Cardiovascular disease risk communication and prevention: a meta-analysis.

BACKGROUND AND AIMS: Knowledge of quantifiable cardiovascular disease (CVD) risk may improve health outcomes and trigger behavioural change in patients or clinicians. This review aimed to investigate the impact of CVD risk communication on patient-perceived CVD risk and changes in CVD risk factors. METHODS: PubMed, Embase, and PsycINFO databases were searched from inception to 6 June 2023, supplemented by citation analysis. Randomized trials that compared any CVD risk communication strategy versus usual care were included. Paired reviewers independently screened the identified records and extracted the data; disagreements were resolved by a third author. The primary outcome was the accuracy of risk perception. Secondary outcomes were clinician-reported changes in CVD risk, psychological responses, intention to modify lifestyle, and self-reported changes in risk factors and clinician prescribing of preventive medicines. RESULTS: Sixty-two trials were included. Accuracy of risk perception was higher among intervention participants (odds ratio = 2.31, 95% confidence interval = 1.63 to 3.27). A statistically significant improvement in overall CVD risk scores was found at 6-12 months (mean difference = -0.27, 95% confidence interval = -0.45 to -0.09). For primary prevention, risk communication significantly increased self-reported dietary modification (odds ratio = 1.50, 95% confidence interval = 1.21 to 1.86) with no increase in intention or actual changes in smoking cessation or physical activity. A significant impact on patients' intention to start preventive medication was found for primary and secondary prevention, with changes at follow-up for the primary prevention group. CONCLUSIONS: In this systematic review and meta-analysis, communicating CVD risk information, regardless of the method, reduced the overall risk factors and enhanced patients' self-perceived risk. Communication of CVD risk to patients should be considered in routine consultations.

Integrative analysis regarding the correlation between collagen-related genes and prostate cancer.

PURPOSE: Prostate cancer (PCa) is a common malignancy in men, with an escalating mortality rate attributed to Recurrence and metastasis. Recent studies have illuminated collagen's critical regulatory role within the tumor microenvironment, significantly influencing tumor progression. Accordingly, this investigation is dedicated to examining the relationship between genes linked to collagen and the prognosis of PCa, with the objective of uncovering any possible associations between them. METHODS: Gene expression data for individuals with prostate cancer were obtained from the TCGA repository. Collagen-related genes were identified, leading to the development of a risk score model associated with biochemical recurrence-free survival (BRFS). A prognostic nomogram integrating the risk score with essential clinical factors was crafted and evaluated for efficacy. The influence of key collagen-related genes on cellular behavior was confirmed through various assays, including CCK8, invasion, migration, cell cloning, and wound healing. Immunohistochemical detection was used to evaluate PLOD3 expression in prostate cancer tissue samples. RESULTS: Our study identified four key collagen-associated genes (PLOD3, COL1A1, MMP11, FMOD) as significant. Survival analysis revealed that low-risk groups, based on the risk scoring model, had significantly improved prognoses. The risk score was strongly associated with prostate cancer prognosis. Researchers then created a nomogram, which demonstrated robust predictive efficacy and substantial clinical applicability.Remarkably, the suppression of PLOD3 expression notably impeded the proliferation, invasion, migration, and colony formation capabilities of PCa cells. CONCLUSION: The risk score, derived from four collagen-associated genes, could potentially act as a precise prognostic indicator for BRFS of patients. Simultaneously, our research has identified potential therapeutic targets related to collagen. Notably, PLOD3 was differentially expressed in cancer and para-cancer tissues in clinical specimens and it also was validated through in vitro studies and shown to suppress PCa tumorigenesis following its silencing.

Prognosis prediction and risk stratification of transarterial chemoembolization or intraarterial chemotherapy for unresectable hepatocellular carcinoma based on machine learning.

