Clusters of Cardiovascular Risk Factors and Their Impact on the 20-Year Cardiovascular Risk in a General Population.

BACKGROUND: Clustering of cardiovascular risk factors (CVRFs) is extraordinarily common and is associated with an increased risk of cardiovascular disease (CVD). However, the particular impact of the sum of CVRFs on cardiovascular morbidity and mortality has not been sufficiently explored in Europe. OBJECTIVE: The aim of this study was to analyze the differences in survival-free probability of CVD in relation to the number of CVRFs in a Spanish population. METHODS: A prospective cohort study was conducted from 1992 to 2016 in a Spanish population that included 1144 subjects with no history of CVD (mean age, 46.7 years) drawn from the general population. We calculated the number of CVRFs for each subject (male sex, smoking, diabetes, hypertension, dyslipidemia, obesity, and left ventricular hypertrophy). Cardiovascular morbidity and mortality records were collected, and survival analysis was applied (competing risk models). RESULTS: There were 196 cardiovascular events (17.1%). The differences in total survival-free probability of cardiovascular morbidity and mortality of the different values of the sum of CVRFs were significant, increasing the risk of CVD (hazard ratio, 1.30; 95% confidence interval, 1.13-1.50) per each additional risk factor. CONCLUSION: Differences in survival-free probability of CVD in relation to the number of CVRFs present were statistically significant. Further studies are needed to corroborate our results.

A critical appraisal of the clinical applicability and risk of bias of the predictive models for mortality and recurrence in patients with oropharyngeal cancer: Systematic review.

The use of predictive models is becoming widespread. However, these models should be developed appropriately (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modeling Studies [CHARMS] and Prediction model Risk Of Bias ASsessment Tool [PROBAST] statements). Concerning mortality/recurrence in oropharyngeal cancer, we are not aware of any systematic reviews of the predictive models. We carried out a systematic review of the MEDLINE/EMBASE databases of those predictive models. In these models, we analyzed the 11 domains of the CHARMS statement and the risk of bias and applicability, using the PROBAST tool. Six papers were finally included in the systematic review and all of them presented high risk of bias and several limitations in the statistical analysis. The applicability was satisfactory in five out of six studies. None of the models could be considered ready for use in clinical practice.

A systematic review of predictive models for recurrence and mortality in patients with tongue cancer.

INTRODUCTION: Predictive models must meet clinical/methodological standards to be used in clinical practice. However, no critique of those models relating to mortality/recurrence in tongue cancer has been done bearing in mind the accepted standards. METHODS: We conducted a systematic review evaluating the methodology and clinical applicability of predictive models for mortality/recurrence in tongue cancer published in MEDLINE and Scopus. For each model, we analysed (domains of CHARMS, Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) the following: source of data, participants, outcome to be predicted, candidate predictors, sample size, missing data, model development, model performance, model evaluation, results and interpretation and discussion. RESULTS: We found two papers that included eight prediction models, neither of which adhered to the CHARMS recommendations. CONCLUSION: Given the quality of tongue cancer models, new studies following current consensus are needed to develop predictive tools applicable in clinical practice.