Tag: statistics

JCO Precis Oncol. 2022 Oct;6:e2200323. doi: 10.1200/PO.22.00323.

ABSTRACT

PURPOSE: Clinical genomic testing is increasingly being used to direct pediatric cancer care. Many centers are interested in offering testing of tumors and paired germline tissues at or near the time of cancer diagnosis. We conducted this study to better understand parent preferences surrounding timing and content of consent conversations for clinical germline genetic testing of their children with cancer as a part of real-time cancer care.

PATIENTS AND METHODS: A seven-question survey developed by the Division of Cancer Predisposition and collaborators at St Jude Children’s Research Hospital (St Jude) was distributed to members of the St Jude Patient Family Advisory Council, which included parents of childhood cancer survivors and bereaved parents whose children with cancer had died. Parents were asked to provide free text comments after each question. Qualitative methods were used to derive codes from parent comments, and survey results were depicted using descriptive statistics.

RESULTS: The survey was completed by 172 parents. Ninety-three (54%) endorsed an approach for consent conversations ≥ 1 month after cancer diagnosis, whereas 58 (34%) endorsed an approach at 1-2 weeks and 21 (12%) at 1-2 days. Needing time to adjust to a new or relapsed cancer diagnosis and feeling overwhelmed were frequent themes; however, parents acknowledged the urgency and importance of testing. Parents desired testing of as many cancer-related genes as possible, with clinical utility the most important factor for proceeding with testing. Most parents (75%) desired germline results to be disclosed in person, preferably by a genetic counselor.

CONCLUSION: Parents described urgency and benefits associated with germline testing, but desired flexibility in timing to allow for initial adjustment after their child’s cancer diagnosis.

PMID:36265116 | DOI:10.1200/PO.22.00323

Arch Prev Riesgos Labor. 2022 Jul 15;25(3):259-270. doi: 10.12961/aprl.2022.25.03.03.

ABSTRACT

INTRODUCTION: To design and validate a scale of perception of teleworking in Peruvian primary schoolteachers.

METHOD: This was a cross-sectional study of 400 primary schoolteachers (61.5% women) between 21 and 61 years of age, from six cities in Peru. Eight items were proposed, corresponding to indicators of training, safety, and flexibility of schedules, derived from the scientific literature. The scale was validated by seven experts who evaluated the relevance, representativeness and clarity of the items. Subsequently, we applied exploratory f (EFA) and confirmatory factor analysis (CFA), using the FACTOR Analysis program and SPSS AMOS version 21.

RESULTS: The Aiken V indicators were statistically significant for the eight items. Before running the AFE, we calculated the KMO coefficient (0.93) and Bartlett’s test (1832.9; gl = 28; p = 0.00). A single factor explained 62.27% of the total variance of the scale and its factor loadings ranged from 0.65 to 0.84. The CFA corroborated the internal structure of the scale (?2 = 58.24, df = 20, p < 0.01; RMR = 0.03; TLI = 0.97; CFI = 0.97; and RMSEA = 0.06) and the reliability was acceptable (? = 0.93; 95% CI = 0.89 – 0.92).

CONCLUSIONS: The scale demonstrates evidence of content-based validity, internal structure and reliability.

PMID:36265110 | DOI:10.12961/aprl.2022.25.03.03

Arch Prev Riesgos Labor. 2022 Jul 15;25(3):285-299. doi: 10.12961/aprl.2022.25.03.05.

ABSTRACT

AIM: To analyse the psychometric properties of the demand scales of the UNIPSICO questionnaire in in Valencian / Catalan language.

METHOD: The sample consisted of 2114 participants from public administration centres of Generalitat Valenciana in Valencia. Data were collected using the UNIPSICO questionnaire, which is grouped into six scales that measure psychosocial risk factors related to job demands (33 items): role conflict (5 items), role ambiguity (5 items), workload (6 items), interpersonal conflicts (6 items), inequity in social exchanges (5 items), and work-family and family-work conflict (6 items). We performed confirmatory factor analysis (CFA) and measured Cronbach alpha and McDonald omega coefficients for the scales.