OBJECTIVE: To develop and validate a risk scoring scale model (RSSM) for stratifying prognostic risk after intra-arterial therapies (IATs) for hepatocellular carcinoma (HCC). METHODS: Between February 2014 and October 2022, 2338 patients with HCC who underwent initial IATs were consecutively enrolled. These patients were divided into training datasets (TD, n = 1700), internal validation datasets (ITD, n = 428), and external validation datasets (ETD, n = 200). Five-years death was used to predict outcome. Thirty-four clinical information were input and five supervised machine learning (ML) algorithms, including eXtreme Gradient Boosting (XGBoost), Categorical Gradient Boosting (CatBoost), Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LGBT), and Random Forest (RF), were compared using the areas under the receiver operating characteristic (AUC) with DeLong test. The variables with top important ML scores were used to build the RSSM by stepwise Cox regression. RESULTS: The CatBoost model achieved the best discrimination when 12 top variables were input, with the AUC of 0.851 (95% confidence intervals (CI), 0.833-0.868) for TD, 0.817 (95%CI, 0.759-0.857) for ITD, and 0.791 (95%CI, 0.748-0.834) for ETD. The RSSM was developed based on the immune checkpoint inhibitors (ICI) (hazard ratios (HR), 0.678; 95%CI 0.549, 0.837), tyrosine kinase inhibitors (TKI) (HR, 0.702; 95%CI 0.605, 0.814), local therapy (HR, 0.104; 95%CI 0.014, 0.747), response to the first IAT (HR, 4.221; 95%CI 2.229, 7.994), tumor size (HR, 1.054; 95%CI 1.038, 1.070), and BCLC grade (HR, 2.375; 95%CI 1.950, 2.894). Kaplan-Meier analysis confirmed the role of RSSM in risk stratification (p < 0.001). CONCLUSIONS: The RSSM can stratify accurately prognostic risk for HCC patients received IAT. On the basis, an online calculator permits easy implementation of this model. CLINICAL RELEVANCE STATEMENT: The risk scoring scale model could be easily implemented for physicians to stratify risk and predict prognosis quickly and accurately, thereby serving as a more favorable tool to strengthen individualized intra-arterial therapies and management in patients with unresectable hepatocellular carcinoma. KEY POINTS: • The Categorical Gradient Boosting (CatBoost) algorithm achieved the optimal and robust predictive ability (AUC, 0.851 (95%CI, 0.833-0.868) in training datasets, 0.817 (95%CI, 0.759-0.857) in internal validation datasets, and 0.791 (95%CI, 0.748-0.834) in external validation datasets) for prediction of 5-years death of hepatocellular carcinoma (HCC) after intra-arterial therapies (IATs) among five machine learning models. • We used the SHapley Additive exPlanations algorithms to explain the CatBoost model so as to resolve the black boxes of machine learning principles. • A simpler restricted variable, risk scoring scale model (RSSM), derived by stepwise Cox regression for risk stratification after intra-arterial therapies for hepatocellular carcinoma, provides the potential forewarning to adopt combination strategies for high-risk patients.

The value of LCI-based modified Kyoto classification risk scoring system in predicting the risk of early gastric cancer.

OBJECTIVE: To study and compare the value of the Kyoto classification risk scoring system and the modified Kyoto classification risk scoring system based on linked color imaging (LCI) in predicting the risk of early gastric cancer. METHODS: One hundred and fifty patients with pathologically confirmed non-cardia early gastric cancer by endoscopic LCI and 150 non-gastric cancer patients matched for age and gender were included. Basic patient data and whole gastric endoscopic images under LCI were collected, and the images were scored according to the LCI-based Kyoto classification risk scoring system and the LCI-based modified Kyoto classification risk scoring system. RESULTS: Compared with the LCI-based Kyoto classification risk scoring system, the LCI-based modified Kyoto classification risk scoring system had a higher AUC for predicting the risk of early gastric cancer (0.723 vs. 0.784, p = 0.023), with a score of ≥3 being the best cutoff value for predicting the risk of early gastric cancer (sensitivity 61.33%, specificity 86.00%), and scores of 3 to 5 were significantly associated with early gastric carcinogenesis significantly (OR = 9.032, 95% CI: 4.995-16.330, p < 0.001). CONCLUSIONS: Compared with the LCI-based Kyoto classification risk scoring system, the LCI-based Kyoto modified classification risk scoring system has a better value for predicting the risk of early gastric cancer, and the score of 3 to 5 is a high-risk factor for the risk of early gastric cancer development, which is more strongly correlated with the risk of early gastric cancer.

Comparison of different methods of first-trimester screening for preterm pre-eclampsia: cohort study.

