Tag: statistics

Clin Cancer Res. 2022 Apr 5:clincanres.3375.2021. doi: 10.1158/1078-0432.CCR-21-3375. Online ahead of print.

ABSTRACT

Background The current recommendation for locoregionally advanced nasopharyngeal carcinoma (NPC) patients is cisplatin-based induction (IC) or adjuvant (AC) chemotherapy plus concurrent chemoradiotherapy (CRT). However, data on the optimal platinum doses for each phase of combined regimens are lacking. Patients and Methods 742 NPC patients in the NPC-0501 Trial treated with CRT plus IC/AC and irradiated with intensity-modulated radiotherapy (IMRT) were analyzed. The optimal platinum dose to achieve the best overall survival (OS) in the concurrent and induction/adjuvant phases were studied. Results Evaluation of the whole series shows the optimal platinum dose was 160 mg/m2 in the concurrent and 260 mg/m2 in the induction/adjuvant phase. Repeating the analyses on 591 patients treated with cisplatin throughout (no replacement by carboplatin) confirmed the same results. The cohort with optimal platinum doses in both phases had better OS than the cohort suboptimal in both phases (Stage III: 90% vs 75%, Stage IVA-B: 80% vs 56%, at 5-year). Multivariable analyses confirmed optimal platinum doses in both phases vs. suboptimal dose in each phase are significant independent factors for OS, with hazard ratio of 0.61 (95% confidence interval [CI]=0.41-0.91) and 0.67 (95% CI=0.48-0.94), respectively. Treatment sequence was statistically insignificant after adjusting for platinum doses. Conclusion Both concurrent and IC/AC are needed for locoregionally advanced NPC, even for patients irradiated by IMRT; the concurrent platinum dosage could be set at {greater than or equal to}160 mg/m2 when coupled with adequate induction/adjuvant dosage at {greater than or equal to}260 mg/m2 (or at least {greater than or equal to}240 mg/m2). To achieve these optimal dosages, IC-CRT at conventional fractionation is favored.

PMID:35381064 | DOI:10.1158/1078-0432.CCR-21-3375

PLoS One. 2022 Apr 5;17(4):e0266082. doi: 10.1371/journal.pone.0266082. eCollection 2022.

ABSTRACT

BACKGROUND: Our objective was to assess differences in TB treatment outcomes between individuals who were HIV negative, HIV positive on anti-retroviral treatment (ART) and HIV positive not on ART, at TB treatment initiation at a rural district hospital in Eastern Cape, South Africa.

METHODS: This was a retrospective cohort study of individuals diagnosed with TB between January 2017 and April 2020 at a district hospital. Adults 15 years and over with reported HIV status and treatment outcome were included (N = 711). A categorical outcome with three levels was considered: unfavorable, down referral, and success. We report descriptive statistics for the association between HIV and ART status and treatment outcome using Chi-square and Fisher’s exact tests. A multinomial baseline logit model was used to estimate odds ratios for treatment outcomes.

RESULTS: Overall, 59% of included patients were HIV positive with 75% on ART. Eighty-eight patients 12% had an unfavorable outcome. Half of all patients were down referred with an additional 37% having a successful outcome. Individuals without HIV were more likely to be down referred (versus unfavorable) compared to individuals with untreated HIV (2.90 OR, 1.36, 6.17 95% CI). There was a greater likelihood for individuals without HIV having a successful TB treatment outcome compared to individuals with untreated HIV (4.98 OR, 2.07, 11.25 95% CI).

CONCLUSION: The majority of individuals had positive TB treatment outcomes (down referred or success). However, people without HIV had nearly five times greater odds of having successful outcomes than those with untreated HIV.

PMID:35381042 | DOI:10.1371/journal.pone.0266082

PLoS One. 2022 Apr 5;17(4):e0266533. doi: 10.1371/journal.pone.0266533. eCollection 2022.

