Correlation between rs1800871, rs1800872 and rs1800896 Polymorphisms at IL-10 Gene and Lung Cancer Risk.

BACKGROUND: The tumorigenesis of lung cancer is complicated, and genetic factor may have the role in the malignant transformation of lung cells. IL-10 gene polymorphisms have been evaluated for their potential roles in lung cancer. However, those studies results are controversial. To clarify the effects of IL-10 rs1800871, rs1800872 and rs1800896 polymorphisms on the risk of lung cancer, a meta-analysis was performed with eligible individual studies. METHODS: Eligible publications were gathered by retrieving PubMed, Web of Science, Embase, Wan Fang, and CNKI up to September 01, 2023. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of such association. RESULTS: A total of 23 studies, including 5950 patients with lung cancer and 8046 healthy controls, were identified in this meta-analysis.  Overall, there was no a significant association between the rs1800871, rs1800872 and rs1800896 polymorphisms at IL-10 gene and susceptibility to lung cancer globally when all studies in the pooled into this meta-analysis. Stratified analysis by ethnicity showed that rs1800872 polymorphism was associated with lung cancer among Asians and Caucasians. However, no significant association was identified between the rs1800871 and rs1800896 and risk of lung cancer. CONCLUSIONS: Pooled data showed that  IL-10 rs1800871, rs1800872 and rs1800896 polymorphisms were not associated with lung cancer globally. Future well-designed large case-control studies with different ethnicities are recommended.

Improving genetic risk prediction across diverse population by disentangling ancestry representations.

Risk prediction models using genetic data have seen increasing traction in genomics. However, most of the polygenic risk models were developed using data from participants with similar (mostly European) ancestry. This can lead to biases in the risk predictors resulting in poor generalization when applied to minority populations and admixed individuals such as African Americans. To address this issue, largely due to the prediction models being biased by the underlying population structure, we propose a deep-learning framework that leverages data from diverse population and disentangles ancestry from the phenotype-relevant information in its representation. The ancestry disentangled representation can be used to build risk predictors that perform better across minority populations. We applied the proposed method to the analysis of Alzheimer's disease genetics. Comparing with standard linear and nonlinear risk prediction methods, the proposed method substantially improves risk prediction in minority populations, including admixed individuals, without needing self-reported ancestry information.

Evaluation of the Risk Identification for Suicide and Enhanced Care Model in a Native American Community.

Importance: There are many prognostic models of suicide risk, but few have been prospectively evaluated, and none has been developed specifically for Native American populations. Objective: To prospectively validate a statistical risk model implemented in a community setting and evaluate whether use of this model was associated with improved reach of evidence-based care and reduced subsequent suicide-related behavior among high-risk individuals. Design, Setting, and Participants: This prognostic study, done in partnership with the White Mountain Apache Tribe, used data collected by the Apache Celebrating Life program for adults aged 25 years or older identified as at risk for suicide and/or self-harm from January 1, 2017, through August 31, 2022. Data were divided into 2 cohorts: (1) individuals and suicide-related events from the period prior to suicide risk alerts being active (February 29, 2020) and (2) individuals and events from the time after alerts were activated. Main Outcomes and Measures: Aim 1 focused on a prospective validation of the risk model in cohort 1. Aim 2 compared the odds of repeated suicide-related events and the reach of brief contact interventions among high-risk cases between cohort 2 and cohort 1. Results: Across both cohorts, a total of 400 individuals identified as at risk for suicide and/or self-harm (mean [SD] age, 36.5 [10.3] years; 210 females [52.5%]) had 781 suicide-related events. Cohort 1 included 256 individuals with index events prior to active notifications. Most index events (134 [52.5%]) were for binge substance use, followed by 101 (39.6%) for suicidal ideation, 28 (11.0%) for a suicide attempt, and 10 (3.9%) for self-injury. Among these individuals, 102 (39.5%) had subsequent suicidal behaviors. In cohort 1, the majority (220 [86.3%]) were classified as low risk, and 35 individuals (13.3%) were classified as high risk for suicidal attempt or death in the 12 months after their index event. Cohort 2 included 144 individuals with index events after notifications were activated. For aim 1, those classified as high risk had a greater odds of subsequent suicide-related events compared with those classified as low risk (odds ratio [OR], 3.47; 95% CI, 1.53-7.86; P = .003; area under the receiver operating characteristic curve, 0.65). For aim 2, which included 57 individuals classified as high risk across both cohorts, during the time when alerts were inactive, high-risk individuals were more likely to have subsequent suicidal behaviors compared with when alerts were active (OR, 9.14; 95% CI, 1.85-45.29; P = .007). Before the active alerts, only 1 of 35 (2.9%) individuals classified as high risk received a wellness check; after the alerts were activated, 11 of 22 (50.0%) individuals classified as high risk received 1 or more wellness checks. Conclusions and Relevance: This study showed that a statistical model and associated care system developed in partnership with the White Mountain Apache Tribe enhanced identification of individuals at high risk for suicide and was associated with a reduced risk for subsequent suicidal behaviors and increased reach of care.

