Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine

Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional "pre-pre-" and "post-post-" analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.11Ysciescopu

Processing of Electronic Health Records using Deep Learning: A review

Availability of large amount of clinical data is opening up new research avenues in a number of fields. An exciting field in this respect is healthcare, where secondary use of healthcare data is beginning to revolutionize healthcare. Except for availability of Big Data, both medical data from healthcare institutions (such as EMR data) and data generated from health and wellbeing devices (such as personal trackers), a significant contribution to this trend is also being made by recent advances on machine learning, specifically deep learning algorithms

Cardio-oncology: concepts and practice

Substantial progress in cancer therapy increasingly allows higher cure rates, and even advanced disease can be stabilized, allowing improved survival with quality of life for months to years, meaning comorbid diseases are a growing determinant of outcome. Cardiovascular events substantially contribute to long-term morbidity and mortality in people living with or surviving cancer. In recognition of this, the subspecialty of cardio-oncology has emerged, and aims to promote cardiovascular heath, whilst facilitating the most effective cancer therapy. This review describes the concept of cardio-oncology, and illustrates the role played by a specialist team in improving outcomes, using heart failure secondary to breast cancer treatment as an example. We aim to highlight pivotal original research and comprehensive summaries of the most relevant topics, providing an overview for cardiologists and oncologists about this increasingly important medical problem

EPMA position paper in cancer:current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision

Child-related characteristics predicting subsequent health-related quality of life in 8- to 14-year-old children with and without cerebellar tumors: a prospective longitudinal study

BackgroundWe identified child-related determinants of health-related quality of life (HRQoL) in children aged 8–14 years who were treated for 2 common types of pediatric brain tumors. MethodsQuestionnaire measures of HRQoL and psychometric assessments were completed by 110 children on 3 occasions over 24 months. Of these 110, 72 were within 3 years of diagnosis of a cerebellar tumor (37 standard-risk medulloblastoma, 35 low-grade cerebellar astrocytoma), and 38 were in a nontumor group. HRQoL, executive function, health status, and behavioral difficulties were also assessed by parents and teachers as appropriate. Regression modeling was used to relate HRQoL z scores to age, sex, socioeconomic status, and 5 domains of functioning: Cognition, Emotion, Social, Motor and Sensory, and Behavior. ResultsHRQoL z scores were significantly lower after astrocytoma than those in the nontumor group and significantly lower again in the medulloblastoma group, both by self-report and by parent-report. In regression modeling, significant child-related predictors of poorer HRQoL z scores by self-report were poorer cognitive and emotional function (both z scores) and greater age (years) at enrollment (B = 0.038, 0.098, 0.136, respectively). By parent-report, poorer cognitive, emotional and motor or sensory function (z score) were predictive of lower subsequent HRQoL of the child (B = 0.043, 0.112, 0.019, respectively), while age at enrollment was not. ConclusionsEarly screening of cognitive and emotional function in this age group, which are potentially amenable to change, could identify those at risk of poor HRQoL and provide a rational basis for interventions to improve HRQoL

Clinical applications of personalized medicine: a new paradigm and challenge

The personalized medicine is an emergent and rapidly developing method of clinical practice that uses new technologies to provide decisions in regard to the prediction, prevention, diagnosis and treatment of disease. The continue evolution of technology and the developments in molecular diagnostics and genomic analysis increased the possibility of an even more understanding and interpretation of the human genome and exome, allowing a "personalized" approach to clinical care, so that the concepts of "Systems Medicine" and "System Biology" are increasingly actual. The purpose of this study is to evaluate the personalized medicine about its indications and benefits, actual clinical applications and future perspectives as well as its issues and health care implications. It was made a careful review of the scientific literature on this field that highlighted the applicability and usefulness of this new medical approach as well as the fact that personalized medicine strategy is even more increasing in numerous fields of applications