This book presents some recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This ...enables the book to handle a broader range of data types than those analyzed by traditional generalized linear models. One example is correlated angular data. This book provides a systematic treatment for the topic of estimating functions. Under this framework, both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to marginal models and mixed-effects models, this book covers topics on joint regression analysis based on Gaussian copulas and generalized state space models for longitudinal data from long time series. Various real-world data examples, numerical illustrations and software usage tips are presented throughout the book. This book has evolved from lecture notes on longitudinal data analysis, and may be considered suitable as a textbook for a graduate course on correlated data analysis. This book is inclined more towards technical details regarding the underlying theory and methodology used in software-based applications. Therefore, the book will serve as a useful reference for those who want theoretical explanations to puzzles arising from data analyses or deeper understanding of underlying theory related to analyses.
Summary
Multi‐compartment models have been playing a central role in modelling infectious disease dynamics since the early 20th century. They are a class of mathematical models widely used for ...describing the mechanism of an evolving epidemic. Integrated with certain sampling schemes, such mechanistic models can be applied to analyse public health surveillance data, such as assessing the effectiveness of preventive measures (e.g. social distancing and quarantine) and forecasting disease spread patterns. This review begins with a nationwide macromechanistic model and related statistical analyses, including model specification, estimation, inference and prediction. Then, it presents a community‐level micromodel that enables high‐resolution analyses of regional surveillance data to provide current and future risk information useful for local government and residents to make decisions on reopenings of local business and personal travels. r software and scripts are provided whenever appropriate to illustrate the numerical detail of algorithms and calculations. The coronavirus disease 2019 pandemic surveillance data from the state of Michigan are used for the illustration throughout this paper.
Summary
The paper presents an incremental updating algorithm to analyse streaming data sets using generalized linear models. The method proposed is formulated within a new framework of renewable ...estimation and incremental inference, in which the maximum likelihood estimator is renewed with current data and summary statistics of historical data. Our framework can be implemented within a popular distributed computing environment, known as Apache Spark, to scale up computation. Consisting of two data‐processing layers, the rho architecture enables us to accommodate inference‐related statistics and to facilitate sequential updating of the statistics used in both estimation and inference. We establish estimation consistency and asymptotic normality of the proposed renewable estimator, in which the Wald test is utilized for an incremental inference. Our methods are examined and illustrated by various numerical examples from both simulation experiments and a real world data analysis.
Summary
Population-based cohort study of 6,548,784 Korean subjects demonstrates that the risk of fracture was higher in patients with diabetes than in nondiabetic subjects. Furthermore, patients with ...type 1 diabetes were associated with a higher risk of fracture than patients with type 2 diabetes for all measurement sites.
Introduction
Diabetes mellitus is associated with increased fracture risk. Although the pathophysiologic effect on bone metabolism differs according to the type of diabetes, a higher risk of fracture in patients with diabetes than in nondiabetic patients has been consistently demonstrated. Considering the ever-increasing number of patients with diabetes, we aimed to provide updated information on whether this phenomenon remains valid in real-world settings by using large-scale population datasets.
Methods
We conducted a retrospective longitudinal study using data from the Korean National Health Insurance Service dataset of preventive health check-ups between January 2009 and December 2016. The hazard ratios were calculated for any fracture, vertebral fracture, and hip fracture and were analyzed according to the presence and type of diabetes. Among 10,585,818 subjects, 6,548,784 were eligible for the analysis (2418 patients with type 1 diabetes mellitus T1DM and 506,208 patients with type 2 diabetes mellitus T2DM).
Results
The mean follow-up duration (in years) was 7.0 ± 1.3 for subjects without diabetes, 6.4 ± 2.0 for those with T1DM, and 6.7 ± 1.7 for T2DM. Patients with T1DM had a higher incidence rate for all types of fractures per 1000 person-years. The fully adjusted hazard ratios (HRs) for any fracture, vertebral fracture, and hip fracture were higher in T1DM than in T2DM (1.37 95% confidence interval (CI): 1.23–1.52 for any fracture, 1.33 95% CI: 1.09–1.63 for vertebral fracture, and 1.99 95% CI: 1.56–2.53 for hip fracture).
Conclusions
In this large-scale population analysis, diabetes was associated with a higher risk of all types of fractures. Patients with T1DM had a higher risk of fracture than those with T2DM for all measurement sites, and hip fractures had the highest risk. Therefore, fracture prevention training for patients with diabetes is advisable.
