Autologistic network model on binary data for disease progression study

This paper focuses on analysis of spatiotemporal binary data with absorbing states. The research was motivated by a clinical study on amyotrophic lateral sclerosis (ALS), a neurological disease marked by gradual loss of muscle strength over time in multiple body regions. We propose an autologistic regression model to capture complex spatial and temporal dependencies in muscle strength among different muscles. As it is not clear how the disease spreads from one muscle to another, it may not be reasonable to define a neighborhood structure based on spatial proximity. Relaxing the requirement for prespecification of spatial neighborhoods as in existing models, our method identifies an underlying network structure empirically to describe the pattern of spreading disease. The model also allows the network autoregressive effects to vary depending on the muscles’ previous status. Based on the joint distribution derived from this autologistic model, the joint transition probabilities of responses among locations can be estimated and the disease status can be predicted in the next time interval. Model parameters are estimated through maximization of penalized pseudo‐likelihood. Postmodel selection inference was conducted via a bias‐correction method, for which the asymptotic distributions were derived. Simulation studies were conducted to evaluate the performance of the proposed method. The method was applied to the analysis of muscle strength loss from the ALS clinical study.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152664/1/biom13111.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152664/2/biom13111-sup-0001-autolog_supp-biom.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152664/3/biom13111-sup-0003-supmat.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152664/4/biom13111_am.pd

Critical design considerations for time-to-event endpoints in amyotrophic lateral sclerosis clinical trials

Background: Funding and resources for low prevalent neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) are limited, and optimising their use is vital for efficient drug development. In this study, we review the design assumptions for pivotal ALS clinical trials with time-to-event endpoints and provide optimised settings for future trials. Methods: We extracted design settings from 13 completed placebo-controlled trials. Optimal assumptions were estimated using parametric survival models in individual participant data (n=4991). Designs were compared in terms of sample size, trial duration, drug use and costs. Results: Previous trials overestimated the hazard rate by 18.9% (95% CI 3.4% to 34.5%, p=0.021). The median expected HR was 0.56 (range 0.33–0.66). Additionally, we found evidence for an increasing mean hazard rate over time (Weibull shape parameter of 2.03, 95% CI 1.93 to 2.15, p<0.001), which affects the design and planning of future clinical trials. Incorporating accrual time and assuming an increasing hazard rate at the design stage reduced sample size by 33.2% (95% CI 27.9 to 39.4), trial duration by 17.4% (95% CI 11.6 to 23.3), drug use by 14.3% (95% CI 9.6 to 19.0) and follow-up costs by 21.2% (95% CI 15.6 to 26.8). Conclusions: Implementing distributional knowledge and incorporating accrual at the design stage could achieve large gains in the efficiency of ALS clinical trials with time-to-event endpoints. We provide an open-source platform that helps investigators to make more accurate sample size calculations and optimise the use of their available resources

Pirfenidone in idiopathic pulmonary fibrosis:expert panel discussion on the management of drug-related adverse events

Pirfenidone is currently the only approved therapy for idiopathic pulmonary fibrosis, following studies demonstrating that treatment reduces the decline in lung function and improves progression-free survival. Although generally well tolerated, a minority of patients discontinue therapy due to gastrointestinal and skin-related adverse events (AEs). This review summarizes recommendations based on existing guidelines, research evidence, and consensus opinions of expert authors, with the aim of providing practicing physicians with the specific clinical information needed to educate the patient and better manage pirfenidone-related AEs with continued pirfenidone treatment. The main recommendations to help prevent and/or mitigate gastrointestinal and skin-related AEs include taking pirfenidone during (or after) a meal, avoiding sun exposure, wearing protective clothing, and applying a broad-spectrum sunscreen with high ultraviolet (UV) A and UVB protection. These measures can help optimize AE management, which is key to maintaining patients on an optimal treatment dose.Correction in: Advances in Therapy, Volume 31, Issue 5, pp 575-576 , doi: 10.1007/s12325-014-0118-8</p

Venetoclax ramp-up strategies for chronic lymphocytic leukaemia in the United Kingdom: a real world multicentre retrospective study

This retrospective, observational study evaluated patterns of inpatient versus outpatient tumour lysis syndrome (TLS) monitoring during venetoclax ramp-up in 170 patients with chronic lymphocytic leukaemia. The primary outcome was clinical/biochemical TLS. Two clinical and four biochemical TLS occurred (4.1%). Five of the six events occurred in high-risk patients, four occurred at 20 mg dose and three at the 6-h time-point. Inpatient versus outpatient TLS rates within the high-risk subgroup were 15% and 8%. Risk category was the only predictor of TLS events in multivariate analysis. Outpatient escalation did not associate with clinically meaningful TLS events, suggesting outpatient escalation has manageable associated TLS risks, including in high-risk cohorts. These observations require confirmation in larger studies

Missense mutations in the copper transporter gene ATP7A cause X-Linked distal hereditary motor neuropathy

Distal hereditary motor neuropathies comprise a clinically and genetically heterogeneous group of disorders. We recently mapped an X-linked form of this condition to chromosome Xq13.1-q21 in two large unrelated families. The region of genetic linkage included ATP7A, which encodes a copper-transporting P-type ATPase mutated in patients with Menkes disease, a severe infantile-onset neurodegenerative condition. We identified two unique ATP7A missense mutations (p.P1386S and p.T994I) in males with distal motor neuropathy in two families. These molecular alterations impact highly conserved amino acids in the carboxyl half of ATP7A and do not directly involve the copper transporter's known critical functional domains. Studies of p.P1386S revealed normal ATP7A mRNA and protein levels, a defect in ATP7A trafficking, and partial rescue of a S. cerevisiae copper transport knockout. Although ATP7A mutations are typically associated with severe Menkes disease or its milder allelic variant, occipital horn syndrome, we demonstrate here that certain missense mutations at this locus can cause a syndrome restricted to progressive distal motor neuropathy without overt signs of systemic copper deficiency. This previously unrecognized genotype-phenotype correlation suggests an important role of the ATP7A copper transporter in motor-neuron maintenance and function

Large-Scale Gene-Centric Meta-Analysis across 39 Studies Identifies Type 2 Diabetes Loci

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with similar to 2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 x 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p <2.4 x 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 x 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 x 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 x 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe