I2ECR: Integrated and Intelligent Environment for Clinical Research

Clinical trials are designed to produce new knowledge about a certain disease, drug or treatment. During these studies, a huge amount of data is collected about participants, therapies, clinical procedures, outcomes, adverse events and so on. A multicenter, randomized, phase III clinical trial in Hematology enrolls up to hundreds of subjects and evaluates post-treatment outcomes on stratified sub- groups of subjects for a period of many years. Therefore, data collection in clinical trials is becoming complex, with huge amount of clinical and biological variables. Outside the medical field, data warehouses (DWs) are widely employed. A Data Ware-house is a “collection of integrated, subject-oriented databases designed to support the decision-making process”. To verify whether DWs might be useful for data quality and association analysis, a team of biomedical engineers, clinicians, biologists and statisticians developed the “I2ECR” project. I2ECR is an Integrated and Intelligent Environment for Clinical Research where clinical and omics data stand together for clinical use (reporting) and for generation of new clinical knowledge. I2ECR has been built from the “MCL0208” phase III, prospective, clinical trial, sponsored by the Fondazione Italiana Linfomi (FIL); this is actually a translational study, accounting for many clinical data, along with several clinical prognostic indexes (e.g. MIPI - Mantle International Prognostic Index), pathological information, treatment and outcome data, biological assessments of disease (MRD - Minimal Residue Disease), as well as many biological, ancillary studies, such as Mutational Analysis, Gene Expression Profiling (GEP) and Pharmacogenomics. In this trial forty-eight Italian medical centers were actively involved, for a total of 300 enrolled subjects. Therefore, I2ECR main objectives are: • to propose an integration project on clinical and molecular data quality concepts. The application of a clear row-data analysis as well as clinical trial monitoring strategies to implement a digital platform where clinical, biological and “omics” data are imported from different sources and well-integrated in a data- ware-house • to be a dynamic repository of data congruency quality rules. I2ECR allows to monitor, in a semi-automatic manner, the quality of data, in relation to the clinical data imported from eCRFs (electronic Case Report Forms) and from biologic and mutational datasets internally edited by local laboratories. Therefore, I2ECR will be able to detect missing data and mistakes derived from non-conventional data- entry activities by centers. • to provide to clinical stake-holders a platform from where they can easily design statistical and data mining analysis. The term Data Mining (DM) identifies a set of tools to searching for hidden patterns of interest in large and multivariate datasets. The applications of DM techniques in the medical field range from outcome prediction and patient classification to genomic medicine and molecular biology. I2ECR allows to clinical stake-holders to propose innovative methods of supervised and unsupervised feature extraction, data classification and statistical analysis on heterogeneous datasets associated to the MCL0208 clinical trial. Although MCL0208 study is the first example of data-population of I2ECR, the environment will be able to import data from clinical studies designed for other onco-hematologic diseases, too

Non-invasive tool to assess heart rhythm in Zebrafish embryos

In the last years the zebrafish (Danio rerio) has emerged as model organism for cardiac research, in spite of the morphological differences with the human heart. In consequence of the similarity to humans in the early function, the zebrafish embryo has been suggested as an ideal model i) to study the molecular mechanism of cardiac development, and ii) to identify genes related to congenital cardiac defects in human [1]. The overall similarity of zebrafish embryos and human, in responses to human cardiotoxic drugs, was demonstrated, for example, in drug-induced cardiac arrhythmia [2]. For this reason, several methods have been developed to assess cardiac functions in zebrafish embryos [3,4]. Unfortunately, all these techniques suffer from drawbacks (time consuming, skillful operator are ended to perform the experiments) which limit their applications for large scale studies. The development in digital imaging has recently made analysis of cardiac functions in genetically modified transparent zebrafish embryos easier. This allowed to assess non-invasively heart rate variability in zebrafish embryos from videos of beating heart, but without measuring heartbeat rhythm, an important indicator of the cardiac function (heartbeat regularity is associated with cardiotoxicity in humans [1]), from power spectrum of heart signal. In the present study, we present a simple, non-invasive method that, by video-recording embryo images using confocal microscopy, and integrating image processing and power spectral analysis, allows to measure the heartbeat rhythm in zebrafish embryos heart chambers (atrium, ventricle, bulb) (Figure 1). The reliability of the herein proposed method was verified. Some embryos undergone treatment by tricaine, a cardiac anaesthetizing drug, in consequence of which a decrease of the heart rate is expected: the heartbeat regularity in tricaine- treated embryos determined from power spectral analysis decreased as compared to no-treated embryos. The results demonstrated that our method is able to assess the cardiac physiology, in term of heart rhythm, in zebrafish embryos

Primary, Bilateral and Diffuse Renal Non-Hodgkin's Lymphoma in a Young Woman Suffering from Turner Syndrome

Primary renal lymphoma (PRL) is a rare form of non-Hodgkin's lymphoma (NHL) restricted to and primarily involving one or both kidneys, with no lymph node extension. It accounts for <1% of extranodal lymphomas, and descriptions in the literature are limited. Here, we describe an unprecedented case of bilateral PRL in a 44-year-old woman with Turner syndrome and discuss both diagnostic and therapeutic issues in the light of the available literature in the field. A personalized approach to this rare disease is necessary

Applying Data Warehousing to a Phase III Clinical Trial From the Fondazione Italiana Linfomi Ensures Superior Data Quality and Improved Assessment of Clinical Outcomes

Data collection in clinical trials is becoming complex, with a huge number of variables that need to be recorded, verified, and analyzed to effectively measure clinical outcomes. In this study, we used data warehouse (DW) concepts to achieve this goal. A DW was developed to accommodate data from a large clinical trial, including all the characteristics collected. We present the results related to baseline variables with the following objectives: developing a data quality (DQ) control strategy and improving outcome analysis according to the clinical trial primary end points

Punctual and kinetic MRD analysis from the Fondazione Italiana Linfomi MCL0208 phase III trial in mantle cell lymphoma

Minimal residual disease (MRD) analysis is a known predictive tool in mantle cell lymphoma (MCL). We describe MRD results from the Fondazione Italiana Linfomi phase III MCL0208 prospective clinical trial assessing lenalidomide maintenance vs observation after autologous transplantation (ASCT), in the first prospective comprehensive analysis of different techniques, molecular markers, and tissues (peripheral blood, PB, and bone marrow, BM), taken at well-defined timepoints. Among the 300 patients enrolled, a molecular marker was identified in 250 (83%), allowing us to analyze 234 patients and 4351 analytical findings from 10 timepoints. ASCT induced high rates of molecular remission (91% in PB and 83% in BM, by quantitative real-time PCR [RQ-PCR]). Nevertheless, the number of patients with persistent clinical and molecular remission decreased over time in both arms (up to 30% after 36 months). MRD predicted early progression and long-term outcome, particularly from 6 months after ASCT (6-month TTP HR 3.83, p<0.001). In single-timepoint analysis, BM outperformed PB, and RQ-PCR was more reliable, while nested PCR appeared applicable to a larger number of patients (234 vs 176). To improve MRD performance we developed a time-varying kinetic model, based on regularly updated MRD results and the Mantle Cell Lymphoma International Prognostic Index, showing an area under the ROC curve (AUROC) of up to 0.87 using BM. Most notably, PB reached an AUROC of up to 0.81: with kinetic analysis it was comparable to BM in performance. MRD is a powerful predictor over the entire natural history of MCL and suitable for models with continuous adaptation of patient risk. Study can be found in EudraCT N. 2009-012807-25 https://eudract.ema.europa.eu/