Accuracy of the Discriminatory Ability of Combined Fecal Microbiota Panel in the Early Detection of Patients with Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) screening and detecting it at an early stage is an effective way to decrease mortality from CRC. Colonoscopy, considered the gold standard (GS) for diagnosing the disease in many countries, has several limitations. Therefore, the main focus of this literature is to investigate the ability of combining candidate gut microbiota for early diagnosis of CRC, both in the presence and absence of GS test outcomes. METHODS: We analyzed the data derived from a case-control study, including 83 screening colonoscopies conducted on subjects aged 18-92 years in Tehran, Iran. The candidate gut microbiota including, ETBF, Enterococcus faecalis, and Porphyromonas gingivalis were quantified in samples using absolute qRT PCR. The Bayesian latent class model (LCM) was employed to combine the values from the multiple bacterial markers in order to optimize the discriminatory ability compared with a single marker. RESULTS: Based on Bayesian logistic regression, we discovered that family history of CRC, physical activity, cigarette smoking, and food diet were all significantly associated with an increased risk of CRC. When comparing ETBF and E. faecalis to P. gingivalis, we have observed that P. gingivalis exhibited greater predictive power in detecting high-risk individuals with CRC. As such, the sensitivity, specificity, and the area under the receiver-operating characteristics curve of combining ETBF, E. faecalis, and P. gingivalis were 98%, 96%, and 0.97, respectively. CONCLUSIONS: This study suggests that the combined use of the three markers markedly improves classification performance compared to pairwise combinations, as well as individual markers, both with and without GS test outcomes. Noticeably, the triple composition of the fecal markers may serve as a reliable non-invasive indicator for the early prediction of CRC.

Gender differences in leukemia outcomes based on health care expenditures using estimates from the GLOBOCAN 2020.

BACKGROUND: Leukemia contributes significantly to the global cancer burden. Due to the importance of evaluating improvements in leukemia outcomes, the current study aimed to examine the variations in mortality-to-incidence ratio (MIR) between genders and association of MIR with the health expenditures in selected countries. METHODS: The leukemia incidence and mortality rates were extracted from the GLOBOCAN 2020 database. In total, 56 countries were included based on the data quality reports and the exclusion of missing data. The associations of MIR and changes in MIR over time ([Formula: see text]MIR) with the human development index (HDI), current health expenditure (CHE) per capita, and current health expenditure as a percentage of gross domestic product (CHE/GDP) were investigated using Spearman's rank correlation coefficient. RESULTS: In 2020, an estimated 474,519 new cases of leukemia were diagnosed globally, and 311,594 deaths occurred due to the disease. Male patients exhibited a higher incidence and mortality of leukemia compared to females on a global scale. Our analysis revealed that the MIRs were the highest and lowest in Egypt (0.79) and the United States (0.29), respectively. Remarkably, countries with greater HDI, higher CHE per capita, and a higher CHE/GDP tended to have lower MIR in both genders and within gender-specific subgroups. The δMIR demonstrated a significant negative correlation with HDI and CHE per capita, whereas no significant associations were observed among female patients for CHE/GDP. Besides, all three indicators showed trends towards negative correlations with δMIR among males, though these trends were not statistically significant (p>0.05). CONCLUSIONS: Generally, leukemia MIRs tended to be most favorable (i.e., lower) in countries with high HDI and high health expenditure. The gender differences observed in leukemia outcomes may reflect the potential influence of social, material, behavioral, and biological factors.

Global long-term trends and spatial cluster analysis of pancreatic cancer incidence and mortality over a 30-year period using the global burden of disease study 2019 data.

