The growing use of measurable residual disease (MRD) assays across haematology-oncology creates an urgent need for clinicians and researchers to reflect on the biological and clinical rationale of this class of biomarkers. In this Viewpoint, we critically examine two premises behind MRD's use in haematology-oncology, focusing on its biological plausibility as a predictive biomarker and surrogate endpoint, and the evidence needed for it to influence decision making in haematological cancers. Examining these premises leads us to advocate for the establishment of more robust biological and clinical evidence to ensure the clinically useful and safe application of MRD. Although achieving the eradication of cancer cells in the form of undetectable MRD seems an attractive goal in haematology-oncology, we highlight the epistemic limitations of this biomarker and need for more clinical evidence to guide its effective use.
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http://dx.doi.org/10.1016/S2352-3026(25)00002-X | DOI Listing |
Philos Trans A Math Phys Eng Sci
March 2025
Division of Applied Mathematics, Brown University, Providence, RI 02906, USA.
When predicting physical phenomena through simulation, quantification of the total uncertainty due to multiple sources is as crucial as making sure the underlying numerical model is accurate. Possible sources include irreducible uncertainty due to noise in the data, uncertainty induced by insufficient data or inadequate parameterization and uncertainty related to the use of misspecified model equations. In addition, recently proposed approaches provide flexible ways to combine information from data with full or partial satisfaction of equations that typically encode physical principles.
View Article and Find Full Text PDFLancet Haematol
March 2025
Centre International de Recherche en Infectiologie (INSERM U1111, CNRS UMR 5308, École Normale supérieure de Lyon), Lymphoma ImmunoBiology team, Faculté de Médecine Lyon sud, Université Claude Bernard Lyon 1, Lyon, France; Service d'hématologie biologique, Hospices Civils de Lyon, Hôpital Lyon Sud, Pierre Bénite, France. Electronic address:
The growing use of measurable residual disease (MRD) assays across haematology-oncology creates an urgent need for clinicians and researchers to reflect on the biological and clinical rationale of this class of biomarkers. In this Viewpoint, we critically examine two premises behind MRD's use in haematology-oncology, focusing on its biological plausibility as a predictive biomarker and surrogate endpoint, and the evidence needed for it to influence decision making in haematological cancers. Examining these premises leads us to advocate for the establishment of more robust biological and clinical evidence to ensure the clinically useful and safe application of MRD.
View Article and Find Full Text PDFPLOS Digit Health
March 2025
Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
This paper introduces the Team Card (TC) as a protocol to address harmful biases in the development of clinical artificial intelligence (AI) systems by emphasizing the often-overlooked role of researchers' positionality. While harmful bias in medical AI, particularly in Clinical Decision Support (CDS) tools, is frequently attributed to issues of data quality, this limited framing neglects how researchers' worldviews-shaped by their training, backgrounds, and experiences-can influence AI design and deployment. These unexamined subjectivities can create epistemic limitations, amplifying biases and increasing the risk of inequitable applications in clinical settings.
View Article and Find Full Text PDFCurr Opin Otolaryngol Head Neck Surg
March 2025
Sean Parker Institute for the Voice, Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medical College, New York.
Purpose Of Review: This review aims to explore the integration of artificial intelligence (AI) in laryngology, with specific focus on the barriers preventing translation from pilot studies into routine clinical practice and strategies for successful implementation.
Recent Findings: Laryngology has seen an increasing number of pilot and proof-of-concept studies demonstrating AI's ability to enhance diagnostics, treatment planning, and patient outcomes. Despite these advancements, few tools have been successfully adopted in clinical settings.
J Biosoc Sci
February 2025
Institute of Epidemiology & Health, University College London (UCL), London, UK.
In recent years, there have been increasing calls for the development and growth of the biosocial as a paradigm through which to tackle complex problems. The use of birth cohorts, mixed methods frameworks, and interdisciplinary work are common in biosocial research. However, these practices are also theoretically and practically complex due to epistemic, methodological, and academic challenges - particularly for early career researchers (ECRs) who face time constraints, funding limitations, and disciplinary expectations.
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