OBJECTIVE: To compare the predictive performance of three different mathematical models for first-trimester screening of pre-eclampsia (PE), which combine maternal risk factors with mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and serum placental growth factor (PlGF), and two risk-scoring systems. METHODS: This was a prospective cohort study performed in eight fetal medicine units in five different regions of Spain between September 2017 and December 2019. All pregnant women with singleton pregnancy and a non-malformed live fetus attending their routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation were invited to participate in the study. Maternal characteristics and medical history were recorded and measurements of MAP, UtA-PI, serum PlGF and pregnancy-associated plasma protein-A (PAPP-A) were converted into multiples of the median (MoM). Risks for term PE, preterm PE (< 37 weeks' gestation) and early PE (< 34 weeks' gestation) were calculated according to the FMF competing-risks model, the Crovetto et al. logistic regression model and the Serra et al. Gaussian model. PE classification was also performed based on the recommendations of the National Institute for Health and Care Excellence (NICE) and the American College of Obstetricians and Gynecologists (ACOG). We estimated detection rates (DR) with their 95% CIs at a fixed 10% screen-positive rate (SPR), as well as the area under the receiver-operating-characteristics curve (AUC) for preterm PE, early PE and all PE for the three mathematical models. For the scoring systems, we calculated DR and SPR. Risk calibration was also assessed. RESULTS: The study population comprised 10 110 singleton pregnancies, including 32 (0.3%) that developed early PE, 72 (0.7%) that developed preterm PE and 230 (2.3%) with any PE. At a fixed 10% SPR, the FMF, Crovetto et al. and Serra et al. models detected 82.7% (95% CI, 69.6-95.8%), 73.8% (95% CI, 58.7-88.9%) and 79.8% (95% CI, 66.1-93.5%) of early PE; 72.7% (95% CI, 62.9-82.6%), 69.2% (95% CI, 58.8-79.6%) and 74.1% (95% CI, 64.2-83.9%) of preterm PE; and 55.1% (95% CI, 48.8-61.4%), 47.1% (95% CI, 40.6-53.5%) and 53.9% (95% CI, 47.4-60.4%) of all PE, respectively. The best correlation between predicted and observed cases was achieved by the FMF model, with an AUC of 0.911 (95% CI, 0.879-0.943), a slope of 0.983 (95% CI, 0.846-1.120) and an intercept of 0.154 (95% CI, -0.091 to 0.397). The NICE criteria identified 46.7% (95% CI, 35.3-58.0%) of preterm PE at 11% SPR and ACOG criteria identified 65.9% (95% CI, 55.4-76.4%) of preterm PE at 33.8% SPR. CONCLUSIONS: The best performance of screening for preterm PE is achieved by mathematical models that combine maternal factors with MAP, UtA-PI and PlGF, as compared to risk-scoring systems such as those of NICE and ACOG. While all three algorithms show similar results in terms of overall prediction, the FMF model showed the best performance at an individual level. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Update review on SUDEP: Risk assessment, background & seizure detection devices.

This review focusses on sudden unexpected death in epilepsy patients (SUDEP) and incorporates risk stratification (through SUDEP risk factors and SUDEP risk scores), hypotheses on the mechanism of SUDEP and eligible seizure detection devices (SDDs) for further SUDEP prevention studies. The main risk factors for SUDEP are the presence and the frequency of generalized tonic-clonic seizures (GTC). In Swedish population-based case control study, the Odds ratio of the presence of GTC in the absence of bedroom sharing is 67. SUDEP risk scoring systems express a score that represents the cumulative presence of SUDEP risk factors, but not the exact effect of their combination. We describe 4 of the available scoring systems: SUDEP-7 inventory, SUDEP-3 inventory, SUDEP-ClinicAl Risk scorE (SUDEP-CARE score) and Kempenhaeghe SUDEP risk score. Although they all include GTC, their design is often different. Three of 4 scoring systems were validated (SUDEP-7 inventory, SUDEP-3 inventory and SUDEP-CARE score). None of the available scoring systems has been sufficiently validated for the use in a general epilepsy population. Plausible mechanisms of SUDEP are discussed. In the MORTEMUS-study (Mortality in Epilepsy Monitoring Unit Study), SUDEP was a postictal cardiorespiratory arrest after a GTC. The parallel respiratory and cardiac dysfunction in SUDEP suggests a central dysfunction of the brainstem centers that are involved in the control of respiration and heart rhythm. In the (consequent) adenosine serotonin hypotheses SUDEP occurs when a postictal adenosine-mediated respiratory depression is not compensated by the effect of serotonin. Other (adjuvant) mechanisms and factors are discussed. Seizure detection devices (SDDs) may help to improve nocturnal supervision. Five SDDs have been validated in phase 3 studies for the detection of TC: Seizure Link®, Epi-Care®, NightWatch, Empatica, Nelli®. They have demonstrated a sensitivity of at least 90 % combined with an acceptable false positive alarm rate. It has not yet been proven that the use will actually lead to SUDEP prevention, but clinical experience supports their effectiveness.