RESULTS: All items had adequate statistical and psychometric values. The six-factor model that reproduces the original structure of the questionnaire presented an adequate fit to the data, and gender invariance. The Cronbach alpha and McDonald omega coefficients were acceptable for the six scales of the instrument.

CONCLUSIONS: These results contribute to the psychometric validation of the questionnaire and allow us to conclude that the demand scales of the UNIPSICO questionnaire translated to Valencian / Catalan language are reliable and possess construct validity for the assessment of psychosocial risk factors in government employees.

PMID:36265108 | DOI:10.12961/aprl.2022.25.03.05

Prev Chronic Dis. 2022 Oct 20;19:E65. doi: 10.5888/pcd19.220113.

ABSTRACT

INTRODUCTION: Breast cancer affects 1 in 8 women in the US and is the most frequently diagnosed cancer in women. In South Dakota, 102 women die from breast cancer each year. We assessed which sociodemographic factors contributed to mortality rates in South Dakota and used spatial analysis to investigate how counties’ observed age-adjusted mortality rates compared with expected rates.

METHODS: We computed standardized incidence ratios (SIRs) of all counties in South Dakota by using the age-adjusted mortality rates, the 2000 US standard population, and the South Dakota estimated population. We used a linear regression model to identify sociodemographic factors associated with breast cancer mortality rates and to compute a new SIR value, after controlling for relevant factors.

RESULTS: Educational level and breast cancer incidence rates were significantly associated with breast cancer mortality rates at the county level. The SIR values based on age-adjusted counts showed which counties had more deaths due to breast cancer than what might be expected using South Dakota as the reference population. After controlling for sociodemographic factors, the range of SIR values decreased and had lower variability.

CONCLUSION: The regression model helped identify factors associated with mortality and provided insights into which risk factors are at play in South Dakota. This information, in combination with the spatial distribution of mortality by county, can be used to help allocate resources to the counties in South Dakota that need them most.

PMID:36265079 | DOI:10.5888/pcd19.220113

J Am Chem Soc. 2022 Oct 20. doi: 10.1021/jacs.2c09120. Online ahead of print.

ABSTRACT

The catalysis by a π-allyl-Co/Ni complex has drawn significant attention recently due to its distinct reactivity in reductive Co/Ni-catalyzed allylation reactions. Despite significant success in reaction development, the critical oxidative addition mechanism to form the π-allyl-Co/Ni complex remains unclear. Herein, we present a study to investigate this process with four catalysis-relevant complexes: Co(^MeBPy)Br₂, Co(^MePhen)Br₂, Ni(^MeBPy)Br₂, and Ni(^MePhen)Br₂. Enabled by an electroanalytical platform, Co(I)/Ni(I) species were found responsible for the oxidative addition of allyl acetate. Kinetic features of different substrates were characterized through linear free-energy relationship (Hammett-type) studies, statistical modeling, and a DFT computational study. In this process, a coordination-ionization-type transition state was proposed, sharing a similar feature with Pd(0)-mediated oxidative addition in Tsuji-Trost reactions. Computational and ligand structural analysis studies support this mechanism, which should provide key information for next-generation catalyst development.

PMID:36265077 | DOI:10.1021/jacs.2c09120

J Appl Clin Med Phys. 2022 Oct 20:e13793. doi: 10.1002/acm2.13793. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: For postoperative breast cancer patients, deformable image registration (DIR) is challenged due to the large deformations and non-correspondence caused by tumor resection and clip insertion. To deal with it, three metrics (fiducial-, region-, and intensity-based) were jointly used in DIR algorithm for improved accuracy.

MATERIALS AND METHODS: Three types of metrics were combined to form a single-objective function in DIR algorithm. Fiducial-based metric was used to minimize the distance between the corresponding point sets of two images. Region-based metric was used to improve the overlap between the corresponding areas of two images. Intensity-based metric was used to maximize the correlation between the corresponding voxel intensities of two images. The two CT images, one before surgery and the other after surgery, were acquired from the same patient in the same radiotherapy treatment position. Twenty patients who underwent breast-conserving surgery and postoperative radiotherapy were enrolled in this study.

