Relation Between Platelet Response to Exercise and Coronary Angiographic Findings in Patients With Effort Angina

Background— Platelet reactivity is increased by exercise in patients with obstructive coronary artery disease (CAD) but not in patients with syndrome X. In this study, we prospectively investigated whether the platelet response to exercise might help distinguish, among patients with angina, those with obstructive CAD from those with normal coronary arteries (NCAs). Methods and Results— Venous blood samples were collected before and 5 minutes after exercise from 194 consecutive patients with stable angina. Platelet reactivity was measured by the platelet function analyzer (PFA)-100 system as the time for flowing whole blood to occlude a collagen-adenosine diphosphate ring (closure time). Coronary angiography showed CAD in 163 patients (84%) and NCA in 31 patients (16%). Baseline closure time was shorter in NCA patients (78.0±16 versus 95.5±23 seconds, P <0.0001). With exercise, closure time decreased in CAD patients (−15.5 seconds; 95% confidence limits [CL], −13.0 to −18.0 seconds; P <0.0001), but increased in NCA patients (12.5 seconds; 95% CL, 7.4 to 17.7 seconds; P =0.0004). An increase in closure time with exercise ≥10 seconds had 100% specificity and positive predictive value for NCAs. Similarly, a decrease ≥10 seconds had 100% specificity and positive predictive value for CAD. A closure time change (increase or decrease) ≥10 seconds allowed a correct classification of 55% of all patients. Conclusions— Among patients with stable angina, the response of platelet reactivity to exercise was predictive of normal or stenosed coronary arteries at angiography. Specifically, an increase in closure time with exercise ≥10 seconds was invariably associated with the presence of NCA

P495: UNLOCKING THE POTENTIAL OF SYNTHETIC PATIENTS FOR ACCELERATING CLINICAL TRIALS: RESULTS OF THE FIRST GIMEMA EXPERIENCE

Background: Artificial intelligence is contributing to improve different medicine areas including clinical trial design. One field that holds a great potential is represented by the use of digital data as an alternative to real ones. The generation of a virtual cohort of patients might be advantageous since an artificial group of patients resembles the real dataset in all the key features but it does not include any identifiable real-patient data, tackling - by a privacy standpoint – the “burden” of collecting data subjects’ consent as well as the shortcomings of common anonymization techniques. Aims: To test the feasibility of this approach and evaluate its potential in clinical trial design, we built an in-silico cohort based on the large dataset of patients enrolled in the GIMEMA AML1310 study (Venditti et al. 2019), which entailed a “3 + 7”-like induction and a risk-adapted, MRD-directed post-remission transplant allocation. Methods: To create the synthetic cohort of patients, a machine learning generative model was constructed from the real individual-level data of the AML1310 study, capturing its patterns and statistical properties. AML1310 enrolled 500 patients (median age 49 years old) in 55 GIMEMA Institutions. All patients were NCCN2009 risk classified and analyzed by morphology, cytogenetics, molecular biology and multiparametric flow cytometry. The subset of 445 patients with ELN2017 risk classification available was used. To this purpose, the R package “synthpop” was used considering a parametric method: for binary data the logistic regression, for a factor with &gt; 2 levels the polytomous logistic regression, for an ordered factor with &gt; 2 levels the ordered polytomous logistic regression. For time to event variables the classification and regression trees method was used. Next, we verified the adherence of the virtual cohort to the original one in terms of age, gender, PS, WBC count, FLT3 and NPM1 mutations, risk category, CR achievement, MRD, transplant rate. Virtual and real cohorts were also compared in terms of survival outcomes. Results: By using the real-patient dataset from the AML1310 trial, a virtual cohort of 850 patients, named synthAML1310, was generated. By comparing the two cohorts, we observed that the clinico-biological characteristics and response evaluations (CR and MRD rates) did not differ significantly. Moreover, as depicted in Figure 1, the curves of OS and DFS were superimposable. Indeed, at 2 years, OS was 57% (52.5%-61.9%) in the original and 59.1% (55.9%-62.6%) in the synthAML1310 cohort. DFS was 55.1% (49.8%-60.9%) in the original and 55.1% (51.3%-59.2%) in the synthetic cohort. Summary/Conclusion: These results demonstrate the success of this approach in producing a virtual dataset that perfectly mimics the original and that, from a “privacy by design” perspective, minimizes the risk of re-identification of patients. Mirroring an AML population treated with a conventional chemotherapeutic approach, synthAML1310 is suitable to represent the control group when testing novel innovative treatments, most likely in an in-silico randomized trial, but also in other settings like propensity score matching analyses in observational studies. Shifting to an in-silico trial would overcome the challenges of randomized trials and it would be beneficial also for patients. since, they would receive only the experimental treatment without being exposed to the “less active“ therapy, thus limiting treatment failures and toxicity. Also, enrolment and the attainment of final results would be faster

