Category: Statistics

Hepatology. 2021 Sep 8. doi: 10.1002/hep.32142. Online ahead of print.

ABSTRACT

BACKGROUND & AIMS: Chronic hepatitis B (CHB) affects over 290 million people globally and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression and machine learning (random forest) models to accurately identify patients with HBV, using only easily-obtained demographic data from a population-based data set.

APPROACH & RESULTS: We identified participants with data on hepatitis B surface antigen (HBsAg), birth year, sex, race/ethnicity, and birthplace from 10 cycles of the National Health and Nutrition Examination Survey (NHANES, 1999-2018) and divided them into two cohorts: training (cycles 2, 3, 5, 6, 8, 10; n = 39,119) and validation (cycles 1, 4, 7, 9; n = 21,569). We then developed and tested our two models. The overall cohort was 49.2% male, 39.7% White, 23.2% Black, 29.6% Hispanic, and 7.5% Asian/Other, with a median birth year of 1973. In multivariable logistic regression, the following factors were associated with HBV infection: birth year 1991 or after (adjusted OR [aOR] of 0.28, P < 0.001), male sex (aOR 1.49, P = 0.0080), Black and Asian/Other vs. White (aOR 5.23 and 9.13, P < 0.001 for both), and being United States-born (vs. foreign-born) (aOR 0.14, P < 0.001). We found that the machine learning model consistently outperformed the logistic regression model, with higher AUROC values (0.83 vs. 0.75 in validation cohort, P < 0.001) and better differentiation of high and low risk individuals.

CONCLUSIONS: Our machine learning model provides a simple, targeted approach to HBV screening, using only easily-obtained demographic data.

PMID:34496066 | DOI:10.1002/hep.32142

PLoS One. 2021 Sep 8;16(9):e0256515. doi: 10.1371/journal.pone.0256515. eCollection 2021.

ABSTRACT

BACKGROUND: The epidemiological transition, touted as occurring in Ghana, requires research that tracks the changing patterns of diseases in order to capture the trend and improve healthcare delivery. This study examines national trends in mortality rate and cause of death at health facilities in Ghana between 2014 and 2018.

METHODS: Institutional mortality data and cause of death from 2014-2018 were sourced from the Ghana Health Service’s District Health Information Management System. The latter collates healthcare service data routinely from government and non-governmental health institutions in Ghana yearly. The institutional mortality rate was estimated using guidelines from the Ghana Health Service. Percent change in mortality was examined for 2014 and 2018. In addition, cause of death data were available for 2017 and 2018. The World Health Organisation’s 11th International Classification for Diseases (ICD-11) was used to group the cause of death.

RESULTS: Institutional mortality decreased by 7% nationally over the study period. However, four out of ten regions (Greater Accra, Volta, Upper East, and Upper West) recorded increases in institutional mortality. The Upper East (17%) and Volta regions (13%) recorded the highest increase. Chronic non-communicable diseases (NCDs) were the leading cause of death in 2017 (25%) and 2018 (20%). This was followed by certain infectious and parasitic diseases (15% for both years) and respiratory infections (10% in 2017 and 13% in 2018). Among the NCDs, hypertension was the leading cause of death with 2,243 and 2,472 cases in 2017 and 2018. Other (non-ischemic) heart diseases and diabetes were the second and third leading NCDs. Septicaemia, tuberculosis and pneumonia were the predominant infectious diseases. Regional variations existed in the cause of death. NCDs showed more urban-region bias while infectious diseases presented more rural-region bias.

CONCLUSIONS: This study examined national trends in mortality rate and cause of death at health facilities in Ghana. Ghana recorded a decrease in institutional mortality throughout the study. NCDs and infections were the leading causes of death, giving a double-burden of diseases. There is a need to enhance efforts towards healthcare and health promotion programmes for NCDs and infectious diseases at facility and community levels as outlined in the 2020 National Health Policy of Ghana.