ABSTRACT

Mycobacterium avium subsp. paratuberculosis (MAP) causes Johne’s disease in animals with zoonotic potential; it has been linked to many chronic diseases in humans, especially gastrointestinal diseases (GID). MAP has been extensively studied in Europe and America, but little reports were published from Africa. Sudan is a unique country with close contact between humans and livestock. Despite such interaction, the one health concept is neglected in dealing with cases of humans with GID. In this study, patients admitted to the reference GID hospital in the Sudan over a period of 8 months were screened for presence of MAP in their faeces or colonic biopsies. A total of 86 patients were recruited for this study, but only 67 were screened for MAP, as 19 did not provide the necessary samples for analysis. Both real-time PCR and culture were used to detect MAP in the collected samples and the microbial diversity in patients´ faecal samples was investigated using 16S rDNA nanopore sequencing. In total, 27 (40.3%) patients were MAP positive: they were 15 males and 12 females, of ages between 21 and 80 years. Logistic regression analysis revealed no statistical significance for all tested variables in MAP positive patients (occupation, gender, contact with animal, milk consumption, chronic disease, etc.). A unique microbiome profile of MAP-positive patients in comparison to MAP-negative was found. These findings suggest that a considerable proportion of the population could be MAP infected or carriers. Therefore, increase awareness at community level is urgently needed to decrease the risk of MAP at human/animal interface. This study represents the first report of MAP in humans in the Sudan; nevertheless, a better view of the situation of MAP in humans in the country requires a larger study including patients with other conditions.

PMID:35381037 | DOI:10.1371/journal.pone.0266533

PLoS One. 2022 Apr 5;17(4):e0266484. doi: 10.1371/journal.pone.0266484. eCollection 2022.

ABSTRACT

Mapping population distribution at a fine spatial scale is essential for urban studies and planning. Numerous studies, mainly supported by geospatial and statistical methods, have focused primarily on predicting population counts. However, estimating their socio-economic characteristics beyond population counts, such as average age, income, and gender ratio, remains unattended. We enhance traditional population estimation by predicting not only the number of residents in an area, but also their demographic characteristics: average age and the proportion of seniors. By implementing and comparing different machine learning techniques (Random Forest, Support Vector Machines, and Linear Regression) in administrative areas in Singapore, we investigate the use of point of interest (POI) and real estate data for this purpose. The developed regression model predicts the average age of residents in a neighbourhood with a mean error of about 1.5 years (the range of average resident age across Singaporean districts spans approx. 14 years). The results reveal that age patterns of residents can be predicted using real estate information rather than with amenities, which is in contrast to estimating population counts. Another contribution of our work in population estimation is the use of previously unexploited POI and real estate datasets for it, such as property transactions, year of construction, and flat types (number of rooms). Advancing the domain of population estimation, this study reveals the prospects of a small set of detailed and strong predictors that might have the potential of estimating other demographic characteristics such as income.

PMID:35381028 | DOI:10.1371/journal.pone.0266484

PLoS One. 2022 Apr 5;17(4):e0266245. doi: 10.1371/journal.pone.0266245. eCollection 2022.

ABSTRACT

BACKGROUND: Colchicine has been used an effective anti-inflammatory drug to treat gout diseases. Owing to its pharmacodynamic of inhibiting interleukins, it has been repurposed to target the cytokine storm post-SARS-CoV-2 invasion. The goal of this meta-analysis was to evaluate the safety profile of colchicine in COVID-19 patients using the gold-standard randomised-control trials.

METHODS: Electronic databases (Pubmed, Google Scholar, and Cochrane) were systematically searched until June 2021 and RCTs were extracted. Outcomes of interest included all-cause mortality, COVID-19 severity, mechanical ventilation, C-reactive protein and D-dimer levels. Using a random-effects model, dichotomous outcomes were pooled using odds ratios (OR) through the generic inverse variance formula while weighted mean differences were calculated using the Wan’s method. P-values < 0.05 were considered statistically significant for all outcomes.

RESULTS: A total population of 16,048 from five RCTs were included in the analysis. Of this, 7957 were randomized to colchicine, and 8091 received standard care, with an average age of 60.67 years. Colchicine was observed to significantly reduce COVID-19 severity (OR: 0.41, 95% CI [0.22, 0.76]; p = 0.005), and CRP levels (WMD: -19.99, 95% CI [-32.09, -7.89]; p = 0.001). However, there was no significant difference in D-dimer levels (WMD: 0.31, 95% CI [-0.61, 1.23]; p = 0.51), mechanical ventilation (OR: 0.42, 95% CI [0.17, 1.03]; p = 0.06; I2 = 74%) and all-cause mortality (OR: 0.98, 95% CI [0.83, 1.16]; p = 0.84) among patients receiving colchicine or standard care.

CONCLUSION: Colchicine treatment decreased CRP levels and COVID-19 severity, with dimer levels, all-cause mortality and mechanical ventilation remaining seemingly unaffected. Thus, clinical trials need to be carried out that allow effective evaluation of colchicine in COVID-19 patients.