INTRODUCTION: Pancreatic cancer (PC) is one of the most fatal malignancies, and its incidence and mortality rates are growing annually throughout the world. In this research, we aimed to investigate the time trends and identify the spatial clusters of incidence and mortality on a global scale over the last 30 years, using the Global Burden of Disease (GBD) study 2019 data. METHODS: Age-standardized incidence and mortality data due to PC were extracted from the GBD study, which was carried out from 1990 to 2019. A Joinpoint regression analysis was utilized to examine trends in the incidence and mortality of PC over the past three decades. As such, spatial analyses were undertaken to detect the spatial distribution and clustering of the metrics globally. RESULTS: It was observed that both the incidence and mortality rates were higher in males than in females worldwide. The global mortality and incidence rates significantly increased by 0.8% per year over the time of follow-up period (p<0.05). By spatial cluster analysis for mortality, European and North African countries, as well as Greenland were explored as hot spots; while South African and Southeast Asian countries were explored as cold spots. Regarding incidence, hot spots were found in European countries, Southern America, and Greenland; whilst cold spots were determined in Southern Africa and Madagascar. CONCLUSIONS: Collectively, the temporal trends disclosed a gradual rise in PC incidence and mortality rates over the period 1990-2019, reflecting the global health concern. We further found geographical variations in the patterns and identified high- and low-risk areas for incidence and mortality. These findings facilitate the design and implementation of more resource-efficient and geographically targeted treatments. Given the results of the current study, a practical approach to minimizing the future PC burden involves planned population-wide interventions, as well as primary prevention through healthier lifestyles.

Evaluating the predictive performance of gut microbiota for the early-stage colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) has been regarded as one of the most frequently diagnosed malignancies among the leading causes of cancer-related morbidity and mortality globally. Diagnosis of CRC at the early-stages of tumour might improve the survival rate of patients. The current study sought to determine the performance of fecal Fusobacterium nucleatum (F. nucleatum) and Streptococcus bovis (S. bovis) for timely predicting CRC. METHODS: Through a case-control study, the fecal sample information of 83 individuals (38 females, 45 males) referring to a hospital in Tehran, Iran was used. All patients underwent a complete colonoscopy, regarded as a gold standard test. Bacterial species including S. bovis and F. nucleatum were measured by absolute quantitative real-time PCR. The Bayesian univariate and bivariate latent class models (LCMs) were applied to estimate the ability of the candidate bacterial markers in order to early detection of patients with CRC. RESULTS: Bayesian univariate LCMs demonstrated that the sensitivities of S. bovis and F. nucleatum were estimated to be 86% [95% credible interval (CrI) 0.82-0.91] and 82% (95% CrI 0.75-0.88); while specificities were 84% (95% CrI 0.78-0.89) and 80% (95% CrI 0.73-0.87), respectively. Moreover, the area under the receiver operating characteristic curves (AUCs) were 0.88 (95% CrI 0.83-0.94) and 0.80 (95% CrI 0.73-0.85) respectively for S. bovis and F. nucleatum. Based on the Bayesian bivariate LCMs, the sensitivities of S. bovis and F. nucleatum were calculated as 93% (95% CrI 0.84-0.98) and 90% (95% CrI 0.85-0.97), the specificities were 88% (95% CrI 0.78-0.93) and 87% (95% CrI 0.79-0.94); and the AUCs were 0.91 (95% CrI 0.83-0.99) and 0.88(95% CrI 0.81-0.96), respectively. CONCLUSIONS: Our data has identified that according to the Bayesian bivariate LCM, S. bovis and F. nucleatum had a more significant predictive accuracy compared with the univariate model. In summary, these intestinal bacteria have been highlighted as novel tools for early-stage CRC diagnosis.

Global pattern of trends in incidence, mortality, and mortality-to-incidence ratio rates related to liver cancer, 1990-2019: a longitudinal analysis based on the global burden of disease study.