PMID:34496000 | DOI:10.1371/journal.pone.0256515

Med Phys. 2021 Sep 8. doi: 10.1002/mp.15214. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to design and evaluate a novel method for the registration of 2D lateral cephalograms and 3D craniofacial cone-beam computed tomography (CBCT) images, providing patient-specific 3D structures from a 2D lateral cephalogram without additional radiation exposure.

METHODS: We developed a cross-modal deformable registration model based on a deep convolutional neural network. Our approach took advantage of a low-dimensional deformation field encoding and an iterative feedback scheme to infer coarse-to-fine volumetric deformations. In particular, we constructed a statistical subspace of deformation fields and parameterized the nonlinear mapping function from an image pair, consisting of the target 2D lateral cephalogram and the reference volumetric CBCT, to a latent encoding of the deformation field. Instead of the one-shot registration by the learned mapping function, a feedback scheme was introduced to progressively update the reference volumetric image and to infer coarse-to-fine deformations fields, accounting for the shape variations of anatomical structures. A total of 220 clinically obtained CBCTs were used to train and validate the proposed model, among which 120 CBCTs were used to generate a training dataset with 24k paired synthetic lateral cephalograms and CBCTs. The proposed approach was evaluated on the deformable 2D-3D registration of clinically obtained lateral cephalograms and CBCTs from growing and adult orthodontic patients.

RESULTS: Strong structural consistencies were observed between the deformed CBCT and the target lateral cephalogram in all criteria. The proposed method achieved state-of-the-art performances with the mean contour deviation of 0.41±0.12 mm on the anterior cranial base, 0.48±0.17 mm on the mandible, and 0.35±0.08 mm on the maxilla, respectively. The mean surface mesh ranged from 0.78 mm to 0.97 mm on various craniofacial structures, and the landmark registration errors ranged from 0.83 mm to 1.24 mm on the growing datasets regarding 14 landmarks. The proposed iterative feedback scheme handled the structural details and improved the registration. The resultant deformed volumetric image was consistent with the target lateral cephalogram in both 2D projective planes and 3D volumetric space regarding the multi-category craniofacial structures.

CONCLUSIONS: The results suggest that the deep learning-based 2D-3D registration model enables the deformable alignment of 2D lateral cephalograms and CBCTs and estimates patient-specific 3D craniofacial structures.

PMID:34496039 | DOI:10.1002/mp.15214

PLoS One. 2021 Sep 8;16(9):e0256831. doi: 10.1371/journal.pone.0256831. eCollection 2021.

ABSTRACT

Current approach for the detection of cancer is based on identifying genetic mutations typical to tumor cells. This approach is effective only when cancer has already emerged, however, it might be in a stage too advanced for effective treatment. Cancer is caused by the continuous accumulation of mutations; is it possible to measure the time-dependent information of mutation accumulation and predict the emergence of cancer? We hypothesize that the mutation history derived from the tandem repeat regions in blood-derived DNA carries information about the accumulation of the cancer driver mutations in other tissues. To validate our hypothesis, we computed the mutation histories from the tandem repeat regions in blood-derived exomic DNA of 3874 TCGA patients with different cancer types and found a statistically significant signal with specificity ranging from 66% to 93% differentiating Glioblastoma patients from other cancer patients. Our approach and findings offer a new direction for future cancer prediction and early cancer detection based on information derived from blood-derived DNA.

PMID:34495981 | DOI:10.1371/journal.pone.0256831

PLoS One. 2021 Sep 8;16(9):e0256980. doi: 10.1371/journal.pone.0256980. eCollection 2021.

