Large-scale real-life analysis of survival and usage of therapies in multiple myeloma.

Survival in multiple myeloma has improved significantly in recent years, especially in young patients. We reviewed the evolution of the survival of patients with MM in three groups based on age at MM diagnosis over three time periods between 1999 and 2020 at our 12 de Octubre Hospital institution (H12O). Then, to confirm our results, we used data from TriNetx, a global health research platform that includes patients from Europe to US. Finally, we analysed differences in the patterns of treatment between networks across the world. Kaplan‒Meier analysis was used to estimate survival probabilities, and between-group differences were tested using the log-rank test and hazard ratio. For patients from H12O, the median OS was 35.61, 55.59 and 68.67 months for the 1999-2009, 2010-2014 and 2015-2020 cohorts, respectively (p = 0.0001). Among all patients included in the EMEA network, the median OS was 20.32 months versus 34.75 months from 1999-2009 versus 2010-2014. The median OS from the 2010-2014 versus 2015-2020 time cohorts was 34.75 months versus 54.43 months, respectively. In relation to the US cohort, the median OS from before 2010 versus 2010-2014 was not reached in either time cohort and neither when comparing the 2010-2014 versus 2015-2019 time cohorts. Bortezomib is the most commonly used drug in the EMEA cohort, while lenalidomide is the most commonly used drug in the US cohort. This large-scale study based on real-world data confirms the previous finding that MM patients have increased their survival in the last two decades.

Impact of COVID-19 in patients with multiple myeloma based on a global data network.

The COVID-19 pandemic has represented a major cause of morbidity/mortality worldwide, overstressing health systems. Multiple myeloma (MM) patients show an increased risk for infections and they are expected to be particularly vulnerable to SARS-CoV-2 infection. Here we have obtained a comprehensive picture of the impact of COVID-19 in MM patients on a local and a global scale using a federated data research network (TriNetX) that provided access to Electronic Medical Records (EMR) from Health Care Organizations (HCO) all over the world. Through propensity score matched analyses we found that the number of new diagnoses of MM was reduced in 2020 compared to 2019 (RR 0.86, 95%CI 0.76-0.96) and the survival of newly diagnosed MM cases decreased similarly (HR 0.61, 0.38-0.81). MM patients showed higher risk of SARS-CoV-2 infection (RR 2.09, 1.58-2.76) and a higher excess mortality in 2020 (difference in excess mortality 9%, 4.4-13.2) than non-MM patients. By interrogating large EMR datasets from HCO in Europe and globally, we confirmed that MM patients have been more severely impacted by COVID-19 pandemic than non-MM patients. This study highlights the necessity of extending preventive measures worlwide to protect vulnerable patients from SARS-CoV-2 infection by promoting social distancing and an intensive vaccination strategies.

Mapping clinical procedures to the ICD-10-PCS: The German operation and procedure classification system use case.

Mappings among terminologies to ensure homogeneous analysis among different data sources is one of the key challenges of semantic interoperability. Concretely, mappings to the International Classification of Diseases 10th Revision Procedure Classification System (ICD-10-PCS) are especially challenging due to its multiaxial structure and lack of terms used by physicians (many terminologies used in real world data (RWD) are initially intended for reimbursement, not for clinical purposes). In this work, we propose a new theoretical methodology for mapping healthcare data to the ICD-10-PCS by exploiting its multiaxial structure to reduce the search spaces within concepts and leveraging the dependencies between axes for inferring additional relevant information. We tested this methodology with a subset of the German Operation and Procedure Classification System (OPS), aiming to integrate heterogeneous data sources queried for clinical research.

ICD-10-CM extension with ICD-9 diagnosis codes to support integrated access to clinical legacy data.

INTRODUCTION: ICD is currently the most widely used terminology to code diagnosis and procedures. The transition from ICD-9-CM to ICD-10-CM became effective on October 1, 2015 in US and many other countries. Projects that use this codification for research purposes, requires advanced methods to exploit data with both versions of ICD. Although the General Equivalence Mappings (GEMs), provided by the Centers for Medicare and Medicaid Services, might help to overcome these challenges, their direct use as translation mappings is not possible, mostly due to the further specificity of ICD-10-CM concepts. OBJECTIVE: We propose a methodology to generate an extended version of ICD-10-CM with selected ICD-9-CM diagnosis codes. METHODS: The extension was generated using the GEMs relations between concepts of both terminologies and the hierarchical relations of ICD-10-CM. RESULTS: This extended ICD-10-CM, together with modifications to the mapping of ICD-9-CM concepts that were not inserted, allows the generation of an improved translation of legacy data, raising the number of 1-to-1 correspondences by +13.81%. CONCLUSION: The extended ICD-10-CM enables the accurate integration of ICD-9-CM and ICD-10-CM diagnosis data into a single terminology. With such analysis of data possible without having to specify both ICD-9-CM and ICD-10-CM separately for each query.

ICD-10-PCS extension with ICD-9 procedure codes to support integrated access to clinical legacy data.

