Category: Statistics

Jpn J Clin Oncol. 2021 Sep 8:hyab142. doi: 10.1093/jjco/hyab142. Online ahead of print.

ABSTRACT

OBJECTIVES: To investigate the prognostic impact of tumor burden in patients receiving nivolumab plus ipilimumab as first-line therapy for previously untreated metastatic renal cell carcinoma (mRCC).

METHODS: We retrospectively evaluated 62 patients with IMDC intermediate- or poor-risk mRCC, treated with nivolumab plus ipilimumab as first-line therapy at five affiliated institutions. Tumor burden was defined as the sum of diameters of baseline targeted lesions according to the RECIST version.1.1. We categorized the patients into two groups based on the median value of tumor burden (i.e., high vs. low). The association of tumor burden with progression-free survival (PFS), overall survival (OS) and objective response rate (ORR) with nivolumab plus ipilimumab treatment was analyzed.

RESULTS: The median tumor burden was 63.0 cm (interquartile range: 34.2-125.8). PFS was significantly shorter in patients with high tumor burden (n = 31) than in those with low tumor burden (n = 31) (median: 6.08 [95% CI: 2.73-9.70] vs. 12.5 [4.77-24.0] months, P = 0.0134). In addition, OS tended to be shorter in patients with high tumor burden; however, there was no statistically significant difference (1-year rate: 77.3 vs. 96.7%, P = 0.166). ORR was not significantly different between patients with high and low tumor burden (35 vs. 55%, P = 0.202). Multivariate analysis of PFS further showed that tumor burden was an independent factor (HR: 2.22 [95% CI: 1.11-4.45], P = 0.0242).

CONCLUSIONS: Tumor burden might be a useful factor for outcome prediction, at least for PFS prediction, in patients receiving nivolumab plus ipilimumab for mRCC. Further prospective studies are warranted to confirm our findings.

PMID:34492101 | DOI:10.1093/jjco/hyab142

Biometrics. 2021 Sep 7. doi: 10.1111/biom.13542. Online ahead of print.

NO ABSTRACT

PMID:34492117 | DOI:10.1111/biom.13542

Public Health Nurs. 2021 Sep 7. doi: 10.1111/phn.12964. Online ahead of print.

ABSTRACT

OBJECTIVES: This study sought to (1) determine the number of persons evicted from the Durham Housing Authority (DHA) over a 5-year period, (2) explore changes in the number of persons with various medical diagnoses and health care utilization patterns before and after eviction, and (3) examine how many persons evicted from DHA became literally homeless.

DESIGN: This was a pre/post cross-sectional quantitative study.

SAMPLE: Heads of households evicted from DHA properties from January 1, 2013 through December 31, 2017 were included in the study.

MEASUREMENTS: We matched people evicted by the DHA in a university health system electronic health record system to determine changes in diagnoses and health care utilization before and after eviction. We also matched the cohort in the homeless management information system to determine how many persons evicted became literally homeless.

RESULTS: Findings indicate statistically significant increases in persons with medical diagnoses in five of ten categories, total hospital admissions, and emergency department visits after eviction. Of the 152 people included in the study, 34 (22%) became literally homeless.

CONCLUSIONS: Health and health care utilization patterns were different before and after eviction. Implications for clinicians are explored.

PMID:34492122 | DOI:10.1111/phn.12964

J Crohns Colitis. 2021 Sep 7:jjab155. doi: 10.1093/ecco-jcc/jjab155. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: There is increasing interest in machine learning-based prediction models in inflammatory bowel diseases (IBD). We synthesized and critically appraised studies comparing machine learning vs. traditional statistical models, using routinely available clinical data for risk prediction in IBD.

METHODS: Through a systematic review till January 1, 2021, we identified cohort studies that derived and/or validated machine learning models, based on routinely collected clinical data in patients with IBD, to predict the risk of harboring or developing adverse clinical outcomes, and reported its predictive performance against a traditional statistical model for the same outcome. We appraised the risk of bias in these studies using the Prediction model Risk of Bias ASsessment (PROBAST) tool.

RESULTS: We included 13 studies on machine learning-based prediction models in IBD encompassing themes of predicting treatment response to biologics and thiopurines, predicting longitudinal disease activity and complications and outcomes in patients with acute severe ulcerative colitis. The most common machine learnings models used were tree-based algorithms, which are classification approaches achieved through supervised learning. Machine learning models outperformed traditional statistical models in risk prediction. However, most models were at high risk of bias, and only one was externally validated.