Black Patients May See Shorter Wait Times for Kidney Transplants.

A race-based formula underestimating disease progress has been discarded.

Statistical learning methods and cross-cultural fairness: Trade-offs and implications for risk assessment instruments.

The use of statistical learning methods has recently increased within the risk assessment literature. They have primarily been used to increase accuracy and the area under the curve (AUC, i.e., discrimination). Processing approaches applied to statistical learning methods have also emerged to increase cross-cultural fairness. However, these approaches are rarely trialed in the forensic psychology discipline nor have they been trialed as an approach to increase fairness in Australia. The study included 380 Aboriginal and Torres Strait Islander and non-Aboriginal and Torres Strait Islander males assessed with the Level of Service/Risk Needs Responsivity (LS/RNR). Discrimination was assessed through the AUC, and fairness was assessed through the cross area under the curve (xAUC), error rate balance, calibration, predictive parity, and statistical parity. Logistic regression, penalized logistic regression, random forest, stochastic gradient boosting, and support vector machine algorithms using the LS/RNR risk factors were used to compare performance against the LS/RNR total risk score. The algorithms were then subjected to pre- and postprocessing approaches to see if fairness could be improved. Statistical learning methods were found to produce comparable or marginally improved AUC values. Processing approaches increased several fairness definitions (namely xAUC, error rate balance, and statistical parity) between Aboriginal and Torres Strait Islanders and non-Aboriginal and Torres Strait Islanders. The findings demonstrate that statistical learning methods may be a useful approach to increasing the discrimination and cross-cultural fairness of risk assessment instruments. However, both fairness and the use of statistical learning methods encompass significant trade-offs that need to be considered. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Predicting survival after radical prostatectomy: Variation of machine learning performance by race.

BACKGROUND: Robust prediction of survival can facilitate clinical decision-making and patient counselling. Non-Caucasian males are underrepresented in most prostate cancer databases. We evaluated the variation in performance of a machine learning (ML) algorithm trained to predict survival after radical prostatectomy in race subgroups. METHODS: We used the National Cancer Database (NCDB) to identify patients undergoing radical prostatectomy between 2004 and 2016. We grouped patients by race into Caucasian, African-American, or non-Caucasian, non-African-American (NCNAA) subgroups. We trained an Extreme Gradient Boosting (XGBoost) classifier to predict 5-year survival in different training samples: naturally race-imbalanced, race-specific, and synthetically race-balanced. We evaluated performance in the test sets. RESULTS: A total of 68,630 patients met inclusion criteria. Of these, 57,635 (84%) were Caucasian, 8173 (12%) were African-American, and 2822 (4%) were NCNAA. For the classifier trained in the naturally race-imbalanced sample, the F1 scores were 0.514 (95% confidence interval: 0.513-0.511), 0.511 (0.511-0.512), 0.545 (0.541-0.548), and 0.378 (0.378-0.389) in the race-imbalanced, Caucasian, African-American, and NCNAA test samples, respectively. For all race subgroups, the F1 scores of classifiers trained in the race-specific or synthetically race-balanced samples demonstrated similar performance compared to training in the naturally race-imbalanced sample. CONCLUSIONS: A ML algorithm trained using NCDB data to predict survival after radical prostatectomy demonstrates variation in performance by race, regardless of whether the algorithm is trained in a naturally race-imbalanced, race-specific, or synthetically race-balanced sample. These results emphasize the importance of thoroughly evaluating ML algorithms in race subgroups before clinical deployment to avoid potential disparities in care.

