Data Visualization Support for Tumor Boards and Clinical Oncology: Protocol for a Scoping Review.

BACKGROUND: Complex and expanding data sets in clinical oncology applications require flexible and interactive visualization of patient data to provide the maximum amount of information to physicians and other medical practitioners. Interdisciplinary tumor conferences in particular profit from customized tools to integrate, link, and visualize relevant data from all professions involved. OBJECTIVE: The scoping review proposed in this protocol aims to identify and present currently available data visualization tools for tumor boards and related areas. The objective of the review will be to provide not only an overview of digital tools currently used in tumor board settings, but also the data included, the respective visualization solutions, and their integration into hospital processes. METHODS: The planned scoping review process is based on the Arksey and O'Malley scoping study framework. The following electronic databases will be searched for articles published in English: PubMed, Web of Knowledge, and SCOPUS. Eligible articles will first undergo a deduplication step, followed by the screening of titles and abstracts. Second, a full-text screening will be used to reach the final decision about article selection. At least 2 reviewers will independently screen titles, abstracts, and full-text reports. Conflicting inclusion decisions will be resolved by a third reviewer. The remaining literature will be analyzed using a data extraction template proposed in this protocol. The template includes a variety of meta information as well as specific questions aiming to answer the research question: "What are the key features of data visualization solutions used in molecular and organ tumor boards, and how are these elements integrated and used within the clinical setting?" The findings will be compiled, charted, and presented as specified in the scoping study framework. Data for included tools may be supplemented with additional manual literature searches. The entire review process will be documented in alignment with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) flowchart. RESULTS: The results of this scoping review will be reported per the expanded PRISMA-ScR guidelines. A preliminary search using PubMed, Web of Knowledge, and Scopus resulted in 1320 articles after deduplication that will be included in the further review process. We expect the results to be published during the second quarter of 2024. CONCLUSIONS: Visualization is a key process in leveraging a data set's potentially available information and enabling its use in an interdisciplinary setting. The scoping review described in this protocol aims to present the status quo of visualization solutions for tumor board and clinical oncology applications and their integration into hospital processes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53627.

Extending cBioPortal for Therapy Recommendation Documentation in Molecular Tumor Boards: Development and Usability Study.

BACKGROUND: In molecular tumor boards (MTBs), patients with rare or advanced cancers are discussed by a multidisciplinary team of health care professionals. Software support for MTBs is lacking; in particular, tools for preparing and documenting MTB therapy recommendations need to be developed. OBJECTIVE: We aimed to implement an extension to cBioPortal to provide a tool for the documentation of therapy recommendations from MTB sessions in a secure and standardized manner. The developed extension should be embedded in the patient view of cBioPortal to enable easy documentation during MTB sessions. The resulting architecture for storing therapy recommendations should be integrable into various hospital information systems. METHODS: On the basis of a requirements analysis and technology analysis for authentication techniques, a prototype was developed and iteratively refined through a user-centered development process. In conclusion, the tool was evaluated via a usability evaluation, including interviews, structured questionnaires, and the System Usability Scale. RESULTS: The patient view of cBioPortal was extended with a new tab that enables users to document MTB sessions and therapy recommendations. The role-based access control was expanded to allow for a finer distinction among the rights to view, edit, and delete data. The usability evaluation showed overall good usability and a System Usability Scale score of 83.57. CONCLUSIONS: This study demonstrates how cBioPortal can be extended to not only visualize MTB patient data but also be used as a documentation platform for therapy recommendations.

MIRACUM-Pipe: An Adaptable Pipeline for Next-Generation Sequencing Analysis, Reporting, and Visualization for Clinical Decision Making.

(1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge of both bioinformatics and oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses and annotation of NGS data including quality control, alignment, variant calling, copy number variation estimation, evaluation of complex biomarkers, and RNA fusion detection. (3) Results: MIRACUM-Pipe offers an easy-to-use, one-prompt standardized solution to analyze NGS data, including quality control, variant calling, copy number estimation, annotation, visualization, and report generation. (4) Conclusions: MIRACUM-Pipe, a versatile pipeline for NGS, can be customized according to bioinformatics and clinical needs and to support clinical decision-making with visual processing and interactive reporting.

Critical evaluation of molecular tumour board outcomes following 2 years of clinical practice in a Comprehensive Cancer Centre.