CONCLUSIONS: Machine learning-based prediction models based on routinely collected data generally perform better than traditional statistical models in risk prediction in IBD, though frequently have high risk of bias. Future studies examining these approaches are warranted, with special focus on external validation and clinical applicability.

PMID:34492100 | DOI:10.1093/ecco-jcc/jjab155

PLoS One. 2021 Sep 7;16(9):e0257112. doi: 10.1371/journal.pone.0257112. eCollection 2021.

ABSTRACT

Public health and social interventions are critical to mitigate the spread of the coronavirus disease 2019 (COVID-19) pandemic. Ethiopia has implemented a variety of public health and social measures to control the pandemic. This study aimed to assess social distancing and public health preventive practices of government employees in response to COVID-19. A cross-sectional study was conducted among 1,573 government employees selected from 46 public institutions located in Addis Ababa. Data were collected from 8th to 19th June 2020 using a paper-based self-administered questionnaire and analyzed using SPSS version 23.0. Descriptive statistics were used to summarize the data. Binary logistic regression analyses were used to identify factors associated with outcome variables (perceived effectiveness of facemask wearing to prevent coronavirus infection, and COVID-19 testing). Majority of the participants reported facemask wearing (96%), avoiding close contact with people including handshaking (94.8%), consistently followed government recommendations (95.6%), frequent handwashing (94.5%), practiced physical distancing (89.5%), avoided mass gatherings and crowded places (88.1%), restricting movement and travelling (71.8%), and stayed home (35.6%). More than 80% of the participants perceived that consistently wearing a facemask is highly effective in preventing coronavirus infection. Respondents from Oromia perceived less about the effectiveness of wearing facemask in preventing coronavirus infection (adjusted OR = 0.27, 95% CI:0.17-0.45). About 19% of the respondents reported that they had ever tested for COVID-19. Respondents between 40-49 years old (adjusted OR = 0.41, 95% CI:0.22-0.76) and 50-66 years (adjusted OR = 0.43, 95% CI:0.19-0.95) were less likely tested for coronavirus than the younger age groups. Similarly, respondents from Oromia were less likely to test for coronavirus (adjusted OR = 0.26, 95% CI:0.12-0.56) than those from national level. Participants who were sure about the availability of COVID-19 testing were more likely to test for coronavirus. About 57% of the respondents perceived that the policy measures in response to the pandemic were inadequate. The findings showed higher social distancing and preventive practices among the government employees in response to COVID-19. Rules and regulations imposed by the government should be enforced and people should properly apply wearing facemasks, frequent handwashing, social and physical distancing measures as a comprehensive package of COVID-19 prevention and control strategies.

PMID:34492089 | DOI:10.1371/journal.pone.0257112

PLoS One. 2021 Sep 7;16(9):e0257024. doi: 10.1371/journal.pone.0257024. eCollection 2021.

ABSTRACT

BACKGROUND: Pediculus humanus capitis or head louse is an obligate ectoparasite and its infestation remains a major public health issue worldwide. Molecular analysis divides head lice into six clades and intra-clade genetic differences have been identified. Several hypotheses have been formulated to elucidate the discrepancies of the variety of head lice among different regions of the world. It is currently concluded that head lice distribution might be associated with human migration history. This study aims to investigate genetic data of human head lice in Thailand. We believe that the analysis could help establish the correlation between local and global head lice populations.

METHOD: We investigated mitochondrial cytochrome b (cytb) gene of the collected 214 head lice to evaluate genetic diversity from 15 provinces among 6 regions of Thailand. The head lice genes were added to the global pool for the phylogenetic tree, Bayesian tree, Skyline plot, and median joining network construction. The biodiversity, neutrality tests, and population genetic differentiation among the 6 Thailand geographic regions were analyzed by DNAsp version 6.

RESULTS: The phylogenetic tree analysis of 214 collected head lice are of clade A and clade C accounting for roughly 65% and 35% respectively. The Bayesian tree revealed a correlation of clade diversification and ancient human dispersal timeline. In Thailand, clade A is widespread in the country. Clade C is confined to only the Central, Southern, and Northeastern regions. We identified 50 novel haplotypes. Statistical analysis showed congruent results between genetic differentiation and population migration especially with South Asia.

