Variation and implications of treatment decisions in early rheumatoid arthritis: results from a nationwide cohort study

Abstract Objectives Trial data have provided an evidence base to guide early treatment in RA. Few studies have investigated rheumatologists’ adherence to guidelines, and subsequent impact on outcomes. The objectives of this study are to characterize baseline prescribing for patients with RA across the National Health Service, identifying treatment decisions that associate with patient outcomes. Methods A nationwide audit of RA collected information on treatment choices, DAS and sociodemographic factors at baseline. Treatment response was assessed at 3 months. Multilevel regression models were used to characterize departmental variations in prescribing. Heat maps were used to visualize geographical variation. Mixed effects regression models were constructed to assess the relationship between treatment decisions and disease outcomes, adjusting for patient and department level covariates. Results A total of 7154 patients with a diagnosis of RA were recruited from 136 departments. There was broad variation in prescribing choices, even between departments close to one another, with evidence of substantial deviation from guidelines. Over 75% of patients received glucocorticoids, fewer than half received combination conventional DMARDs. Early glucocorticoid therapy associated with achieving a good treatment response [odds ratio 1.93 (95% CI 1.31, 2.84), P-value = 0.001]. The association was maintained following propensity modelling and imputation. Conclusion Guideline adherence varies between departments and cannot be explained by case-mix alone. Departments that prescribe early adjunctive steroid achieve better short-term outcomes. Further research should work to ensure that the early arthritis evidence base translates into better outcomes for patients.

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Evaluation of Antifungal Activity of CalvatiaCraniiformis and IverMectin as Novel Alternative Therapies for Aspergillus Niger Associated Acute Otitis Media with Special Refer to SocioDemographic Factors Among Rural Children of Diyala Province-Iraq

International Journal of Pharmaceutical and Clinical Research ◽

10.25258/ijpcr.v9i08.9583 ◽

2017 ◽

Vol 9 (08) ◽

Cited By ~ 1

Author(s):

Ghassan H. Jameel ◽

Ali Ibrahim Ali Al-Ezzy

Keyword(s):

Antifungal Activity ◽

Aspergillus Niger ◽

Otitis Media ◽

Family Size ◽

Acute Otitis Media ◽

Sociodemographic Factors ◽

P Value ◽

Rural Children ◽

Alcohol Extract ◽

Family Economy

Objectives are to determine antifungal activity of Ivermectin and Calvatiacraniiformis as a novel alternative therapy for aspergillus niger associated acute otitis media (AOM) among rural children of Diyala province; correlation of sociodemographic factors with frequency of infection. Ear swabs taken from 58 infected children and cultured onSabouraud dextrose agar for 7-14 days .Macroscopic and microscopic criteria used for diagnosis of A.niger .High isolation rate for A.niger (27.59%) among children of (4-6) years with significant difference between age groups ( p value 0.039); genders ( p value 0.004);house status(p value=0.018);family size (p value =0.00006334) and month of infection (p value=0.000). A.niger infection negatively correlated with patients age (p value =0.039), family economy and house status (p value =0.000),family size (p value =0.000). Alcohol extract of C.craniiformis (100mg, 200mg, 400mg, 500mg, 600mg, 800mg and 1000 mg) and ivermectin (0.5%,1 % and 2%) restricted the growth of A. niger after 3 days .Significance difference reported between all concentrations except 100 mg and 200 mg ; 600 mg and 800 mg. Significance difference in inhibitory activity between concentration 1% and 2%,0.5% and 2% of Ivermectin respectively. Conclusions: A.niger infections positively correlated with family size and inversely with age and family economy. The growth of A nigersignificantly restricted by alcohol extract of C.craniiformis and Ivermectin in concentration dependent manner. The powerful concentration was 1000mg, for C.craniiformis and 2% for Ivermectin. Thus, C.craniiformis and Ivermectin consider a novel antifungal agents that can be used in clinical practice for treatment of A.niger associated otitis media that represents a clinical problem in children and need serious attention from clinicians.