Cemented paste backfill (CPB) plays a vital role in tailings management where the CPB slurry is hydraulically conveyed from the surface to underground voids in pipelines. To enhance transport ...efficiency, accurate prediction of their flow characteristics is always required during CPB design. The objective of this study is to investigate the flow characteristics of the CPB slurry by using computational fluid dynamics (CFD) method. In this method, a mixture model was utilized to represent the multi-phase characteristics of pipe flow and a reaction flow model was used to consider the hydration effect. The performance of the mixing model was verified using the experimental results and the influence of the cement hydration was discussed. A comprehensive sensitivity study was performed to investigate the coupled effect of the tailings-to-cement ratio (TCR), inlet velocity (IV), slurry concentration (SC) and particle size (PS). The results indicated that three zones were formed during pipe transportation due to the deposition of coarse tailings and the suspension of fine tailings. The velocity along the pipe cross-section was arch-like with a high velocity near the middle and low velocity near the wall. Cement hydration needs to be considered in the pipe system design and all influencing factors (TCR, IV, SC and PS) had important effects on the pipe flow of CPB transportation. The obtained results can provide guiding significance to the mining industry and backfill practitioners during the pipe system design.
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•CFD method was used to investigate the flow characteristics of the CPB slurry.•A mixture model was used to represent the multi-phase characteristics of pipe flow.•A reaction model was used to consider the hydration effect.•A comprehensive sensitivity study was performed on TCR, IV, SC, and PS.•Three zones were formed during the pipe flow and all factors had important effects.
The spatiotemporal variations of surface air pollutants (O3, NO2, SO2, CO, and PM10) with four land-use types, residence (R), commerce (C), industry (I) and greenbelt (G), have been investigated at ...283 stations in South Korea during 2002-2013, using routinely observed data. The volatile organic compound (VOC) data at nine photochemical pollutant monitoring stations available since 2007 were utilized in order to examine their effect on the ozone chemistry. The land-use types, set by the Korean government, were generally consistent with the satellite-derived land covers and with the previous result showing anti-correlation between O3 and NO2 in diverse urban areas. The relationship between the two pollutants in the Seoul Metropolitan Area (SMA) residence land-use areas was substantially different from that outside of the SMA, probably due to the local differences in vehicle emissions. The highest concentrations of air pollutants in the diurnal, weekly, and annual cycles were found in industry for SO2 and PMPM10, in commerce for NO2 and CO, and in greenbelt for O3. The concentrations of air pollutants, except for O3, were generally higher in big cities during weekdays, while O3 showed its peak in suburban areas or small cities during weekends. The weekly cycle and trends of O3 were significantly out of phase with those of NO2, particularly in the residential and commercial areas, suggesting that vehicle emission was a major source in those areas. The ratios of VOCs to NO2 for each of the land-use types were in the order of I (10.2) > C (8.7) > G (3.9) > R (3.6), suggesting that most areas in South Korea were likely to be VOC-limited for ozone chemistry. The pollutants (NO2, SO2, CO, and PMPM10 except for O3 have decreased, most likely due to the effective government control. The total oxidant values (OX = O3 + NO2) with the land-use types were analyzed for the local and regional (or background) contributions of O3, respectively, and the order of OX (ppb) was C (57.4) > R (53.6) > I (50.7) > G (45.4), indicating the greenbelt observation was close to the background.
Background
Serotonin (5‐hydroxytryptamine, 5HT) is involved in hypothalamic regulation of energy consumption. Also, the gut microbiome can influence neuronal signaling to the brain through vagal ...afferent neurons. Therefore, serotonin concentrations in the central nervous system and the composition of the microbiota can be related to obesity.
Objective
To examine adipokine, and, serotonin concentrations, and the gut microbiota in lean dogs and dogs with experimentally induced obesity.
Animals
Fourteen healthy Beagle dogs were used in this study.
Methods
Seven Beagle dogs in the obese group were fed commercial food ad libitum, over a period of 6 months to increase their weight and seven Beagle dogs in lean group were fed a restricted amount of the same diet to maintain optimal body condition over a period of 6 months. Peripheral leptin, adiponectin, 5HT, and cerebrospinal fluid (CSF‐5HT) levels were measured by ELISA. Fecal samples were collected in lean and obese groups 6 months after obesity was induced. Targeted pyrosequencing of the 16S rRNA gene was performed using a Genome Sequencer FLX plus system.
Results
Leptin concentrations were higher in the obese group (1.98 ± 1.00) compared to those of the lean group (1.12 ± 0.07, P = .025). Adiponectin and 5‐hydroytryptamine of cerebrospinal fluid (CSF‐5HT) concentrations were higher in the lean group (27.1 ± 7.28) than in the obese group (14.4 ± 5.40, P = .018). Analysis of the microbiome revealed that the diversity of the microbial community was lower in the obese group. Microbes from the phylum Firmicutes (85%) were predominant group in the gut microbiota of lean dogs. However, bacteria from the phylum Proteobacteria (76%) were the predominant group in the gut microbiota of dogs in the obese group.
Conclusions and Clinical Importance
Decreased 5HT levels in obese group might increase the risk of obesity because of increased appetite. Microflora enriched with gram‐negative might be related with chronic inflammation status in obese dogs.
Summary
Follow-up raloxifene therapy after denosumab discontinuation resulted in a decrease in bone mass to the pre-denosumab levels and a rebound increase of bone turnover markers. The decrease in ...lumbar bone mineral density was particularly evident when the body mass index was low, there were previous vertebral fractures, or lumbar bone mineral density before denosumab administration was low.
