Category: Statistics

Chron Respir Dis. 2022 Jan-Dec;19:14799731221104099. doi: 10.1177/14799731221104099.

ABSTRACT

Quality of life (QOL) in patients with Chronic obstructive pulmonary disease (COPD) is a major global concern in respiratory care with the specific instruments used rarely being developed using a modular approach. This paper is aimed to develop the COPD scale of the system of QOL Instruments for Chronic Diseases (QLICD-COPD) by the modular approach based on Classical Test Theory and Generalizability Theory (GT). 114 inpatients with COPD were used to provide the data measuring QOL three times before and after treatments. The psychometric properties of the scale were evaluated with respect to validity, reliability and responsiveness employing correlation analysis, factor analyses, multi-trait scaling analysis, and also GT analysis. The Results showed that Multi-trait scaling analysis, correlation and factor analyses confirmed good construct validity and criterion-related validity with almost all correlation coefficients or factor loadings being above 0.40. The internal consistency α and test-retest reliability coefficients (Pearson r and Intra-class correlations ICC) for all domains except for the social domain were larger than 0.70, ranging between 0.70-0.86 with r = 0.85 for the overall. The overall score and scores for physical and the specific domains had statistically significant changes after treatments with moderate effect size SRM (standardized response mean) ranging from 0.32 to 0.44. All G-coefficients and index of dependability were all greater than 0.80 exception of social domain (0.546 and 0.500 respectively), confirming the reliability of the scale further. It concluded that the QLICD-COPD has good validity, reliability, and moderate responsiveness, and can be used as the QOL instrument for patients with COPD.

PMID:36000309 | DOI:10.1177/14799731221104099

J Med Virol. 2022 Aug 24. doi: 10.1002/jmv.28085. Online ahead of print.

ABSTRACT

OBJECTIVES: To summarize the clinical characteristics and explore the role of treatment types in outcomes among psoriasis patients with Coronavirus Disease 2019 (COVID-19).

METHODS: The principal summary measures used were pooled prevalence and risk ratio (RR) with 95% confidential interval (CI). R statistic software was used for all the analysis.

RESULTS: A total of 19 studies including 4073 psoriasis patients with COVID-19 were eligible for the meta-analysis. The overall hospitalization rate is about 20.2% (95% CI, 12.7% – 28.7%), and changed to be 18.0 (95% CI, 9.9% – 27.6%) or 14.1 (95% CI, 5.9% – 24.6%) after systemic or biologic treatment. Moreover, the overall fatality rate is 1.5% (95% CI, 0.4% – 3.0%), and turned to be 0.7 (95% CI, 0 – 2.0%) or 0.5 (95% CI, 0 – 2.2%) after systemic or biologic therapy. Notably, a lower hospitalization risk ratio was found in patients receiving biologic therapy than those receiving other treatments (RR = 0.62, 95%CI, 0.42-0.94). The results were consistent after sensitivity analysis and trim-and-fill analysis.

CONCLUSIONS: Systemic, especially biologic therapy could lessen the clinical severity in psoriasis patients with COVID-19. Our finding will help to guide current recommendations and provide a reference for clinical decision-making. This article is protected by copyright. All rights reserved.

PMID:36000295 | DOI:10.1002/jmv.28085

Biostatistics. 2022 Aug 24:kxac036. doi: 10.1093/biostatistics/kxac036. Online ahead of print.

ABSTRACT

Set-based association tests are widely popular in genetic association settings for their ability to aggregate weak signals and reduce multiple testing burdens. In particular, a class of set-based tests including the Higher Criticism, Berk-Jones, and other statistics have recently been popularized for reaching a so-called detection boundary when signals are rare and weak. Such tests have been applied in two subtly different settings: (a) associating a genetic variant set with a single phenotype and (b) associating a single genetic variant with a phenotype set. A significant issue in practice is the choice of test, especially when deciding between innovated and generalized type methods for detection boundary tests. Conflicting guidance is present in the literature. This work describes how correlation structures generate marked differences in relative operating characteristics for settings (a) and (b). The implications for study design are significant. We also develop novel power bounds that facilitate the aforementioned calculations and allow for analysis of individual testing settings. In more concrete terms, our investigation is motivated by translational expression quantitative trait loci (eQTL) studies in lung cancer. These studies involve both testing for groups of variants associated with a single gene expression (multiple explanatory factors) and testing whether a single variant is associated with a group of gene expressions (multiple outcomes). Results are supported by a collection of simulation studies and illustrated through lung cancer eQTL examples.

PMID:36000269 | DOI:10.1093/biostatistics/kxac036

J Biopharm Stat. 2022 Jul 4;32(4):567-581. doi: 10.1080/10543406.2022.2080692. Epub 2022 Jun 15.