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The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

Journal of Cancer Science and Therapeutics ◽

10.36879/jcst.19.000109 ◽

2019 ◽

pp. 1-5

Keyword(s):

Decision Making ◽

Logistic Regression ◽

Skin Necrosis ◽

Regression Models ◽

Multivariable Analysis ◽

P Value ◽

Flap Necrosis ◽

Single Institution ◽

Logistic Regression Models ◽

The Impact

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

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CANTARE: finding and visualizing network-based multi-omic predictive models

BMC Bioinformatics ◽

10.1186/s12859-021-04016-8 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Janet C. Siebert ◽

Martine Saint-Cyr ◽

Sarah J. Borengasser ◽

Brandie D. Wagner ◽

Catherine A. Lozupone ◽

...

Keyword(s):

Random Forests ◽

Predictive Models ◽

Regression Models ◽

Dynamic Range ◽

P Value ◽

Published Data ◽

Logistic Regression Models ◽

Pairwise Models ◽

Biological Insight ◽

Analytical Approaches

Abstract Background One goal of multi-omic studies is to identify interpretable predictive models for outcomes of interest, with analytes drawn from multiple omes. Such findings could support refined biological insight and hypothesis generation. However, standard analytical approaches are not designed to be “ome aware.” Thus, some researchers analyze data from one ome at a time, and then combine predictions across omes. Others resort to correlation studies, cataloging pairwise relationships, but lacking an obvious approach for cohesive and interpretable summaries of these catalogs. Methods We present a novel workflow for building predictive regression models from network neighborhoods in multi-omic networks. First, we generate pairwise regression models across all pairs of analytes from all omes, encoding the resulting “top table” of relationships in a network. Then, we build predictive logistic regression models using the analytes in network neighborhoods of interest. We call this method CANTARE (Consolidated Analysis of Network Topology And Regression Elements). Results We applied CANTARE to previously published data from healthy controls and patients with inflammatory bowel disease (IBD) consisting of three omes: gut microbiome, metabolomics, and microbial-derived enzymes. We identified 8 unique predictive models with AUC > 0.90. The number of predictors in these models ranged from 3 to 13. We compare the results of CANTARE to random forests and elastic-net penalized regressions, analyzing AUC, predictions, and predictors. CANTARE AUC values were competitive with those generated by random forests and penalized regressions. The top 3 CANTARE models had a greater dynamic range of predicted probabilities than did random forests and penalized regressions (p-value = 1.35 × 10–5). CANTARE models were significantly more likely to prioritize predictors from multiple omes than were the alternatives (p-value = 0.005). We also showed that predictive models from a network based on pairwise models with an interaction term for IBD have higher AUC than predictive models built from a correlation network (p-value = 0.016). R scripts and a CANTARE User’s Guide are available at https://sourceforge.net/projects/cytomelodics/files/CANTARE/. Conclusion CANTARE offers a flexible approach for building parsimonious, interpretable multi-omic models. These models yield quantitative and directional effect sizes for predictors and support the generation of hypotheses for follow-up investigation.

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Recommendations for Abnormal Behaviour Ethograms in Monkey Research

Animals ◽

10.3390/ani11051461 ◽

2021 ◽

Vol 11 (5) ◽

pp. 1461

Author(s):

Andrea Polanco ◽

Brenda McCowan ◽

Lee Niel ◽

David L. Pearl ◽

Georgia Mason

Keyword(s):

