Baseline Risk Research Articles

Development and internal validation of a clinical prediction model for osteopenia in Chinese middle-aged and elderly men: a prospective cohort study

BackgroundEarly identification of patients at risk of osteopenia is an essential step in reducing the population at risk for fractures. We aimed to develop and validate a prediction model for osteopenia in Chinese middle-aged and elderly men that provides individualized risk estimates.MethodsIn this prospective cohort study, 1109 patients who attend regular physical examinations in the Second Medical Centre of Chinese PLA General Hospital were enrolled from 2015.03 to 2015.09. The baseline risk factors included dietary habits, exercise habits, medical histories and medication records. Osteopenia during follow-up were collected from Electronic Health Records (EHRs) and telephone interviews. Internal validation was conducted using bootstrapping to correct the optimism. The independent sample T-test analysis, Mann_Whitney U test, Chi-Square Test and multivariable Cox regression analysis were utilized to identify predictive factors for osteopenia in Chinese middle-aged and elderly men. A nomogram based on the seven variables was built for clinical use. Concordance index (C-index), receiver operating characteristic curve (ROC), decision curve analysis (DCA) and calibration curve were used to evaluate the efficiency of the nomogram.ResultsThe risk factors included in the prediction model were bone mineral density at left femoral neck (LNBMD), hemoglobin (Hb), serum albumin (ALB), postprandial blood glucose (PBG), fatty liver disease (FLD), smoking and tea consumption. The C-index for the risk nomogram was 0.773 in the prediction model, which presented good refinement. The AUC of the risk nomogram at different time points ranged from 0.785 to 0.817, exhibiting good predictive ability and performance. In addition, the DCA showed that the nomogram had a good clinical application value. The nomogram calibration curve indicated that the prediction model was consistent.ConclusionsOur study provides a novel nomogram and a web calculator that can effectively predict the 7-year incidence risk of osteopenia in Chinese middle-aged and elderly men. It is convenient for clinicians to prevent fragility fractures in the male population.

Student Progression and Dropout Rates Using Convolutional Neural Network: A Case Study of the Arab Open University

Pre-trained convolutional neural network (CNN) structures are considered as one of the emerging education management tools that can help improve the quality of education by allowing decision makers to manipulate important indicators. These indicators, which are categorized as student and institution specific factors, may influence student progress, retention or dropout rates. In this paper, we develop a deep learning model of predicting students’ satisfactions and their expected outcomes and associated early failures. The model can also predict dropout rates and identify the main baseline risk factors that influence such rates. The academic data of 12,000 students enrolled from 2018 in the Arab Open University student information system are used as CNNs training dataset to ensure that all institution levels are represented. Then, the trained network provides a probabilistic model that indicates, for each student, the probability of dropout. Based on the prediction model, the study presents an early warning system framework to generate alerts and recommendations to allow early and effective institutional intervention. Experiments are achieved by using the proposed dataset and the performance of our approach is considerably better compared to the competitive models in terms of training/validation accuracy and mean square errors.

When to reinvite initially ineligible populations for targeted lung cancer screening?

IntroductionTargeted low-dose CT lung cancer screening reduces lung cancer mortality. England’s Targeted Lung Health Check programme uses risk prediction tools to determine eligibility for biennial screening among people with a...

Trends in gestational age at live birth in Scotland from 2005 to 2019: a population-based study

Background Gestation at birth is associated with short and long-term outcomes. This study used high quality, national, administrative data to examine trends in gestation at birth in Scotland. Methods This observational study used maternity hospital discharge records for 2005 to 2019 to determine trends in the percentage of live births that were preterm (<37 weeks gestation), term (37–41 weeks), and post-term (≥42 weeks), overall and by maternal age and deprivation category. Preterm births were further examined by category of preterm birth (moderate to late [32–36 weeks]; very [28–31 weeks]; extremely [<28 weeks] preterm), and onset of labour (spontaneous; provider-initiated). Singleton and multiple births were examined separately. Aggregate logistic regression was used to estimate the annual change in the odds of a birth being in a specified gestational category. Results The percentage of singleton births in Scotland that were preterm decreased from 2005 (6.5%, 3,361/51,665) to 2010 (5.8%, 3268/56344), then increased to 2019 (7.2%, 3,408/47,507). The percentage of singleton births that were spontaneous moderate to late, very, and extremely preterm all increased between 2010 and 2019. The percentage of singleton births that were provider-initiated moderate to late preterm also increased between 2010 and 2019, however provider-initiated very or extremely preterm birth decreased. The percentage of singleton births that were preterm increased over time across all maternal age and deprivation categories, with increases greatest in groups at highest baseline risk. The percentage of singleton births that were post-term increased from 2005 to 2009, then decreased to 2019. Conclusions There has been an increase in spontaneous preterm birth from 2010 to 2019, which is not fully explained by changes in maternal age or deprivation. Further research to examine the contribution of other, preventable, risk factors is warranted. Trends in provider-initiated preterm birth, and post-term birth, are likely to reflect changing clinical practice.

