Multiple Risk Models Research Articles

Analysis Using Various Models on the Effect of Metabolic Surgery on Cardiovascular Disease Risk in the Chinese Population with Obesity.

Some research have indicated that Bariatric andmetabolic surgery(BMS) can reduce the risk of cardiovascular disease (CVD) among individuals with obesity. However, there are few reports available that focuses on assessing effect of BMS on the risk of CVD in Chinese population using multiple models. This research aims to assess the function of BMS on the risk of CVD in Chinese patients with obesity using multiple CVD risk models. We performed a retrospective analysis of the basic data and glycolipid metabolism data preoperatively and postoperatively from patients with obesity at our hospital. Subgroup analysis was carried out according to different surgical procedures. Then, the function of BMS on the risk of CVD in the Chinese population was assessed using four models, including: China-PAR risk model, Framingham risk score (FRS), World Health Organization (WHO) risk model, and Globorisk model. We enrolled 64 patients, 24 (37.5%) of whom underwent laparoscopic sleeve gastrectomy (LSG) while 40 (62.5%) underwent Roux-en-Y gastric bypass (RYGB). The 10-year CVD risk for patients calculated using the China-PAR risk model decreased from 6.3% preoperatively to 2.0% at 1 year postoperatively and was statistically significantly different. Similarly, the 10-year CVD risk of patients calculated using the FRS, WHO, Global risk model decreased significantly at 1 year postoperatively compared to preoperatively. When the FRS risk model was used to calculate the patients' 30-year postoperative CVD risk, there was a significant decrease at 1 year after surgery compared to the preoperative period. When employing various models to evaluate the 10-year CVD risk for LSG and RYGB, no statistically significant difference was found in the 1-year postoperative RRR between the procedures. The CVD risk after BMS was significantly reduced compared to preoperatively. In terms of improving cardiovascular risk, SG and RYGB appear to be equally effective.

The Society of Thoracic Surgeons Adult Cardiac Surgery Database: 2023 Update on Procedure Data and Research

The Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database is one of the largest and most comprehensive contemporary clinical databases in use. It now contains >9 million procedures from 1010 participants and 3651 active surgeons. Using audited data collection, it has provided the foundation for multiple risk models, performance metrics, health policy decisions, and a trove of research studies to improve the care of patients in need of cardiac surgical procedures. This annual report provides an update on the current status of the database and summarizes the development of new risk models and the STS Online Risk Calculator. Further, it provides insights into current practice patterns, such as the change in the demographics among patients undergoing aortic valve replacement, the use of minimally invasive techniques for valve and bypass surgery, or the adoption of surgical ablation and left atrial appendage ligation among patients with atrial fibrillation. Lastly, an overview of the research conducted using the STS Adult Cardiac Surgery Database and future directions for the database are provided.

Parsimonious versus extensive score: can we simplify bleeding risk stratification after percutaneous coronary intervention without losing specificity?

Abstract Background/Introduction Prediction of bleeding risk in patients receiving dual antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI) has been repeatedly attempted and resulted in multiple risk models. To promote the adoption and use of risk stratification among clinicians, a consortium in the South East of the Netherlands, the "ZON-HR", has created a simple binary variant of the existing logistic models. This model includes commonly available factors which can be incorporated into the PCI report to generate stratification. In this "parsimonious" model, high bleeding risk (HBR) is stratified according to: history of intracranial haemorrhage, previous spontaneous bleeding, Hb < 11 g/dL, eGFR< 30. Purpose We aimed to perform an external validation of our model for bleeding risk and to demonstrate its discriminative value in comparison with the PRECISE DAPT score, an acknowledged risk score. Methods We performed a post hoc analysis of the GLOBAL LEADERS trial, a multicenter randomized trial, comparing ticagrelor monotherapy after one month of DAPT with standard DAPT after PCI. We stratified the patients for HBR according to the ZON-HR or a PRECISE-DAPT score ≥ 25. Bleeding events one year after PCI were compared in the entire population and in subgroups for chronic coronary syndrome (CCS), acute coronary syndrome (ACS), Ticagrelor monotherapy and DAPT. Results Of the 15968 patients included in GLOBAL LEADERS, 1059 patients were excluded due to missing variables required for either model. Among the 14909 patients, 17% had HBR according to the PRECISE DAPT score, 4% according to ZON-HR and 3% according to both. Bleeding events occurred in 8.5% and 13% of HBR defined by PRECISE DAPT or ZON-HR respectively. Patients with HBR according to both models showed 13% bleedings as opposed to 5% in non-HBR. Table 1 presents the sensitivity and specificity. Regression analysis (figure 1) demonstrated that patients with HBR according to either model have significantly more bleedings. This was also significant in all subgroups except for ACS patients receiving standard DAPT when the ZON-HR model was used. Conclusion The ZON-HR model is more conservative compared to the PRECISE DAPT score as depicted by the sensitivity and specificity. This can be explained by the larger number of risk factors used in the PRECISE DAPT score that cumulatively contributes to the sensitivity as opposed to the binary ZON-HR model which is more specific. However, the survival curves and hazard ratios showed good predictive value of both models for bleeding risk in the overall population.Table 1.Figure 1.