RESULTS: For target registration error, the difference between the proposed and the conventional registration methods was statistically significant for soft tissue (2.06 vs. 7.82, p = 0.00024 < 0.05) and body boundary (3.70 vs. 6.93, p = 0.021 < 0.05). For visual assessment, the proposed method achieved better matching result for soft tissue and body boundary.

CONCLUSIONS: Comparing to the conventional method, the registration accuracy of the proposed method was significantly improved. This method provided a feasible way for target volume delineation of tumor bed in postoperative radiotherapy of breast cancer patients.

PMID:36265074 | DOI:10.1002/acm2.13793

JMIR Med Inform. 2022 Sep 7. doi: 10.2196/35622. Online ahead of print.

ABSTRACT

BACKGROUND: The Covid-19 disease has multiple symptoms, being anosmia, varying from 75-95%, and ageusia, varying from 50-80% of infected patients, the most prevalent ones. An automatic assessment tool for these symptoms will help monitor the disease in a fast and non-invasive manner.

OBJECTIVE: We hypothesized that people with Covid-19 experiencing anosmia and ageusia had different voice features than those without such symptoms. Our objective was to develop an artificial intelligence pipeline to identify and internally validate a vocal biomarker of these symptoms for remotely monitoring them.

METHODS: This study is made on population-based data. Participants were assessed daily through an online questionnaire and asked to register two different types of voice recordings, they were adults (older than 18 years old) that were confirmed by a PCR test to be positive for Covid-19 in Luxembourg and that passed through the exclusion criteria. Statistical methods like Recursive Feature Elimination (RFE) for dimensionality reduction, multiple statistical learning methods, and hypothesis tests were used throughout this study. The TRIPOD Prediction Model Development checklist was used to structure the research.

RESULTS: This study included 259 participants. Young (<35 years old) and females showed a higher rate of ageusia and anosmia. Participants were 41 (SD = 13) years old on average and the dataset was balanced for sex (134 females (52%) and 125 males (48%) out of 259). The analyzed symptom was present in 94 out of 259 (36%) participants of the population and in 450 out of 1636 (28%) audio recordings. Two machine learning models were built, one for Android and one for iOS devices and both had high accuracy, being 88% for Android and 85% for iOS. The final biomarker was then calculated using these models and internally validated.

CONCLUSIONS: This study demonstrates that people with Covid-19 who have anosmia and ageusia have different voice features from those without it. Upon further validation, these vocal biomarkers could be nested in digital devices to improve symptom assessment in clinical practice and enhance telemonitoring of Covid-19-related symptoms.

CLINICALTRIAL: Approved by the National Research Ethics Committee of Luxembourg (study number 202003/07) in April 2020 and is registered Clinicaltrials.gov NCT04380987, https://clinicaltrials.gov/ct2/show/NCT04380987.

PMID:36265042 | DOI:10.2196/35622

JMIR Form Res. 2022 Sep 22. doi: 10.2196/38562. Online ahead of print.

ABSTRACT

BACKGROUND: The COVID-19 pandemic has greatly boosted working from home as a way of working, which is likely to continue for most companies in the future, either in fully remote or hybrid form. To manage stress levels in employees working from home, insights into the stressors and de-stressors in a home office first need to be studied. We present an international remote study with employees working from home by making use of state-of-the-art technology, i.e. smartwatches and questionnaires through smartphones.

OBJECTIVE: Firstly, to determine stressors and de-stressors in people working from home. Secondly, to identify smartwatch measurements that could represent these stressors and de-stressors.

METHODS: Employees working from home from three regions of the world (United States, United Kingdom, and Hong Kong) were asked to wear a smartwatch continuously for seven days, fill in five questionnaires each day and two additional questionnaires before and after the measurement week. The entire study was done remotely. Univariate statistical analyses comparing variable distributions between low and high stress levels were followed by multivariate analysis using logistic regression, considering multicollinearity by using Variance Inflation Factor filtering.