Macaca Mulatta ◽

Regression Models ◽

Convergent Validity ◽

P Value ◽

Morphological Similarity ◽

Abnormal Behaviour ◽

Logistic Regression Models ◽

The Third ◽

Welfare Implications ◽

Self Stimulation

Laboratory monkey ethograms currently include subcategories of abnormal behaviours that are based on superficial morphological similarity. Yet, such ethograms may be misclassifying behaviour, with potential welfare implications as different abnormal behaviours are likely to have distinct risk factors and treatments. We therefore investigated the convergent validity of four hypothesized subcategories of abnormal behaviours (‘motor’, e.g., pacing; ‘self-stimulation’, e.g., self-sucking; ‘postural’, e.g., hanging; and ‘self-abuse’, e.g., self-biting). This hypothesis predicts positive relationships between the behaviours within each subcategory. Rhesus macaque (Macaca mulatta) data on 19 abnormal behaviours were obtained from indoor-housed animals (n = 1183). Logistic regression models, controlling for sex, age, and the number of observations, revealed that only 1/6 ‘motor’ behaviours positively predicted pacing, while 2/3 ‘self-abuse’ behaviours positively predicted self-biting (one-tailed p-value < 0.05). Furthermore, ‘self-stimulation’ behaviours did not predict self-sucking, and none of the ‘postural’ behaviours predicted hanging. Thus, none of the subcategories fully met convergent validity. Subsequently, we created four new valid subcategories formed of comorbid behaviours. The first consisted of self-biting, self-hitting, self-injurious behaviour, floating limb, leg-lifting, and self-clasping. The second comprised twirling, bouncing, rocking, swinging, and hanging. The third comprised pacing and head-twisting, while the final subcategory consisted of flipping and eye-poking. Self-sucking, hair-plucking, threat-biting, and withdrawn remained as individual behaviours. We encourage laboratories to replicate the validation of these subcategories first, and for scientists working with other species to validate their ethograms before using them in welfare assessments.

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NCDB Analysis of Melanoma 2004–2015: Epidemiology and Outcomes by Subtype, Sociodemographic Factors Impacting Clinical Presentation, and Real-World Survival Benefit of Immunotherapy Approval

Cancers ◽

10.3390/cancers13061455 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1455

Author(s):

Sunny R. K. Singh ◽

Sindhu J. Malapati ◽

Rohit Kumar ◽

Christopher Willner ◽

Ding Wang

Keyword(s):

Metastatic Melanoma ◽

Metastatic Disease ◽

Real World ◽

Care Delivery ◽

Sociodemographic Factors ◽

P Value ◽

Real World Data ◽

Factors Associated ◽

Improvement In Survival ◽

The Impact

Background: The incidence of invasive melanoma is rising, and approval for the first immune checkpoint inhibitor (ICI) to treat metastatic melanoma occurred in 2011. We aim to describe the epidemiology and outcomes in recent years, sociodemographic factors associated with the presence of metastasis at diagnosis, and the real‐world impact of ICI approval on survival based on melanoma subtype and race. Methods: This is a retrospective analysis of the National Cancer Database (NCDB) from the years 2004–2015. The primary outcome was the overall survival of metastatic melanoma by subtype. Secondary outcomes included sociodemographic factors associated with the presence of metastasis at diagnosis and the impact of treatment facility type and ICI approval on the survival of metastatic melanoma. Results: Of the 419,773 invasive melanoma cases, 93.80% were cutaneous, and 4.92% were metastatic at presentation. The odds of presenting with metastatic disease were higher in African Americans (AA) compared to Caucasians (OR 2.37; 95% CI 2.11–2.66, p < 0.001). Treatment of metastatic melanoma at an academic/research facility was associated with lower mortality versus community cancer programs (OR 0.75, 95 % CI 0.69–0.81, p-value<0.001). Improvement in survival of metastatic melanoma was noted for Caucasians after the introduction of ICI (adjusted HR 0.80, 95% CI 0.78–0.83, p < 0.001); however, this was not statistically significant for AA (adjusted HR 0.80, 95% CI 0.62–1.02, p‐value = 0.073) or ocular cases (HR 1.03, 95% CI 0.81–1.31, p‐value 0.797). Conclusion: Real‐world data suggest a 20% improvement in survival of metastatic melanoma since the introduction of ICI. The disproportionately high odds of metastatic disease at presentation in AA patients with melanoma suggest the need for a better understanding of the disease and improvement in care delivery.

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The Differential Effects of Caregiving Intensity on Overnight Hospitalization in the Previous 2 Years

Innovation in Aging ◽

10.1093/geroni/igaa057.249 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 76-76

Author(s):

Kylie Meyer ◽

Zachary Gassoumis ◽

Kathleen Wilber

Keyword(s):