Patient Preference and Risk Assessment in Opioid Prescribing Disparities: A Secondary Analysis of a Randomized Clinical Trial.

Importance: Although racial disparities in acute pain control are well established, the role of patient analgesic preference and the factors associated with these disparities remain unclear. Objective: To characterize racial disparities in opioid prescribing for acute pain after accounting for patient preference and to test the hypothesis that racial disparities may be mitigated by giving clinicians additional information about their patients' treatment preferences and risk of opioid misuse. Design, Setting, and Participants: This study is a secondary analysis of data collected from Life STORRIED (Life Stories for Opioid Risk Reduction in the ED), a multicenter randomized clinical trial conducted between June 2017 and August 2019 in the emergency departments (EDs) of 4 academic medical centers. Participants included 1302 patients aged 18 to 70 years who presented to the ED with ureter colic or musculoskeletal back and/or neck pain. Interventions: The treatment arm was randomized to receive a patient-facing intervention (not examined in this secondary analysis) and a clinician-facing intervention that consisted of a form containing information about each patient's analgesic treatment preference and risk of opioid misuse. Main Outcomes and Measures: Concordance between patient preference for opioid-containing treatment (assessed before ED discharge) and receipt of an opioid prescription at ED discharge. Results: Among 1302 participants in the Life STORRIED clinical trial, 1012 patients had complete demographic and treatment preference data available and were included in this secondary analysis. Of those, 563 patients (55.6%) self-identified as female, with a mean (SD) age of 40.8 (14.1) years. A total of 455 patients (45.0%) identified as White, 384 patients (37.9%) identified as Black, and 173 patients (17.1%) identified as other races. After controlling for demographic characteristics and clinical features, Black patients had lower odds than White patients of receiving a prescription for opioid medication at ED discharge (odds ratio [OR], 0.42; 95% CI, 0.27-0.65). When patients who did and did not prefer opioids were considered separately, Black patients continued to have lower odds of being discharged with a prescription for opioids compared with White patients (among those who preferred opioids: OR, 0.43 [95% CI, 0.24-0.77]; among those who did not prefer opioids: OR, 0.45 [95% CI, 0.23-0.89]). These disparities were not eliminated in the treatment arm, in which clinicians were given additional data about their patients' treatment preferences and risk of opioid misuse. Conclusions and Relevance: In this secondary analysis of data from a randomized clinical trial, Black patients received different acute pain management than White patients after patient preference was accounted for. These disparities remained after clinicians were given additional patient-level data, suggesting that a lack of patient information may not be associated with opioid prescribing disparities. Trial Registration: ClinicalTrials.gov Identifier: NCT03134092.

Racial/Ethnic Disparities in the Performance of Prediction Models for Death by Suicide After Mental Health Visits.