PMID:35381033 | DOI:10.1371/journal.pone.0266245

PLoS One. 2022 Apr 5;17(4):e0266232. doi: 10.1371/journal.pone.0266232. eCollection 2022.

ABSTRACT

BACKGROUND: As of July 2021, there has been more than 185 million documented cases of the novel coronavirus (SARS-CoV-2) infections and more than 4 million deaths globally. Despite more than 90% of documented cases being classified as “recovered” from SARS-CoV-2 infection, a proportion of patients reported a wide variety of persisting symptoms after the initial onset or acute phase of the infection, often referred to as “Long Covid”. As data on the symptomatology of post-acute SARS-CoV-2 infection gradually becomes available, there is an urgent need to organise and synthesise the data in order to define what constitutes Long Covid and assist with its management in clinical and community settings.

METHODS: This protocol follows the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (PRISMA-P) guidelines. A comprehensive literature search strategy will be developed in accordance with the Cochrane highly sensitive search guidelines. The following electronic databases will be searched for studies to include in the systematic review and meta-analysis: MEDLINE (via PubMed), Scopus, Google Scholar, Web of Science (Web of Knowledge), Science direct, EMBASE, Mednar, Psych INFO, and EBSCOhost. Dual screening will be applied at every screening stage. Two reviewers will independently screen titles, abstracts and full text of potentially eligible studies following the predefined inclusion and exclusion criteria in order to select studies to include in the review. As heterogeneity is anticipated between the included studies, data will be pooled in a meta-analysis using a random effects model. A clustering analytic approach will be applied to identify symptoms groupings and assign the symptoms into clusters. R statistical software will be used for the meta-analysis. Highly heterogenous data will be synthesised narratively. The studies will be assessed, for quality using quality assessment tools appropriate for each study design. Two reviewers will independently undertake the quality of studies assessments.

DISSEMINATION PLANS: Findings of the systematic review will be disseminated through a peer-reviewed publication and presentation of findings at conferences, workshops and government and private sector stakeholder engagement meetings.

CLINICAL TRIAL REGISTRATION: PROSPERO registration number: CRD4202126589. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD4202126589.

PMID:35381027 | DOI:10.1371/journal.pone.0266232

PLoS One. 2022 Apr 5;17(4):e0265471. doi: 10.1371/journal.pone.0265471. eCollection 2022.

ABSTRACT

When dealing with longitudinal data, linear mixed-effects models (LMMs) are often used by researchers. However, LMMs are not always the most adequate models, especially if we expect a nonlinear relationship between the outcome and a continuous covariate. To allow for more flexibility, we propose the use of a semiparametric mixed-effects model to evaluate the overall treatment effect on the hemodynamic responses during bone graft healing and build a prediction model for the healing process. The model relies on a closed-form expectation-maximization algorithm, where the unknown nonlinear function is estimated using a Lasso-type procedure. Using this model, we were able to estimate the effect of time for individual mice in each group in a nonparametric fashion and the effect of the treatment while accounting for correlation between observations due to the repeated measurements. The treatment effect was found to be statistically significant, with the autograft group having higher total hemoglobin concentration than the allograft group.

PMID:35381007 | DOI:10.1371/journal.pone.0265471

PLoS One. 2022 Apr 5;17(4):e0266010. doi: 10.1371/journal.pone.0266010. eCollection 2022.

ABSTRACT

Spatial event data is heavily used in contemporary research on political violence. Such data are oftentimes mapped onto grid-cells or administrative regions to draw inference about the determinants of conflict intensity. This setup can identify geographic determinants of violence, but is also prone to methodological issues. Problems resulting from spatial aggregation and dependence have been raised in methodological studies, but are rarely accounted for in applied research. As a consequence, we know little about the empirical relevance of these general problems and the trustworthiness of a popular research design. We address these questions by simulating conflict events based on spatial covariates from seven high-profile conflicts. We find that standard designs fail to deliver reliable inference even under ideal conditions at alarming rates. We also test a set of statistical remedies which strongly improve the results: Controlling for the geographic area of spatial units eliminates an important source of spurious correlation. In time-series analyses, the same result can be achieved with unit-level fixed effects. Under outcome diffusion, spatial lag models with area controls produce most reliable inference. When those are computationally intractable, geographically larger aggregations lead to similar improvements. Generally, all analyses should be performed at two separate levels of geographic aggregation. To facilitate future research into geographic methods, we release the Simple Conflict Event Generator (SCEG) developed for this analysis.

