Key points:
- The TARGET trial is the first randomized trial designed to assess the impact of an on-site CT-FFR strategy using machine learning compared to standard care in patients with new onset stable chest pain with an intermediate-to-high pretest of coronary artery disease probability found to have intermediate stenosis on CCTA.
- Utilization of on-site CT-FFR compared to standard care with stress testing reduced the proportion of patients referred for invasive coronary angiography who did not have obstructive coronary artery disease or require intervention within 90 days. In addition, the on-site CT-FFR strategy increased revascularization overall but did not improve quality of life, symptoms of angina, or clinical outcomes.
- On-site CT-FFR measurement was based on a deep learning algorithm, which has been shown to perform equally well as computational fluid dynamics CT-FFR in identifying hemodynamically significant stenosis.
- The TARGET trial provides support for the use of on-site CT-FFR in the management of intermediate-to-high risk patients with stable chest pain and is expected to further consolidate the role of CCTA as a “gatekeeper” of the Cath lab.
The results of the TARGET trial, an investigator-initiated, prospective, multicenter, randomized control trial involving patients with symptoms of stable angina and coronary artery disease conducted in China, was presented today by Dr. Yundai Chen from the Chinese PLA General Hospital at the ACC 2023 conference today.
The aim of the TARGET trial is to assess the impact of an on-site CT-FFR strategy using machine learning compared to standard care in patients with new onset stable chest pain with an intermediate-to-high pretest probability of coronary artery disease probability found to have intermediate stenosis on CCTA. The study aims to determine whether the utilization of on-site CT-FFR reduces the proportion of patients referred for invasive coronary angiography who did not have obstructive coronary artery disease or require intervention within 90 days
The primary endpoint in this study was the proportion of patients who underwent invasive coronary angiography and were found to have either no obstructive coronary artery disease or obstructive disease but did not receive intervention within a 90-day period. This endpoint was considered as the key measure of the effectiveness of the diagnostic and treatment strategies employed in the study. The study aimed to identify patients who could benefit from more tailored management approaches in order to optimize patient outcomes.
Of 7683 patients with new onset chest pain and possible stable angina who underwent CCTA were assessed for eligibility, and of these, 1,216 were enrolled and randomized in the trial. The patient population had a median age of 60 (65% men). The extent and severity of coronary artery disease by CCTA were comparable between the two groups.
In comparison to the standard care group, the CT-FFR care group demonstrated a decrease in the percentage of patients undergoing invasive coronary angiography without obstructive coronary artery disease or with obstructive disease who did not receive intervention within 90 days (28.3% [119/421] versus 46.2% [223/483], P<0.001). The reduction was primarily driven by a decrease in the percentage of patients diagnosed with non-obstructive coronary artery disease in the CT-FFR care group compared to the standard care group (20.9% [88/421] versus 38.0% [184/483]). In the CT-FFR and standard care groups, respectively, the percentage of patients with obstructive disease who did not undergo intervention within 90 days was 7.4% [31/421] and 8.1% [39/483].
The utilization of on-site CT-FFR with machine learning decreased the rate of patients with stable coronary artery disease undergoing invasive coronary angiography without obstruction or intervention within 90 days. However, it led to an increase in overall revascularization without any improvement in symptoms, quality of life, or reduction in major adverse cardiovascular events.