BACKGROUND: Liver cancer (LC) is considered as one of the most dominant malignant tumors which ranked 4th and in terms of global mortality and incidence, respectively. This work aimed to investigate the global temporal trends in LC mortality-to-incidence ratio (MIR) and its components, with a particular focus on examining long-term effect of human development index (HDI) on these metrics in a 30-year follow-up. METHODS: The age-standardized LC incidence and mortality data were derived from the global burden of disease (GBD) study 2019. We first leveraged joinpoint piecewise linear regression analysis to ascertain time trends in LC incidence, mortality, and MIR complement [1-MIR] and the average annual percentage change (AAPC) of the rates over the period 1990-2019. Then, the association between the metrics and HDI was explored through longitudinal multilevel models (LMMs). RESULTS: The incidence rates paralleled the mortality rates worldwide and they had similar significant monotonic decrementing trends with AAPC values of - 1.10% (95% confidence interval (CI): - 1.40, - 0.90%) and - 1.40% (- 1.50, - 1.30%), respectively from 1990 to 2019. The [1-MIR] rates were around 0 and showed an increasing pattern from 1.70 to 8.10 per 100,000 people (AAPC, 4.90%) at the same period of time. Results from the LMMs displayed that the majority of the variation lies at the country level accounted for about 88% of the total variance. Moreover, our analysis supported that the HDI was negatively associated with either incidence or mortality over time (p < 0.05). CONCLUSIONS: Our findings highlighted that the global long-term temporal trends of LC incidence and mortality decreased slightly during 1990-2019 which may reflect improved therapeutic strategies and public health interventions. Besides, the low rates of [1-MIR] revealed the five-year relative survival rate was poor implying LC is diagnosed late in its development. Thereby, the policymakers' focus must be on early screening and detection of liver cancer.

The impact of HIV on the risk of COVID-19 death among hospitalized patients.

BACKGROUND: Little is known about the association between Human Immunodeficiency Virus (HIV) infection and risk of death among hospitalized COVID-19 patients. We aimed to investigate this association using a multicenter study. MATERIAL AND METHODS: This multicenter study was conducted using the registry database of Coronavirus Control Operations Headquarter from March 21, 2021 to January 18, 2020 in the province of Tehran, Iran. The interest outcome was COVID-19 death among hospitalized patients living with and without HIV. The Cox regression models with robust standard error were used to estimate the association between HIV infection and risk of COVID-19 death. The subgroup and interaction analysis were also performed in this study. RESULTS: 326052 patients with COVID-19 were included in the study, of whom 127 (0.04%) were living with HIV. COVID-19 patients with HIV were more likely to be female, older, and to have symptoms such as fever, muscular pain, dyspnea and cough. The death proportion due to COVID-19 was 18 (14.17%) and 21595 (6.63%) among HIV and non-HIV patients, respectively. Patients living with HIV had lower mean survival time compared to those without HIV (26.49 vs. 15.31 days, P-value = 0.047). Crude risk of COVID-19 death was higher among HIV patients than in non-HIV group (hazard ratio[HR]: 1.60, 1.08-2.37). Compared to those without HIV, higher risk of COVID-19 death was observed among patients with HIV after adjusting for sex (1.60, 1.08-2.36), comorbidities (1.49, 1.01-2.19), cancer (1.59, 1.08-2.33), and PO2 (1.68, 1.12-2.50). However, the risk of COVID-19 death was similar in patients with and without HIV after adjusting for age (1.46, 0.98-2.16) and ward (1.30, 0.89-1.89). CONCLUSION: We found no strong evidence of association between HIV infection and higher risk of COVID-19 death among hospitalized patients. To determine the true impact of HIV on the risk of COVID-19 death, factors such as age, comorbidities, hospital ward, viral load, CD4 count, and antiretroviral treatment should be considered.

Trend analysis of cardiovascular disease mortality, incidence, and mortality-to-incidence ratio: results from global burden of disease study 2017.

BACKGROUND: Cardiovascular diseases (CVDs) are one of the global leading causes of concern due to the rising prevalence and consequence of mortality and disability with a heavy economic burden. The objective of the current study was to analyze the trend in CVD incidence, mortality, and mortality-to-incidence ratio (MIR) across the world over 28 years. METHODS: The age-standardized CVD mortality and incidence rates were retrieved from the Global Burden of Disease (GBD) Study 2017 for both genders and different world super regions with available data every year during the period 1990-2017. Additionally, the Human Development Index was sourced from the United Nations Development Programme (UNDP) database for all countries at the same time interval. The marginal modeling approach was implemented to evaluate the mean trend of CVD incidence, mortality, and MIR for 195 countries and separately for developing and developed countries and also clarify the relationship between the indices and Human Development Index (HDI) from 1990 to 2017. RESULTS: The obtained estimates identified that the global mean trend of CVD incidence had an ascending trend until 1996 followed by a descending trend after this year. Nearly all of the countries experienced a significant declining mortality trend from 1990 to 2017. Likewise, the global mean MIR rate had a significant trivial decrement trend with a gentle slope of 0.004 over the time interval. As such, the reduction in incidence and mortality rates for developed countries was significantly faster than developing counterparts in the period 1990-2017 (p < 0.05). Nevertheless, the developing nations had a more rather shallow decrease in MIR compared to developed ones. CONCLUSIONS: Generally, the findings of this study revealed that there was an overall downward trend in CVD incidence and mortality rates, while the survival rate of CVD patients was rather stable. These results send a satisfactory message that global effort for controlling the CVD burden was quite successful. Nonetheless, there is an urgent need for more efforts to improve the survival rate of patients and lower the burden of this disease in some areas with an increasing trend of either incidence or mortality.