Effect of various hepatectomy procedures on circulating tumor cells in postoperative patients: a case-matched comparative study.

The objective of this study is to elucidate the prevalence of systemic circulating tumor cells (CTCs) prior to and following resection of hepatocellular carcinoma (HCC), and to compare the disparities in postoperative CTCs in terms of quantity and classifications between the open liver resection (OPEN) and laparoscopic liver resection (LAP) cohorts. From September 2015 to May 2022, 32 consecutive HCC patients who underwent laparoscopic liver resection at Southwest Hospital were retrospectively enrolled in this study. The clinicopathological data were retrieved from a prospectively collected computer database. Patients in the OPEN group matched at a 1:1 ratio with patients who underwent open liver resection during the study period on age, gender, tumor size, number of tumors, tumor location, hepatitis B surface antigen (HBsAg) positivity, alpha-fetoprotein (AFP) level, TNM and Child-Pugh staging from the database of patients to form the control group. The Can-Patrol CTC enrichment technique was used to enrich and classify CTCS based on epithelial-mesenchymal transformation phenotypes. The endpoint was disease-free survival (DFS), and the Kaplan-Meier method and multiple Cox proportional risk model were used to analyze the influence of clinicopathological factors such as total CTCs and CTC phenotype on prognosis. The mean age of the 64 patients with primary liver cancer was 52.92 years (23-71), and 89.1% were male. The postoperative CTC clearance rate was more significant in the OPEN group. The total residual CTC and phenotypic CTC of the LAP group were significantly higher than those of the OPEN group (p = 0.017, 0.012, 0.049, and 0.030, respectively), which may increase the possibility of metastasis (p = 0.042). In Kaplan-Meier analysis, DFS was associated with several clinicopathological risk factors, including Barcelona Clinical Liver Cancer (BCLC) stage, tumor size, and vascular invasion. Of these analyses, BCLC Stage [p = 0.043, HR (95% CI) =2.03(1.022-4.034)], AFP [p = 0.007, HR (95% CI) =1.947 (1.238-3.062)], the number of positive CTCs [p = 0.004, HR (95% CI) =9.607 (2.085-44.269)] and vascular invasion [p = 0.046, HR (95% CI) =0.475 (0.22-1.023)] were significantly associated with DFS. In comparison to conventional OPEN technology, LAP technology has the capacity to augment the quantity of epithelial, mixed, and mesenchymal circulating tumor cells (CTCs). Following the surgical procedure, there was a notable increase in the total CTCs, epithelial CTCs, and mixed CTCs within the LAP group, indicating a potential drawback of LAP in facilitating the release of CTCs.

Simple and Multi Risk Assessment Framework for Information Security using Process Flow Diagram

Organizations need a simple risk assessment framework to understand them. In contrast, risk analysis requires some mathematical tools to be able to estimate risk based on understanding and availability. In practice, the assets, for which the risk will be calculated, are dependent on one another, resulting in inevitable complexity. We propose a framework that addresses these three situations with a process flow diagram. Simplicity is obtained from a conceptual model based on data flow diagrams which are widely used in information system design. This conceptual model can be translated into several risk models at once: graph, Boolean algebra, Boole’s algebra, and set theory. The complexity of asset dependencies is overcome when translating the conceptual model to the risk model. Solutions were shown in case studies of information systems for COVID-19 personal protective equipment in Indonesia, which require the construction of a simple information system, support multiple risk models, and take into account asset dependencies. The multi-risk model enables implementation proofing by testing the risk models used in each other.

Risk Models for Developing Pancreatic Fistula After Pancreatoduodenectomy: Validation in a Nationwide Prospective Cohort.