Importance: Clinical prediction models estimated with health records data may perpetuate inequities. Objective: To evaluate racial/ethnic differences in the performance of statistical models that predict suicide. Design, Setting, and Participants: In this diagnostic/prognostic study, performed from January 1, 2009, to September 30, 2017, with follow-up through December 31, 2017, all outpatient mental health visits to 7 large integrated health care systems by patients 13 years or older were evaluated. Prediction models were estimated using logistic regression with LASSO variable selection and random forest in a training set that contained all visits from a 50% random sample of patients (6 984 184 visits). Performance was evaluated in the remaining 6 996 386 visits, including visits from White (4 031 135 visits), Hispanic (1 664 166 visits), Black (578 508 visits), Asian (313 011 visits), and American Indian/Alaskan Native (48 025 visits) patients and patients without race/ethnicity recorded (274 702 visits). Data analysis was performed from January 1, 2019, to February 1, 2021. Exposures: Demographic, diagnosis, prescription, and utilization variables and Patient Health Questionnaire 9 responses. Main Outcomes and Measures: Suicide death in the 90 days after a visit. Results: This study included 13 980 570 visits by 1 433 543 patients (64% female; mean [SD] age, 42 [18] years. A total of 768 suicide deaths were observed within 90 days after 3143 visits. Suicide rates were highest for visits by patients with no race/ethnicity recorded (n = 313 visits followed by suicide within 90 days, rate = 5.71 per 10 000 visits), followed by visits by Asian (n = 187 visits followed by suicide within 90 days, rate = 2.99 per 10 000 visits), White (n = 2134 visits followed by suicide within 90 days, rate = 2.65 per 10 000 visits), American Indian/Alaskan Native (n = 21 visits followed by suicide within 90 days, rate = 2.18 per 10 000 visits), Hispanic (n = 392 visits followed by suicide within 90 days, rate = 1.18 per 10 000 visits), and Black (n = 65 visits followed by suicide within 90 days, rate = 0.56 per 10 000 visits) patients. The area under the curve (AUC) and sensitivity of both models were high for White, Hispanic, and Asian patients and poor for Black and American Indian/Alaskan Native patients and patients without race/ethnicity recorded. For example, the AUC for the logistic regression model was 0.828 (95% CI, 0.815-0.840) for White patients compared with 0.640 (95% CI, 0.598-0.681) for patients with unrecorded race/ethnicity and 0.599 (95% CI, 0.513-0.686) for American Indian/Alaskan Native patients. Sensitivity at the 90th percentile was 62.2% (95% CI, 59.2%-65.0%) for White patients compared with 27.5% (95% CI, 21.0%-34.7%) for patients with unrecorded race/ethnicity and 10.0% (95% CI, 0%-23.0%) for Black patients. Results were similar for random forest models, with an AUC of 0.812 (95% CI, 0.800-0.826) for White patients compared with 0.676 (95% CI, 0.638-0.714) for patients with unrecorded race/ethnicity and 0.642 (95% CI, 0.579-0.710) for American Indian/Alaskan Native patients and sensitivities at the 90th percentile of 52.8% (95% CI, 50.0%-55.8%) for White patients, 29.3% (95% CI, 22.8%-36.5%) for patients with unrecorded race/ethnicity, and 6.7% (95% CI, 0%-16.7%) for Black patients. Conclusions and Relevance: These suicide prediction models may provide fewer benefits and more potential harms to American Indian/Alaskan Native or Black patients or those with undrecorded race/ethnicity compared with White, Hispanic, and Asian patients. Improving predictive performance in disadvantaged populations should be prioritized to improve, rather than exacerbate, health disparities.

Performance of intensive care unit severity scoring systems across different ethnicities in the USA: a retrospective observational study.

BACKGROUND: Despite wide use of severity scoring systems for case-mix determination and benchmarking in the intensive care unit (ICU), the possibility of scoring bias across ethnicities has not been examined. Guidelines on the use of illness severity scores to inform triage decisions for allocation of scarce resources, such as mechanical ventilation, during the current COVID-19 pandemic warrant examination for possible bias in these models. We investigated the performance of the severity scoring systems Acute Physiology and Chronic Health Evaluation IVa (APACHE IVa), Oxford Acute Severity of Illness Score (OASIS), and Sequential Organ Failure Assessment (SOFA) across four ethnicities in two large ICU databases to identify possible ethnicity-based bias. METHODS: Data from the electronic ICU Collaborative Research Database (eICU-CRD) and the Medical Information Mart for Intensive Care III (MIMIC-III) database, built from patient episodes in the USA from 2014-15 and 2001-12, respectively, were analysed for score performance in Asian, Black, Hispanic, and White people after appropriate exclusions. Hospital mortality was the outcome of interest. Discrimination and calibration were determined for all three scoring systems in all four groups, using area under receiver operating characteristic (AUROC) curve for different ethnicities to assess discrimination, and standardised mortality ratio (SMR) or proxy measures to assess calibration. FINDINGS: We analysed 166 751 participants (122 919 eICU-CRD and 43 832 MIMIC-III). Although measurements of discrimination were significantly different among the groups (AUROC ranging from 0·86 to 0·89 [p=0·016] with APACHE IVa and from 0·75 to 0·77 [p=0·85] with OASIS), they did not display any discernible systematic patterns of bias. However, measurements of calibration indicated persistent, and in some cases statistically significant, patterns of difference between Hispanic people (SMR 0·73 with APACHE IVa and 0·64 with OASIS) and Black people (0·67 and 0·68) versus Asian people (0·77 and 0·95) and White people (0·76 and 0·81). Although calibrations were imperfect for all groups, the scores consistently showed a pattern of overpredicting mortality for Black people and Hispanic people. Similar results were seen using SOFA scores across the two databases. INTERPRETATION: The systematic differences in calibration across ethnicities suggest that illness severity scores reflect statistical bias in their predictions of mortality. FUNDING: There was no specific funding for this study.