Construction and validation of a risk-scoring model to predict lymph node metastasis in T1b-T2 esophageal cancer.

BACKGROUND: Lymph node status is an important factor in determining preoperative treatment strategies for stage T1b-T2 esophageal cancer (EC). Thus, the aim of this study was to investigate the risk factors for lymph node metastasis (LNM) in T1b-T2 EC and to establish and validate a risk-scoring model to guide the selection of optimal treatment options. METHODS: Patients who underwent upfront surgery for pT1b-T2 EC between January 2016 and December 2022 were analyzed. On the basis of the independent risk factors determined by multivariate logistic regression analysis, a risk-scoring model for the prediction of LNM was constructed and then validated. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminant ability of the model. RESULTS: The incidence of LNM was 33.5% (214/638) in our cohort, 33.4% (169/506) in the primary cohort and 34.1% (45/132) in the validation cohort. Multivariate analysis confirmed that primary site, tumor grade, tumor size, depth, and lymphovascular invasion were independent risk factors for LNM (all P < 0.05), and patients were grouped based on these factors. A 7-point risk-scoring model based on these variables had good predictive accuracy in both the primary cohort (AUC, 0.749; 95% confidence interval 0.709-0.786) and the validation cohort (AUC, 0.738; 95% confidence interval 0.655-0.811). CONCLUSION: A novel risk-scoring model for lymph node metastasis was established to guide the optimal treatment of patients with T1b-T2 EC.

Development of a machine learning-based risk model for postoperative complications of lung cancer surgery.

PURPOSE: To develop a comorbidity risk score specifically for lung resection surgeries. METHODS: We reviewed the medical records of patients who underwent lung resections for lung cancer, and developed a risk model using data from 2014 to 2017 (training dataset), validated using data from 2018 to 2019 (validation dataset). Forty variables were analyzed, including 35 factors related to the patient's overall condition and five factors related to surgical techniques and tumor-related factors. The risk model for postoperative complications was developed using an elastic net regularized generalized linear model. The performance of the risk model was evaluated using receiver operating characteristic curves and compared with the Charlson Comorbidity Index (CCI). RESULTS: The rate of postoperative complications was 34.7% in the training dataset and 21.9% in the validation dataset. The final model consisted of 20 variables, including age, surgical-related factors, respiratory function tests, and comorbidities, such as chronic obstructive pulmonary disease, a history of ischemic heart disease, and 12 blood test results. The area under the curve (AUC) for the developed risk model was 0.734, whereas the AUC for the CCI was 0.521 in the validation dataset. CONCLUSIONS: The new machine learning model could predict postoperative complications with acceptable accuracy. CLINICAL REGISTRATION NUMBER: 2020-0375.

The Ethics of Risk Prediction for Psychosis and Suicide Attempt in Youth Mental Health.

OBJECTIVE: To identify potential clinical utility of polygenic risk scores (PRS) and exposomic risk scores (ERS) for psychosis and suicide attempt in youth and assess the ethical implications of these tools. STUDY DESIGN: We conducted a narrative literature review of emerging findings on PRS and ERS for suicide and psychosis as well as a literature review on the ethics of PRS. We discuss the ethical implications of the emerging findings for the clinical potential of PRS and ERS. RESULTS: Emerging evidence suggests that PRS and ERS may offer clinical utility in the relatively near future but that this utility will be limited to specific, narrow clinical questions, in contrast to the suggestion that population-level screening will have sweeping impact. Combining PRS and ERS might optimize prediction. This clinical utility would change the risk-benefit balance of PRS, and further empirical assessment of proposed risks would be necessary. Some concerns for PRS, such as those about counseling, privacy, and inequities, apply to ERS. ERS raise distinct ethical challenges as well, including some that involve informed consent and direct-to-consumer advertising. Both raise questions about the ethics of machine-learning/artificial intelligence approaches. CONCLUSIONS: Predictive analytics using PRS and ERS may soon play a role in youth mental health settings. Our findings help educate clinicians about potential capabilities, limitations, and ethical implications of these tools. We suggest that a broader discussion with the public is needed to avoid overenthusiasm and determine regulations and guidelines for use of predictive scores.

Renal Outcomes in Older Adults with Antineutrophil Cytoplasmic Autoantibody-Associated Vasculitis: A New Prediction Model.