Predicting Injuries in Elite Female Football Players With Global-Positioning-System and Multiomics Data.

Injury prevention is a crucial aspect of sports, particularly in high-performance settings such as elite female football. This study aimed to develop an injury prediction model that incorporates clinical, Global-Positioning-System (GPS), and multiomics (genomics and metabolomics) data to better understand the factors associated with injury in elite female football players. We designed a prospective cohort study over 2 seasons (2019-20 and 2021-22) of noncontact injuries in 24 elite female players in the Spanish Premiership competition. We used GPS data to determine external workload, genomic data to capture genetic susceptibility, and metabolomic data to measure internal workload. Forty noncontact injuries were recorded, the most frequent of which were muscle (63%) and ligament (20%) injuries. The baseline risk model included fat mass and the random effect of the player. Six genetic polymorphisms located at the DCN, ADAMTS5, ESRRB, VEGFA, and MMP1 genes were associated with injuries after adjusting for player load (P < .05). The genetic score created with these 6 variants determined groups of players with different profile risks (P = 3.1 × 10-4). Three metabolites (alanine, serotonin, and 5-hydroxy-tryptophan) correlated with injuries. The model comprising baseline variables, genetic score, and player load showed the best prediction capacity (C-index: .74). Our model could allow efficient, personalized interventions based on an athlete's vulnerability. However, we emphasize the necessity for further research in female athletes with an emphasis on validation studies involving other teams and individuals. By expanding the scope of our research and incorporating diverse populations, we can bolster the generalizability and robustness of our proposed model.

Impact of Lipoprotein(a) Levels on Cardiovascular Risk Estimation.

A new cardiovascular risk (CVR) calculator that incorporates Lipoprotein(a) [Lp(a)] levels has recently been designed. To estimate CVR using the new score and to identify the reduction in low-density lipoprotein cholesterol (LDL-C) or systolic blood pressure (SBP) necessary to balance the risk attributable to Lp(a). CVR throughout life and at 10 years was estimated with the new score in patients in primary prevention, both considering and not considering the value of Lp(a). When the estimated risk considering Lp(a) levels exceeded the baseline risk, the reduction in LDL-C levels or SBP necessary to balance the risk attributable to Lp(a) was calculated. In total, 671 patients (mean age 54.2 years, 47.2% women) were included. Globally, 22.7% of the population had high Lp(a) values (>50 mg/dL or >125 nmol/L). When calculating CVR throughout life and considering the Lp(a) value, the global risk increased in 66.7% of cases (median 19.3%). Similar results were observed when we assessed the 10-year risk. The risk associated with Lp(a) could be completely compensated by decreasing LDL-C (average 21 mg/dL) or SBP (average 6.3 mmHg) in 79.2% and 74.7% of cases, respectively. When calculating the CVR with the new score, two-thirds and one-third of the population were bidirectionally recategorized as 'up' or 'down,' respectively. The decrease in LDL-C or SBP mitigated the increased risk caused by Lp(a) levels across a substantial proportion of patients.

P2Y12 monotherapy versus standard dual antiplatelet therapy after percutaneous coronary intervention: a systematic review and meta-analysis

Abstract Funding Acknowledgements None. Introduction Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 receptor inhibitor after percutaneous coronary intervention (PCI) is the recommended therapy for lowering the ischemic risk among patients with acute coronary syndrome (ACS). However, the increased incidence of bleeding is a major concern. Monotherapy with a P2Y12 inhibitor after short-term DAPT to reduce adverse cardiovascular events and bleeding rates has not been fully established and remains uncertain. This meta-analysis aims to determine the effectiveness of P2Y12 inhibitor monotherapy after short-term DAPT in reducing cardiovascular and bleeding events. Methods A comprehensive search of randomized controlled trials (RCTs) examining the use of short-term DAPT followed by P2Y12 monotherapy in patients with ACS who underwent PCI was conducted. Outcome measures for all-cause mortality, myocardial infarction, and bleeding rates were analyzed using a random-effects model via Review Manager V5.4. Results A total of six randomized controlled trials (RCTs) with 36,724 subjects were analyzed. There were no significant differences in all-cause mortality (RR 0.89 [95% CI: 0.78-1.02], I² = 0%, p = 0.10) and myocardial infarction (RR 1.00 [95% CI: 0.88-1.14], I² = 0%, p = 0.72) between the P2Y12 inhibitor group and dual antiplatelet therapy (DAPT) group. There was a lower rate of major bleeding in the P2Y12 group compared to the DAPT group (RR 0.65 [95% CI: 0.49-0.88], I² = 76%, p = 0.002). The major sources of substantial heterogeneity are due to different intervals of de-escalation and baseline risk factors prior to PCI in each study. Conclusion P2Y12 monotherapy has similar rates of all-cause mortality and myocardial infarction. However, early de-escalation leads to a lower incidence of bleeding. P2Y12 monotherapy showed a 35% decreased risk of bleeding compared to the DAPT strategy. This suggests that P2Y12 monotherapy is a preferable antiplatelet strategy in patients undergoing PCI, especially in the high-risk bleeding population.