Association of Vitamin D Levels, Race/Ethnicity, and Clinical Characteristics With COVID-19 Test Results.

Importance: Deficient (ie, <20 ng/mL) or insufficient (ie, 20 to <30 ng/mL) 25-hydroxyvitamin D (also known as calcifediol) levels are more common in Black individuals than White individuals and are associated with increased coronavirus disease 2019 (COVID-19) risk. Whether COVID-19 risk is associated with differences in vitamin D levels of 30 ng/mL or greater is not known. Objective: To examine whether COVID-19 test results are associated with differences in vitamin D levels of 30 ng/mL or greater, including for White individuals and for Black individuals. Design, Setting, and Participants: This retrospective cohort study was conducted at an academic medical center in Chicago, Illinois. Participants included individuals with data on vitamin D level within 365 days before COVID-19 testing, which was conducted from March 3 to December 30, 2020. Data were analyzed from September 11, 2020, to February 5, 2021. Exposures: The last vitamin D level before COVID-19 testing was categorized as less than 20 ng/mL (ie, deficient), 20 to less than 30 ng/mL (ie, insufficient), 30 to less than 40 ng/mL, or 40 ng/mL or greater. Treatment was defined by vitamin D type and dose 14 days before COVID-19 testing and treatment changes after last vitamin D level. Main Outcomes and Measures: The main outcome was a positive result for COVID-19 in polymerase chain reaction testing. Multivariable analyses tested whether previously measured vitamin D level was associated with having test results positive for COVID-19 in White individuals and in Black individuals, controlling for months and treatment changes since the vitamin D level was measured, as well as demographic characteristics and comorbidity indicators. Results: A total of 4638 individuals (mean [SD] age 52.8 [19.5] years; 3205 [69%] women) had data for a vitamin D level within 1 year before COVID-19 testing, including 2288 (49%) Black individuals, 1999 (43%) White individuals, and 351 individuals (8%) who were another race/ethnicity (eg, Asian, Mideast Indian, >1 race). Stratified by vitamin D level, 1251 individuals (27%) had less than 20 ng/mL, 1267 individuals (27%) had 20 to less than 30 ng/mL, 1023 individuals (22%) had 30 to less than 40 ng/mL, and 1097 individuals (24%) had 40 ng/mL or greater. Lower vitamin D levels were more common in Black individuals (<20 ng/mL: 829 of 2288 Black individuals [36%]) than White individuals (<20 ng/mL: 315 of 1999 White individuals [16%]). A total of 333 individuals (7%) had test results positive for COVID-19, including 102 White individuals (5%) and 211 Black individuals (9%). Multivariate analysis controlling for time since last vitamin D level measurement was used to estimate the outcomes associated with levels 14 days before COVID-19 testing. A positive test result for COVID-19 was not significantly associated with vitamin D levels in White individuals but was associated with vitamin D levels in Black individuals (compared with ≥40 ng/mL: <20 ng/mL incidence rate ratio [IRR], 2.55 [95% CI, 1.26-5.15]; P = .009; 20 to <30 ng/mL IRR, 1.69 [95% CI, 0.75-3.84]; P = .21; 30 to <40 ng/mL IRR, 2.64 [95% CI, 1.24-5.66]; P = .01). Stratified by vitamin D level, estimated COVID-19 positivity rates in Black individuals were 9.72% (95% CI, 6.74%-13.41%) for individuals with a vitamin D level less than 20 ng/mL, 6.47% (95% CI, 3.33%-10.28%) for individuals with a vitamin D level of 20 to less than 30 ng/mL, 10.10% (95% CI, 6.00%-15.47%) for individuals with a vitamin D level of 30 to less than 40 ng/mL, and 3.82% (95% CI, 1.78%-6.68%) for individuals with a vitamin D level of 40 ng/mL or higher. Multivariate analysis in individuals with a vitamin D level of 30 ng/mL or greater found that the IRR of a positive COVID-19 test result was 0.97 (95% CI, 0.94-0.99; P = .008) per 1-ng/mL increase in vitamin D overall and 0.95 (95% CI, 0.91-0.98; P = .003) per 1-ng/mL increase in vitamin D in Black individuals. Conclusions and Relevance: In this single-center retrospective cohort study, COVID-19 risk increased among Black individuals with vitamin D level less than 40 ng/mL compared with those with 40 ng/mL or greater and decreased with increasing levels among individuals with levels greater than 30 ng/mL. No significant associations were noted for White individuals. Randomized clinical trials should examine whether increasing vitamin D level to greater than 40 ng/mL affects COVID-19 risk.

