Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review Article Swipe
Iryna Manuilova
,
Jan Bossenz
,
Annemarie Bianka Weise
,
Dominik Boehm
,
Cosima Strantz
,
Philipp Unberath
,
Niklas Reimer
,
Patrick Metzger
,
Thomas Pauli
,
Silke D Werle
,
Susann Schulze
,
Sonja Hiemer
,
Arsenij Ustjanzew
,
Hans A. Kestler
,
Hauke Busch
,
Benedikt Brors
,
Jan Christoph
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.2196/58705
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.2196/58705
Background Understanding the similarities of patients with cancer is essential to advancing personalized medicine, improving patient outcomes, and developing more effective and individualized treatments. It enables researchers to discover important patterns, biomarkers, and treatment strategies that can have a significant impact on cancer research and oncology. In addition, the identification of previously successfully treated patients supports oncologists in making treatment decisions for a new patient who is clinically or molecularly similar to the previous patient. Objective The planned review aims to systematically summarize, map, and describe existing evidence to understand how patient similarity is defined and used in cancer research and clinical care. Methods To systematically identify relevant studies and to ensure reproducibility and transparency of the review process, a comprehensive literature search will be conducted in several bibliographic databases, including Web of Science, PubMed, LIVIVIVO, and MEDLINE, covering the period from 1998 to February 2024. After the initial duplicate deletion phase, a study selection phase will be applied using Rayyan, which consists of 3 distinct steps: title and abstract screening, disagreement resolution, and full-text screening. To ensure the integrity and quality of the selection process, each of these steps is preceded by a pilot testing phase. This methodological process will culminate in the presentation of the final research results in a structured form according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) flowchart. The protocol has been registered in the Journal of Medical Internet Research. Results This protocol outlines the methodologies used in conducting the scoping review. A search of the specified electronic databases and after removing duplicates resulted in 1183 unique records. As of March 2024, the review process has moved to the full-text evaluation phase. At this stage, data extraction will be conducted using a pretested chart template. Conclusions The scoping review protocol, centered on these main concepts, aims to systematically map the available evidence on patient similarity among patients with cancer. By defining the types of data sources, approaches, and methods used in the field, and aligning these with the research questions, the review will provide a foundation for future research and clinical application in personalized cancer care. This protocol will guide the literature search, data extraction, and synthesis of findings to achieve the review’s objectives. International Registered Report Identifier (IRRID) DERR1-10.2196/58705
Related Topics
Concepts
Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.2196/58705
- https://s3.ca-central-1.amazonaws.com/assets.jmir.org/assets/preprints/preprint-58705-accepted.pdf
- OA Status
- gold
- Cited By
- 2
- References
- 26
- Related Works
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- OpenAlex ID
- https://openalex.org/W4400676958
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400676958Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2196/58705Digital Object Identifier
- Title
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Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping ReviewWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-16Full publication date if available
- Authors
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Iryna Manuilova, Jan Bossenz, Annemarie Bianka Weise, Dominik Boehm, Cosima Strantz, Philipp Unberath, Niklas Reimer, Patrick Metzger, Thomas Pauli, Silke D Werle, Susann Schulze, Sonja Hiemer, Arsenij Ustjanzew, Hans A. Kestler, Hauke Busch, Benedikt Brors, Jan ChristophList of authors in order
- Landing page
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https://doi.org/10.2196/58705Publisher landing page
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https://s3.ca-central-1.amazonaws.com/assets.jmir.org/assets/preprints/preprint-58705-accepted.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://s3.ca-central-1.amazonaws.com/assets.jmir.org/assets/preprints/preprint-58705-accepted.pdfDirect OA link when available
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Protocol (science), Similarity (geometry), Computer science, Data science, Psychology, Information retrieval, Medicine, Artificial intelligence, Alternative medicine, Pathology, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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26Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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