Sequential knockoffs for continuous and categorical predictors: With application to a large psoriatic arthritis clinical trial pool.

Knockoffs provide a general framework for controlling the false discovery rate when performing variable selection. Much of the Knockoffs literature focuses on theoretical challenges and we recognize a need for bringing some of the current ideas into practice. In this paper we propose a sequential algorithm for generating knockoffs when underlying data consists of both continuous and categorical (factor) variables. Further, we present a heuristic multiple knockoffs approach that offers a practical assessment of how robust the knockoff selection process is for a given dataset. We conduct extensive simulations to validate performance of the proposed methodology. Finally, we demonstrate the utility of the methods on a large clinical data pool of more than 2000 patients with psoriatic arthritis evaluated in four clinical trials with an IL-17A inhibitor, secukinumab (Cosentyx), where we determine prognostic factors of a well established clinical outcome. The analyses presented in this paper could provide a wide range of applications to commonly encountered datasets in medical practice and other fields where variable selection is of particular interest.

Advancing data science in drug development through an innovative computational framework for data sharing and statistical analysis.

BACKGROUND: Novartis and the University of Oxford's Big Data Institute (BDI) have established a research alliance with the aim to improve health care and drug development by making it more efficient and targeted. Using a combination of the latest statistical machine learning technology with an innovative IT platform developed to manage large volumes of anonymised data from numerous data sources and types we plan to identify novel patterns with clinical relevance which cannot be detected by humans alone to identify phenotypes and early predictors of patient disease activity and progression. METHOD: The collaboration focuses on highly complex autoimmune diseases and develops a computational framework to assemble a research-ready dataset across numerous modalities. For the Multiple Sclerosis (MS) project, the collaboration has anonymised and integrated phase II to phase IV clinical and imaging trial data from ≈35,000 patients across all clinical phenotypes and collected in more than 2200 centres worldwide. For the "IL-17" project, the collaboration has anonymised and integrated clinical and imaging data from over 30 phase II and III Cosentyx clinical trials including more than 15,000 patients, suffering from four autoimmune disorders (Psoriasis, Axial Spondyloarthritis, Psoriatic arthritis (PsA) and Rheumatoid arthritis (RA)). RESULTS: A fundamental component of successful data analysis and the collaborative development of novel machine learning methods on these rich data sets has been the construction of a research informatics framework that can capture the data at regular intervals where images could be anonymised and integrated with the de-identified clinical data, quality controlled and compiled into a research-ready relational database which would then be available to multi-disciplinary analysts. The collaborative development from a group of software developers, data wranglers, statisticians, clinicians, and domain scientists across both organisations has been key. This framework is innovative, as it facilitates collaborative data management and makes a complicated clinical trial data set from a pharmaceutical company available to academic researchers who become associated with the project. CONCLUSIONS: An informatics framework has been developed to capture clinical trial data into a pipeline of anonymisation, quality control, data exploration, and subsequent integration into a database. Establishing this framework has been integral to the development of analytical tools.

Does correction of carpal malalignment influence the union rate of scaphoid nonunion surgery?

The aim of this retrospective study was to assess the relation between carpal malalignment correction and radiological union rates in surgery for scaphoid nonunions. A total of 59 scaphoid waist fracture nonunions treated with open reduction and palmar tricortical autograft were divided according to their pre- and postoperative scapholunate (SL) and radiolunate (RL) angles. We found that carpal malalignment failed to correct in 32 of 59 (54.2%) patients despite meticulous surgical technique and placement of an appropriately sized wedge-shaped graft. In total, 43 (72.9%) fractures united at a mean of 4.47 months (range 3-11). Of the 27 fractures with postoperative SL and RL angles within the normal range, 21 united, whereas 22 of the 32 remaining fractures that failed to achieve postoperative angles within the normal range went on to union. The postoperative SL and RL angles were not related to union. Our findings suggest that in scaphoid fracture nonunion surgery, carpal malalignment may not be corrected in a substantial proportion of patients, but such correction may not be essential for bony union. Our findings also show that there is no marked collapse of the scaphoid graft in the early postoperative period. LEVEL OF EVIDENCE: IV.

Managing uncertainty in inherited cardiac pathologies-an international multidisciplinary survey.

Multi-gene testing is useful in genetically heterogeneous conditions, including inherited cardiac pathologies. Increasing the number of genes analysed increases diagnostic yield of variants of certain, likely, or uncertain pathogenicity. Concerns exist regarding management of variants of uncertain/likely pathogenicity in conditions of oligogenic inheritance or variable expressivity. We surveyed a sample of colleagues across different specialties and departments internationally to compare management of patients with class 3 or class 4 variants in genes associated with non-syndromic cardiomyopathy or arrhythmia. An electronic survey regarding clinical management of variants ( www.surveymonkey.com/r/cardiacvariants ) was designed and distributed to colleagues internationally via professional bodies and direct email. 150 respondents (88 centres, 27 countries) completed the survey, most of whom were Clinical Geneticists or Genetic Counsellors. Most respondents offer pre-symptomatic testing to asymptomatic relatives of an individual with class 4 or class 5 variants. A minority of respondents offer pre-symptomatic testing for class 3 variants. Considering class 4 variants, 22 (15%) are fully reassuring that the patient with a negative predictive test would not develop the familial phenotype, while 123 (82%) counselled patients about the possibility of variant reclassification. Variability existed between and within centres and specialties. Multiple "free text" comments were provided. Recurring themes including need for multidisciplinary input, technical concerns, and concern regarding duty to review variants of uncertain significance. This study demonstrates that variability in management of likely pathogenic/uncertain variants exists. Close multi-disciplinary input is essential. The development of disorder or gene-specific evidence-based guidelines might ameliorate uncertainty in management.