Since the creation of The International Classification of Diseases (ICD), new versions have been released to keep updated with the current medical knowledge. Migrations of Electronic Health Records (EHR) from ICD-9 to ICD-10-PCS as clinical procedure codification system, has been a significant challenge and involved large resources. In addition, it created new barriers for integrated access to legacy medical procedure data (frequently ICD-9 coded) with current data (frequently ICD-10-PCS coded). This work proposes a solution based on extending ICD-10-PCS with a subgroup of ICD-9-CM concepts to facilitate such integrated access. The General Equivalence Mappings (GEMs) has been used as foundation to set the terminology relations of these inserted concepts in ICD-10-PCS hierarchy, but due to the existence of 1-to-many mappings, advanced rules are required to seamlessly integrate both terminologies. With the generation of rules based on GEMs relationships, 2014 ICD-9 concepts were included within the ICD-10-PCS hierarchy. For the rest of the concepts, a new method is also proposed to increase 1-to-1 mappings. As results, with the suggested approach, the percentage of ICD-9-CM procedure concepts that can be mapped accurately (avoiding mappings to a large number of concepts) rise from 11.56% to 69.01% of ICD-9-Proc, through the extended ICD-10-PCS hierarchy.

SNOMED2HL7: A tool to normalize and bind SNOMED CT concepts to the HL7 Reference Information Model.

BACKGROUND: Current clinical research and practice requires interoperability among systems in a complex and highly dynamic domain. There has been a significant effort in recent years to develop integrative common data models and domain terminologies. Such efforts have not completely solved the challenges associated with clinical data that are distributed among different and heterogeneous institutions with different systems to encode the information. Currently, when providing homogeneous interfaces to exploit clinical data, certain transformations still involve manual and time-consuming processes that could be automated. OBJECTIVES: There is a lack of tools to support data experts adopting clinical standards. This absence is especially significant when links between data model and vocabulary are required. The objective of this work is to present SNOMED2HL7, a novel tool to automatically link biomedical concepts from widely used terminologies, and the corresponding clinical context, to the HL7 Reference Information Model (RIM). METHODS: Based on the recommendations of the International Health Terminology Standards Development Organisation (IHTSDO), the SNOMED Normal Form has been implemented within SNOMED2HL7 to decompose and provide a method to reduce the number of options to store the same information. The binding of clinical terminologies to HL7 RIM components is the core of SNOMED2HL7, where terminology concepts have been annotated with the corresponding options within the interoperability standard. A web-based tool has been developed to automatically provide information from the normalization mechanisms and the terminology binding. RESULTS: SNOMED2HL7 binding coverage includes the majority of the concepts used to annotate legacy systems. It follows HL7 recommendations to solve binding overlaps and provides the binding of the normalized version of the concepts. The first version of the tool, available at http://kandel.dia.fi.upm.es:8078, has been validated in EU funded projects to integrate real world data for clinical research with an 88.47% of accuracy. CONCLUSIONS: This paper presents the first initiative to automatically retrieve concept-centered information required to transform legacy data into widely adopted interoperability standards. Although additional functionality will extend capabilities to automate data transformations, SNOMED2HL7 already provides the functionality required for the clinical interoperability community.

Nanoinformatics: developing new computing applications for nanomedicine.

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended "nanotype" to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others.

Biomedical informatics publications: a global perspective. Part II: Journals.

BACKGROUND: Biomedical Informatics (BMI) is a broad discipline, having evolved from both Medical Informatics (MI) and Bioinformatics (BI). An analysis of publications in the fieldshould provide an indication about the geographic distribution of BMI research contributions and possible lessons for the future, both for research and professional practice. OBJECTIVES: In part I of our analysis of biomedical informatics publications we presented results from BMI conferences. In this second part, we analyse BMI journals, which provide a broader perspective and comparison between data from conferences and journals that ought to confirm or suggest alternatives to the original distributional findings from the conferences. METHODS: We manually collected data about authors and their geographical origin from various MI journals: the International Journal of Medical Informatics (IJMI), the Journal of Biomedical Informatics (JBI), Methods of In formation in Medicine (MIM) and The Journal of the American Medical Informatics Association (JAMIA). Focusing on first authors, we also compared these findings with data from the journal Bioinformatics. RESULTS: Our results confirm those obtained in our analysis of BMI conferences - that local and regional authors favor their corresponding MI journals just as they do their conferences. Consideration of other factors, such as the increasingly open source nature of data and software tools, is consistent with these findings. CONCLUSIONS: Our analysis suggests various indicators that could lead to further, deeper analyses, and could provide additional insights for future BMI research and professional activities.

Biomedical informatics publications: a global perspective: part I: conferences.