Electronic Cigarettes and Cardiovascular Risk: Caution Waiting for Evidence

Electronic cigarettes use is a growing trend in contemporary societies, with the propensity to compete with traditional tobacco smoking. Some preclinical studies demonstrated the toxic and detrimental effects of electronic cigarettes liquid components. Its impact on human health remains unknown and insufficiently studied. While some studies suggest that electronic cigarettes use might be associated with endothelial dysfunction, impaired platelet function and increased risk of adverse clinical events, other studies did not confirm these findings and epidemiological data mostly suggest that the use of electronic cigarettes appears to be safer than that of traditional tobacco cigarettes. This article provides an up-to-date overview of the current state of knowledge regarding electronic cigarettes and their impact on human health, with special emphasis on their effect on cardiovascular diseases

Relationship between coronary plaque morphology of the left anterior descending artery and 12 months clinical outcome: the CLIMA study

Abstract Aims The CLIMA study, on the relationship between coronary plaque morphology of the left anterior descending artery and twelve months clinical outcome, was designed to explore the predictive value of multiple high-risk plaque features in the same coronary lesion [minimum lumen area (MLA), fibrous cap thickness (FCT), lipid arc circumferential extension, and presence of optical coherence tomography (OCT)-defined macrophages] as detected by OCT. Composite of cardiac death and target segment myocardial infarction was the primary clinical endpoint. Methods and results From January 2013 to December 2016, 1003 patients undergoing OCT evaluation of the untreated proximal left anterior descending coronary artery in the context of clinically indicated coronary angiogram were prospectively enrolled at 11 independent centres (clinicaltrial.gov identifier NCT02883088). At 1-year, the primary clinical endpoint was observed in 37 patients (3.7%). In a total of 1776 lipid plaques, presence of MLA 180° (HR 2.4, 95% CI 1.2–4.8), and OCT-defined macrophages (HR 2.7, 95% CI 1.2–6.1) were all associated with increased risk of the primary endpoint. The pre-specified combination of plaque features (simultaneous presence of the four OCT criteria in the same plaque) was observed in 18.9% of patients experiencing the primary endpoint and was an independent predictor of events (HR 7.54, 95% CI 3.1–18.6). Conclusion The simultaneous presence of four high-risk OCT plaque features was found to be associated with a higher risk of major coronary events

Epigenetics and chemoresistance in colorectal cancer: an opportunity for treatment tailoring and novel therapeutic strategies

Colorectal cancer is the second leading cause of cancer-related deaths in the world. Despite many therapeutic opportunities, prognosis remains dismal for patients with metastatic disease, and a significant portion of early-stage patients develop recurrence after chemotherapy. Epigenetic gene regulation is a major mechanism of cancer initiation and progression, through the inactivation of several tumor suppressor genes. Emerging evidence indicates that epigenetics may also play a key role in the development of chemoresistance. In the present review, we summarize epigenetic mechanisms triggering resistance to three commonly used agents in colorectal cancer: 5-fluorouracil, irinotecan and oxaliplatin. Those epigenetic biomarkers may help stratify colorectal cancer patients and develop a tailored therapeutic approach. In addition, epigenetic modifications are reversible through specific drugs: histone-deacetylase and DNA-methyl-transferase inhibitors. Preclinical studies suggest that these drugs may reverse chemoresistance in colorectal tumors. In conclusion, an epigenetic approach to colorectal cancer chemoresistance may pave the way to personalized treatment and to innovative therapeutic strategies