INTRODUCTION: Older patients with antineutrophil cytoplasmic autoantibody-associated vasculitis (AAV) commonly experience renal impairment and poor prognoses. This study aimed to establish a risk-scoring system for predicting composite renal outcomes in older patients with AAV. METHODS: This retrospective observational study included all patients with AAV hospitalized in a single-center tertiary hospital in China between January 2013 and April 2022. Patients aged ≥65 years were defined as older adults and short-term composite renal outcomes included a ≥25% reduction in estimated glomerular filtration rate (eGFR) (for AKI), renal replacement therapy, provision of renal replacement therapy (long-term dialysis, kidney transplant, or sustained eGFR <15 mL/min/1.73 m), or all-cause mortality. Patients were randomly divided into development and validation cohorts (2:1). Logistic regression analysis was performed in the development cohort to analyze risk factors. The scoring system was established accordingly and further validated in the validation cohort. RESULTS: 1,203 patients were enrolled in the study, among whom the older adult group accounted for 36% with a mean age of 71. The older adult group had a worse prognosis, a higher mortality rate, a higher rate of end-stage renal disease, and worsening renal function. Logistic regression showed that age >75 years, chronic heart disease, and elevated serum creatinine and D-dimer values were risk factors for poor prognosis in patients with AAV. The development and validation cohorts in patients with AAV produced area under the curve values of 0.82 (0.78-0.86) and 0.83 (0.77-0.89), respectively. CONCLUSION: We established a risk-scoring system based on baseline clinical characteristics to predict composite renal outcomes in patients with AAV. Our results suggest that more attention should be paid to older patients with severe renal impairment and active inflammation.

A risk scoring system for early diagnosis of anastomotic leakage after subtotal esophagectomy for esophageal cancer.

BACKGROUND: Anastomotic leakage (AL) is one of the most critical postoperative complications after subtotal esophagectomy in patients with esophageal cancer. This study attempted to develop an optimal scoring system for stratifying the risk for AL. METHODS: The study included 171 patients who underwent subtotal esophagectomy for esophageal cancer followed by esophagogastrostomy in the cervical region from January 2011 to April 2021 at Nagoya University Hospital. AL was defined by radiologic or endoscopic evidence of anastomotic breakdown using some modalities. A risk scoring system for an early diagnosis of AL was established using factors determined in the multivariate analysis. A score was calculated for each patient, and the patients were classified into three categories according to the risk for AL: low-, intermediate- and high-risk. The trend of the risk for AL among the categories was evaluated. RESULTS: Twenty-nine patients (17%) developed AL. Multivariate analysis demonstrated that sinistrous gross features of drain fluid (P < 0.001; odds ratio (OR), 10.2), radiologic air bubble sign (P < 0.001; OR, 15.0) and the level of drain amylase ≥280 U/L on postoperative Day 7 (P < 0.001; OR, 9.0) were significantly associated with AL. According to the matching number of the above three risk factors and categorization into three risk groups, the incidence of AL was 6.1% (8/131) in the low-risk group, 45.5% (15/33) in the intermediate-risk group and 85.7% (6/7) in the high-risk group (area under curve, 0.81; 95% confidence interval, 0.72-0.90). CONCLUSIONS: The present AL-risk scoring system may be useful in postoperative patient care after subtotal esophagectomy.

Analysis of factors affecting nonalcoholic fatty liver disease in Chinese steel workers and risk assessment studies.