BACKGROUND: Recently, molecular tumour boards (MTBs) have been integrated into the clinical routine. Since their benefit remains debated, we assessed MTB outcomes in the Comprehensive Cancer Center Ostbayern (CCCO) from 2019 to 2021. METHODS AND RESULTS: In total, 251 patients were included. Targeted sequencing was performed with PCR MSI-evaluation and immunohistochemistry for PD-L1, Her2, and mismatch repair enzymes. 125 treatment recommendations were given (49.8%). High-recommendation rates were achieved for intrahepatic cholangiocarcinoma (20/30, 66.7%) and gastric adenocarcinoma (10/16, 62.5%) as opposed to colorectal cancer (9/36, 25.0%) and pancreatic cancer (3/18, 16.7%). MTB therapies were administered in 47 (18.7%) patients, while 53 (21.1%) received alternative treatment regimens. Thus 37.6% of recommended MTB therapies were implemented (47/125 recommendations). The clinical benefit rate (complete + partial + mixed response + stable disease) was 50.0% for MTB and 63.8% for alternative treatments. PFS2/1 ratios were 34.6% and 16.1%, respectively. Significantly improved PFS could be achieved for m1A-tier-evidence-based MTB therapies (median 6.30 months) compared to alternative treatments (median 2.83 months; P = 0.0278). CONCLUSION: The CCCO MTB yielded a considerable recommendation rate, particularly in cholangiocarcinoma patients. The discrepancy between the low-recommendation rates in colorectal and pancreatic cancer suggests the necessity of a weighted prioritisation of entities. High-tier recommendations should be implemented predominantly.

Searching of Clinical Trials Made Easier in cBioPortal Using Patients' Genetic and Clinical Profiles.

BACKGROUND: Molecular tumor boards (MTBs) cope with the complexity of an increased usage of genome sequencing data in cancer treatment. As for most of these patients, guideline-based therapy options are exhausted, finding matching clinical trials is crucial. This search process is often performed manually and therefore time consuming and complex due to the heterogeneous and challenging dataset. OBJECTIVES: In this study, a prototype for a search tool was developed to demonstrate how cBioPortal as a clinical and genomic patient data source can be integrated with ClinicalTrials.gov, a database of clinical studies to simplify the search for trials based on genetic and clinical data of a patient. The design of this tool should rest on the specific needs of MTB participants and the architecture of the integration should be as lightweight as possible and should not require manual curation of trial data in advance with the goal of quickly and easily finding a matching study. METHODS: Based on a requirements analysis, interviewing MTB experts, a prototype was developed. It was further refined using a user-centered development process with multiple feedback loops. Finally, the usability of the application was evaluated with user interviews including the thinking-aloud protocol and the system usability scale (SUS) questionnaire. RESULTS: The integration of ClinicalTrials.gov in cBioPortal is achieved by a new tab in the patient view where the genomic profile for the search is prefilled and additional parameters can be adjusted. These parameters are then used to query the application programming interface (API) of ClinicalTrials.gov. The returned search results subsequently are ranked and presented to the user. The evaluation of the application resulted in an SUS score of 83.5. CONCLUSION: This work demonstrates the integration of cBioPortal with ClinicalTrials.gov to use clinical and genomic patient data to search for appropriate trials within an MTB.

cbpManager: a web application to streamline the integration of clinical and genomic data in cBioPortal to support the Molecular Tumor Board.

BACKGROUND: Extensive sequencing of tumor tissues has greatly improved our understanding of cancer biology over the past years. The integration of genomic and clinical data is increasingly used to select personalized therapies in dedicated tumor boards (Molecular Tumor Boards) or to identify patients for basket studies. Genomic alterations and clinical information can be stored, integrated and visualized in the open-access resource cBioPortal for Cancer Genomics. cBioPortal can be run as a local instance enabling storage and analysis of patient data in single institutions, in the respect of data privacy. However, uploading clinical input data and genetic aberrations requires the elaboration of multiple data files and specific data formats, which makes it difficult to integrate this system into clinical practice. To solve this problem, we developed cbpManager. RESULTS: cbpManager is an R package providing a web-based interactive graphical user interface intended to facilitate the maintenance of mutations data and clinical data, including patient and sample information, as well as timeline data. cbpManager enables a large spectrum of researchers and physicians, regardless of their informatics skills to intuitively create data files ready for upload in cBioPortal for Cancer Genomics on a daily basis or in batch. Due to its modular structure based on R Shiny, further data formats such as copy number and fusion data can be covered in future versions. Further, we provide cbpManager as a containerized solution, enabling a straightforward large-scale deployment in clinical systems and secure access in combination with ShinyProxy. cbpManager is freely available via the Bioconductor project at https://bioconductor.org/packages/cbpManager/ under the AGPL-3 license. It is already used at six University Hospitals in Germany (Mainz, Gießen, Lübeck, Halle, Freiburg, and Marburg). CONCLUSION: In summary, our package cbpManager is currently a unique software solution in the workflow with cBioPortal for Cancer Genomics, to assist the user in the interactive generation and management of study files suited for the later upload in cBioPortal.