Functional Neurological Disorder Presenting After Concussion: A Retrospective Case Series.

Although a majority of individuals recover from a concussion within weeks of the index injury, a substantial minority of patients report persistent postconcussion symptoms. Some of these symptoms may reflect a diagnosis of functional neurological disorder (FND). The authors evaluated the relationship between persistent postconcussion symptoms and FND symptoms. In this retrospective chart review, the authors characterized demographic and clinical information from 50 patients with a confirmed diagnosis of FND whose functional neurological symptoms started after a concussion. Patients who developed FND after a concussion had high rates of baseline risk factors for both persistent postconcussion symptoms and FND. After the concussive event, functional neurological symptoms presented abruptly or developed insidiously over time. Functional neurological symptoms ranged widely and included gait symptoms, seizures, speech and language symptoms, weakness, sensory symptoms, tremors, and vision and oculomotor symptoms. Functional neurological symptoms can arise after a concussion. FND should be considered in the differential diagnosis of individuals presenting with neurological symptoms beginning after a concussion. By failing to recognize functional symptoms, clinicians may inadvertently reinforce negative health-related beliefs regarding a patient's injured brain.

Etrasimod for the Treatment of Ulcerative Colitis: Analysis of Infection Events From the ELEVATE UC Clinical Program.

Infections are a safety concern in patients with ulcerative colitis (UC). Etrasimod is an oral, once-daily (QD), selective sphingosine 1phosphate (S1P)1,4,5 receptor modulator for the treatment of moderately to severely active UC. It leads to selective and reversible lymphocyte sequestration, and partial peripheral lymphocyte count decrease. We report infection events from the phase 3 ELEVATE program. Proportions, incidence rates (IRs; per 100 patient-years) and descriptive analyses of all, serious, severe, herpes zoster, and opportunistic infections are reported in the Pivotal UC cohort (ELEVATE UC 52 and ELEVATE UC 12). Cox regression models evaluated potential baseline risk factors. In this analysis (n=787), proportions (IRs) of all infection events were similar for patients receiving etrasimod 2mg QD (18.8% [41.1]) or placebo (17.7% [49.0]). Serious infections occurred in three (0.6%) and five (1.9%) patients receiving etrasimod and placebo, respectively. Two herpes zoster events were reported in each group (etrasimod: 0.4%; placebo: 0.8%); all localized and non-serious. One opportunistic infection event was reported in each group. No patient with an absolute lymphocyte count (ALC) <0.2 × 109/L reported serious/severe or opportunistic infections; no baseline risk factors were identified for such events. No deaths occurred. Patients receiving etrasimod demonstrated no increased risk of infection. The incidence of serious infections and herpes zoster was similar in each group. Among patients receiving etrasimod, no association between ALC <0.5 × 109/L and infection events was observed. Longer-term follow-up will further characterize the etrasimod safety profile.

Abstract PO5-15-11: A Novel Biosignature to Predict Radiation Therapy Response in Early-Stage Invasive Breast Cancer Treated with Breast-Conserving Surgery