ABSTRACT

BACKGROUND: A DNA-prime/human adenovirus serotype 5 (HuAd5) boost vaccine encoding Plasmodium falciparum (Pf) circumsporozoite protein (PfCSP) and Pf apical membrane antigen-1 (PfAMA1), elicited protection in 4/15 (27%) of subjects against controlled human malaria infection (CHMI) that was statistically associated with CD8+ T cell responses. Subjects with high level pre-existing immunity to HuAd5 were not protected, suggesting an adverse effect on vaccine efficacy (VE). We replaced HuAd5 with chimpanzee adenovirus 63 (ChAd63), and repeated the study, assessing both the two-antigen (CSP, AMA1 = CA) vaccine, and a novel three-antigen (CSP, AMA1, ME-TRAP = CAT) vaccine that included a third pre-erythrocytic stage antigen [malaria multiple epitopes (ME) fused to the Pf thrombospondin-related adhesive protein (TRAP)] to potentially enhance protection.

METHODOLOGY: This was an open label, randomized Phase 1 trial, assessing safety, tolerability, and VE against CHMI in healthy, malaria naïve adults. Forty subjects (20 each group) were to receive three monthly CA or CAT DNA priming immunizations, followed by corresponding ChAd63 boost four months later. Four weeks after the boost, immunized subjects and 12 infectivity controls underwent CHMI by mosquito bite using the Pf3D7 strain. VE was assessed by determining the differences in time to parasitemia as detected by thick blood smears up to 28-days post CHMI and utilizing the log rank test, and by calculating the risk ratio of each treatment group and subtracting from 1, with significance calculated by the Cochran-Mantel-Haenszel method.

RESULTS: In both groups, systemic adverse events (AEs) were significantly higher after the ChAd63 boost than DNA immunizations. Eleven of 12 infectivity controls developed parasitemia (mean 11.7 days). In the CA group, 15 of 16 (93.8%) immunized subjects developed parasitemia (mean 12.0 days). In the CAT group, 11 of 16 (63.8%) immunized subjects developed parasitemia (mean 13.0 days), indicating significant protection by log rank test compared to infectivity controls (p = 0.0406) and the CA group (p = 0.0229). VE (1 minus the risk ratio) in the CAT group was 25% compared to -2% in the CA group. The CA and CAT vaccines induced robust humoral (ELISA antibodies against CSP, AMA1 and TRAP, and IFA responses against sporozoites and Pf3D7 blood stages), and cellular responses (IFN-γ FluoroSpot responses to CSP, AMA1 and TRAP) that were not associated with protection.

CONCLUSIONS: This study demonstrated that the ChAd63 CAT vaccine exhibited significant protective efficacy, and confirmed protection was afforded by adding a third antigen (T) to a two-antigen (CA) formulation to achieve increased VE. Although the ChAd63-CAT vaccine was associated with increased frequencies of systemic AEs compared to the CA vaccine and, historically, compared to the HuAd5 vectored malaria vaccine encoding CSP and AMA1, they were transient and associated with increased vector dosing.

PMID:34495988 | DOI:10.1371/journal.pone.0256980

PLoS One. 2021 Sep 8;16(9):e0256018. doi: 10.1371/journal.pone.0256018. eCollection 2021.

ABSTRACT

BACKGROUND: The Penn Alcohol Craving Scale (PACS) is an instrument with good psychometric properties that is widely used to assess alcohol craving. Based on the assumption that the experience of craving is independent of substance type, the Polish version of the PACS was modified to measure drug craving, thus creating the Penn Drug Craving Scale (PDCS). The analyses presented in the paper aim to verify the hypothesis that the PDCS has a unidimensional structure, is highly reliable and features longitudinal measurement invariance.

METHODS: The research was conducted in 14 inpatient and 13 outpatient randomly selected facilities that provide psychosocial therapy to people with substance use disorder (SUD) in Poland, during June 2018 -July 2019. The data used for the analyses came from 282 patients diagnosed on the basis of ICD-10 criteria (F11.2-F19.2). The paper presents analyses with the application of: [1] confirmatory factor analysis (CFA) conducted on the basis of a polychoric correlation matrix and the WLSMV estimator; [2] a reliability estimate using Cronbach’s alpha and coefficient omega; [3] verification of longitudinal measurement invariance between the beginning and end of therapy; [4] evaluation of criterion validity; [5] normalisation of the raw scores.