Challenges and Experiences Extending the cBioPortal for Cancer Genomics to a Molecular Tumor Board Platform.

In Molecular Tumor Boards (MTBs), therapy recommendations for cancer patients are discussed. To aid decision-making based on the patient's molecular profile, the research platform cBioPortal was extended based on users' requirements. Additionally, a comprehensive dockerized workflow was developed to support the deployment of cBioPortal and connected services. In this work, we present the challenges and experiences of nearly two years of implementing and deploying an MTB platform based on cBioPortal and compare those to findings of a previous study.

FhirSpark - Implementing a Mediation Layer to Bring FHIR to the cBioPortal for Cancer Genomics.

cBioPortal is a commonly used data warehousing solution for genomic cancer studies. The software is being extended for patient care application in a molecular tumor board by the MIRACUM consortium within the Medical Informatics Initiative Germany. A key feature for this use case is the ability to enter therapy recommendations for individual patients, which requires interoperability with the hospital information system. A RESTful interface between cBioPortal and an external mediation layer was selected from the different implementation options. It achieves interoperability by using a FHIR capable server to store data and applying the HL7 FHIR Genomics Reporting implementation guide. For systems not supporting the FHIR standard, the well-established HL7 Version 2 standard is available as a fallback export format.

EHR-Independent Predictive Decision Support Architecture Based on OMOP.

BACKGROUND: The increasing availability of molecular and clinical data of cancer patients combined with novel machine learning techniques has the potential to enhance clinical decision support, example, for assessing a patient's relapse risk. While these prediction models often produce promising results, a deployment in clinical settings is rarely pursued. OBJECTIVES: In this study, we demonstrate how prediction tools can be integrated generically into a clinical setting and provide an exemplary use case for predicting relapse risk in melanoma patients. METHODS: To make the decision support architecture independent of the electronic health record (EHR) and transferable to different hospital environments, it was based on the widely used Observational Medical Outcomes Partnership (OMOP) common data model (CDM) rather than on a proprietary EHR data structure. The usability of our exemplary implementation was evaluated by means of conducting user interviews including the thinking-aloud protocol and the system usability scale (SUS) questionnaire. RESULTS: An extract-transform-load process was developed to extract relevant clinical and molecular data from their original sources and map them to OMOP. Further, the OMOP WebAPI was adapted to retrieve all data for a single patient and transfer them into the decision support Web application for enabling physicians to easily consult the prediction service including monitoring of transferred data. The evaluation of the application resulted in a SUS score of 86.7. CONCLUSION: This work proposes an EHR-independent means of integrating prediction models for deployment in clinical settings, utilizing the OMOP CDM. The usability evaluation revealed that the application is generally suitable for routine use while also illustrating small aspects for improvement.

Mapping the Entire Record-An Alternative Approach to Data Access from Medical Logic Modules.

OBJECTIVES: This study aimed to describe an alternative approach for accessing electronic medical records (EMRs) from clinical decision support (CDS) functions based on Arden Syntax Medical Logic Modules, which can be paraphrased as "map the entire record." METHODS: Based on an experimental Arden Syntax processor, we implemented a method to transform patient data from a commercial patient data management system (PDMS) to tree-structured documents termed CDS EMRs. They are encoded in a specific XML format that can be directly transformed to Arden Syntax data types by a mapper natively integrated into the processor. The internal structure of a CDS EMR reflects the tabbed view of an EMR in the graphical user interface of the PDMS. RESULTS: The study resulted in an architecture that provides CDS EMRs in the form of a network service. The approach enables uniform data access from all Medical Logic Modules and requires no mapping parameters except a case number. Measurements within a CDS EMR can be addressed with straightforward path expressions. The approach is in routine use at a German university hospital for more than 2 years. CONCLUSION: This practical approach facilitates the use of CDS functions in the clinical routine at our local hospital. It is transferrable to standard-compliant Arden Syntax processors with moderate effort. Its comprehensibility can also facilitate teaching and development. Moreover, it may lower the entry barrier for the application of the Arden Syntax standard and could therefore promote its dissemination.

Requirements Analysis and Specification for a Molecular Tumor Board Platform Based on cBioPortal.

