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dc.contributorVall d'Hebron Barcelona Hospital Campus
dc.contributor.authorDe Grandis, Maria Caterina
dc.contributor.authorElez, Elena
dc.contributor.authorBaraibar, Iosune
dc.contributor.authorPrior, Olivia
dc.contributor.authorBalaguer-Montero, Maria
dc.contributor.authorSalvà, Francesc
dc.contributor.authorRos, Javier
dc.contributor.authorR Castells, Marta
dc.contributor.authorTabernero, Josep
dc.contributor.authorPerez-Lopez, Raquel
dc.date.accessioned2025-10-27T13:39:34Z
dc.date.available2025-10-27T13:39:34Z
dc.date.issued2025-08
dc.identifier.citationde Grandis MC, Baraibar I, Prior O, Balaguer-Montero M, Salvà F, Ros J, et al. Differentiating low tumor burden from oligometastatic disease in colorectal cancer: a call for individualized therapeutic approaches. ESMO Open. 2025 Aug;10(8):105520.
dc.identifier.issn2059-7029
dc.identifier.urihttp://hdl.handle.net/11351/13939
dc.descriptionArtificial intelligence; Colorectal cancer; Immunotherapy
dc.description.abstractMetastatic colorectal cancer (mCRC) remains a major clinical challenge; however, tumor burden significantly influences treatment outcomes. In this review, we explore the biological and clinical relevance of low tumor burden (LTB) in mCRC. The primary challenge in defining LTB mCRC lies in establishing a standardized definition that extends beyond the current focus on oligometastatic disease. Patients with LTB mCRC exhibit distinct clinical characteristics that may impact both prognosis and therapeutic response. Evidence suggests that LTB patients often respond better to systemic therapies and may derive potential benefits from targeted and immunotherapy approaches. However, establishing a clear definition is crucial for consistent patient stratification, and for guiding research and selecting the most appropriate therapeutic strategies, particularly in the context of emerging treatments such as immunotherapy. Recent studies using advanced imaging modalities, liquid biopsies, and lactate dehydrogenase (LDH) measurements offer novel approaches to evaluate tumor burden more accurately. These developments, coupled with emerging evidence that patients with LTB may benefit from immunotherapy, highlight the need for further research focused on LTB mCRC patients. Additionally, artificial intelligence (AI) could enhance tumor detection, automate three-dimensional (3D) volume quantification, extract radiomics-based prognostic information, and integrate multimodal data. These capabilities may enhance our ability to stratify patients and guide treatment decisions, potentially leading to better outcomes for mCRC patients. Future studies should focus on refining the definition of LTB, validating these new assessment techniques, and evaluating their impact on treatment outcomes in mCRC patients.
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesESMO Open;10(8)
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceScientia
dc.subjectIntel·ligència artificial - Aplicacions a la medicina
dc.subjectCòlon - Càncer - Tractament
dc.subjectRecte - Càncer - Tractament
dc.subjectMedicina personalitzada
dc.subject.meshColorectal Neoplasms
dc.subject.mesh/therapy
dc.subject.meshPrecision Medicine
dc.subject.meshTumor Burden
dc.subject.meshArtificial Intelligence
dc.titleDifferentiating low tumor burden from oligometastatic disease in colorectal cancer: a call for individualized therapeutic approaches
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1016/j.esmoop.2025.105520
dc.subject.decsneoplasias colorrectales
dc.subject.decs/terapia
dc.subject.decsmedicina de precisión
dc.subject.decscarga tumoral
dc.subject.decsinteligencia artificial
dc.relation.publishversionhttps://doi.org/10.1016/j.esmoop.2025.105520
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.audienceProfessionals
dc.contributor.organismesInstitut Català de la Salut
dc.contributor.authoraffiliation[de Grandis MC] Department of Oncology, Veneto Institute of Oncology IOV – IRCCS, Padova, Italy. [Baraibar I, Salvà F, Ros J, Rodríguez-Castells M, Tabernero J, Élez E] Servei d’Oncologia Mèdica, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Vall d’Hebron Institut d’Oncologia (VHIO), Barcelona, Spain. [Prior O, Balaguer-Montero] Grup de Radiòmica, Vall d’Hebron Institut d’Oncologia (VHIO), Barcelona, Spain. [Perez-Lopez R] Grup de Radiòmica, Vall d’Hebron Institut d’Oncologia (VHIO), Barcelona, Spain. Servei de Radiodiagnòstic, Vall d’Hebron Hospital Universitari, Barcelona, Spain
dc.identifier.pmid40803019
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess


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