Abstract Introduction: Radiation therapy (RT) is a standard component of treatment for most patients with early-stage, hormone receptor-positive, invasive breast cancer (BC) following breast-conserving surgery (BCS). RT recommendations are primarily based on clinicopathologic (CP) factors, such as tumor size, nodal status, and histological grade. While these factors provide prognostic information, their ability to accurately identify patients at a higher risk of ipsilateral breast recurrence (IBR) or those who will significantly benefit from RT is unclear. Therefore, incorporation of additional predictive markers beyond CP factors is warranted and there remains a need to refine the selection criteria for patients who will derive the greatest benefit from RT. In this study, we aimed to explore the role of immune and metabolic signaling axes as potential predictive markers for RT response in hormone receptor-positive breast cancer patients. Methods: A cohort of 939 women from Sweden were diagnosed with BC between 1987 and 2004. A subset of 471 patients was diagnosed with T1-T2N0M0 BC and underwent BCS with negative margins. Patients were treated with BCS plus/minus RT (median dose 50Gy) based upon physician preference. Biomarkers were assayed in formalin-fixed paraffin-embedded tissue micro arrays using multiplex immunofluorescence and multi-spectral imaging in a CLIA lab (Laguna Hills, CA). Immune and metabolic axes were defined employing biomarkers and used to classify patients into three risk groups: 1) Low Risk (lower baseline risk and no RT benefit), 2) Elevated Risk (higher baseline risk and significant RT benefit), and 3) Residual Risk (higher baseline risk and suboptimal RT benefit). Risk groups were analyzed for IBR rate using Kaplan-Meier and Cox proportional hazards analyses. Risk group prognosis and RT prediction was assessed for RT-risk group interaction in multivariable analysis, adjusting for CP factors. Results: Among the patients with complete biomarker data, 261 were hormone receptor-positive, and had a median follow-up of 140 months. Median age was 62 years (28-88 years), and median tumor size was 1.1 cm (0.1-4 cm). Some patients (21%) received endocrine therapy (ET), and most (76%) received RT, with 79% of patients who received ET also receiving RT. In the overall population, RT following BCS was associated with a reduction in HR for recurrence (HR=0.3, 95%CI [0.1, 0.5], p&amp;lt; 0.001). Patients classified as Low Risk (41%) did not have a significant benefit from RT (HR=0.9, 95%CI [0.1, 8.3], p=0.95) in multivariable analysis adjusted for CP factors. For patients who were classified as Elevated Risk (31%), multivariable analysis showed a higher IBR rate without RT (HR=5.7, 95%CI [1.3, 25.1], p&amp;lt; 0.021) relative to the Low Risk group who had a significant benefit from RT (HR=0.1, 95%CI [0.02, 0.2], p&amp;lt; 0.001). Patients classified into the Residual Risk group (28%) had no significant reduction from RT (HR=0.7, 95%CI [0.2, 2.0], p=0.61). However, in multivariable analysis adjusted for CP factors, patients treated with RT in the Residual Risk group had higher IBR rates (HR=3.7, 95%CI [1.6, 8.7], p=0.0026) compared to RT-treated patients in other risk groups. The biosignature was predictive for RT benefit in multivariable analysis adjusted for CP factors (p-interaction &amp;lt; 0.001). Conclusions:The biosignature used in this study demonstrated the potential to identify patients who may derive limited benefit from RT, allowing for tailored therapeutic approaches. These findings underscore the importance of individualized treatment decisions based on risk stratification. Further clinical validation and refinement of risk stratification strategies are warranted to optimize outcomes in hormone receptor-positive, BC patients undergoing BCS. Citation Format: Troy Bremer, Karuna Mittal, Chirag Shah, Frank Vicini, Steven Shivers, Charlotta Wadsten. A Novel Biosignature to Predict Radiation Therapy Response in Early-Stage Invasive Breast Cancer Treated with Breast-Conserving Surgery [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-15-11.

Abstract PO1-02-02: Update of RSClin with extended TAILORx follow-up and development and validation of a new tool for risk of late distant recurrence