To evaluate the performance of published fistula risk models by external validation, and to identify independent risk factors for postoperative pancreatic fistula (POPF). Multiple risk models have been developed to predict POPF after pancreatoduodenectomy. External validation in high-quality prospective cohorts is, however, lacking or only performed for individual models. A post hoc analysis of data from the stepped-wedge cluster cluster-randomized Care After Pancreatic Resection According to an Algorithm for Early Detection and Minimally Invasive Management of Pancreatic Fistula versus Current Practice (PORSCH) trial was performed. Included were all patients undergoing pancreatoduodenectomy in the Netherlands (January 2018-November 2019). Risk models on POPF were identified by a systematic literature search. Model performance was evaluated by calculating the area under the receiver operating curves (AUC) and calibration plots. Multivariable logistic regression was performed to identify independent risk factors associated with clinically relevant POPF. Overall, 1358 patients undergoing pancreatoduodenectomy were included, of whom 341 patients (25%) developed clinically relevant POPF. Fourteen risk models for POPF were evaluated, with AUCs ranging from 0.62 to 0.70. The updated alternative fistula risk score had an AUC of 0.70 (95% confidence intervals [CI]: 0.69-0.72). The alternative fistula risk score demonstrated an AUC of 0.70 (95% CI: 0.689-0.71), whilst an AUC of 0.70 (95% CI: 0.699-0.71) was also found for the model by Petrova and colleagues. Soft pancreatic texture, pathology other than pancreatic ductal adenocarcinoma or chronic pancreatitis, small pancreatic duct diameter, higher body mass index, minimally invasive resection and male sex were identified as independent predictors of POPF. Published risk models predicting clinically relevant POPF after pancreatoduodenectomy have a moderate predictive accuracy. Their clinical applicability to identify high-risk patients and guide treatment strategies is therefore questionable.

The Association of Polymorphisms in Genes Encoding Antioxidant Enzymes GPX1 (rs1050450), SOD2 (rs4880) and Transcriptional Factor Nrf2 (rs6721961) with the Risk and Development of Prostate Cancer.

Background and Objectives: Mounting evidence implicates oxidative damage in prostate carcinogenesis, contributing to modifications of macromolecules that drive cellular malignant transformation. Functional single-nucleotide polymorphisms (SNPs) of enzymes involved in redox homeostasis can disrupt pro-oxidant–antioxidant balance, leading to accumulation of reactive oxygen species and oxidative damage. We investigated the potential role of genetic polymorphisms of antioxidant enzymes glutathione peroxidase 1 (GPX1 rs1050450) and superoxide dismutase 2 (SOD2 rs4880) and regulatory antioxidant protein nuclear factor erythroid 2-related factor 2 (Nrf2 rs6721961) in the susceptibility to prostate cancer development (PC) and prognosis. Materials and Methods: We conducted a case–control study consisting of 235 patients with PC and 240 controls. Gene polymorphisms were determined by quantitative polymerase chain reaction (qPCR) and polymerase chain reaction with confronting two-pair primers (PCR-CTTP) methods. Multiple risk models were composed to inspect the separate and mutual effect of multiple genes and in combination with acquired contributory factors on the risk of PC development. Results: Independently, carriers of at least one SOD2*C allele had increased risk of PC development, which was significantly further amplified in advanced statistical models. When tested in combination, individuals with both SOD2*C allele and Nrf2*C/C genotype were also at increased risk of PC development, which was augmented when combined with acquired contributory factors. During the mean 75 ± 25 months of follow-up, investigated gene polymorphisms did not affect overall survival. Conclusion: Our results suggest that these gene polymorphisms could be used as risk biomarkers of PC evolution.

Anxiety and depression related to childhood maltreatment in teenagers: Comparing multiple individual risk model, cumulative risk model and latent profile analysis