CONCLUSIONS: Pediculosis remains problematic among children in the rural areas in Thailand. Cytb gene analysis of human head lice illustrated clade distribution and intra-clade diversity of different areas. Our study reported novel haplotypes of head lice in Thailand. Moreover, the statistic calculation provided a better understanding of their relationship with human, as an obligate human parasite and might help provide a better insight into the history of human population migration. Determination of the correlation between phylogenetic data and pediculicide resistance gene as well as residing bacteria are of interest for future studies.

PMID:34492093 | DOI:10.1371/journal.pone.0257024

PLoS One. 2021 Sep 7;16(9):e0257045. doi: 10.1371/journal.pone.0257045. eCollection 2021.

ABSTRACT

BACKGROUND: In the year 2019, around 5 million children under age five died and most of the deaths happened in developing countries. Though large numbers of deaths are reported in such countries, limited availability of data poses a substantial challenge on generating reliable estimates. Hence, this study aims to assess the prevalence and factors associated with under-five mortality in southeastern Ethiopia.

METHODS: A register based cross sectional study was conducted from 1st September 2014 to July 2019 in Asella teaching and referral hospital. A total of 4901 under-five age children registered on the admission and discharge book of pediatric ward with complete information were included for the analysis. Data entry and analysis were conducted using Epidata Version 7 and SPSS version 21, respectively. Descriptive statistics were used to explore the characteristics of the study participants and their condition at discharge. Adjusted Odds Ratio (AOR) with its 95% Confidence interval and P-value less than 5% was used to decide the statistically significant association.

RESULTS: The prevalence of under-five mortality among admitted children in Asella Teaching and Referral hospital was 8.7% (95% CI 7.91-9.50%). Post-Neonatal and Child mortality were found to be 9.1% and 8.18%, respectively. Moreover, large numbers of death (45.2%) were seen within the first 2 days of admission. Address (AOR:1.4(1.08-1.81)), HIV status (AOR:4.64 (2.19-9.8)), severe acute malnutrition (AOR:2.82 (2.03-3.91)), hypovolemic shock (AOR:4.32 (2.31-8.1)), type I diabetes with DKA (AOR:3.53(1.34-9.29) and length of stay in the hospital for ≤2 days (AOR: 4.28 (3.09-5.95)) as well as 3-4 days (AOR: 1.48 (1.02-2.15)) were among the identified predictors.

CONCLUSIONS: Though childhood mortality is swiftly decreasing, and access and utilization of health care is improving in Ethiopia, our study found large prevalence of under-five mortality, 8.7% and higher number of deaths in early days of admission. Improving the quality of service has a paramount importance in reducing the mortality and managing associated factors contributing to under-five mortality among admitted children.

PMID:34492085 | DOI:10.1371/journal.pone.0257045

PLoS Pathog. 2021 Sep 7;17(9):e1009883. doi: 10.1371/journal.ppat.1009883. Online ahead of print.

ABSTRACT

SARS-CoV-2 infection outbreaks in minks have serious implications associated with animal health and welfare, and public health. In two naturally infected mink farms (A and B) located in Greece, we investigated the outbreaks and assessed parameters associated with virus transmission, immunity, pathology, and environmental contamination. Symptoms ranged from anorexia and mild depression to respiratory signs of varying intensity. Although the farms were at different breeding stages, mortality was similarly high (8.4% and 10.0%). The viral strains belonged to lineages B.1.1.218 and B.1.1.305, possessing the mink-specific S-Y453F substitution. Lung histopathology identified necrosis of smooth muscle and connective tissue elements of vascular walls, and vasculitis as the main early key events of the acute SARS-CoV-2-induced broncho-interstitial pneumonia. Molecular investigation in two dead minks indicated a consistently higher (0.3-1.3 log10 RNA copies/g) viral load in organs of the male mink compared to the female. In farm A, the infected farmers were responsible for the significant initial infection of 229 out of 1,000 handled minks, suggesting a very efficient human-to-mink transmission. Subsequent infections across the sheds wherein animals were being housed occurred due to airborne transmission. Based on a R0 of 2.90 and a growth rate equal to 0.293, the generation time was estimated to be 3.6 days, indicative of the massive SARS-CoV-2 dispersal among minks. After the end of the outbreaks, a similar percentage of animals were immune in the two farms (93.0% and 93.3%), preventing further virus transmission whereas, viral RNA was detected in samples collected from shed surfaces and air. Consequently, strict biosecurity is imperative during the occurrence of clinical signs. Environmental viral load monitoring, in conjunction with NGS should be adopted in mink farm surveillance. The minimum proportion of minks that need to be immunized to avoid outbreaks in farms was calculated at 65.5%, which is important for future vaccination campaigns.