Introduction
Selective estrogen receptor modulators may be an alternative to bisphosphonates for treating rebound resorption after discontinuing denosumab. This study aimed to investigate the effects of follow-up raloxifene therapy after denosumab discontinuation in postmenopausal women.
Methods
This retrospective observational study included 61 patients who received 12-month follow-up raloxifene therapy after denosumab discontinuation. The primary endpoint was the bone mineral density change. The secondary endpoints were the changes in bone turnover markers and the incidence of new vertebral fractures.
Results
Raloxifene administration for 12 months after denosumab discontinuation resulted in a significantly lower bone mineral density at all sites compared to the level at 6 months after the last denosumab treatment (lumbar spine, − 5.48%; femoral neck, − 2.95%; total hip, − 3.52%; all,
p
< 0.001). The decrease in lumbar bone mineral density was particularly evident when the body mass index was low, there were previous vertebral fractures, or lumbar bone mineral density before denosumab administration was low. Marked increases in the bone turnover markers from baseline were noted after switching to raloxifene. However, no new vertebral fractures occurred during raloxifene treatment.
Conclusions
Follow-up raloxifene therapy after denosumab discontinuation resulted in a decrease in bone mass to the pre-denosumab levels and a rebound increase of bone turnover markers. Therefore, raloxifene administered sequentially after denosumab discontinuation was not effective in preventing rebound phenomenon.
Data sharing barriers present paramount challenges arising from multicenter clinical studies where multiple data sources are stored and managed in a distributed fashion at different local study ...sites. Merging such data sources into a common data storage for a centralized statistical analysis requires a data use agreement, which is often time-consuming. Data merging may become more burdensome when propensity score modeling is involved in the analysis because combining many confounding variables, and systematic incorporation of this additional modeling in a meta-analysis has not been thoroughly investigated in the literature. Motivated from a multicenter clinical trial of basal insulin treatment for reducing the risk of post-transplantation diabetes mellitus, we propose a new inference framework that avoids the merging of subject-level raw data from multiple sites at a centralized facility but needs only the sharing of summary statistics. Unlike the architecture of federated learning, the proposed collaborative inference does not need a center site to combine local results and thus enjoys maximal protection of data privacy and minimal sensitivity to unbalanced data distributions across data sources. We show theoretically and numerically that the new distributed inference approach has little loss of statistical power compared to the centralized method that requires merging the entire data. We present large-sample properties and algorithms for the proposed method. We illustrate its performance by simulation experiments and the motivating example on the differential average treatment effect of basal insulin to lower risk of diabetes among kidney-transplant patients compared to the standard-of-care.
Summary
Background
Early identification and treatment of actinic cheilitis (AC) is recommended. Although photodynamic therapy (PDT) is an attractive therapeutic option for AC, PDT for AC does not ...result in the same satisfactory outcomes as in actinic keratosis (AK).
Objectives
The aim of our study was to compare efficacy, recurrence rate, cosmetic outcome and safety between erbium:yttrium–aluminium–garnet ablative fractional laser‐assisted methyl aminolaevulinate–PDT (Er:YAG AFL MAL‐PDT) and standard MAL‐PDT.
Methods
Thirty‐three patients with histologically confirmed AC randomly received either one session of Er:YAG AFL MAL‐PDT or two sessions of MAL‐PDT. In the MAL‐PDT group, the second session of MAL‐PDT was administered 7 days later. Patients were followed up at 1 week and 3 and 12 months, and biopsies were taken from all patients at 3 and 12 months after the last treatment session. At the final 12‐month follow‐up, cosmetic outcomes were assessed. Adverse events were assessed at week 1 of the treatment phase and every subsequent follow‐up visit.
Results
In the per‐protocol (PP) population, Er:YAG AFL MAL‐PDT was significantly more effective (92% complete response rate) than MAL‐PDT (59%; P = 0·040) at the 3‐month follow‐up, and differences in efficacy remained significant at the 12‐month follow‐up (85% in Er:YAG AFL MAL‐PDT and 29% in MAL‐PDT). The recurrence rate was significantly lower for Er:YAG AFL MAL‐PDT (8%) than for MAL‐PDT (50%) group at 12 months (P = 0·029). No significant difference in cosmetic outcome or safety was observed between Er:YAG AFL MAL‐PDT and MAL‐PDT.
Conclusions
Ablative fractional laser pretreatment has significant benefit for the treatment of AC with PDT.
What's already known about this topic?
Photodynamic therapy (PDT) is less efficient for actinic cheilitis (AC) than for actinic keratosis.
Use of an erbium:yttrium–aluminium–garnet ablative fractional laser (Er:YAG AFL) improves the methyl aminolaevulinate (MAL) penetration into deeper portions of lesions.
What does this study add?
The present study showed Er:YAG AFL‐assisted MAL‐PDT is better for the treatment of AC and requires fewer sessions than conventional MAL‐PDT.
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