Psychosocial outcomes following germline multigene panel testing in an ethnically and economically diverse cohort of patients.

BACKGROUND: Little is known about the psychological outcomes of germline multigene panel testing, particularly among diverse patients and those with moderate-risk pathogenic variants (PVs). METHODS: Study participants (N = 1264) were counseled and tested with a 25- or 28-gene panel and completed a 3-month postresult survey including the Multidimensional Impact of Cancer Risk Assessment (MICRA). RESULTS: The mean age was 52 years, 80% were female, and 70% had cancer; 45% were non-Hispanic White, 37% were Hispanic, 10% were Asian, 3% were Black, and 5% had another race/ethnicity. Approximately 28% had a high school education or less, and 23% were non-English-speaking. The genetic test results were as follows: 7% had a high-risk PV, 6% had a moderate-risk PV, 35% had a variant of uncertain significance (VUS), and 52% were negative. Most participants (92%) had a total MICRA score ≤ 38, which corresponded to a mean response of "never," "rarely," or only "sometimes" reacting negatively to results. A multivariate analysis found that mean total MICRA scores were significantly higher (more uncertainty/distress) among high- and moderate-risk PV carriers (29.7 and 24.8, respectively) than those with a VUS or negative results (17.4 and 16.1, respectively). Having cancer or less education was associated with a significantly higher total MICRA score; race/ethnicity was not associated with the total MICRA score. High- and moderate-risk PV carriers did not differ significantly from one another in the total MICRA score, uncertainty, distress, or positive experiences. CONCLUSIONS: In a diverse population undergoing genetic counseling and multigene panel testing for hereditary cancer risk, the psychological response corresponded to test results and showed low distress and uncertainty. Further studies are needed to assess patient understanding and subsequent cancer screening among patients from diverse backgrounds. LAY SUMMARY: Multigene panel tests for hereditary cancer have become widespread despite concerns about adverse psychological reactions among carriers of moderate-risk pathogenic variants (mutations) and among carriers of variants of uncertain significance. This large study of an ethnically and economically diverse cohort of patients undergoing panel testing found that 92% "never," "rarely," or only "sometimes" reacted negatively to results. Somewhat higher uncertainty and distress were identified among carriers of high- and moderate-risk pathogenic variants, and lower levels were identified among those with a variant of uncertain significance or a negative result. Although the psychological response corresponded to risk, reactions to testing were favorable, regardless of results.

The Impact of Race and Age on Distribution of Metastases in Patients with Prostate Cancer.

PURPOSE: We investigated the effect of race and age on the distribution of prostate cancer metastases. MATERIALS AND METHODS: Records for patients with metastatic prostate cancer were abstracted from the National Inpatient Sample database (2008-2015). RESULTS: Of 6,963 patients with metastatic prostate cancer 3,881 (72.2%) were Caucasian and 1,494 (27.8%) were African American. Bone metastases were the most common site of metastases in Caucasian and African American patients (83.9% and 87.0%, respectively), followed by distant lymph node metastases in Caucasian (13.9% of Caucasian vs 13.2% of African American), liver metastases in African American (13.8% of African American vs 13.3% of Caucasian) and lung metastases in Caucasian and African American patients (9.3% and 13.1%, respectively). No clinically meaningful differences were recorded in age and race analyses, except for lymph node metastases (61.1% to 23.4% in Caucasian vs 39.0% to 25.1% in African American patients), which decreased with age. Specific single organ metastatic sites, outside of bone and lymph nodes, were low in both racial groups (2.1% or less). The rate of brain metastases was also rare in both racial groups at 1.4% or less, regardless of other metastatic locations. Thoracic metastases, in the absence of bone and abdominal metastases, were present in 1.9% of Caucasian and African American patients. CONCLUSIONS: The most important finding according to age and race resided in rates of lymph node metastases. Conversely, all other racial and age related differences were subtle. Nonetheless, they are important in the context of planning and/or design of clinical trials. Finally, brain (1.4%) and thoracic (1.9%) metastases affect few patients and routine brain and chest imaging may not be warranted.

