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In the results of a late-breaking trial yesterday, using data from the randomised TIM-HF2 trial, Professor Martin Möckel (Charité Campus Virchow-Klinikum and Mitte, Berlin, Germany) reported that biomarkers can be used to effectively tailor remote patient management (RPM) to individuals most likely to benefit from this approach (LBT36).
The TIM-HF2 trial was the first to report that RPM in patients with least one hospitalisation for heart failure improved survival compared with standard-of-care (SOC) management.1 “However,” explains Prof. Möckel, “this potentially life-saving approach, which involves significant use of healthcare resources and input from patients, does not benefi t everyone.”
This prospective biomarkers sub-study sought to investigate the allocation of RPM based on biomarker levels measured during the trial (NT-proBNP and the relatively newer biomarker, midregional - proadrenomedullin [MR-proADM]). In contrast to the standard approach of trying to modify or target the biomarkers, the novel analytical approach used biomarkers to identify patients at a high risk of events, with RPM then being employed to modify the consequences of this risk.
Only 38% of patients in the SOC arm, and 35% of those in the RPM arm, had a primary endpoint event (% lost days due to all-cause death or cardiovascular hospitalisation). Biomarker cut-off levels to distinguish between patients with and without an event were identified in the SOC arm. These were then applied to the primary and secondary endpoints in both randomised arms according to three different sensitivity scenarios, based on recommending 100%, 98% and 95.5% of patients with an event to RPM.
In all three sensitivity scenarios, the significant benefit of RPM vs standard of care was similar to that in the primary analysis, with hazard ratios of 0.71 (p<0.05) and 0.70, respectively.
Biomarker cut-off levels for the 95.5% sensitivity related to the secondary endpoint all-cause mortality—MR-proADM <0.75 nmol/L and NT-proBNP <383.3 ng/L— are in line with those reported in other studies or recommended in guidelines. This level of sensitivity resulted in the greatest reduction in the number of patients being allocated to RPM; the number-needed-to-treat to prevent one death being reduced from the 28 identified in the primary analysis to 23. “The use of a combination of MR-proADM and NT-proBNP biomarkers allows the more precise and effective allocation of RPM,” concludes Prof. Möckel.
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