Abstract Background: RSClin® (Sparano et al J Clin Oncol 2020, PMID 33306425) is an educational tool that estimates the 10-year risk of distant recurrence (DR) and the absolute benefit of chemotherapy in HR-positive, HER2-negative, node-negative early breast cancer. The RSClin tool integrates the Recurrence Score® (RS) result with the clinical-pathological features tumor grade, tumor size and patient age using patient-specific meta-analysis (PSMA) applied to the NSABP B-14, TAILORx and NSABP B-20 studies. Approximately 3 years of additional follow-up data have accumulated in the TAILORx study since the RSClin tool was developed, including 50% more DR events in the RS 11-25 group (375 vs. 250), and 46% more DR events in the overall population (561 vs. 384). Methods: The RSClin tool estimates were updated to include the extended follow-up data from TAILORx. As before, the PSMA included 10,004 women with hormone-receptor positive, HER2-negative, node-negative breast cancer from the NSABP B-14 (n=577) trial receiving endocrine therapy (ET) alone and the TAILORx trial receiving ET alone (n=4854) or chemotherapy (CT) plus ET (n=4573). The baseline risk estimate used TAILORx event rates with ET alone. Since there was evidence of differing hazard ratios in years 0-5 versus 5+, models using time-varying effects were used. A patient-specific estimator of absolute CT benefit was computed by combining a PSMA estimate of the individualized relative CT effect from the TAILORx and NSABP B-20 (n=550 HER2-negative) trials with risk estimates for ET alone. Similar methods were used to develop and validate a new tool for assessing the risk of late DR (from year 5 to 10) in patients who survive DR-free for 5 years on ET alone after surgery. External validation of DR risk estimation was performed in an independent cohort of 1098 women enrolled in the Clalit Health Service registry. Results: With the updated data, the model integrating RS result with clinical-pathological features was more informative for DR risk than either RS result alone or the clinical-pathological features alone, both for 10-year DR risk and for late DR risk (likelihood ratio tests, each p≤.001). The updated 10-year RSClin risk estimates are similar to the existing RSClin tool risk estimates with slightly lower risk estimates for very high RS results and more precise estimates for mid-range RS results. The updated chemotherapy effect estimates are slightly lower than for the existing RSClin. The updated RSClin tool 10-year risk estimates were strongly associated with DR risk in the independent Clalit registry (Cox regression p&amp;lt; .001) and closely approximated the observed DR risk (Lin concordance 0.87). The new tool’s late DR risk estimates beyond 5 years were strongly associated with late DR risk in the Clalit registry (Cox regression p=.002) and closely approximated the observed late DR risk (Lin concordance 0.92). Conclusions: The RSClin tool 10-year DR risk estimates have been updated to incorporate extended follow-up data from the TAILORx study. A new tool for assessing late DR risk has been developed and validated that provides more prognostic information than either clinical-pathological features or genomic risk used individually. Citation Format: Joseph Sparano, Michael Crager, Robert Gray, Gong Tang, Jess Hoag, Frederick Baehner, Charles Geyer, Steven Shak, Norman Wolmark, Salomon Stemmer. Update of RSClin with extended TAILORx follow-up and development and validation of a new tool for risk of late distant recurrence [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-02-02.

Abstract PS10-09: Development of an absolute risk prediction model for premenopausal breast cancer in an international consortium

Abstract Risk prediction models that have been developed for overall breast cancer risk are based on a limited number of premenopausal cases in individual cohorts. As some risk factors differ in their associations with pre- versus postmenopausal breast cancer, a distinct risk prediction model is needed for premenopausal breast cancer. We developed a risk prediction model for premenopausal breast cancer using 779,601 participants and 9,665 incident cases from 18 prospective studies within the Premenopausal Breast Cancer Collaborative Group (PBCCG), across North America (N=9), Europe (N=6), Australia (N=1), and Asia (N=2). Data were split, within each cohort, into training (2/3) and testing (1/3) datasets. Individual risk was assessed in five-year intervals, using variables reported at the start of the time interval. Cox proportional hazards regression was used to model risk factors in a backwards-selection method, stratified by cohort: age at menarche, age at first birth, parity, breastfeeding (months), height (cm), BMI (kg/m2), BMI at age 18, recent weight change (kg), alcohol consumption (drinks/week), first-degree family history of breast cancer, and personal history of benign breast disease. To enable the use of information from all cohorts despite differences in missing variables by design, cohorts were grouped by available variables and risk models were fit for each group. In cohorts with incomplete data, model coefficients were adjusted based on the correlation of covariates with the missing variables in the complete case dataset. Coefficients were meta-analyzed with inverse variance weighting to obtain final coefficients. Discrimination was evaluated in the testing dataset by calculation of the c-index. Work is ongoing to calibrate the model based on five-year absolute risk using GLOBOCAN continent- and age-specific incidence rates to represent baseline risk. The final model included age at menarche, parity, height, BMI, BMI at age 18, first-degree family history of breast cancer, and history of benign breast disease. Young adulthood BMI and BMI (at start of the 5-year risk interval) were associated with a decreased risk (Hazard Ratio (HR) (95% confidence interval (CI)) per 5 kg/m2 = 0.87 (0.81-0.93) and 0.90 (0.86-0.95), respectively) as was parity (HR (95% CI) = 0.92 (0.90-0.94)). Height was associated with increased risk (HR (95% CI) per 10 cm = 1.14 (1.07-1.21)), while history of benign breast disease and family history were associated with larger increases in risk (HR (95% CI) = 1.64 (1.30-2.06) and 1.76 (1.63-1.90), respectively). Model discrimination was higher than that reported for women under 50 years in existing breast cancer risk prediction models considering clinical factors (AUC (95% CI) = 0.61 (0.59-0.62)). Calibration of absolute 5-year risk is ongoing. Several factors driving risk prediction of postmenopausal breast cancer have similar influence on risk of premenopausal breast cancer, while family history has a stronger influence on premenopausal breast cancer risk. Our model demonstrates acceptable discrimination and will enable individual 5-year absolute risk prediction for premenopausal breast cancer. Citation Format: Kristen Brantley, Michael Jones, Minouk Schoemaker, Hazel Nichols, Anthony Swerdlow, Robert MacInnis, Roger Milne, Tess Clenenden, Yu Chen, Xiao-Ou Shu, Wei Zheng, Woon-Puay Koh, Jian-Min Yuan, Cari Kitahara, Martha Linet, Dale Sandler, Bernard A Rosner, Peter Kraft, A. Heather Eliassen. Development of an absolute risk prediction model for premenopausal breast cancer in an international consortium [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS10-09.