Diagnostic accuracy of maternal serum multiple marker screening for early detection of gestational diabetes mellitus in the absence of a gold standard test.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with adverse diabetic complications for both mother and child during pregnancy. The common Gold Standard (GS) for diagnosis of GDM is 75 g oral glucose tolerance test (OGTT) during 24-28 gestational weeks which seems a little late for any proper intervention. This study aimed to employ the Bayesian latent class models (LCMs) for estimating the early diagnostic power of combination of serum multiple marker in detecting GDM during 14-17 weeks of gestation. METHODS: Data from a sample of 523 pregnant women who participated in gestational diabetes screening tests at health centers affiliated to Shahid Beheshti University of Medical Sciences in Tehran, Iran from 2017 to 2018 were used. The beta-human chorionic gonadotropin (ß-hCG), unconjugated estriol (uE3), and alfa-fetoprotein (AFP) values were extracted from case records for all participants. The Bayesian LCMs were applied for estimating sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of combining the three biomarkers' results in the absence of GS, adjusting for maternal age and body mass index. RESULTS: The mean (standard deviation) maternal age of the participants was 28.76 (±5.33) years. Additionally, the mean (standard deviation) BMI was 24.57 (±3.22) kg/m2. According to the Bayesian model, the cSensitivity, cSpecificity, and cAUC for the optimal composite diagnostic test were estimated as 94% (95% credible interval (CrI) [0.91-0.99]), 86% (95% CrI [0.80-0.92]), and 0.92 (95% CrI [0.87-0.98]), respectively. CONCLUSIONS: Overall, the findings revealed that the combination of uE3, AFP, and ß-hCG results might be considered as an acceptable predictor for detecting GDM with a rather high level of accuracy in the early second trimester of pregnancy without a GS.

Application of latent class analysis in diagnosis of graft-versus-host disease by serum markers after allogeneic haematopoietic stem cell transplantation.

Graft-versus-host disease (GVHD) is one of the major causes of morbidity and mortality in 25-70% of patients. The gold standard (GS) test to confirm the diagnosis of GVHD has some limitations. The current study was conducted to evaluate the accuracy of three serum markers in diagnosing GVHD without a GS. 94 patients who were hospitalized for allogeneic transplantation were studied. Mean levels from day of haematopoietic stem cell transplantation (HSCT) to discharge of serum uric acid (UA), lactate dehydrogenase (LDH), and creatinine (Cr) were measured for all participants. We adapted a Bayesian latent class analysis to modelling the results of each marker and combination of markers. The Sensitivity, Specificity, and area under receiver operating characteristic curve (AUC) for LDH were as 51%, 81%, and 0.70, respectively. For UA, the Sensitivity, Specificity, and AUC were 54%, 75%, and 0.71, respectively. The estimated Sensitivity, Specificity, and AUC of Cr were 72%, 94%, and 0.86, respectively. Adjusting for covariates, the combined Sensitivity, Specificity, and AUC of the optimal marker combination were 76%, 83%, and 0.94, respectively. To conclude, our findings suggested that Cr had the strongest diagnosis power for GVHD. Moreover, the classification accuracy of the three-marker combination outperforms the other combinations.

Years Lived with Disability due to Alzheimer's Disease and Other Dementias in Asian and North African Countries: A Trend Analysis.