BackgroundFew studies have employed person-centered approaches (i.e. latent profile analysis in this study) to investigate the specific patterns of childhood maltreatment in a large sample of Chinese adolescents, and little is known about the predictive validity of latent profile analysis on internalizing problems, compared with multiple individual risk model and cumulative risk model. ObjectiveThe purpose of this study was to investigate whether differential patterns of maltreatment existed by employing latent profile analysis with a sample of 9071 Chinese adolescents, and further examined the predictive validity of latent profile analysis on internalizing problems, relative to the cumulative risk and multiple individual risk model. ParticipantsUsing a stratified sampling approach, 10,515 participants (Mean age = 14.24; SD = 1.73) were chosen from three different types of middle schools in Chongqing city, China. 9071 valid responses (males = 4775; females = 4296) were obtained for final analysis. MethodsParticipants reported their childhood maltreatment experience, anxiety and depression symptoms. Latent profile analysis was used to obtain possible patterns of maltreatment with Mplus version 7. 4. Bolck-Croon-Hagenaars (BCH) method was used to test the association between maltreatment patterns and anxiety and depression symptoms. Relative weight analysis and analysis of variance (ANOVA) were used to test the predictive validity of latent profile analysis, multiple individual risk and cumulative risk model. ResultsUsing latent profile analysis, two patterns of childhood maltreatment were uncovered (“No Maltreatment” and “Multiple Maltreatment”). Further analysis showed that multiple individual risk model accounted for the largest variance in anxiety (R2 = 26.7%) and depression (R2 = 33%), followed by the latent profile analysis (R2 = 14.7% for anxiety and 18.6% for depression) and the cumulative risk model (R2 = 12.9% for anxiety and 15.2% for depression). ConclusionsOur findings suggested that the multiple individual risk model is the optimal model for identifying adolescents at the risk of developing anxiety and depression symptoms, and the results suggested emotional abuse and emotional neglect are risk factors for higher levels of anxiety and depression among adolescents.

Analysis of clinical risk models vs. clinician's assessment for prediction of coronary artery disease among predominantly female population.

Multiple risk models are used to predict the presence of obstructive coronary artery disease (CAD) in patients with chest pain. We aimed to compare the performance of these models to an experienced cardiologist's assessment utilizing coronary angiography (CA) as a reference. We prospectively enrolled patients without known CAD referred for elective CA. We assessed pretest probability of CAD using the following risk models: Diamond-Forrester (original and updated), Duke Clinical score, ACC/AHA, CAD consortium (basic and clinical) and PROMISE minimal risk tool. All patients completed self-administrative Rose angina questionnaire. Independently, an experienced cardiologist assessed the patients to provide a binary prediction of obstructive CAD prior to CA. Obstructive CAD was defined as >80% stenosis in epicardial coronary arteries by visual assessment, or fractional flow reserve <0.80 in intermediate lesions (30-80%). A total of 150 patients were recruited (100 women, 50 men). Mean age was 58 (32-78) years. Obstructive CAD was found in 31 patients (21%). The area under the curve (AUC) for all the clinical risk prediction models (except the Duke Clinical Score, AUC 0.73, P = 0.07) was significantly lower compared with the clinician's assessment (AUC 0.51-0.65 vs. 0.81, respectively, P < 0.01). The clinician's assessment had sensitivity comparable to the Duke Clinical score, which was higher than all other clinical models. There was no difference in prediction performance on the basis of sex in this predominantly female population. In stable patients with chest pain and suspected CAD, current clinical risk models which are universally based upon the characteristics of the chest pain, show suboptimal performance in predicting obstructive CAD. These findings have important clinical implications, as current appropriateness criteria for recommending CA are on the basis of these risk models.

Identification and Construction of a Long Noncoding RNA Prognostic Risk Model for Stomach Adenocarcinoma Patients.

Background Long noncoding RNA-based prognostic biomarkers have demonstrated great potential in the diagnosis and prognosis of cancer patients. However, systematic assessment of a multiple lncRNA-composed prognostic risk model is lacking in stomach adenocarcinoma (STAD). This study is aimed at constructing a lncRNA-based prognostic risk model for STAD patients. Methods RNA sequencing data and clinical information of STAD patients were retrieved from The Cancer Genome Atlas (TCGA) database. Differentially expressed lncRNAs (DElncRNAs) were identified using the R software. Univariate and multivariate Cox regression analyses were performed to construct a prognostic risk model. The survival analysis, C-index, and receiver operating characteristic (ROC) curve were employed to assess the sensitivity and specificity of the model. The results were verified using the GEPIA online tool and our clinical samples. Pearson correlation coefficient analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed to indicate the potential biological functions of the selected lncRNA. Results A total of 1917 DElncRNAs were identified from 343 cases of STAD tissues and 30 cases of noncancerous tissues. According to univariate and multivariable Cox regression analyses, four DElncRNAs (AC129507.1, LINC02407, AL022316.1, and AP000695.2) were selected to establish a prognostic risk model. There was a significant difference in the overall survival between high-risk patients and low-risk patients based on this risk model. The C-index of the model was 0.652. The area under the curve (AUC) for the ROC curve was 0.769. GEPIA results confirmed the expression and prognostic significance of AP000695.2 in STAD. Our clinical data confirmed that upregulated expression of AP000695.2 was correlated with the T stage, distant metastasis, and TNM stage in STAD. GO and KEGG analyses demonstrated that AP000695.2 was closely related to the tumorigenesis process. Conclusions In this study, we constructed a lncRNA-based prognostic risk model for STAD patients. Our study will provide novel insight into the diagnosis and prognosis of STAD patients.