ABSTRACT

In oncology drug development, indication selection and optimal dose identification are the primary objectives for the early phase of clinical trials and could significantly impact the probability of success. Master protocols, e.g., basket trial, umbrella trial, and platform trial, have become popular in practice considering the connection of trial designs with multiple indications and treatment candidates. They also enable the optimization of operational resources and maximize the capability of data-driven decision-making. However, most of the available designs are developed with the efficacy endpoint only for treatment effect estimation and testing, without consideration of the safety end point. Thus, it often lacks a comprehensive quantitative framework to allow optimal treatment selection, which could put future development at risk. We propose an optimal Bayesian platform trial design with multiple end points (PMED) to characterize the overall benefit-risk profile. The design is further extended to allow treatment and indication selection within and across arms, with continuous monitoring on multiple interim analyses for futility. In addition, we propose dynamic borrowing across arms to increase the efficiency and accuracy of estimation given the level of similarity across arms. A hierarchical hypothesis structure is utilized to achieve optimal indication and treatment combination selection by controlling family-wise error. Through simulation studies, we show that PMED is a robust design under the studied scenarios with superb power and controlled family-wise error rate.

PMID:36000260 | DOI:10.1080/10543406.2022.2080692

J R Soc Interface. 2022 Aug;19(193):20220361. doi: 10.1098/rsif.2022.0361. Epub 2022 Aug 24.

ABSTRACT

UK grasslands perform important environmental and economic functions, but their future productivity under climate change is uncertain. Spring hay yields from 1902 to 2016 at one site (the Park Grass Long Term Experiment) in southern England under four different fertilizer regimes were modelled in response to weather (seasonal temperature and rainfall). The modelling approach applied comprised: (1) a Bayesian model comparison to model parametrically the heteroskedasticity in a gamma likelihood function; (2) a Bayesian varying intercept multiple regression model with an autoregressive lag one process (to incorporate the effect of productivity in the previous year) of the response of hay yield to weather from 1902 to 2016. The model confirmed that warmer and drier years, specifically, autumn, winter and spring, in the twentieth and twenty-first centuries reduced yield. The model was applied to forecast future spring hay yields at Park Grass under different climate change scenarios (HadGEM2 and GISS RCP 4.5 and 8.5). This application indicated that yields are forecast to decline further between 2020 and 2080, by as much as 48-50%. These projections are specific to Park Grass, but implied a severe reduction in grassland productivity in southern England with climate change during the twenty-first century.

PMID:36000226 | DOI:10.1098/rsif.2022.0361

Foot Ankle Spec. 2022 Aug 23:19386400221116467. doi: 10.1177/19386400221116467. Online ahead of print.

ABSTRACT

BACKGROUND: The objective of this study was to evaluate return to activity following flatfoot reconstruction with lateral column lengthening (LCL) by assessing functional postoperative data and identifying patient characteristics associated with poor function following surgery.

METHODS: Consecutive patients that underwent operative flatfoot correction including LCL and other necessary procedures from 2014 to 2019 by 3 fellowship trained foot and ankle orthopedic surgeons were retrospectively administered Foot and Ankle Ability Measure (FAAM) Activities of Daily Living (ADL) and FAAM Sports questionnaires with no preoperative scoring available. Patient demographic factors, comorbidities, and radiographic features were evaluated as predictors of outcome scores to simulate return to activity. Statistical analysis, including student’s t-tests and analysis of variance, was performed.

RESULTS: A total of 54 patients were included. A body mass index (BMI) of 30 kg/m² or greater was associated with a lower ADL score (P = .002) and Sports score (P = .002). Preoperative hindfoot valgus of 9° or higher was associated with higher ADL scores (P = .040). Neither age nor any flatfoot radiographic parameters yielded significant differences in functional scores.

CONCLUSION: This study demonstrated relatively high average FAAM scores in both the ADL and the sports subscales, consistent with previous studies. This study also identified lower BMI and greater preoperative hindfoot valgus as potential predictors of improved functional outcome following reconstruction.

LEVEL OF EVIDENCE: Level III: Retrospective case control.

PMID:36000219 | DOI:10.1177/19386400221116467

Acta Clin Belg. 2022 Aug 24:1-9. doi: 10.1080/17843286.2022.2114678. Online ahead of print.

ABSTRACT

OBJECTIVES: The aim of this study was to examine the effects of comprehensive cardiac rehabilitation (CCR) in patients after acute coronary syndrome (ACS) resolved by percutaneous coronary intervention (PCI) on left ventricular diastolic dysfunction (LVDD) and to extract the parameters that have the greatest influence on LVDD improvement.

METHODS: The study included 85 subjects who were divided into intervention (N = 56) and control (N = 29) groups depending on CCR attendance. Initially and after 12 weeks, patients of both groups were subjected to echocardiography to assess LVDD, as well as CPET to assess improvement in functional capacity.