BACKGROUND: The global incidence of nonalcoholic fatty liver disease (NAFLD) is rapidly escalating, positioning it as a principal public health challenge with significant implications for population well-being. Given its status as a cornerstone of China's economic structure, the steel industry employs a substantial workforce, consequently bringing associated health issues under increasing scrutiny. Establishing a risk assessment model for NAFLD within steelworkers aids in disease risk stratification among this demographic, thereby facilitating early intervention measures to protect the health of this significant populace. METHODS: Use of cross-sectional studies. A total of 3328 steelworkers who underwent occupational health evaluations between January and September 2017 were included in this study. Hepatic steatosis was uniformly diagnosed via abdominal ultrasound. Influential factors were pinpointed using chi-square (χ2) tests and unconditional logistic regression analysis, with model inclusion variables identified by pertinent literature. Assessment models encompassing logistic regression, random forest, and XGBoost were constructed, and their effectiveness was juxtaposed in terms of accuracy, area under the curve (AUC), and F1 score. Subsequently, a scoring system for NAFLD risk was established, premised on the optimal model. RESULTS: The findings indicated that sex, overweight, obesity, hyperuricemia, dyslipidemia, occupational dust exposure, and ALT serve as risk factors for NAFLD in steelworkers, with corresponding odds ratios (OR, 95% confidence interval (CI)) of 0.672 (0.487-0.928), 4.971 (3.981-6.207), 16.887 (12.99-21.953), 2.124 (1.77-2.548), 2.315 (1.63-3.288), 1.254 (1.014-1.551), and 3.629 (2.705-4.869), respectively. The sensitivity of the three models was reported as 0.607, 0.680 and 0.564, respectively, while the precision was 0.708, 0.643, and 0.701, respectively. The AUC measurements were 0.839, 0.839, and 0.832, and the Brier scores were 0.150, 0.153, and 0.155, respectively. The F1 score results were 0.654, 0.661, and 0.625, with log loss measures at 0.460, 0.661, and 0.564, respectively. R2 values were reported as 0.789, 0.771, and 0.778, respectively. Performance was comparable across all three models, with no significant differences observed. The NAFLD risk score system exhibited exceptional risk detection capabilities with an established cutoff value of 86. CONCLUSIONS: The study identified sex, BMI, dyslipidemia, hyperuricemia, occupational dust exposure, and ALT as significant risk factors for NAFLD among steelworkers. The traditional logistic regression model proved equally effective as the random forest and XGBoost models in assessing NAFLD risk. The optimal cutoff value for risk assessment was determined to be 86. This study provides clinicians with a visually accessible risk stratification approach to gauge the propensity for NAFLD in steelworkers, thereby aiding early identification and intervention among those at risk.

Role of risk scoring systems in predicting life expectancy after carotid endarterectomy in asymptomatic patients.

OBJECTIVE: The aim of this study is to compare and to test the performance of all available risk scoring systems (RSSs) designed to predict long-term survival rate in asymptomatic candidate patients for carotid endarterectomy (CEA) for significant carotid artery stenosis. METHODS: Data on asymptomatic patients who underwent CEA in three high-volume centers were prospectively recorded. Through literature research using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations, six RSSs were identified for the intent of the study. Primary endpoints were 3- and 5-year survival rates after CEA. All items used as variables to compose multiple RSSs were applied to every patient in the study population. The 3- and 5-year mortality prediction rates for each score were assessed by sensitivity, specificity, and predictive negative and positive value calculation, as well as univariable Cox proportional hazard models with the Harrell C index. RESULTS: During the study period, 825 CEAs in 825 asymptomatic patients were analyzed. All items used in RSSs were available in the dataset, with some concerns regarding their definition and application among RSSs. The 3- and 5-year survival rates of the study cohort were 94.5% and 90.3%, respectively. Among the six RSSs analyzed, no RSS demonstrated optimal results in terms of mortality rate prediction accuracy, although some scores had good diagnostic and risk of death precision. CONCLUSIONS: RSSs, when used alone, fail to optimally detect postoperative life expectancy in asymptomatic CEA patient candidates. Further prospective controlled studies are needed to compose and validate RSSs with better calibration to predict outcomes.

A pharmacogenomic assessment of psychiatric adverse drug reactions to levetiracetam.

OBJECTIVE: Levetiracetam (LEV) is an effective antiseizure medicine, but 10%-20% of people treated with LEV report psychiatric side-effects, and up to 1% may have psychotic episodes. Pharmacogenomic predictors of these adverse drug reactions (ADRs) have yet to be identified. We sought to determine the contribution of both common and rare genetic variation to psychiatric and behavioral ADRs associated with LEV. METHODS: This case-control study compared cases of LEV-associated behavioral disorder (n = 149) or psychotic reaction (n = 37) to LEV-exposed people with no history of psychiatric ADRs (n = 920). All samples were of European ancestry. We performed genome-wide association study (GWAS) analysis comparing those with LEV ADRs to controls. We estimated the polygenic risk scores (PRS) for schizophrenia and compared cases with LEV-associated psychotic reaction to controls. Rare variant burden analysis was performed using exome sequence data of cases with psychotic reactions (n = 18) and controls (n = 122). RESULTS: Univariate GWAS found no significant associations with either LEV-associated behavioural disorder or LEV-psychotic reaction. PRS analysis showed that cases of LEV-associated psychotic reaction had an increased PRS for schizophrenia relative to contr ols (p = .0097, estimate = .4886). The rare-variant analysis found no evidence of an increased burden of rare genetic variants in people who had experienced LEV-associated psychotic reaction relative to controls. SIGNIFICANCE: The polygenic burden for schizophrenia is a risk factor for LEV-associated psychotic reaction. To assess the clinical utility of PRS as a predictor, it should be tested in an independent and ideally prospective cohort. Larger sample sizes are required for the identification of significant univariate common genetic signals or rare genetic signals associated with psychiatric LEV ADRs.

