ABSTRACT Clinical Prediction Models (CPMs) compute an individual's risk of an outcome, given a set of predictors. Guidance states CPMs should be constructed using data sampled from the target population. However, researchers might have access to ancillary data sets from different time points, countries, or healthcare settings, which could support model development. This study explores in which situations the ancillary data affect CPM performance, given potential heterogeneity. We conducted a simulation study to assess the impact of heterogeneity between the target and the ancillary data sets, and their relative sample size, on CPM performance. Target and ancillary populations were generated with varying degrees of heterogeneity. CPMs were developed using target‐only logistic regression, logistic and intercept updating, and importance weighting using propensity scores. These models were evaluated on independent data using calibration, discrimination, and prediction stability. Also, a real‐world case study was used as an illustrative example of application using the SWEDEHEART registry. Incorporating ancillary data generally improve CPM performance. Logistic and Intercept Recalibration often outperformed the target‐only regression approach. However, Logistic Recalibration showed greater variability and instability in calibration, while Intercept Recalibration performed poorly under predictor–outcome association shift. The importance weighting method demonstrated consistent performance across a wide range of scenarios and appears to be a reliable alternative, particularly in practical settings where the presence and type of data distribution shift is often unknown.
Haya Elayan, M. Sperrin, G. Martin et al.· Biometrical journal. Biometr...· 0 citations
BACKGROUND AND AIM
Randomized trials conducted in the early 2000s established the survival benefit of primary prevention implantable cardioverter-defibrillator (ICD) therapy in patients with reduced left ventricular ejection fraction (LVEF) after myocardial infarction. However, management of myocardial infarction and heart failure has substantially evolved since that time. We investigated whether the estimated association between primary prevention ICD implantation in post-myocardial infarction patients with reduced LVEF and mortality reduction has changed over time.
METHODS
We analyzed individual participant data from 32,214 patients with LVEF ≤35% after myocardial infarction included in the PROFID pooled cohort, comprising 7,477 patients carrying a primary prevention ICD (ICD patients) and 24,737 patients without an ICD (non-ICD patients). The primary endpoint was all-cause mortality. Propensity scores were estimated using multivariable logistic regression including age, sex, LVEF, renal function, and diabetes, and overlap weighting was applied to balance treatment groups. Time period-specific analyses were performed across three prespecified time periods defined by inclusion year: 1995-2004, 2005-2014, and 2015-2020. Weighted cumulative mortality curves were generated for each time period. Temporal changes in the estimated association between ICD implantation and mortality reduction were assessed using a weighted Cox proportional hazards model.
RESULTS
A total of 12,097 deaths occurred during a mean follow-up of 43.7 months. The estimated association between ICD implantation and mortality changed significantly across time (P for interaction <0.001). In weighted time period-specific analyses, the estimated mortality reduction associated with ICD implantation progressively decreased over more recent periods. The hazard ratio for ICD versus non-ICD patients was 0.54 (95% CI 0.47-0.62; P<0.001) in 1995-2004, 0.67 (95% CI 0.62-0.72; P<0.001) in 2005-2014, and 0.89 (95% CI 0.73-1.07; P=0.221) in 2015-2020, with negligible separation of the weighted cumulative mortality curves in the most recent time period.
CONCLUSIONS
In this analysis including a large cohort of post-myocardial infarction patients with reduced LVEF, the estimated mortality reduction associated with primary prevention ICD implantation progressively decreased over time.
A. Sepehri Shamloo, T. Chiba, J. G. Tijssen et al.· European Heart Journal· 0 citations
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