Clinicians in molecular tumor boards (MTB) are confronted with a growing amount of genetic high-throughput sequencing data. Today, at German university hospitals, these data are usually handled in complex spreadsheets from which clinicians have to obtain the necessary information. The aim of this work was to gather a comprehensive list of requirements to be met by cBioPortal to support processes in MTBs according to clinical needs. Therefore, oncology experts at nine German university hospitals were surveyed in two rounds of interviews. To generate an interview guideline a scoping review was conducted. For visual support in the second round, screenshot mockups illustrating the requirements from the first round were created. Requirements that cBioPortal already meets were skipped during the second round. In the end, 24 requirements with sometimes several conceivable options were identified and 54 screenshot mockups were created. Some of the identified requirements have already been suggested to the community by other users or are currently being implemented in cBioPortal. This shows, that the results are in line with the needs expressed by various disciplines. According to our findings, cBioPortal has the potential to significantly improve the processes and analyses of an MTB after the implementation of the identified requirements.

A Toolbox for Functional Analysis and the Systematic Identification of Diagnostic and Prognostic Gene Expression Signatures Combining Meta-Analysis and Machine Learning.

The identification of biomarker signatures is important for cancer diagnosis and prognosis. However, the detection of clinical reliable signatures is influenced by limited data availability, which may restrict statistical power. Moreover, methods for integration of large sample cohorts and signature identification are limited. We present a step-by-step computational protocol for functional gene expression analysis and the identification of diagnostic and prognostic signatures by combining meta-analysis with machine learning and survival analysis. The novelty of the toolbox lies in its all-in-one functionality, generic design, and modularity. It is exemplified for lung cancer, including a comprehensive evaluation using different validation strategies. However, the protocol is not restricted to specific disease types and can therefore be used by a broad community. The accompanying R package vignette runs in ~1 h and describes the workflow in detail for use by researchers with limited bioinformatics training.

A REST Service for the Visualization of Clinical Time Series Data in the Context of Clinical Decision Support.

BACKGROUND: University Hospital Erlangen provides clinical decision support (CDS) functions in the intensive care setting, that are based on the Arden Syntax standard. These CDS functions generate extensive output, including patient data charts. In the course of the migration of our CDS platform we revised the charting tool because although the tool was generally perceived as useful, the clinical users reported several shortcomings. OBJECTIVE: During the migration of our CDS platform, we aimed at resolving the reported shortcomings and at developing a reusable and parameterizable charting tool, driven by best practices and requirements of local clinicians. METHODS: We conducted a requirements analysis with local clinicians and searched the literature for well-established guidelines for clinical charts. Using a charting library, we then implemented the tool based on the found criteria and provided it with a REST interface. RESULTS: The criteria catalog included 18 requirements, all of which were successfully implemented. The new charting tool fully replaced the previous implementation in clinical routine. It also provides a web interface that enables clinicians to configure charts without programming skills. CONCLUSION: The new charting tool combines local preferences with best practices for visualization of clinical time series data. With its REST interface and reusable design it can be easily integrated in existing CDS platforms.

Developing New Analysis Functions for a Translational Research Platform: Extending the cBioPortal for Cancer Genomics.

BACKGROUND: The cBioPortal is a prevalent open-source translational research platform, allowing private instances and extensions. OBJECTIVE: Our aim was to build up an own instance of cBioPortal, identify missing functionality by interviewing researchers, and implementing these extensions. METHODS: We examined the code base of the cBioPortal and conducted a requirements analysis with researchers. Then an own extension was implemented and a usability evaluation was performed. RESULTS: We developed a new tab in the results view of cBioPortal adding the option to analyze the correlation of gene expression and mutation patterns. CONCLUSION: While extending the cBioPortal is possible, there are still some challenges to overcome. A plug-in concept and a more detailed documentation would greatly facilitate the development of own extensions.

An Extension of the Arden Syntax to Facilitate Clinical Document Generation.

While clinical information systems usually store patient records in database tables, human interpretations as well as information transfer between institutions often require that clinical data can be represented as documents. To automate document generation from patient data in conjunction with the rich computational facilities of clinical decision support, we propose a template-based extension of the Arden Syntax, and discuss the benefits and limitations observed during a pilot application for patient recruitment. While the original Arden Syntax supports string concatenation as well as the substitution of unnamed placeholders, we integrated an additional method based on embedding expressions into strings. A dedicated parser identifies the expressions and automatically substitutes them at runtime, which can for example be harnessed to display the most recent value from a time series. The resulting mechanism supports the generation of extensive clinical documents without the need to apply specific operators. To evaluate the proposed extension, we implemented an Arden module that identifies an intensive care patient cohort that conforms to the eligibility criteria of a clinical trial and outputs a concise patient overview in different document formats. While string interpolation in the original Arden standard has been tailored to clinical event monitoring, we interpret that our accessible approach usefully extends Arden's data-to-text capabilities. Future research might target the development of an interactive template editor that would hide the complexity of formatting directives and conditional expressions behind a graphical user interface, and explore how computer-linguistic formalisms might facilitate advanced features such as automatic inflections of verbs and nouns.