Variation in content discussed by specialty in consultations for clinically localized prostate cancer

IntroductionMultidisciplinary consultations improve decisional conflict and guideline-concordant treatment for men with prostate cancer (PC), but differences in the content discussed by specialty during consultations are unknown. MethodsWe audiorecorded and transcribed 50 treatment consultations for localized PC across a multidisciplinary sample of urologists, radiation oncologists, and medical oncologists. Conversation was coded for narrative content using an open coding approach, grouping similar topics into major content areas. The number of words devoted to each content area per consult was used as a proxy for time spent. Multivariable Poisson regression calculated incidence rate ratios (IRR) for content-specific word count across specialties after adjustment for tumor risk and patient demographics. ResultsCoders identified 8 narrative content areas: overview of PC; medical history; baseline risk; cancer prognosis; competing risks; treatment options; physician recommendations; and shared decision making (SDM). In multivariable models, specialties significantly differed in proportion of time spent on treatment options, SDM, competing risks, and cancer prognosis. Urologists spent 1.8-fold more time discussing cancer prognosis than medical oncologists (IRR1.80, 95%CI:1.14–2.83) and radiation oncologists (IRR1.84, 95%CI:1.10–3.07). Urologists (IRR11.38, 95%CI:6.62–19.56) and medical oncologists (IRR10.60, 95%CI:6.01–18.72) spent over 10-fold more time discussing competing risks than radiation oncologists. Medical oncologists (IRR2.60, 95%CI:1.65–4.10) and radiation oncologists (IRR1.77, 95%CI:1.06–2.95) spent 2.6- and 1.8-fold more time on SDM than urologists, respectively. ConclusionsSpecialists focus on different content in PC consultations. Our results suggest that urologists should spend more time on SDM and radiation oncologists on competing risks. Our results also highlight the importance of medical oncologists in facilitating SDM.

Temporal trends in the contribution of modifiable cardiovascular risk factors to cardiovascular and all-cause mortality in patients undergoing myocardial perfusion imaging in a large city in Brazil

BackgroundMost cardiovascular (CV) events stem from modifiable, but it remains uncertain whether their impact on mortality has decreased in recent years as a result of treatment, particularly in low- and middle-income countries. We evaluated the temporal trends in the population attributable fraction (PAF) of modifiable risk factors to CV mortality in patients undergoing myocardial perfusion imaging (MPI) for suspected coronary artery disease in a large city in Brazil. MethodsThe cohort comprised 25,127 patients without established CV disease undergoing MPI in a referral center in Curitiba, Brazil, from 2010 to 2018. Baseline demographic, clinical and risk factors were prospectively collected. Modifiable risk factors encompassed hypertension, dyslipidemia, diabetes mellitus, sedentary lifestyle, obesity, and smoking. The primary outcome was CV death occurring up to 4 years of follow-up. The PAF of each risk factor was calculated for each triennium using multivariable Cox proportional regression models, adjusting for age, sex and family history of premature coronary disease. ResultsOver 9 years, there were 1438 deaths, 444 due to CV causes. In the first triennium, sedentary lifestyle exhibited the highest PAF (49%) for CV death, followed by hypertension (17%), diabetes mellitus (8%) and smoking habit (6%). The PAF for all risk factors combined remained relatively stable thorough the triennia (2010–2012: 57% vs 2013–2015: 64% vs 2016–2018: 47%, p = NS). ConclusionIn this large cohort of patients referred to MPI, the PAF of modifiable CV risk factors did not diminish in the last decade, with sedentary lifestyle having the largest contribution for CV mortality. Condensed abstractThis study examinated temporal trends in the impact of modifiable cardiovascular (CV) risk factors on CV and overall mortality in a cohort of 25,127 patients undergoing myocardial perfusion imaging from 2010 to 2018. Sedentary behavior consistently had the greatest impact on both CV and overall mortality, followed by hypertension and diabetes. Smoking had a lesser effect, while obesity showed no independent association with the outcomes. The contributions of these modifiable CV risk factors remained stable over the study period, suggesting that interventions promoting physical activity may be essential in mitigating the burden of CV disease.

