Abstract 174: Clinical Prediction Models for Cardiovascular Disease: The Tufts PACE CPM Database

Abstract

Background: Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease (CVD) there are numerous CPMs available though the extent of this literature is not well described. Methods and Results: We conducted a systematic review for articles containing CPMs for CVD published between January 1990 through May 2012. CVD includes coronary artery disease (CAD), congestive heart failure (CHF), arrhythmias, stroke, venous thromboembolism (VTE) and peripheral vascular disease (PVD). We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. We included articles that describe newly developed CPMs that predict the risk of developing an outcome (prognostic models) or the probability of a specific diagnosis (diagnostic models). There are 796 models included in this database representing 31 distinct index conditions. 717 (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. There are 215 CPMs for patients with CAD, 168 CPMs for population samples at risk for incident CVD, and 79 models for patients with CHF (Figure). De novo CPMs predicting mortality were most commonly published for patients with known CAD (98 models) followed by HF (63 models) and stroke (24 models). There are 77 distinct index/ outcome (I/O) pairings and models are roughly evenly split between those predicting short term outcomes (< 3 months) and those predicting long term outcomes (< 6 months). There are 41 diagnostic CPMs included in this database, most commonly predicting diagnoses of CAD (11 models), VTE (10 models), and acute coronary syndrome (5 models). Of the de novo models in this database 450 (63%) report a c-statistic and 259 (36%) report either the Hosmer-Lemeshow statistic or show a calibration plot. Conclusions: There is an abundance of CPMs available for many CVD conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood.

Discrimination and Calibration of Clinical Prediction Models

“…Discrimination and calibration are both important characteristics in the evaluation of model performance; however, they remain underreported in the published medical literature. A systematic review addressing prediction models of cardiovascular outcomes noted that only 63% reported on discrimination and only 36% reported on calibration …”

Enhancement of Risk Prediction With Machine Learning

“…These models ostensibly offer clinicians a way of assigning risk to individual patients to allow for precision management decisions and risk-adjusted reporting of performance measures. 1 An important performance measure for percutaneous coronary intervention (PCI) is postprocedure bleeding, which is not only the most common noncardiac complication after PCI but is also associated with increased mortality, morbidity, and cost. 2 Rao et al 3 developed a 31-variable risk prediction model, developed from data from the National Cardiovascular Data Registry (NCDR), that demonstrated reasonable model performance with a C statistic of 0.77.…”

“…During the past decade, there has been a significant rise in the development of risk prediction models in cardiovascular disease. These models ostensibly offer clinicians a way of assigning risk to individual patients to allow for precision management decisions and risk-adjusted reporting of performance measures . An important performance measure for percutaneous coronary intervention (PCI) is postprocedure bleeding, which is not only the most common noncardiac complication after PCI but is also associated with increased mortality, morbidity, and cost .…”

Can We Improve Mortality Estimation in Women After Treadmill Testing by Using Sex-Specific Scores?

“…The abundance of currently available clinical prediction models (CPMs) has been demonstrated by a recent systematic review. 1 This review unearthed 796 scientific articles on the topic of CPMs and cardiovascular disease published from 1990 to 2012, with 90% being novel and the remainder recalibration or other adaptations of prior CPMs. Although utilization of CPMs is currently low, it promises to decrease use of the routine subjective eyeball test.…”

“…The use of predictive analytics in modern cardiology has had a significant impact in decreasing the subjectivity of forecasting cardiovascular events. The abundance of currently available clinical prediction models (CPMs) has been demonstrated by a recent systematic review . This review unearthed 796 scientific articles on the topic of CPMs and cardiovascular disease published from 1990 to 2012, with 90% being novel and the remainder recalibration or other adaptations of prior CPMs.…”