PMID:34492088 | DOI:10.1371/journal.ppat.1009883

PLoS One. 2021 Sep 7;16(9):e0256978. doi: 10.1371/journal.pone.0256978. eCollection 2021.

ABSTRACT

Kenaf (Hibiscus cannabinus L.) is an industrial crop used as a raw material in various fields and is cultivated worldwide. Compared to high potential for its utilization, breeding sector is not vigorous partially due to laborous breeding procedure. Thus, efficient breeding methods are required for varieties that can adapt to various environments and obtain optimal production. For that, identifying kenaf’s characteristics is very important during the breeding process. Here, we investigated if RGB based vegetative index (VI) could be associated with traits for biomass. We used 20 varieties and germplasm of kenaf and RGB images taken with unmanned aerial vehicles (UAVs) for field selection in early and late growth stage. In addition, measuring the stem diameter and the number of nodes confirmed whether the vegetative index value obtained from the RGB image could infer the actual plant biomass. Based on the results, it was confirmed that the individual surface area and estimated plant height, which were identified from the RGB image, had positive correlations with the stem diameter and node number, which are actual growth indicators of the rate of growth further, biomass could also be estimated based on this. Moreover, it is suggested that VIs have a high correlation with actual growth indicators; thus, the biomass of kenaf could be predicted. Interstingly, those traits showing high correlation in the late stage had very low correlations in the early stage. To sum up, the results in the current study suggest a more efficient breeding method by reducing labor and resources required for breeding selection by the use of RGB image analysis obtained by UAV. This means that considerable high-quality research could be performed even with a tight budget. Furthermore, this method could be applied to crop management, which is done with other vegetative indices using a multispectral camera.

PMID:34492059 | DOI:10.1371/journal.pone.0256978

PLoS One. 2021 Sep 7;16(9):e0256799. doi: 10.1371/journal.pone.0256799. eCollection 2021.

ABSTRACT

BACKGROUND: Health facilities in developing countries are increasingly adopting Electronic Health Records systems (EHRs) to support healthcare processes. However, only limited studies are available that assess the actual use of the EHRs once adopted in these settings. We assessed the state of the 376 KenyaEMR system (national EHRs) implementations in healthcare facilities offering HIV services in Kenya.

METHODS: The study focused on seven EHRs use indicators. Six of the seven indicators were programmed and packaged into a query script for execution within each KenyaEMR system (KeEMRs) implementation to collect monthly server-log data for each indicator for the period 2012-2019. The indicators included: Staff system use, observations (clinical data volume), data exchange, standardized terminologies, patient identification, and automatic reports. The seventh indicator (EHR variable Completeness) was derived from routine data quality report within the EHRs. Data were analysed using descriptive statistics, and multiple linear regression analysis was used to examine how individual facility characteristics affected the use of the system.

RESULTS: 213 facilities spanning 19 counties participated in the study. The mean number of authorized users who actively used the KeEMRs was 18.1% (SD = 13.1%, p<0.001) across the facilities. On average, the volume of clinical data (observations) captured in the EHRs was 3363 (SD = 4259). Only a few facilities(14.1%) had health data exchange capability. 97.6% of EHRs concept dictionary terms mapped to standardized terminologies such as CIEL. Within the facility EHRs, only 50.5% (SD = 35.4%, p< 0.001) of patients had the nationally-endorsed patient identifier number recorded. Multiple regression analysis indicated the need for improvement on the mode of EHRs use of implementation.

CONCLUSION: The standard EHRs use indicators can effectively measure EHRs use and consequently determine success of the EHRs implementations. The results suggest that most of the EHRs use areas assessed need improvement, especially in relation to active usage of the system and data exchange readiness.

PMID:34492070 | DOI:10.1371/journal.pone.0256799