A national population-based cohort study to investigate inequalities in maternal mortality in the United Kingdom, 2009-17.

BACKGROUND: Disparities have been documented in maternal mortality rates between women from different ethnic, age and socio-economic groups in the UK. It is unclear whether there are differential changes in these rates amongst women from different groups over time. The objectives of this analysis were to describe UK maternal mortality rates in different age, ethnic and socio-economic groups between 2009 and 2017, and to identify whether there were changes in the observed inequalities, or different trends amongst population subgroups. METHODS: Maternal mortality rates with 95% confidence intervals (CI) in specific age, deprivation and ethnic groups were calculated using numbers of maternal deaths as numerator and total maternities as denominator. Relative risks (RR) with 95% CI were calculated and compared using ratios of relative risk. Change over time was investigated using non-parametric tests for trend across ordered groups. RESULTS: Women from black and Asian groups had a higher mortality rate than white women in most time periods, as did women aged 35 and over and women from the most deprived quintile areas of residence. There was evidence of an increasing trend in maternal mortality amongst black women and a decrease in mortality amongst women from the least deprived areas, but no trends over time in any of the other ethnic, age or IMD groups were seen. There was a widening of the disparity between black and white women (RR 2.59 in 2009-11 compared with 5.27 in 2015-17, ratio of the relative risks 2.03, 95% CI 1.11, 3.72). CONCLUSIONS: The clear differences in the patterns of maternal mortality amongst different ethnic, age and socio-economic groups emphasise the importance of research and policies focussed specifically on women from black and minority ethnic groups, together with other disadvantaged groups, to begin to reduce maternal mortality in the UK.

Networks as culture: understanding and accounting for risks within networks of medico-social actors.

The anthropological part of the present research project addresses the issue of risk and uncertainties relating to perinatality and disability, and draws from the discourses of professionals in a perinatal network in the French Lorraine region. From an anthropological point of view, it is necessary to determine how and to what extent the views of professionals determine the network's management policies. The place conferred to 'the user' in these representations is one of several important issues to be analysed in order to gain better understanding of the management of relationships that result from it. What is the position of professionals who 'negotiate' and 'organise' the cost of the risk of disability when grasped in connection with their images of the 'users' (children and parents)? This qualitative study consisted of 40 semi-structured interviews conducted with 20 medical, social, and community professionals, all involved directly or indirectly with the network. The results demonstrate the importance of a network assessment as a 'culture' from the social and cultural relations of network professionals. These relations form the cement of a structure made of interpersonal ties and rooted in particular histories around a 'user' that are conveyed through individual narratives.

Obesity and cardiovascular disease risk among Africans residing in Europe and Africa: the RODAM study.

BACKGROUND: The association between anthropometric variables and cardiovascular disease (CVD) risk among Africans is unclear. We examined the discriminative ability of anthropometric variables and estimate cutoffs for predicting CVD risk among Africans. METHODS: The Research on Obesity and Diabetes among African Migrants (RODAM) study was a multisite cross-sectional study of Africans in Ghana and Europe. We calculated AHA/ACC Pooled Cohort Equations (PCE) scores for 3661 participants to ascertain CVD risk, and compared a body shape index (ABSI), body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), Relative Fat Mass (RFM), and Waist to Height Ratio (WHtR). Logistic regression and receiver operating curve analyses were performed to derive cutoffs for identifying high predicted CVD risk (PCE score ≥7.5%). RESULTS: Among men, WC (adjusted Odds Ratio (aOR): 2.25, 95% CI; 1:50-3:37) was strongly associated with CVD risk. Among women, WC (aOR: 1.69, 95% CI: 1:33-2:14) also displayed the strongest association with CVD risk in the BMI-adjusted model but WHR displayed the strongest fit. All variables were superior discriminators of high CVD risk in men (c-statistic range: 0.887-0.891) than women (c-statistic range: 0.677-0.707). The optimal WC cutoff for identifying participants at high CVD risk was 89 cm among men and identified the most cases (64%). Among women, the recommended WC cutoff of 94 cm or WHR cutoff of 0.90 identified the most cases (92%). CONCLUSIONS: Anthropometric variables were stronger discriminators of high CVD risk in African men than women. Greater WC was associated with high CVD risk in men while WHR and WC were associated with high CVD risk in women.

