Cardiovascular Disease Prognostic Models in Latin America and the Caribbean: A Systematic Review

Abstract

Background Cardiovascular prognostic models guide treatment allocation and support clinical decisions. Whether there are valid models for Latin American and Caribbean (LAC) populations is unknown. Objective This study sought to identify and critically appraise cardiovascular prognostic models developed, tested, or recalibrated in LAC populations. Methods The systematic review followed the CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) framework (PROSPERO [International Prospective Register of Systemic Reviews]: CRD42018096553). Reports were included if they followed a prospective design and presented a multivariable prognostic model; reports were excluded if they studied symptomatic individuals or patients. The following search engines were used: EMBASE, MEDLINE, Scopus, SciELO, and LILACS. Risk of bias assessment was conducted with PROBAST (Prediction model Risk Of Bias ASsessment Tool). No quantitative summary was conducted due to large heterogeneity. Results From 2,506 search results, 8 studies (N = 130,482 participants) were included for qualitative synthesis. We could not identify any cardiovascular prognostic model developed for LAC populations; reviewed reports evaluated available models or conducted a recalibration analysis. Only 1 study included a Caribbean population (Puerto Rico); 3 studies were retrieved from Chile; 2 from Argentina, Brazil, Colombia, and Uruguay; and 1 from Mexico. Four studies included population-based samples, and the other 4 included people affiliated to a health facility (e.g., prevention clinics). Most studied participants were older than 50 years, and there were more women in 5 reports. The Framingham model was assessed 6 times, and the American College of Cardiology/American Heart Association pooled equation was assessed twice. Across the prognostic models assessed, calibration varied widely from one population to another, showing great overestimation particularly in some subgroups (e.g., highest risk). Discrimination (e.g., C-statistic) was acceptable for most models; for Framingham it ranged from 0.66 to 0.76. The American College of Cardiology/American Heart Association pooled equation showed the best discrimination (0.78). That there were few outcome events was the most important methodological limitation of the identified studies. Conclusions No cardiovascular prognostic models have been developed in LAC, hampering key evidence to inform public health and clinical practice. Validation studies need to improve methodological issues.

Prediction Models for Prognosis of Cervical Cancer: Systematic Review and Critical Appraisal

“…Our systematic review showed several methodological pitfalls in the development or validation of the models, especially in the analysis domain which was the main cause of high ROB. Similar to reviews assessing the quality of prognostic models for other diseases including oropharyngeal cancer, chronic lymphocytic leukemia, and chronic obstructive pulmonary disease (19,20,39,40), inadequate sample size, improper handling of missing data, and incomplete evaluation of model performance were the main problems in analysis domain and needed to be emphasized. Besides this, several other methodological details should also be noted.…”

Prognostic models for predicting in-hospital paediatric mortality in resource-limited countries: a systematic review

“…Thus, this review highlights the need for researchers to adhere to the TRIPOD guidelines that were created to help authors of prognostic models write complete and transparent reports. Of note, the quality of clinical predictive models does not appear to have improved over time as previous reviews from 1996, 61 1997, 62 2001, 63 2005, 64 2011, 8 2012, 65 2016, 66 67 2017 68 –2019 69 have consistently identified suboptimal methodologies in the development of the score/predictive models especially in the domain of analysis. Poorly derived models may result in overoptimistic results and misleading performances.…”

Insulin Resistance Indexes as Biomarkers of Lifetime Cardiovascular Risk among Adults from Peru

“…The ACC/AHA risk score was calculated to measure general CVR over 10 years [ 22 ]. This score presented the best discrimination (AUC = 0.78) of general CVR in a Latin American population [ 19 ]. The population was categorized as low, borderline, intermediate, and high risk according to the ACC/AHA 2019 guidelines on the primary care of cardiovascular diseases [ 23 ].…”

“…Different equations and scales make it possible to quantify CVR, their differences being mainly due to the specific parameters established for the calculation and population to apply [ 18 ]. The most common risk score used in the Latin American population is the Framingham and American College of Cardiology/American Heart Association (ACC/AHA) risk score, which estimates the risk of developing myocardial infarct, stroke, or peripheral artery disease at 10 years [ 19 ]. In Peru, the prevalence of high CVR is approximately 29%; however, young, middle-aged, and older adult proportions could change the prevalence of CVR in the risk calculators at 10 years [ 20 ].…”