Confirmed disability progression as a marker of permanent disability in multiple sclerosis.

BACKGROUND AND PURPOSE: The prevention of disability over the long term is the main treatment goal in multiple sclerosis (MS); however, randomized clinical trials evaluate only short-term treatment effects on disability. This study aimed to define criteria for 6-month confirmed disability progression events of MS with a high probability of resulting in sustained long-term disability worsening. METHODS: In total, 14,802 6-month confirmed disability progression events were identified in 8741 patients from the global MSBase registry. For each 6-month confirmed progression event (13,321 in the development and 1481 in the validation cohort), a sustained progression score was calculated based on the demographic and clinical characteristics at the time of progression that were predictive of long-term disability worsening. The score was externally validated in the Cladribine Tablets Treating Multiple Sclerosis Orally (CLARITY) trial. RESULTS: The score was based on age, sex, MS phenotype, relapse activity, disability score and its change from baseline, number of affected functional system domains and worsening in six of the domains. In the internal validation cohort, a 61% lower chance of improvement was estimated with each unit increase in the score (hazard ratio 0.39, 95% confidence interval 0.29-0.52; discriminatory index 0.89). The proportions of progression events sustained at 5 years stratified by the score were 1: 72%; 2: 88%; 3: 94%; 4: 100%. The results of the CLARITY trial were confirmed for reduction of disability progression that was >88% likely to be sustained (events with score ˃1.5). CONCLUSIONS: Clinicodemographic characteristics of 6-month confirmed disability progression events identify those at high risk of sustained long-term disability. This knowledge will allow future trials to better assess the effect of therapy on long-term disability accrual.

A risk scoring system for advanced colorectal neoplasia in high-risk participants to improve current colorectal cancer screening in Tianjin, China.

BACKGROUND: Given the limited effectiveness of the current Chinese colorectal cancer (CRC) screening procedure, adherence to colonoscopy remains low. We aim to develop and validate a scoring system based on individuals who were identified as having a high risk in initial CRC screening to achieve more efficient risk stratification and improve adherence to colonoscopy. METHODS: A total of 29,504 screening participants with positive High-Risk Factor Questionnaire (HRFQ) or faecal immunochemical test (FIT) who underwent colonoscopy in Tianjin from 2012-2020 were enrolled in this study. Binary regression analysis was used to evaluate the association between risk factors and advanced colorectal neoplasia. Internal validation was also used to assess the performance of the scoring system. RESULTS: Male sex, older age (age ≥ 50 years), high body mass index (BMI ≥ 28 kg/m2), current or past smoking and weekly alcohol intake were identified as risk factors for advanced colorectal neoplasm. The odds ratios (ORs) for significant variables were applied to construct the risk score ranging from 0-11: LR, low risk (score 0-3); MR, moderate risk (score 4-6); and HR, high risk (score 7-11). Compared with subjects with LR, those with MR and HR had ORs of 2.47 (95% confidence interval, 2.09-2.93) and 4.59 (95% confidence interval, 3.86-5.44), respectively. The scoring model showed an outstanding discriminatory capacity with a c-statistic of 0.64 (95% confidence interval, 0.63-0.65). CONCLUSIONS: Our results showed that the established scoring system could identify very high-risk populations with colorectal neoplasia. Combining this risk score with current Chinese screening methods may improve the effectiveness of CRC screening and adherence to colonoscopy.

Strategies to minimise the current disadvantages experienced by women in faecal immunochemical test-based colorectal cancer screening.