RESULTS: The CFA results confirmed a unidimensional PDCS structure (RMSEA = 0.047, 95% CI: 0.000-0.103; CFI = 0.999; TLI = 0.999) and a high reliability of the scale (ω = 0.93). Moreover, a strict longitudinal measurement invariance of the instrument was confirmed.

CONCLUSIONS: Accurate assessment of craving is possible only with valid and reliable instruments. Therefore, the psychometric properties of the PDCS were verified based on the latest statistical approaches. The scale is a valid and highly reliable tool featuring longitudinal measurement invariance and can be usefully used for research and clinical purposes. Thus, the Polish version of the PACS has been modified and successfully applied to the population of people with SUD.

PMID:34495966 | DOI:10.1371/journal.pone.0256018

PLoS Med. 2021 Sep 8;18(9):e1003727. doi: 10.1371/journal.pmed.1003727. Online ahead of print.

ABSTRACT

BACKGROUND: Seasonal malaria chemoprevention (SMC) has shown high protective efficacy against clinical malaria and severe malaria in a series of clinical trials. We evaluated the effectiveness of SMC treatments against clinical malaria when delivered at scale through national malaria control programmes in 2015 and 2016.

METHODS AND FINDINGS: Case-control studies were carried out in Mali and The Gambia in 2015, and in Burkina Faso, Chad, Mali, Nigeria, and The Gambia in 2016. Children aged 3-59 months presenting at selected health facilities with microscopically confirmed clinical malaria were recruited as cases. Two controls per case were recruited concurrently (on or shortly after the day the case was detected) from the neighbourhood in which the case lived. The primary exposure was the time since the most recent course of SMC treatment, determined from SMC recipient cards, caregiver recall, and administrative records. Conditional logistic regression was used to estimate the odds ratio (OR) associated with receipt of SMC within the previous 28 days, and SMC 29 to 42 days ago, compared with no SMC in the past 42 days. These ORs, which are equivalent to incidence rate ratios, were used to calculate the percentage reduction in clinical malaria incidence in the corresponding time periods. Results from individual countries were pooled in a random-effects meta-analysis. In total, 2,126 cases and 4,252 controls were included in the analysis. Across the 7 studies, the mean age ranged from 1.7 to 2.4 years and from 2.1 to 2.8 years among controls and cases, respectively; 42.2%-50.9% and 38.9%-46.9% of controls and cases, respectively, were male. In all 7 individual case-control studies, a high degree of personal protection from SMC against clinical malaria was observed, ranging from 73% in Mali in 2016 to 98% in Mali in 2015. The overall OR for SMC within 28 days was 0.12 (95% CI: 0.06, 0.21; p < 0.001), indicating a protective effectiveness of 88% (95% CI: 79%, 94%). Effectiveness against clinical malaria for SMC 29-42 days ago was 61% (95% CI: 47%, 72%). Similar results were obtained when the analysis was restricted to cases with parasite density in excess of 5,000 parasites per microlitre: OR 0.90 (95% CI: 0.79, 0.96; p < 0.001) and 0.59 (95% CI: 0.34, 0.74; p < 0.001) for SMC 0-28 days and 29-42 days ago, respectively. Potential limitations include the possibility of residual confounding due to an association between exposure to malaria and access to SMC, or differences in access to SMC between patients attending a clinic and community controls; however, neighbourhood matching of cases and controls, and covariate adjustment, attempted to control for these aspects, and the observed decline in protection over time, consistent with expected trends, argues against a major bias from these sources.

CONCLUSIONS: SMC administered as part of routine national malaria control activities provided a very high level of personal protection against clinical malaria over 28 days post-treatment, similar to the efficacy observed in clinical trials. The case-control design used in this study can be used at intervals to ensure SMC treatments remain effective.