RESULTS: The study showed that 23 patients (27.1%) of both groups demonstrated the improvement of LVDD degree. The improvement of the LVDD degree in the intervention group was significant, whereas in the control group, it did not change (a one-degree improvement in 22 (39.3%) patients of the intervention group (p < 0.001) and only 1 (3.4%) (p > 0.05) in the control group). Multivariate binary logistic regression showed that key parameters in LVDD improvement were participation in the CCR, E/A ratio and haemoglobin value. We created a model, for prediction of LVDF improvement, with a cut-off value of 33 (area = 0.9, p < 0.0005), a sensitivity of 87.0% and a specificity of 85.5%.

CONCLUSIONS: CCR can be used as an effective non-pharmacological measure to improve LVDD and functional capacity in patients after ACS. The statistical model may have practical application in prediction of clinical benefit in such a group of patients.

PMID:36000216 | DOI:10.1080/17843286.2022.2114678

Health Econ. 2022 Aug 23. doi: 10.1002/hec.4581. Online ahead of print.

ABSTRACT

This paper estimates the impact of Daylight Saving Time (DST) on deaths from suicide and substance abuse in the United States. Using Multiple Cause-of-Death Mortality Data from the National Vital Statistics System of the National Center for Health Statistics from 1979 to 1988, the effect is identified in two ways: a regression discontinuity design that exploits discrete time changes in the Spring and Fall; and a fixed effects model that uses a policy change and a switching mechanism that introduces random variation to DST’s start and end dates. This is one of the first attempts to estimate the impact of DST on deaths due to suicide and substance abuse and the first to use either identification strategy. The results from both methods suggest that the sleep disruptions during the Spring transition cause the suicide rate to rise by 6.25 percent and the death rate from suicide and substance abuse combined to increase by 6.59 percent directly after the time change. There is no evidence for any change in these outcomes during the Fall transition. The contrasting results from Spring to Fall suggest the entire effect can be attributed to disruptions in sleep patterns rather than changes in ambient light exposure.

PMID:36000150 | DOI:10.1002/hec.4581

Clin Teach. 2022 Aug 23:e13523. doi: 10.1111/tct.13523. Online ahead of print.

ABSTRACT

BACKGROUND: Although the ubiquitous presence of ambiguity and uncertainty in medical practice is widely acknowledged, a greater understanding of contextual factors for educators to consider in helping students learn to respond to ambiguity and uncertainty adaptively is needed. Drawing on self-determination theory, the purpose of this study was to explore the unique roles of basic psychological needs-autonomy, competence and relatedness-in medical students’ tolerance of ambiguity and uncertainty.

METHODS: This was a cross-sectional survey study of third-year medical students (n = 70) at a large Canadian university. In regression analysis, the three basic psychological needs were entered as predictors of medical students’ tolerance of ambiguity and uncertainty while controlling for students’ age and gender.

RESULTS: Of the three needs, the need for competence was determined to be statistically significant in relation to students’ tolerance of ambiguity and uncertainty (β = 0.326; p = 0.038). The needs for autonomy and relatedness were determined to be not statistically significant (β = -0.170; p = 0.274 and β = 0.154; p = 0.218, respectively).

DISCUSSION: We observed that medical students, who experienced satisfaction of the need for competence in the learning environment, reported greater tolerance of ambiguity and uncertainty. Potential implications for medical education are discussed, based on self-determination theory.

PMID:36000148 | DOI:10.1111/tct.13523

Cureus. 2022 Jul 21;14(7):e27107. doi: 10.7759/cureus.27107. eCollection 2022 Jul.

ABSTRACT

BACKGROUND: Infection has been a major cause of morbidity and mortality in systemic lupus erythematosus (SLE) patients. One of the infections encountered in SLE patients is candidiasis. Therefore, we aimed to conduct a case-control study to explore the risk factors associated with candidiasis in SLE patients in our center.

METHODS: Medical records of 20 SLE patients with fungal infection were obtained, and a case-control study was conducted with an age and sex-matched control group of 20 patients. Data were obtained from the Cipto Mangunkusumo National General Hospital. SLE confirmatory diagnosis was based on Systemic Lupus Erythematosus International Collaborating Clinics (SLICC) 2012 criteria. Patients with comorbidities of various chronic diseases (diabetes, HIV, and chronic kidney disease) were excluded. Statistical analysis was conducted using the Mann-Whitney U test with statistical significance defined as a p-value < 0.05.

RESULT: Based on the analysis, a maximum corticosteroid dose of 24 (4-250) mg/day for the last one year was associated with the development of fungal infection (p = 0.047). Lower absolute lymphocyte count (748 cells/mm³ versus 1635 cells/mm³) was also associated with the occurrence of candidiasis in SLE patients (p = 0.008).

CONCLUSION: Physicians should be aware that corticosteroid use in SLE patients may cause candidiasis. Monitoring of maximum corticosteroid dose and absolute lymphocyte count is important to help prevent candidiasis. Patients should also be educated regarding the risk of candidiasis from corticosteroid use.

PMID:36000133 | PMC:PMC9391667 | DOI:10.7759/cureus.27107