Currently, women are disadvantaged compared to men in colorectal cancer (CRC) screening, particularly in programmes that use faecal immunochemical tests for haemoglobin (FIT) followed by colonoscopy. Although there is no single cause for all the known disadvantages, many can be attributed to the ubiquitous finding that women have lower faecal haemoglobin concentrations (f-Hb) than men; there are many plausible reasons for this. Generally, a single f-Hb threshold is used in CRC screening programmes, leading to lower positivity for women than men, which causes poorer outcomes for women, including lower CRC detection rate, higher interval cancer (IC) proportion, and higher CRC mortality. Many of the now widely advocated risk scoring strategies do include factors taking account of sex, but these have not been extensively piloted or introduced. Using different f-Hb thresholds for the sexes seems advantageous, but there are difficulties, including deciding which characteristic should be selected to achieve equivalency, for example, positivity, IC proportions, or specificity. Moreover, additional colonoscopy resources, often constrained, would be required. Governments and their agencies should be encouraged to prioritise the allocation of resources to put simple strategies into practice, such as different f-Hb thresholds to create equal positivity in both sexes.

Primary ambulatory thromboprophylaxis in patients with pancreatic cancer receiving chemotherapy: hope or hype?

Thrombosis is the second leading cause of death in cancer patients. Patients with pancreatic cancer (PC) have a very high risk of developing venous thromboembolism (VTE). Even though primary ambulatory thromboprophylaxis (PATP) could decrease this risk, there are uncertain issues with regard to the choice and dose of anticoagulants, duration of anticoagulant therapy, and patient selection criteria. In addition, the current practice guidelines on PATP in PC patients are equivocal. This review critically appraises the evidence on the use of PATP in PC patients receiving chemotherapy.

A preoperative risk prediction model for high malignancy potential gastrointestinal stromal tumors of the stomach.

BACKGROUND: Gastric gastrointestinal stromal tumors (GISTs) exhibit various degrees of aggression and malignant potential. However, no systematic preoperative evaluation strategy to predict the malignancy potential of gastric GISTs has yet been developed. This study aimed to develop a reliable and easy-to-use preoperative risk-scoring model for predicting high malignancy potential (HMP) gastric GISTs. METHODS: The data of 542 patients with pathologically confirmed gastric GISTs who underwent resection were reviewed. Multivariate logistic regression analysis was used to identify significant predictors of HMP. The risk-scoring system (RSS) was based on the predictive factors for HMP, and its performance was validated using a split-sample approach. RESULTS: A total of 239 of 542 (44.1%) surgically resected gastric GISTs had HMP. Multivariate analysis demonstrated that tumor size, location, and surface changes were independent risk factors for HMP. Based on the accordant regression coefficients, the presence of surface ulceration was assigned 1 point. Tumor sizes of 4-6 cm and > 6 cm were assigned 2 and 5 points, respectively. Two points were assigned to cardia or fundus locations. A score of 3 points was the optimal cut-off value for HMP prediction. HMP were found in 19.8% and 82.7% of the low and high-risk groups of the RSS, respectively. The area under the receiver-operating characteristic curve for predicting HMP was 0.81 (95% confidence interval (CI) 0.75-0.86). Discrimination was good after validation (0.75, 95% CI 0.69-0.81). CONCLUSION: This simple RSS could be useful for predicting the malignancy potential of gastric GISTs and may aid preoperative clinical decision making to ensure optimal treatment.

The risk scoring system for assessing the technical difficulty of endoscopic submucosal dissection in cases of remnant gastric cancer after distal gastrectomy.

BACKGROUND: Endoscopic submucosal dissection (ESD) for remnant gastric cancer (RGC) after distal gastrectomy (DG) is considered technically challenging due to the narrow working space, and severe fibrosis and staples from the previous surgery. Technical difficulties of ESD for RGC after DG have not been thoroughly investigated. This study aimed to develop and validate a risk-scoring system for assessing the technical difficulty of ESD for RGC after DG in a large multicenter cohort. METHODS: We investigated patients who underwent ESD for RGC after DG in 10 institutions between April 2008 and March 2018. A difficult case was defined as ESD lasting ≥ 120 min, involving piecemeal resection, or the occurrence of perforation during the procedure. A risk-scoring system for the technical difficulty of the procedure was developed based on multiple logistic regression analyses, and its performance was internally validated using bootstrapping. RESULTS: A total of 197 consecutive patients with 201 lesions were analyzed. There were 90 and 111 difficult and non-difficult cases, respectively. The scoring model consisted of four independent risk factors and points of risk scores were assigned for each as follows: tumor size > 20 mm: 2 points; anastomosis site: 2 points; suture line: 1 point; and non-expert endoscopist: 2 points. The C-statistics of the scoring system for technical difficulty was 0.72. CONCLUSIONS: We developed a validated risk-scoring model for predicting the technical difficulty of ESD for RGC after DG that can contribute to its safer and more reliable performance.