Jul 2026· ESMO real world data and digital oncology· Vol 13, pp. 100731· 0 citations· 19 references
Medicine
TL;DR
An international ring test documenting CDSS usage, performance, and manual interpretation revealed clinically relevant discrepancies between laboratories and interpreters, underscoring the need for structured external quality assessment schemes for CDSS tools in addition to the existing laboratory workflow schemes.
Abstract
Background The EU4Health project PCM4EU aimed to improve survival rates and quality of life of patients with cancer based on precision cancer medicine. To achieve this, enhanced expertise and quality of molecular cancer diagnostics are key. Clinical decision support systems (CDSS) have become increasingly important after the introduction of comprehensive genomic diagnostic profiling. While external quality assessment schemes are mandatory for most diagnostic laboratory tests, similar programs for CDSS tools are currently lacking. To address this, we piloted an international ring test documenting CDSS usage, performance, and manual interpretation. Materials and methods Twenty synthetic datasets were generated, mimicking small variant call sets from a typical targeted 500-gene panel (VCF format) across multiple cancer types (10 tumour-normal pairs and 10 tumour-only). Participants received standardised instructions via e-mail and at a virtual meeting and submitted results using a structured response form. Results Eight laboratories from seven countries participated. All participants submitted results for the 10 tumour-only cases; one submitted results from two assessors. Tumour-only cases contained 6-18 variants where interpretation could be critical. Oncogenic calls for hotspot variants showed good agreement across the various CDSS tools applied; however, variability existed regarding reported variants and clinical interpretation. Conclusion The pilot ring test revealed clinically relevant discrepancies between laboratories and interpreters, underscoring the need for structured external quality assessment schemes for CDSS tools in addition to the existing laboratory workflow schemes. It also highlighted several challenges related to the generation of realistic synthetic data, the design of reporting formats, the definition of ground truth, and the manual interpretation of results.
Abstract Objectives Multidisciplinary team (MDT) meetings are key to delivering cancer care. Increasing caseload and limited resources make them less effective and unsustainable. The aim of this quality improvement project was to assess novel artificial intelligence-based clinical decision support (CDS) technology to d...
H. Jeffery, A. Sinha, B. Shifa et al.· BMJ Health & Care Informatic...· 0 citations
PURPOSE
Oncologists struggle to know which patients are near end of life to enable timely transitions to supportive care. We developed an electronic health record-based prognostic model to identify patients with metastatic breast cancer (MBC) at high risk of near-term death.
METHODS
For model development, we identifi...
E. Ray, Xin-Yi Zhang, Lisette N. Dunham et al.· JCO Oncology Practice· 0 citations
Abstract Background Maintenance of oncology clinical practice guidelines (CPGs) is increasingly challenged by the rapid growth of trial data and therapeutic complexity. While large language models (LLMs) have shown promise in information retrieval, their utility in the rigorous, end-to-end workflow of guideline mainten...
Manuel Knauer, Julian Greß, J. Kather et al.· JMIR AI· 0 citations
Breast cancer remains one of the most common and life threatening cancers worldwide, and early detection is strongly associated with improved survival and reduced treatment burden. This study investigates the ability of Large Language Models to perform diagnostic prediction from structured breast cancer related data....
Habibe Karayiğit, F. Kalelioğlu· International Journal of Int...· 0 citations
The appropriate role of AI-assisted decision support as an adjunct to, rather than a substitute for, multidisciplinary review in rectal cancer management is defined.
Ryan J Meyer, Tamir E. Bresler, Tadevos T Makaryan et al.· The American surgeon· 0 citations
Multidisciplinary teams (MDTs) are central to colorectal cancer management, where treatment decisions increasingly depend on the integration of tumor stage, molecular characteristics, patient fitness, and multimodal treatment strategies. However, MDT workflows are time-consuming, subject to inter-team variability, and...
A. Nikitaras, S. M. Tsoti, M. Pramateftakis· Frontiers in Oncology· 0 citations
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