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Although natriuretic peptide levels have been associated with incident heart failure and prognosis of heart failure patients, trials on natriuretic peptide-guided treatment have provided inconsistent results. Existing trials mostly used predefined screening intervals and target levels, which do not account for variations in temporal patterns of circulating biomarkers between individuals. This may hamper their potential use for therapy guidance. In contrast, a personalized screening approach with screening intervals and target levels based on the evolution of biomarkers in individual patients may further improve risk assessment and therapy guidance. Such personalized screening intervals maximize information gain on the individual patients’ disease progression, while minimizing the necessary number of measurements. In the Bio-SHiFT study, we demonstrated that individual temporal patterns of serially measured chronic heart failure (CHF)-related biomarkers are associated with the prognosis of CHF patients. We also demonstrated a method to obtain a patient-specific dynamic estimate of prognosis. This estimate is updated after every additional measurement, as each measurement provides additional information. This personalized risk assessment can also be used to derive personalized screening intervals for future CHF patients. However, the benefits of this approach, over predefined screening intervals and targets, have not yet been investigated in CHF patients. Here, we compare personalized scheduling of N-terminal pro-B-type natriuretic peptide (NT-proBNP) measurements to a predefined, fixed scheduling approach. In 263 stable CHF patients from the Bio-SHiFT study, NT-proBNP was measured trimonthly according to a prespecified, fixed schedule. The composite primary endpoint (PE) consisted of cardiac death, cardiac transplantation, left ventricular assist device implantation or heart failure hospitalization. Using joint models for time-to-event and longitudinal data, we modelled the association between repeated NTproBNP measurements and the PE. Subsequently, we performed a simulation study where we generated 750 patients with baseline characteristics and NTproBNP profiles similar to the 263 patients included in the Bio-SHiFT study. We divided these patients into a training (700 patients) and testing (50 patients) set. In the training set, we fitted a new joint model for NT-proBNP. We compared scheduling of NT-proBNP

european journal of preventive cardiology

Personalized screening intervals for measurement of N-terminal pro-B-type natriuretic peptide improve efficiency of prognostication in patients with chronic heart failure