User-Driven Development of a Novel Molecular Tumor Board Support Tool

Halfmann, Marc; Stenzhorn, Holger; Gerjets, Peter; Kohlbacher, Oliver; Oestermeier, Uwe

doi:10.1007/978-3-030-06016-9_18

Cited by 5 publications

(6 citation statements)

References 2 publications

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“…A video published by them demonstrates how different tools, including cBioPortal, can be combined in a single user interface [42]. Among other requirements, they discovered, like we did, that a function "to search for comparable local cases" [12] is demanded by clinical experts.…”

Section: Related Workmentioning

confidence: 89%

“…We came across two related works taking place in Germany. Halfmann et al report that they developed a tool that aims to support the preparation process of a molecular tumor board as well as the presentation of a patient case during a meeting [12]. A video published by them demonstrates how different tools, including cBioPortal, can be combined in a single user interface [42].…”

Section: Related Workmentioning

confidence: 99%

“…The objective of this work is to provide a requirements specification for an IT platform based on cBioPortal that supports processes in molecular tumor boards to find and document a therapy recommendation. To our knowledge, there is so far no systematic assessment of such requirements from the point of view of MTB participants in different hospitals, even though there are already existing tools that integrate numerous data sources and even support the documentation process in a uniform MTB tool [12,13]. Our work could serve as a blueprint for the development of further tools based on cBioPortal for MTBs in Germany and worldwide.…”

Section: Introductionmentioning

confidence: 97%

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

et al. 2020

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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 Diagnostics 2020, 10, 93 2 of 15 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.

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Section: Related Workmentioning

confidence: 89%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

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

et al. 2020

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“…While there are other works regarding software solutions for MTBs, these developments are still in early stages. Halfmann et al 32 developed an MTB support tool also using a user-driven development process. Their tool focuses on the presentation part of an MTB and not on the preparation including the search for clinical trials for MTB patients and furthermore, the study did not include a usability evaluation.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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.

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“…Surprisingly, few related studies involve clinicians. For example, Halfmann et al (67) in their study used questionnaires and interviews as the methods to gather information about requirements, workflows, weaknesses, and potential functionalities from MTB organisers. They performed a task analysis and used the results to develop a layout.…”

Section: Discussionmentioning

confidence: 99%

Data-driven support to decision-making in molecular tumour boards for lymphoma: A design science approach

et al. 2022

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BackgroundThe increasing amount of molecular data and knowledge about genomic alterations from next-generation sequencing processes together allow for a greater understanding of individual patients, thereby advancing precision medicine. Molecular tumour boards feature multidisciplinary teams of clinical experts who meet to discuss complex individual cancer cases. Preparing the meetings is a manual and time-consuming process.PurposeTo design a clinical decision support system to improve the multimodal data interpretation in molecular tumour board meetings for lymphoma patients at Karolinska University Hospital, Stockholm, Sweden. We investigated user needs and system requirements, explored the employment of artificial intelligence, and evaluated the proposed design with primary stakeholders.MethodsDesign science methodology was used to form and evaluate the proposed artefact. Requirements elicitation was done through a scoping review followed by five semi-structured interviews. We used UML Use Case diagrams to model user interaction and UML Activity diagrams to inform the proposed flow of control in the system. Additionally, we modelled the current and future workflow for MTB meetings and its proposed machine learning pipeline. Interactive sessions with end-users validated the initial requirements based on a fictive patient scenario which helped further refine the system.ResultsThe analysis showed that an interactive secure Web-based information system supporting the preparation of the meeting, multidisciplinary discussions, and clinical decision-making could address the identified requirements. Integrating artificial intelligence via continual learning and multimodal data fusion were identified as crucial elements that could provide accurate diagnosis and treatment recommendations.ImpactOur work is of methodological importance in that using artificial intelligence for molecular tumour boards is novel. We provide a consolidated proof-of-concept system that could support the end-to-end clinical decision-making process and positively and immediately impact patients.ConclusionAugmenting a digital decision support system for molecular tumour boards with retrospective patient material is promising. This generates realistic and constructive material for human learning, and also digital data for continual learning by data-driven artificial intelligence approaches. The latter makes the future system adaptable to human bias, improving adequacy and decision quality over time and over tasks, while building and maintaining a digital log.

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User-Driven Development of a Novel Molecular Tumor Board Support Tool

Cited by 5 publications

References 2 publications

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

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

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

Data-driven support to decision-making in molecular tumour boards for lymphoma: A design science approach

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