Assessment of Discordance Among Smoldering Multiple Myeloma Risk Models

This cohort study assesses the concordance of 3 models to stratify risk for progression to multiple myeloma in an independent cohort of patients with smoldering multiple myeloma.

Contrasting cumulative risk and multiple individual risk models of the relationship between Adverse Childhood Experiences (ACEs) and adult health outcomes

BackgroundA very large body of research documents relationships between self-reported Adverse Childhood Experiences (srACEs) and adult health outcomes. Despite multiple assessment tools that use the same or similar questions, there is a great deal of inconsistency in the operationalization of self-reported childhood adversity for use as a predictor variable. Alternative conceptual models are rarely used and very limited evidence directly contrasts conceptual models to each other. Also, while a cumulative numeric ‘ACE Score’ is normative, there are differences in the way it is calculated and used in statistical models. We investigated differences in model fit and performance between the cumulative ACE Score and a ‘multiple individual risk’ (MIR) model that enters individual ACE events together into prediction models. We also investigated differences that arise from the use of different strategies for coding and calculating the ACE Score.MethodsWe merged the 2011–2012 BRFSS data (N = 56,640) and analyzed 3 outcomes. We compared descriptive model fit metrics and used Vuong’s test for model selection to arrive at best fit models using the cumulative ACE Score (as both a continuous or categorical variable) and the MIR model, and then statistically compared the best fit models to each other.ResultsThe multiple individual risk model was a better fit than the categorical ACE Score for the ‘lifetime history of depression’ outcome. For the outcomes of obesity and cardiac disease, the cumulative risk and multiple individual risks models were of comparable fit, but yield different and complementary inferences.ConclusionsAdditional information-rich inferences about ACE-health relationships can be obtained from including a multiple individual risk modeling strategy. Results suggest that investigators working with large srACEs data sources could empirically derive the number of items, as well as the exposure coding strategy, that are a best fit for the outcome under study. A multiple individual risk model could also be considered in addition to the cumulative risk model, potentially in place of estimation of unadjusted ACE-outcome relationships.

Preschool Speech Intelligibility and 8-Year Literacy: A Moderated Mediation Analysis

Purpose The aims of this study were (a) to examine the relationship between speech intelligibility at the age of 5 years and literacy skills at the age of 8 years, (b) to explore the possible mediating or moderating role of broader language skills at 5 years in the relationship of interest, and (c) to assess whether the potential risk factors (child gender; maternal education levels; and family history of speech, language, reading, and writing difficulties) influence the relationship between speech intelligibility and literacy in terms of moderated mediation effects. Method We used mother-reported questionnaire data on 16,184 children participating in the population-based, prospective Norwegian Mother, Father and Child Cohort Study as well as conducted linear regression analyses using the PROCESS macro in SPSS. In addition, logistic regression was conducted to make predictions about risk. Results The association between speech intelligibility at 5 years and literacy skills at 8 years was statistically significant (β = .168, p < .001). Children with speech problems at 5 years had a risk ratio of 2.38 (95% CI [2.10, 2.70]) and an odds ratio of 2.74 (95% CI [2.35, 3.19]), as compared to children without such problems. Broader language skills at 5 years partially mediated the relationship between speech intelligibility at 5 years and literacy at 8 years, and the effect of language skills appeared to be moderated by child gender, a family history of language difficulties, a family history of reading difficulties, and maternal education. Conclusions Severity of speech problems indexed by parent-reported speech intelligibility in preschool predicted school-age literacy problems. Broader language skills are a crucial mediating mechanism through which these problems are linked, and the mediated relationship is amplified by female gender, low maternal education, family history of language difficulties, and family history of reading difficulties. The findings call for increased use of a multiple-risk model when planning early interventions in children with unclear speech.

Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries.

Background: Metabolic syndrome (MetS) is a cluster of cardiometabolic disturbances that increases the risk of cardiovascular diseases (CVD) and type 2 diabetes mellitus (DM). The early identification of high-risk individuals is the key for halting these conditions. The world is facing a growing epidemic MetS although the magnitude in Egypt is unknown. Objectives: To describe MetS and its determinants among apparently healthy individuals residing in urban and rural communities in Egypt and to establish a model for MetS prediction. Methods: A cross-sectional study was conducted with 270 adults from rural and urban districts in Alexandria, Egypt. Participants were clinically evaluated and interviewed for sociodemographic and lifestyle factors and dietary habits. MetS was defined according to the harmonized criteria set by the AHA/NHLBI. The risk of ischemic heart diseases (IHDs), DM and fatty liver were assessed using validated risk prediction charts. A multiple risk model for predicting MetS was developed, and its performance was compared. Results: In total, 57.8% of the study population met the criteria for MetS and were at high risk for developing IHD, DM, and fatty liver. Silent CVD risk factors were identified in 20.4% of the participants. In our proposed multivariate logistic regression model, the predictors of MetS were obesity [OR (95% CI) = 16.3 (6.03-44.0)], morbid obesity [OR (95% CI) = 21.7 (5.3-88.0)], not working [OR (95% CI) = 2.05 (1.1-3.8)], and having a family history of chronic diseases [OR (95% CI) = 4.38 (2.23-8.61)]. Consumption of caffeine once per week protected against MetS by 27.8-fold. The derived prediction rule was accurate in predicting MetS, fatty liver, high risk of DM, and, to a lesser extent, a 10-year lifetime risk of IHD. Conclusion: Central obesity and sedentary lifestyles are accountable for the rising rates of MetS in our society. Interventions are needed to minimize the potential predisposition of the Egyptian population to cardiometabolic diseases.

Risk prediction of recurrent venous thromboembolism: a multiple genetic risk model

A single genetic biomarker is unable to accurately predict the risk for venous thromboembolism (VTE) recurrence. We aimed to: (a) develop a multiple single nucleotide polymorphisms (SNPs) model to predict the risk of VTE recurrence and (b) validate a previously described genetic risk score (GRS) and compare its performance with the model developed in this study. Twenty-two SNPs, including established and putative SNPs associated with VTE risk, were genotyped in the Malmö thrombophilia study cohort (MATS; n = 1465, follow-up ~ 10 years) by using TaqMan PCR. Out of 22-SNPs, 12 had an association with the risk of VTE recurrence and were included for calculating GRSs. The risk of VTE recurrence was calculated by stratifying patients according to number of risk alleles. In 12-SNP GRS, patients with ≥ 7 risk alleles were associated with higher risk of VTE recurrence compared to patients having ≤ 6 risk alleles. In a simplified model (8-SNP GRS), the discriminative power of 8-SNP GRS was similar to that of 12-SNP GRS based on post-test probabilities (PP). Furthermore, 8-SNP GRS further improved the risk prediction of VTE recurrence in unprovoked VTE and male patients (PP% = 15.4 vs 8.3, 17.1 vs 7.2 and 19.0 vs 7.1 for high risk groups vs low risk groups in whole population, males and unprovoked VTE patients respectively). In addition, we also validated previously described 5-SNP GRS in our cohort and found that the 8-SNP GRS performed better than the 5-SNP GRS in terms of higher PP. Our results show that a multiple SNP GRS consisting of 8-SNPs may be an effective model for prediction of VTE recurrence, particularly in unprovoked VTE and male patients.

A genetic risk nomogram for patients with colorectal liver metastases: the central role of BRAF mutational status in stratifying outcomes