In Asia, which has a rapidly aging population, dementia is the most prominent disease. This article presents an application of Latent Growth Mixture Model (LGMM) to identify classes of individual Alzheimer's Disease (AD) and other dementias Years Lived with Disability (YLD) rates for Asian and North African countries based on the unobserved heterogeneity. The AD and other dementias YLD data for both sexes and age-standardized groups reported by the Global Burden of Disease (GBD) Study database during 1990-2015 for 55 Asian and North African countries were analyzed via LGMM. Findings of LGMMs identified four classes of YLD trajectories. Among the specified classes, a class was related to a single country (Turkey) with the highest starting point in 1990 (intercept of 218.52 per 100,000) and upward trend. Another class with increasing trend (a slope of 2.66 per 100,000) consisted of India, China, Singapore, Japan, and Egypt. Other countries in Asia and North Africa (Classes 3 and 4) had a downward trend of YLD rates. The upward trend for some parts of Asia and North Africa might be attributed to appropriate therapeutic strategies, higher levels of awareness, related medical cares, and increase in life expectancy in these countries.

Application of multiple-group latent growth model to determine the effect of shift work on body mass index among petrochemical industries staff.

Background: Shift work can be defined as work activity scheduled in which employees work outside standard daytime hours. Some reports have shown that shift work is associated with several health problems. The main objective of this research was to explore the effect of shift work on body mass index (BMI) over time among Iranian petroleum industry staff. Methods: This longitudinal study sample was consisted of 3,686 (1,872 day workers and 1,814 shift workers) petrochemical industries staff in Mahshahr, southwest of Iran, from 2012 to 2015. The weight and height of these staff were measured using standard techniques and equipment. Multiple-group latent growth curve modeling was used to determine the effect of shift working on BMI trajectories over this period of time via Mplus software, version 6.0. Results: The mean (±SD) age of the shift workers and day workers were 38.96 (±8.36) and 43.33 (±8.35) years, respectively. Findings from the modeling approach showed that the slope of BMI in shift workers on average was 0.14 kg/m2 greater than the day workers in years under study (p<0.001). Conclusion: The findings of the current study suggest that shift work can be considered as a potential risk indicator for higher weight gain in petrochemical staff. Hence, health policy-makers should organize health screening programs and periodical checkups to find high-risk staff and control unhealthy lifestyle factors in these industries.

Application of Bayesian Hierarchical Model for Detecting Effective Factors on Growth Failure of Infants Less Than Two Years of Age in a Multicenter Longitudinal Study.

BACKGROUND: Nowadays, one of the major public health problems among children is growth failure. It can be characterized in terms of either inadequate growth or the inability to maintain growth. OBJECTIVES: The main objective of this study was to examine the effects of some factors on growth failure among a sample of infants less than two years old. MATERIALS AND METHODS: The present longitudinal archival study relied on data gathered from health files from February 2007 to July 2010 for 1,358 children under two years of age, selected from eight health centers in the east and northeast parts of Tehran, Iran. In the present study, growth failure refers to at least a 50 g decrease in an infant's weight as recorded at each attendance in comparison to the previous measurement. The impacts of risk indicators were assessed using the Bayesian hierarchical logistic regression modeling technique. RESULTS: The highest and lowest percentage of growth failure was 5.8% and 0.1%, respectively, in the eleventh and the first month after birth. The obtained results from the Bayesian hierarchical modeling revealed that diarrhea (95% credible interval (CrI): 0.70 - 3.31), discontinuation of breastfeeding (95% CrI: 0.77 - 5.96), and respiratory infections (95% CrI: 2.07 - 4.61) were significant risk factors for growth failure. The random term at the child level was significant (95% CrI: 0.74 - 7.82), while the variation in centers was extremely small (95% CrI: 0.004 - 4.22). CONCLUSIONS: It was noted that a relatively high prevalence of growth failure was observed in the study sample. For minimizing the impact of significant risk factors on growth failure, the early detection of growth failure and its risk indicators is of great importance. In addition, when the focus of the analysis is on the different nested sources of variability and the data has a hierarchical structure, using a hierarchical modeling approach is recommended to achieve more accurate results.