Prevalence of Cardiovascular and Cancer Risk Factors Among Rheumatoid Arthritis Patients Prescribed Janus Kinase Inhibitors and Tumor Necrosis Factor Inhibitors: A Cross-Sectional Study.

The study was to determine the prevalence of baseline risk factors for cardiovascular outcomes and cancer among commercially-insured patients with rheumatoid arthritis (RA) during their first dispensed treatment for either tumor necrosis factor inhibitors (TNFi) or JAK inhibitors (JAKi). Patients with RA from August 16, 2019 to March 31, 2022 were identified in the Merative MarketScan Commercial and Medicare databases. The first date that a TNFi or JAKi was dispensed was the index date, and baseline risk factors were assessed among patients continuously eligible for 12 months before the index date. Patients who had the following were stratified into an elevated risk category: age ≥65 years, smoking, or a history of a major adverse cardiovascular event, venous thromboembolism, or cancer. The prevalence of modifiable risk factors was also reported: hypertension, hyperlipidemia, obesity, and diabetes. The crude prevalence and prevalence difference (PD) were reported. A total of 12,673 patients (TNFi [n = 7,748; 61%] and JAKi [n = 4,925; 39%]) met inclusion criteria. The prevalence of elevated risk was the same for all patients using TNFi (n = 2,051; 26%) and JAKi (n = 1,262; 26%). Compared with patients having low risk, patients with an elevated risk also had a higher prevalence of at least one primary modifiable risk factor for both patients using JAKi (79% vs 58%; PD 21%, 95% confidence interval [CI] 18%-24%) and TNFi (81% vs 60%; PD 21%, 95% CI 19%-23%). In recent years, JAKi and TNFi were used in similar proportions to treat RA among commercially-insured patients at elevated cardiovascular and cancer risk. Because uncontrolled disease, modifiable comorbidities, and treatment with JAKi are associated with these adverse events, future studies evaluating how practice patterns may be affected by the emergence of safety data will be of value.

Effects of icosapent ethyl according to baseline residual risk in patients with atherosclerotic cardiovascular disease: results from REDUCE-IT.

Icosapent ethyl lowers triglycerides and significantly reduces major adverse cardiovascular events (MACE), though treatment effects may vary between individuals. This study aimed to determine the relative and absolute effects of icosapent ethyl on MACE according to baseline CVD risk in patients with atherosclerotic cardiovascular disease (ASCVD). Participants from REDUCE-IT with ASCVD were included (n = 5,785). The primary outcome was 3-point MACE, i.e. non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death. Baseline 5-year risk of MACE was estimated using the ESC guideline-recommended SMART2 risk score. Modification of the relative treatment effects of icosapent ethyl by baseline risk was assessed using Cox proportional hazards models including a treatment-by-risk interaction. Next, treatment effects were assessed stratified by quartiles of baseline risk. During a median follow-up of 4.8 years (interquartile range 3.2-5.3), MACE occurred in 361 vs 489 patients in the icosapent ethyl vs placebo group (95% confidence interval [CI]); hazard ratio (HR) 0.72 (0.63-0.82), absolute risk reduction (ARR) 4.4% (2.6-6.2%), number needed to treat (NNT) 23 (16-38), 5-year Kaplan-Meier estimated cumulative incidence reduction (CIR) 5.7% (3.5-7.9%). Icosapent ethyl significantly reduced MACE in all risk quartiles, with an HR (95% CI) of 0.62 (0.43-0.88), 0.66 (0.48-0.92), 0.69 (0.53-0.90), and 0.78 (0.63-0.96) respectively (p for treatment-by-risk interaction = 0.106). The ARR (95% CI) increased across risk quartiles, i.e. was 3.9% (1.0-6.8%), 4.3% (1.2-7.3%), 5.1% (1.4-8.7%), and 5.6% (1.3-10.0%) respectively. This translates to NNTs (95% CI) of 26 (15-98), 24 (14-84), 20 (11-70), and 18 (10-77). The 5-year CIR (95% CI) was 4.8% (1.3-8.2%), 5.0% (1.3-8.7%), 6.1% (1.7-10.5%), and 7.7% (2.3-13.2%) respectively. Consistent results were obtained for 5-point MACE, additionally including coronary revascularization and unstable angina. Among patients with ASCVD and elevated triglyceride levels, icosapent ethyl significantly reduces the risk of MACE irrespective of baseline CVD risk, though absolute benefits are largest for patients at the highest risk.