PMID:34495978 | DOI:10.1371/journal.pmed.1003727

PLoS One. 2021 Sep 8;16(9):e0255519. doi: 10.1371/journal.pone.0255519. eCollection 2021.

ABSTRACT

Advances in remote sensing and machine learning enable increasingly accurate, inexpensive, and timely estimation of poverty and malnutrition indicators to guide development and humanitarian agencies’ programming. However, state of the art models often rely on proprietary data and/or deep or transfer learning methods whose underlying mechanics may be challenging to interpret. We demonstrate how interpretable random forest models can produce estimates of a set of (potentially correlated) malnutrition and poverty prevalence measures using free, open access, regularly updated, georeferenced data. We demonstrate two use cases: contemporaneous prediction, which might be used for poverty mapping, geographic targeting, or monitoring and evaluation tasks, and a sequential nowcasting task that can inform early warning systems. Applied to data from 11 low and lower-middle income countries, we find predictive accuracy broadly comparable for both tasks to prior studies that use proprietary data and/or deep or transfer learning methods.

PMID:34495951 | DOI:10.1371/journal.pone.0255519

PLoS Biol. 2021 Sep 8;19(9):e3001385. doi: 10.1371/journal.pbio.3001385. Online ahead of print.

ABSTRACT

Intrauterine infection/inflammation (IUI) is a major contributor to preterm labor (PTL). However, IUI does not invariably cause PTL. We hypothesized that quantitative and qualitative differences in immune response exist in subjects with or without PTL. To define the triggers for PTL, we developed rhesus macaque models of IUI driven by lipopolysaccharide (LPS) or live Escherichia coli. PTL did not occur in LPS challenged rhesus macaques, while E. coli-infected animals frequently delivered preterm. Although LPS and live E. coli both caused immune cell infiltration, E. coli-infected animals showed higher levels of inflammatory mediators, particularly interleukin 6 (IL-6) and prostaglandins, in the chorioamnion-decidua and amniotic fluid (AF). Neutrophil infiltration in the chorio-decidua was a common feature to both LPS and E. coli. However, neutrophilic infiltration and IL6 and PTGS2 expression in the amnion was specifically induced by live E. coli. RNA sequencing (RNA-seq) analysis of fetal membranes revealed that specific pathways involved in augmentation of inflammation including type I interferon (IFN) response, chemotaxis, sumoylation, and iron homeostasis were up-regulated in the E. coli group compared to the LPS group. Our data suggest that the intensity of the host immune response to IUI may determine susceptibility to PTL.

PMID:34495952 | DOI:10.1371/journal.pbio.3001385

Ying Yong Sheng Tai Xue Bao. 2020 Aug;31(8):2663-2670. doi: 10.13287/j.1001-9332.202008.009.

ABSTRACT

The policy of natural forest protection project (NFPP) is of great significance to the protection and restoration of natural forests. It remains unclear about how to play the role of NFPP transfer payment in forest ecological benefits. Based on panel data of “China Forestry Statistical Yearbook” from 2011 to 2017, we used forest management area and forest tending area as indicators to measure forest ecological benefits, and used spatial lag model and intermediary effect model to analyze the impacts of the transfer payment funds of NFPP on the forest ecological benefits in key state-owned forest areas. The results showed that forest ecological benefits in the key state-owned forest areas in the second phase of NFPP had improved year by year. There was a significant spatial spillover effect of forest ecological benefits of forestry bureaus. The transfer funds of NFPP had a significant positive effect on the ecological benefits of forest resources in key state-owned forest areas. There was a partial intermediary effect between the improvement of human capital and the establishment of first-line management and protection stations. The central government should increase investment in the transfer payment funds of NFPP. Forest administrations should increase the proportion of funds used in improving human capital and establishing first-line management and protection stations.

PMID:34494789 | DOI:10.13287/j.1001-9332.202008.009