BACKGROUND: In the past decade, Medical Informatics (MI) and Bioinformatics (BI) have converged towards a new discipline, called Biomedical Informatics (BMI) bridging informatics methods across the spectrum from genomic research to personalized medicine and global healthcare. This convergence still raises challenging research questions which are being addressed by researchers internationally, which in turn raises the question of how biomedical informatics publications reflect the contributions from around the world in documenting the research. OBJECTIVES: To analyse the worldwide participation of biomedical informatics researchers from professional groups and societies in the best-known scientific conferences in the field. The analysis is focused on their geographical affiliation, but also includes other features, such as the impact and recognition of the conferences. METHODS: We manually collected data about authors of papers presented at three major MI conferences: Medinfo, MIE and the AMIA symposium. In addition, we collected data from a BI conference, ISMB, as a comparison. Finally, we analyzed the impact and recognition of these conferences within their scientific contexts. RESULTS: Data indicate a predominance of local authors at the regional conferences (AMIA and MIE), whereas other conferences with a world-wide scope (Medinfo and ISMB) had broader participation. Our analysis shows that the influence of these conferences beyond the discipline remains somewhat limited. CONCLUSIONS: Our results suggest that for BMI to be recognized as a broad discipline, both in the geographical and scientific sense, it will need to extend the scope of collaborations and their interdisciplinary impacts worldwide.

Biomedical ontologies: toward scientific debate.

OBJECTIVES: Biomedical ontologies have been very successful in structuring knowledge for many different applications, receiving widespread praise for their utility and potential. Yet, the role of computational ontologies in scientific research, as opposed to knowledge management applications, has not been extensively discussed. We aim to stimulate further discussion on the advantages and challenges presented by biomedical ontologies from a scientific perspective. METHODS: We review various aspects of biomedical ontologies going beyond their practical successes, and focus on some key scientific questions in two ways. First, we analyze and discuss current approaches to improve biomedical ontologies that are based largely on classical, Aristotelian ontological models of reality. Second, we raise various open questions about biomedical ontologies that require further research, analyzing in more detail those related to visual reasoning and spatial ontologies. RESULTS: We outline significant scientific issues that biomedical ontologies should consider, beyond current efforts of building practical consensus between them. For spatial ontologies, we suggest an approach for building "morphospatial" taxonomies, as an example that could stimulate research on fundamental open issues for biomedical ontologies. CONCLUSIONS: Analysis of a large number of problems with biomedical ontologies suggests that the field is very much open to alternative interpretations of current work, and in need of scientific debate and discussion that can lead to new ideas and research directions.

An agent- and ontology-based system for integrating public gene, protein, and disease databases.

In this paper, we describe OntoFusion, a database integration system. This system has been designed to provide unified access to multiple, heterogeneous biological and medical data sources that are publicly available over Internet. Many of these databases do not offer a direct connection, and inquiries must be made via Web forms, returning results as HTML pages. A special module in the OntoFusion system is needed to integrate these public 'Web-based' databases. Domain ontologies are used to do this and provide database mapping and unification. We have used the system to integrate seven significant and widely used public biomedical databases: OMIM, PubMed, Enzyme, Prosite and Prosite documentation, PDB, SNP, and InterPro. A case study is detailed in depth, showing system performance. We analyze the system's architecture and methods and discuss its use as a tool for biomedical researchers.

Designing new methodologies for integrating biomedical information in clinical trials.

OBJECTIVES: To propose a modification to current methodologies for clinical trials, improving data collection and cost-efficiency. To describe a system to integrate distributed and heterogeneous medical and genetic databases for improving information access, retrieval and analysis of biomedical information. METHODS: Data for clinical trials can be collected from remote, distributed and heterogeneous data sources. In this distributed scenario, we propose an ontologybased approach, with two basic operations: mapping and unification. Mapping outputs the semantic model of a virtual repository with the information model of a specific database. Unification provides a single schema for two or more previously available virtual repositories. In both processes, domain ontologies can improve other traditional approaches. RESULTS: Private clinical databases and public genomic and disease databases (e.g., OMIM, Prosite and others) were integrated. We successfully tested the system using thirteen databases containing clinical and biological information and biomedical vocabularies. CONCLUSIONS: We present a domain-independent approach to biomedical database integration, used in this paper as a reference for the design of future models of clinico-genomic trials where information will be integrated, retrieved and analyzed. Such an approach to biomedical data integration has been one of the goals of the IST INFOBIOMED Network of Excellence in Biomedical Informatics, funded by the European Commission, and the new ACGT (Advanced Clinico-Genomic Trials on Cancer) project, where the authors will apply these methods to research experiments.

ONTOFUSION: ontology-based integration of genomic and clinical databases.

ONTOFUSION is an ontology-based system designed for biomedical database integration. It is based on two processes: mapping and unification. Mapping is a semi-automated process that uses ontologies to link a database schema with a conceptual framework-named virtual schema. There are three methodologies for creating virtual schemas, according to the origin of the domain ontology used: (1) top-down--e.g. using an existing ontology, such as the UMLS or Gene Ontology--, (2) bottom-up--building a new domain ontology-- and (3) a hybrid combination. Unification is an automated process for integrating ontologies and hence the database to which they are linked. Using these methods, we employed ONTOFUSION to integrate a large number of public genomic and clinical databases, as well as biomedical ontologies.