PMID:35381020 | DOI:10.1371/journal.pone.0266010

PLoS One. 2022 Apr 5;17(4):e0264626. doi: 10.1371/journal.pone.0264626. eCollection 2022.

ABSTRACT

BACKGROUND: There was limited data on treatment outcomes among patients with diabetic ketoacidosis (DKA) in Ethiopia.

OBJECTIVE: The aim of the study was to determine the treatment outcomes of DKA patients attending Debre Tabor General Hospital.

METHOD: A retrospective study was conducted at Debre Tabor General Hospital and data were collected from June 1 to June 30 of 2018. Participants included in the study were all diabetic patients with DKA admitted from August 2010 to May 31, 2018. The primary outcomes were the treatment outcomes of DKA including (in-hospital glycemic control, the length of hospital stay and in-hospital mortality). The statistical analysis was carried out using Statistical Package for Social Sciences (SPSS) version 22. Descriptive statistics was presented in the form of means with standard deviation and binary regression was conducted to determine factors that affect length of hospital stay among DKA patients.

RESULT: 387 patients were included in the study. The mean age of patients was 33.30± 14.96 years. The most common precipitating factor of DKA was new onset diabetes mellitus 150(38.8%). The mean length of hospital stay was 4.64(±2.802) days. The mean plasma glucose at admission and discharge was 443.63(±103.33) and 172.94 (±80.60) mg/dL, respectively. The majority 370 (95.60%) of patients improved and discharged whereas 17 (4.40%) patients died in the hospital. Patients with mild and moderate DKA showed short hospital stay; AOR: 0.16 [0.03-0.78] and AOR:0.17[0.03-0.96] compared with severe DKA. Diabetic ketoacidosis precipitated by infection were nearly five times more likely to have long hospital stay than DKA precipitated by other causes; AOR: 4.59 [1.08-19.42]. In addition, serum glucose fluctuation during hospitalization increased the likelihood of long hospital stay, AOR: 2.15[1.76-2.63].

CONCLUSIONS: New onset type 1 diabetes was the major precipitating factor for DKA. Admitted DKA patients remained in hospital for a duration of approximately five days. About five out of hundred DKA patients ended up with death in the hospital. Infection, serum glucose fluctuations and severity of DKA were determinants of long hospital stay. Early prevention of precipitating factors and adequate management of DAK are warranted to reduce length of hospital stay and mortality.

PMID:35381004 | DOI:10.1371/journal.pone.0264626

J Behav Addict. 2022 Apr 4. doi: 10.1556/2006.2022.00009. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Data regarding the association between ultra-processed food (UPF) consumption and eating disorders (ED) are scarce. Our aim was to investigate whether UPF intake was associated with different ED types in a large population-based study.

METHODS: 43,993 participants (mean age = 51.0 years; 76.1% women) of the French NutriNet-Santé web-cohort who were screened for ED in 2014 via the Sick-Control-One stone-Fat-Food (SCOFF) questionnaire, were included in the analysis. The clinical algorithm Expali TM tool was used to identify four ED types: restrictive, bulimic, binge eating, and other (not otherwise specified). Mean dietary intake was evaluated from at least 2 self-administered 24-h dietary records (2013-2015); categorization of food as ultra-processed or not relied on the NOVA classification. The associations between UPF intake (as percent and reflecting mean daily UPF quantity (g/d) within the dietary intake, %UPF) and ED types were evaluated using polytomous logistic regression models.

RESULTS: 5,967 participants (13.6%) were categorized as likely ED (restrictive n = 444; bulimic n = 1,575; binge eating n = 3,124; other ED n = 824). The fully-adjusted analyses revealed a positive association between UPF intake and bulimic, binge eating, and other ED: ED risk (odds ratio, OR) for an absolute 10-percentage point incremental increase in %UPF intake were 1.08 (1.01-1.14; P = 0.02), 1.21 (1.16-1.26; P < 0.0001), and 1.11 (1.02-1.20; P = 0.02), respectively. No significant association was detected for restrictive ED.

DISCUSSION AND CONCLUSION: This study revealed an association of UPF intake with different ED types among French adults. Future research is needed to elucidate the direction of the observed associations.

PMID:35380986 | DOI:10.1556/2006.2022.00009