Individualized prevention of proton pump inhibitor related adverse events by risk stratification

Proton pump inhibitors (PPIs) are commonly used for gastric acid-related disorders, but their safety profile and risk stratification for high-burden diseases need further investigation. Analyzing over 2 million participants from five prospective cohorts from the US, the UK, and China, we found that PPI use correlated with increased risk of 15 leading global diseases, such as ischemic heart disease, diabetes, respiratory infections, and chronic kidney disease. These associations showed dose-response relationships and consistency across different PPI types. PPI-related absolute risks increased with baseline risks, with approximately 82% of cases occurring in those at the upper 40% of the baseline predicted risk, and only 11.5% of cases occurring in individuals at the lower 50% of the baseline risk. While statistical association does not necessarily imply causation, its potential safety concerns suggest that personalized use of PPIs through risk stratification might guide appropriate decision-making for patients, clinicians, and the public.

Analysis of Self-Rescue Possibilities for Pedestrians in the Aftermath of Destabilization during a Flood Event

Human safety is paramount in flood disasters. Current research indicates that the majority of fatalities in such disasters are due to people moving in water. Existing studies on human stability in floods have primarily focused on the static resistance of a standing posture against water flow, neglecting the realistic scenario where people need to move and attempt self-rescue in the aftermath of destabilization. This paper introduces an analysis of the stability during the self-rescue process following a fall in floodwaters, providing insights into the baseline risks of human impact in floods. The self-rescue process is defined as the recovery to a standing position after a fall, segmented into four postures: sitting, kneeling, squatting, and standing. Additionally, considering the significant variability of the current method (D×v water depth multiplied by flow velocity) used to assess human stability in floods, this research thoroughly investigates previously undefined parameters, including submerged volume, frontal area, wet friction coefficient, and flow resistance coefficient. This leads to the development of a physically meaningful self-rescue risk assessment formula, which is validated against previous studies for accuracy, with the aim of contributing new insights to flood risk management and public education.

Exploration and practice of cardio-oncology

With the improvement of oncology diagnosis and treatment, the survival time of cancer patients has been significantly prolonged, and the cancer therapy-related cardiovascular toxicity such as radiotherapy, chemotherapy, immunotherapy, and surgery are becoming more and more prominent, and it is in this context that the germ of Cardio-Oncology exploration has come into being. The multidisciplinary Cardio-Oncology team aims to establish a multidisciplinary prevention and control system to assess patients' baseline risk factors, individualized monitoring, and weighing the risk-benefit ratio of cancer therapy. At present, the connotation of the discipline of Cardio-Oncology has been expanded horizontally and deepened vertically in China, and Cardio-Oncology treatment centers have blossomed all over the country. Moreover, international and domestic scholars continue to improve Cardio-Oncology guidelines and consensus through their own practice, and develop artificial intelligence software to help the development of the discipline. It is believed that in the future, with the training of Cardio-Oncologists and the output of high-quality clinical research evidence, cardiovascular safety of cancer patients can be ensured more scientifically and effectively.

Assessment of Climate Change-Induced Water Scarcity Risk by Using a Coupled System Dynamics and Bayesian Network Modeling Approaches

AbstractThe water scarcity risk induced by climate change is contributing to a sequence of hydrological and socioeconomic impacts. Certain numbers of related impacts are locked in already and are expected to be much greater in the future. So, there is still a lack of understanding of its dynamics, origin, propagation, and the mutual interaction of its drivers. In recent years, several model-based approaches have been introduced to tackle the complexity, dynamics, and uncertainty of water scarcity specifically. However, the coupled modeling while addressing different aspects of the risk of water scarcity under the climate change scenarios has been rarely done. For bridging this gap, in this research, the combination of complementary System Dynamics modeling and Bayesian Network was applied to Qazvin Plain in Iran with five AOGCM models under two Shared Socioeconomic Pathways (SSP) scenarios (126 and 585). Key findings of this research show: 1) Baseline risk assessment indicates a low probability of water scarcity; however, in the future 30-year time horizon with continuous change in hazard, vulnerability, and exposure for SSP126, the risk fell in the extreme category with an average probability of 41%. Under SSP585, the risk varies between extreme and high categories with an average probability of 47%. 2) Economic development, particularly regional gross domestic product (RGDP) in 2045–2054 in SSP585 can diminish the negative projected consequences of climate change and therefore investments in adaptation policies could offset negative consequences, highlighting the role of economic growth in climate resilience. 3) It is projected that crop yield and income will receive the largest negative effects due to cutting back the agriculture area. 4) Considering the interplay of climate change, economic development, and water extraction policies is essential for the design, operation, and management of water-related activities. The proposed integrated methodology provides a comprehensive framework for understanding climate change-induced water scarcity risks, their drivers, and potential consequences. This approach facilitates adaptive decision-making to address the evolving challenges posed by climate change.