Clinical Trial Service Unit

About: Clinical Trial Service Unit is a based out in . It is known for research contribution in the topics: Population & Stroke. The organization has 428 authors who have published 1387 publications receiving 181920 citations.

A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography

Abstract: BACKGROUND Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). However, inflammation is not the only process involved in atherogenesis and we hypothesized that additional radiomic signatures of adverse fibrotic and microvascular PVAT remodelling, may further improve cardiac risk prediction. METHODS AND RESULTS We present a new artificial intelligence-powered method to predict cardiac risk by analysing the radiomic profile of coronary PVAT, developed and validated in patient cohorts acquired in three different studies. In Study 1, adipose tissue biopsies were obtained from 167 patients undergoing cardiac surgery, and the expression of genes representing inflammation, fibrosis and vascularity was linked with the radiomic features extracted from tissue CT images. Adipose tissue wavelet-transformed mean attenuation (captured by FAI) was the most sensitive radiomic feature in describing tissue inflammation (TNFA expression), while features of radiomic texture were related to adipose tissue fibrosis (COL1A1 expression) and vascularity (CD31 expression). In Study 2, we analysed 1391 coronary PVAT radiomic features in 101 patients who experienced major adverse cardiac events (MACE) within 5 years of having a CCTA and 101 matched controls, training and validating a machine learning (random forest) algorithm (fat radiomic profile, FRP) to discriminate cases from controls (C-statistic 0.77 [95%CI: 0.62-0.93] in the external validation set). The coronary FRP signature was then tested in 1575 consecutive eligible participants in the SCOT-HEART trial, where it significantly improved MACE prediction beyond traditional risk stratification that included risk factors, coronary calcium score, coronary stenosis, and high-risk plaque features on CCTA (Δ[C-statistic] = 0.126, P < 0.001). In Study 3, FRP was significantly higher in 44 patients presenting with acute myocardial infarction compared with 44 matched controls, but unlike FAI, remained unchanged 6 months after the index event, confirming that FRP detects persistent PVAT changes not captured by FAI. CONCLUSION The CCTA-based radiomic profiling of coronary artery PVAT detects perivascular structural remodelling associated with coronary artery disease, beyond inflammation. A new artificial intelligence (AI)-powered imaging biomarker (FRP) leads to a striking improvement of cardiac risk prediction over and above the current state-of-the-art.

Analyses of cancer data from three ezetimibe trials.

Abstract: Background Five years of statin therapy lowers low-density lipoprotein (LDL) cholesterol substantially and, over a 5-year period, results in reductions in the incidence of cardiovascular events. The Simvastatin and Ezetimibe in Aortic Stenosis (SEAS) trial (ClinicalTrials.gov number, NCT00092677) has raised the hypothesis that adding ezetimibe to statin therapy for larger LDL cholesterol reductions might increase the incidence of cancer. Methods We compared the results of a hypothesis-generating analysis of the incidence of cancer in the SEAS trial of ezetimibe plus simvastatin in 1873 patients (mean followup after ezetimibe or matching placebo was begun, 4.1 years) with a hypothesistesting analysis of cancer data from the two large ongoing trials of this regimen: the Study of Heart and Renal Protection (SHARP) (NCT00125593) with 9264 patients (mean follow-up, 2.7 years) and the Improved Reduction of Outcomes: Vytorin Efficacy International Trial (IMPROVE-IT) (NCT00202878), currently with 11,353 patients (mean follow-up, 1.0 year). Results In the SEAS trial, assignment to ezetimibe was associated with an increase in any new onset of cancer (101 patients in the active-treatment group vs. 65 in the control group) from several cancer sites. In SHARP and IMPROVE-IT combined, there was no overall excess of cancer (313 active-treatment vs. 326 control; risk ratio, 0.96; 95% confidence interval, 0.82 to 1.12; P = 0.61) and no significant excess at any particular site. Among patients assigned to ezetimibe, there were more, albeit not significantly more, deaths from cancer (97, vs. 72 in the control group; P = 0.07), but there were also fewer, although not significantly fewer, other cases of cancer (216, vs. 254 in the control group; P = 0.08). There was no evidence of a trend in the risk ratio for incidence of or death from cancer with increasing duration of follow-up. Conclusions The available results from these three trials do not provide credible evidence of any adverse effect of ezetimibe on rates of cancer. Follow-up of longer duration will permit the balance of risks and benefits to be determined more reliably.