Health Services ◽

Fixed Effects ◽

Regression Models ◽

P Value ◽

Logistic Regression Models ◽

Spousal Caregiving ◽

Health Insurance Status ◽

Race Ethnicity ◽

Self Assessed Health ◽

Retirement Study

Abstract Caregiving for a spouse is considered a major stressor many Americans will encounter during their lifetimes. Although most studies indicate caregiving is associated with experiencing diminished health outcomes, little is known about how this role affects caregivers’ use of acute health services. To understand how spousal caregiving affects the use of acute health services, we use data from the Health and Retirement Study. We apply fixed effects (FE) logistic regression models to examine odds of experiencing an overnight hospitalization in the previous two years according to caregiving status, intensity, and changes in caregiving status and intensity. Models controlled for caregiver gender, age, race, ethnicity, educational attainment, health insurance status, the number of household residents, and self-assessed health. Overall, caregivers were no more likely to experience an overnight hospitalization compared to non-caregivers (OR 0.92; CI 0.84 to 1.00; p-value=0.057). However, effects varied according to the intensity of caregiving and the time spent in this role. Compared to non-caregivers, for example, spouses who provided care to someone with no need for assistance with activities of daily living had lower odds of experiencing a hospitalization (OR 0.77; CI 0.66 to 0.89). In contrast, caregivers who provided care to someone with dementia for 4 to <6 years had 3.29 times the odds of experiencing an overnight hospitalization (CI 1.04 to 10.38; p-value=0.042). Findings indicate that, although caregivers overall appear to use acute health services about as much as non-caregivers, large differences exist between caregivers. Results emphasize the importance of recognizing diversity within caregiving experiences.

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Online News and Protest Participation in a Political Context: Evidence from Self-Reported Cross-Sectional Data

Social Media + Society ◽

10.1177/2056305120984456 ◽

2021 ◽

Vol 7 (1) ◽

pp. 205630512098445

Author(s):

Nora Kirkizh ◽

Olessia Koltsova

Keyword(s):

Digital Media ◽

Regression Models ◽

Online News ◽

Political Context ◽

Government Control ◽

Multilevel Regression ◽

Traditional Media ◽

Cross Sectional ◽

Internet Media ◽

The Relationship

Availability of alternative information through social media, in particular, and digital media, in general, is often said to induce social discontent, especially in states where traditional media are under government control. But does this relation really exist, and is it generalizable? This article explores the relationship between self-reported online news consumption and protest participation across 48 nations in 2010–2014. Based on multilevel regression models and simulations, the analysis provides evidence that those respondents who reported that they had attended a protest at least once read news online daily or weekly. The study also shows that the magnitude of the effect varies depending on the political context: surprisingly, despite supposedly unlimited control of offline and online media, autocratic countries demonstrated higher effects of online news than transitional regimes, where the Internet media are relatively uninhibited.

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Examining the Effects of the Sacramento Dockless E-Bike Share on Bicycling and Driving

Sustainability ◽

10.3390/su13010368 ◽

2021 ◽

Vol 13 (1) ◽

pp. 368

Author(s):

Dillon T. Fitch ◽

Hossain Mohiuddin ◽

Susan L. Handy

Keyword(s):

Travel Behavior ◽

Regression Models ◽

Population Level ◽

Panel Survey ◽

Multilevel Regression ◽

Combine Data ◽

Cross Sectional ◽

Individual Level ◽

Before And After ◽

Bike Share

One way cities are looking to promote bicycling is by providing publicly or privately operated bike-share services, which enable individuals to rent bicycles for one-way trips. Although many studies have examined the use of bike-share services, little is known about how these services influence individual-level travel behavior more generally. In this study, we examine the behavior of users and non-users of a dockless, electric-assisted bike-share service in the Sacramento region of California. This service, operated by Jump until suspended due to the coronavirus pandemic, was one of the largest of its kind in the U.S., and spanned three California cities: Sacramento, West Sacramento, and Davis. We combine data from a repeat cross-sectional before-and-after survey of residents and a longitudinal panel survey of bike-share users with the goal of examining how the service influenced individual-level bicycling and driving. Results from multilevel regression models suggest that the effect of bike-share on average bicycling and driving at the population level is likely small. However, our results indicate that people who have used-bike share are likely to have increased their bicycling because of bike-share.

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Abbreviated MRI Protocol for the Assessment of Ablated Area in HCC Patients

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18073598 ◽

2021 ◽

Vol 18 (7) ◽

pp. 3598

Author(s):

Vincenza Granata ◽

Roberta Grassi ◽

Roberta Fusco ◽

Sergio Venanzio Setola ◽

Andrea Belli ◽

...