Background: Patients with colorectal liver metastases (CRLM) exhibit considerable variation in overall survival (OS). Attempts to predict post-hepatectomy oncological outcomes have led to the development of multiple risk models. The addition of genetic markers to risk models may further improve prognostic stratification. We sought to develop a prognostic nomogram which incorporates both “BRAF” and “KRAS” mutational status for the first time. Methods: We analysed an international cohort of 853 patients with a known “BRAF” status, treated at 7 tertiary-care centres. Independent predictors of OS were determined through multivariable Cox regression; the identified variables were then incorporated into the nomogram and assigned points according to their respective linear predictors. Results: The nomogram (figure) incorporated the following variables: patient age, primary lymph node metastasis, extrahepatic disease, synchronous CRLM, carcinoembryonic antigen levels, tumor size and number, R1 resection, “BRAF” and “KRAS” mutational status. Importantly, the presence of “BRAF” V600E mutation was awarded the most points [score (s) = 76] and significantly improved the nomogram’s accuracy (p = 0.003). The resulting OS model achieved good prognostic discrimination [C-statistic = 0.66 (0.62–0.69)] and divided patients into 3 tertiles with distinct survival. Patients in tertile 3 (s > 131) exhibited substantially worse survival (5-year OS: 26%) than patients in tertile 2 (s: 112–131; 5-year OS: 46%; p = 0.001); in turn, patients in tertile 1 had significantly better prognosis (s < 112; 5-year OS: 66%; p = 0.021). Conclusion: The proposed genetic risk nomogram demonstrated very good prognostic discrimination in an international multi-institutional cohort. Importantly, “BRAF” V600E mutational status substantially improved prognostic accuracy and should be considered for inclusion in future risk models.

Predator size influences intraspecific multiple predator effects in swimming crab-Manila clam system

Interactions between multiple predators, whether conspecific or interspecific, has been the subject of many researches. There is a shortage of studies investigating how different size classes of a single species interact with one another to generate multiple predator effects. Here, we used a comprehensive experimental design, consisting of calculation of per capita consumption rates, to examine multiple predator effects on prey when swimming crabs (Portunus trituberculatus) of multiple sizes foraged on manila clams (Ruditapes philippinarum) using a video recording analysis system in the laboratory. We identified multiple predator effects on prey by comparing observed predation rate to that predicted from the multiple risk model. The observed predation rate of crab was significantly lower than predicted value when a conspecific competitor appeared. Swimming crab significantly decreased foraging time budgets when a conspecific competitor appeared. The proportion of time medium-sized crabs spent searching for and handling clam decreased in the presence of competitors. The encounter rate between crabs and clam decreased while the probability of capture upon encounter and the probability of consumption upon capture increased when a conspecific competitor appeared. The handling time per clam significantly decreased when a conspecific competitor appeared. Most encounters between crabs were fighting (2.31–4.14 times/h), secondly chasing (1.02–3.07 times/h), and threatening (1.24–2.09 times/h), and the fewest encounters were non-aggression (0.13–0.49 times/h). The results indicated that swimming crab foraging behavior was affected by the chasing, threatening and fighting behavior of a conspecific competitor and this affected the predation rate on prey, which led to non-independent multiple predator effects in the swimming crab-Manila clam system.

Understanding Child Outcomes within a Multiple Risk Model: Examining Parental Incarceration

The risks in children’s lives often co-occur and overlap in time. The purpose of this study is to examine the impact of parental incarceration within a multiple risk model that allows for the control of other prominent risk factors in a child’s life. The impact of four primary parental risk factors (parental mental illness, parental substance use, parental mental illness, and poverty) on seven child outcomes (school failure, criminal behaviors, being arrested, behavioral difficulties, emotional difficulties, alcohol use, and drug use) was examined. The study utilizes a statistical analysis that is rarely seen in social work research and helps the researcher to better understand the individual contributions of various risk factors. The accumulation of multiple risk factors in a child’s life was found to significantly increase the likelihood that several negative outcomes would occur. The research, however, suggests further that this is an over simplification of the phenomenon and that specific risk factors are more likely to contribute to specific child outcomes.

Less is more: Testing financial integration using identification-robust asset pricing models

We revisit financial market integration and study the impact of multiple risk factors and model specification on inference. Our tests exploit a method correct in finite sample that jointly assesses coefficient significance and detects identification problems. Results on four countries show that multiple sources of risk in international asset pricing models lead to lack of identification and spurious inference. We find that domestic factor models are well identified which is not the case for global and international models. Nonetheless, domestic models do not provide a base for testing financial market integration. Given that constraint, the best-identified international model includes few factors and reveals that financial integration varies over time and across countries.

Short-term and long-term cardiovascular risk, metabolic syndrome and HIV in Tanzania

ObjectiveTo compare short-term and long-term cardiovascular disease (CVD) risk scores and prevalence of metabolic syndrome in HIV-infected adults receiving and not receiving antiretroviral therapy (ART) to HIV-negative controls.MethodsA cross-sectional study...