS 36.1%). In CSS, the reporting of the matching algorithm improved in 2014 and 2015 (P = .04), and the reporting of variables used to estimate PS was better in top surgery journals (P = .008). However, there were no statistically significant differences for the inclusion of non baseline variables and reporting of comparability of baseline characteristics. Conclusions: The use of PS in cancer studies has dramatically increased recently, but there is substantial room for improvement in the quality of reporting even in top journals. Herein we have proposed reporting guidelines for PS analyses that are broadly applicable to different areas of medical research that will allow better evaluation and comparison across studies applying this approach.postprin

The Wasteland of Random Supergravities

We show that in a general \cal{N} = 1 supergravity with N \gg 1 scalar fields, an exponentially small fraction of the de Sitter critical points are metastable vacua. Taking the superpotential and Kahler potential to be random functions, we construct a random matrix model for the Hessian matrix, which is well-approximated by the sum of a Wigner matrix and two Wishart matrices. We compute the eigenvalue spectrum analytically from the free convolution of the constituent spectra and find that in typical configurations, a significant fraction of the eigenvalues are negative. Building on the Tracy-Widom law governing fluctuations of extreme eigenvalues, we determine the probability P of a large fluctuation in which all the eigenvalues become positive. Strong eigenvalue repulsion makes this extremely unlikely: we find P \propto exp(-c N^p), with c, p being constants. For generic critical points we find p \approx 1.5, while for approximately-supersymmetric critical points, p \approx 1.3. Our results have significant implications for the counting of de Sitter vacua in string theory, but the number of vacua remains vast.Comment: 39 pages, 9 figures; v2: fixed typos, added refs and clarification

Characterising chromosome rearrangements: recent technical advances in molecular cytogenetics

Genomic rearrangements can result in losses, amplifications, translocations and inversions of DNA fragments thereby modifying genome architecture, and potentially having clinical consequences. Many genomic disorders caused by structural variation have initially been uncovered by early cytogenetic methods. The last decade has seen significant progression in molecular cytogenetic techniques, allowing rapid and precise detection of structural rearrangements on a whole-genome scale. The high resolution attainable with these recently developed techniques has also uncovered the role of structural variants in normal genetic variation alongside single-nucleotide polymorphisms (SNPs). We describe how array-based comparative genomic hybridisation, SNP arrays, array painting and next-generation sequencing analytical methods (read depth, read pair and split read) allow the extensive characterisation of chromosome rearrangements in human genomes

Segal–Bargmann transform: the q-deformation

International audienc