Keyword(s):

Treatment Response ◽

Predictive Value ◽

Random Order ◽

P Value ◽

Liver Imaging ◽

Data Systems ◽

Post Contrast ◽

Conventional Mri ◽

Mri Protocol ◽

Mri Study

Background: Liver Imaging Reporting and Data Systems (LI-RADS) Treatment Response Algorithm (TRA) was created to provide a standardized assessment of hepatocellular carcinoma (HCC) following loco regional therapy. The aim of this study was to compare sensitivity of standard MRI protocol versus abbreviated protocol (only T1-Weigthed fat suppressed (FS) sequences pre- and post-contrast phase) in the detection of ablated area according to LI-RADS Treatment Response (LR-TR) categories. Methods: From January 2015 to June 2020, we selected 64 patients with HCC, who underwent Radiofrequency ablation (RFA) or Microwave ablation (MWA) treatment. According to inclusion criteria, 136 pathologically proven treated HCC (median 2, range 1–3 per patient; mean size 20.0 mm; range 15–30 mm) in 58 patients (26 women, 32 men; median age, 74 years; range, 62–83 years) comprised our study population. For each ablated area, abbreviated protocol, and standard Magnetic Resonance Imaging (MRI) studies were independently and blindly assessed in random order within and between three expert radiologists. Each radiologist assessed the ablated area by using the following categories: “LR-TR Non-viable” = 1; “LR-TR Equivocal” = 2 and “LR-TR Viable” = 0. Results: According to the concordance between MRI and Contrast enhancement ultrasound (CEUS) among 136 treated HCCs, 115 lesions were assessed as non-viable or totally ablate and 21 as viable or partially ablate. The accuracy for standard MRI protocol and abbreviated MRI protocol for predicting pathologic tumor viability of a consensus reading was 98.6% (sensitivity = 100%; specificity = 98.3%; positive predictive value = 91.3% and negative predictive value = 100%). No differences were found in sensitivity or specificity between standard MRI LR-TR viable and abbreviated MRI LR-TR viable categories (p value > 0.05 at McNemar test). Conclusion: The abbreviated dynamic protocol showed similar diagnostic accuracy to conventional MRI study in the assessment of treated HCCs, with a reduction of the acquisition study time of 30% respect to conventional MRI.

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Trends in the prevalence of metabolic syndrome and its components in Mexican adults, 2006-2018

Salud Pública de México ◽

10.21149/12835 ◽

2021 ◽

Vol 63 (6, Nov-Dic) ◽

pp. 713-724

Author(s):

Rosalba Rojas-Martínez ◽

Carlos A Aguilar-Salinas ◽

Martín Romero-Martínez ◽

Lilia Castro-Porras ◽

Donaji Gómez-Velasco ◽

...

Keyword(s):

Cardiovascular Disease ◽

Metabolic Syndrome ◽

Regression Models ◽

Significant Risk ◽

P Value ◽

Logistic Regression Models ◽

Mexican Adults ◽

Diabetes Risk Score ◽

Linear Trends

Objective. To examine trends in the prevalence of metabolic syndrome (MS) and its components. Materials and methods. Data from 27 800 Mexican adults who participated in Ensanut 2006, 2012, 2016 and 2018 were analyzed. Linear regression was used across each Ensanut period to assess temporal linear trends in the prevalence of MS. Logistic regression models were obtained to calculate the percentage change, p-value for the trend and the association between the presence of MS and the risk of developing type 2 diabetes mellitus (T2DM) over 10 years using the Finnish Diabetes Risk Score (FINDRISC) and cardiovascular disease (CVD) using Globorisk. Results. The prevalence of MS in Mexican adults according to the harmonized definition was: 40.2, 57.3, 59.99 and 56.31%, in 2006, 2012, 2016 and 2018 respectively (p for trend <0.0001). In 2018, 7.62% of metabolic syndrome cases had a significant risk for incident DM2 and 11.6% for CVD. Conclusion. It is estimated that there are 36.5 million Mexican adults living with metabolic syndrome, of which 2 million and 2.5 million have a high risk of developing T2DM or cardiovascular disease respectively, over the next 10 years.

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