Perceived Risk of Developing Diabetes in the General Population and Asian Americans: Systematic Review.

Introduction: The purpose of this systematic review was to explore perceived diabetes risk with foci on prediabetic persons and Asian Americans. Persons with prediabetes and of Asian descent are at higher risk for developing diabetes, but little is known about their perceived diabetes risk. Method: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guided this systematic review. Electronic searches were conducted in three databases. The authors conducted eligibility determination, data extraction, synthesis, and evaluation. Twelve articles were selected. Results: Key findings include (1) limited studies including Asian populations, (2) a low percentage of persons in the general population with moderate to high levels of perceived diabetes risk, (3) a lack of congruency between actual and perceived diabetes risk in the general population, and (4) no interventions effectively changing the level of perceived diabetes risk. Discussion: More studies regarding perceived diabetes risk are needed, especially with a focus on Asian Americans.

Diet Associations With Nonalcoholic Fatty Liver Disease in an Ethnically Diverse Population: The Multiethnic Cohort.

BACKGROUND AND AIMS: Epidemiological data on dietary risk factors for nonalcoholic fatty liver disease (NAFLD) from population-based studies, particularly in an ethnically diverse population, are scarce. We examined dietary factors in relation to NAFLD risk in African Americans, Japanese Americans, Latinos, native Hawaiians, and whites in the Multiethnic Cohort (MEC). APPROACH AND RESULTS: A nested case-control analysis was conducted within the MEC, a large prospective study with >215,000 older adult participants in Hawaii and California. NAFLD was identified using Medicare claims data, and controls were selected among participants without liver disease and individually matched to cases by birth year, sex, ethnicity, and length of Medicare enrollment. Diet was assessed at baseline through a validated quantitative food frequency questionnaire. Diet-NAFLD associations were quantified by odds ratios and 95% confidence intervals using multivariable conditional logistic regression. The study consisted of 2,974 NAFLD cases (518 with cirrhosis, 2,456 without cirrhosis) and 29,474 matched controls. Red meat (P trend = 0.010), processed red meat (P trend = 0.004), poultry (P trend = 0.005), and cholesterol (P trend = 0.005) intakes were positively associated with NAFLD, while dietary fiber intake (P trend = 0.003) was inversely associated with risk. Stronger associations were observed between red meat and cholesterol and NAFLD with cirrhosis than without cirrhosis (P heterogeneity ≤0.014). CONCLUSIONS: Dietary factors are independently associated with NAFLD and NAFLD-related cirrhosis in a multiethnic population. Decreasing the consumption of cholesterol, red and processed meat, and poultry and increasing consumption of fiber may reduce the risk for NAFLD and related advanced liver disease.

Validation of Asia-Pacific Colorectal Screening Score for Asymptomatic Participants and Outpatients in Northwest District of China.

INTRODUCTION: Asia-Pacific Colorectal Screening (APCS) score has been implemented for colorectal cancer screening in asymptomatic cohort in many regions. However, no study has validated its efficiency in Asian outpatients with mild-self-limited gastrointestinal symptoms yet. The purpose of this study was to validate its efficiency in asymptomatic subjects and outpatients in Ningxia. METHODS: The records of 329 asymptomatic participants and 300 outpatients were collected and analyzed from database in the General Hospital of Ningxia Medical University from September 2017 to April 2018. These 2 main groups were divided into 3 tiers based on the scores calculated by the category of APCS score. The detection rates of advanced colorectal neoplasia (ACRN) were further compared according to histopathological classifications of tissues acquired during colonoscopy. RESULTS: Among the 329 participants screened in the asymptomatic cohort, 78 subjects (23.7%) were in the low-risk (LR) tier, 187 subjects (56.8%) in the moderate-risk (MR) tier, and 64 subjects (19.5%) in the high-risk (HR) tier. The percentage of ACRN in the LR, MR, and HR groups was 1.3, 8.6, and 20.3%, respectively. In the 300 outpatient cohorts, 78 patients (26%) were in the LR tier, 140 patients (46.7%) in the MR tier, and 82 patients (27.3%) in the HR tier. The detection rates of ACRN in the LR, MR, and HR groups were 0, 10, and 39%, respectively. CONCLUSION: APCS score is an effective method for ACRN screening in asymptomatic and also the outpatient subjects. Individuals with HR scores should be given priority for colonoscopy.