RESULTS: A total of 202 people participated, with 198 participants finishing the experiment. Stressors found are other people and daily life getting in the way of work (P=.05), job intensity (P=.007), a history of burn-out (P=.03), anxiety towards the pandemic (P=.04) and environmental noise (P=.008). De-stressors found are access to sunlight (P=.02) and fresh air (P<.001) during the workday and going outdoors (P<.001), having breaks (P<.001), exercising (P<.001), and having social interactions (P<.001). The smartwatch measurements positively related to stress were number of active intensity periods (P<.001), number of highly active intensity periods (P=.04), steps (P<.001) and the standard deviation in heart rate (P<.001). In a multivariate setting only history of burn-out (P<.001) and family and daily life getting in way of work (P<.001) were positively associated with stress, while self-reports of social activities (P<.001) and going outdoors (P=.03) were negatively associated with stress. Stress prediction models based on questionnaire data had similar performance (F1=.51) compared to models based on automatic measurable data alone (F1=.47).

CONCLUSIONS: The results show that there are stressors and de-stressors when working from home that should be considered when managing stress in employees. Some of these stressors and de-stressors are (in)directly measurable with unobtrusive sensors, and prediction models based on this data show promising results for the future of automatic stress detection and management.

CLINICALTRIAL: This study is registered under Registration ID NL9378 in the Dutch Trial Register (NTR).

PMID:36265030 | DOI:10.2196/38562

PLoS One. 2022 Oct 20;17(10):e0276313. doi: 10.1371/journal.pone.0276313. eCollection 2022.

ABSTRACT

BACKGROUND: The XRCC3 p.Thr241Met (rs861539) polymorphism has been extensively studied for its association with glioma risk, but results remain conflicting. Therefore, we performed a systematic review and meta-analysis to resolve this inconsistency.

METHODS: Studies published up to June 10, 2022, were searched in PubMed, Web of Science, Scopus, VIP, Wanfang, and China National Knowledge Infrastructure databases and screened for eligibility. Then, the combined odds ratio (OR) of the included studies was estimated based on five genetic models, i.e., homozygous (Met/Met vs. Thr/Thr), heterozygous (Thr/Met vs. Thr/Thr), dominant (Thr/Met + Met/Met vs. Thr/Thr), recessive (Met/Met vs. Thr/Thr + Thr/Met) and allele (Met vs. Thr). The study protocol was preregistered at PROSPERO (registration number: CRD42021235704).

RESULTS: Overall, our meta-analysis of 14 eligible studies involving 12,905 subjects showed that the p.Thr241Met polymorphism was significantly associated with increased glioma risk in both homozygous and recessive models (homozygous, OR = 1.381, 95% CI = 1.081-1.764, P = 0.010; recessive, OR = 1.305, 95% CI = 1.140-1.493, P<0.001). Subgroup analyses by ethnicity also revealed a statistically significant association under the two aforementioned genetic models, but only in the Asian population and not in Caucasians (P>0.05).

CONCLUSION: We demonstrated that the XRCC3 p.Thr241Met polymorphism is associated with an increased risk of glioma only in the homozygous and recessive models.

PMID:36264998 | DOI:10.1371/journal.pone.0276313

PLoS One. 2022 Oct 20;17(10):e0276210. doi: 10.1371/journal.pone.0276210. eCollection 2022.

ABSTRACT

The Equilibrium Optimizer (EO) is a recently proposed intelligent optimization algorithm based on mass balance equation. It has a novel principle to deal with global optimization. However, when solving complex numerical optimization problems and engineering problems, the algorithm will get stuck into local optima and degrade accuracy. To address the issue, an improved Equilibrium Optimizer (IEO) based on multi-strategy optimization is proposed. First, Tent mapping is used to generate the initial location of the particle population, which evenly distributes the particle population and lays the foundation for diversified global search process. Moreover, nonlinear time parameter is used to update the position equation, which dynamically balances the exploration and exploitation phases of improved algorithm. Finally, Lens Opposition‑based Learning (LOBL) is introduced, which avoids local optimization by improving the population diversity of the algorithm. Simulation experiments are carried out on 23 classical functions, IEEE CEC2017 problems and IEEE CEC2019 problems, and the stability of the algorithm is further analyzed by Friedman statistical test and box plots. Experimental results show that the algorithm has good solution accuracy and robustness. Additionally, six engineering design problems are solved, and the results show that improved algorithm has high optimization efficiency achieves cost minimization.

PMID:36264991 | DOI:10.1371/journal.pone.0276210