{"title":"Permitting disclosed AI assistance in peer review: parity, confidentiality, and recognition.","authors":"Anna Carobene","doi":"10.1515/cclm-2025-1140","DOIUrl":"https://doi.org/10.1515/cclm-2025-1140","url":null,"abstract":"","PeriodicalId":10390,"journal":{"name":"Clinical chemistry and laboratory medicine","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145112091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Carobene, Janne Cadamuro, Glynis Frans, Hanoch Goldshmidt, Zeljiko Debeljak, Sander De Bruyne, William van Doorn, Johannes Elias, Habib Özdemir, Salomon Martin Perez, Helena Lame, Alexander Tolios, Federico Cabitza, Andrea Padoan
{"title":"EFLM checklist for the assessment of AI/ML studies in laboratory medicine: enhancing general medical AI frameworks for laboratory-specific applications.","authors":"Anna Carobene, Janne Cadamuro, Glynis Frans, Hanoch Goldshmidt, Zeljiko Debeljak, Sander De Bruyne, William van Doorn, Johannes Elias, Habib Özdemir, Salomon Martin Perez, Helena Lame, Alexander Tolios, Federico Cabitza, Andrea Padoan","doi":"10.1515/cclm-2025-0841","DOIUrl":"10.1515/cclm-2025-0841","url":null,"abstract":"<p><p>The integration of artificial intelligence (AI) and machine learning (ML) into laboratory medicine shows promise for advancing diagnostic, prognostic, and decision-support tools; however, routine clinical implementation remains limited and heterogeneous. Laboratory data presents unique methodological and semantic complexities - method dependency, analyte-specific variation, and contextual sensitivity-not adequately addressed by general-purpose AI reporting guidelines. To bridge this gap, the EFLM Committee on Digitalisation and Artificial Intelligence (C-AI) proposes an expanded checklist to support assessment of requirements and recommendations for the development of AI/ML models based on laboratory data. Building upon the widely adopted ChAMAI checklist (Checklist for assessment of medical AI), our proposal introduces six additional items, each grounded in the CRoss Industry Standard Process for Data Mining (CRISP-DM) framework and tailored to the specificities of laboratory workflows. These extensions address: (1) explicit documentation of laboratory data characteristics; (2) consideration of biological and analytical variability; (3) the role of metadata and peridata in contextualizing results; (4) analyte harmonization and standardization practices; (5) rigorous external validation with attention to dataset similarity; and (6) the implementation of FAIR data principles for transparency and reproducibility. Together, these recommendations aim to foster robust, interpretable, and generalizable AI systems that are fit for deployment in clinical laboratory settings. By incorporating these laboratory-aware considerations into model development pipelines, researchers and practitioners can enhance both the scientific rigor and practical applicability of AI tools. We advocate for the adoption of this extended checklist by developers, reviewers, and regulators to promote trustworthy and reproducible AI in laboratory medicine.</p>","PeriodicalId":10390,"journal":{"name":"Clinical chemistry and laboratory medicine","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145085324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Tafasitamab interference in immunofixation electrophoresis.","authors":"Rebecca S Treger, Susan L Fink","doi":"10.1515/cclm-2025-1015","DOIUrl":"https://doi.org/10.1515/cclm-2025-1015","url":null,"abstract":"","PeriodicalId":10390,"journal":{"name":"Clinical chemistry and laboratory medicine","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145079698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Federica Di Maggio, Giulia Togo, Ettore Pavone, Alessandra Calabrese, Petra Claudia Camilla D'Orsi, Maria Luisa Marciano, Giovanni Marino, Franco Ionna, Francesco Salvatore, Marcella Nunziato
{"title":"Predictive genomic medicine enlarges the spectrum of predisposing mutations for head and neck cancers via a panel of 56 genes selected for human neoplasia in Southern Italy: a pilot study.","authors":"Federica Di Maggio, Giulia Togo, Ettore Pavone, Alessandra Calabrese, Petra Claudia Camilla D'Orsi, Maria Luisa Marciano, Giovanni Marino, Franco Ionna, Francesco Salvatore, Marcella Nunziato","doi":"10.1515/cclm-2025-1159","DOIUrl":"https://doi.org/10.1515/cclm-2025-1159","url":null,"abstract":"<p><strong>Objectives: </strong>Oral squamous cell carcinoma (OSCC) is the most prevalent form of squamous cell carcinomas of the head and neck (SCCHN), accounting for over 90 % of all oral cavity malignancies (approximately 275,000 new cases are worldwide diagnosed annually). Early-stage oral squamous cell carcinoma (T1 and T2) has a 5-year survival rate of up to 80 %. Survival rates decrease to 20-30 % at later stages (T3-T4). Each year, there are between 275,000 and 300,000 new cases of OSCC, and over 150,000 deaths worldwide. OSCC are usually non-hereditary tumors, although familial epidemiology has been recently reported.</p><p><strong>Methods: </strong>From 2022 to 2024, we enrolled 56 patients from the complex structure of maxillofacial surgery and ORL, National Cancer Institute - IRCCS - Fondazione G. Pascale. The individuals enrolled underwent molecular testing via a multigene panel of 56 genes related to cancer predisposition customized in our laboratory. The panel included <i>BRCA1</i> and <i>BRCA2</i>.</p><p><strong>Results: </strong>We identified a total of 7 pathogenic mutations annotated in clinical databases as ClinVar, in <i>BRCA2</i> (two different variants), <i>BRCA1</i>, <i>MUTYH</i>, <i>BRIP1</i>, <i>FANCM</i> and <i>FANCC</i> genes (approximately 12.5 % of our patients). The results show a frequent predisposition to head and neck tumors similar to or even greater than that observed in other types of neoplasia, such as breast and ovarian cancers or colon cancer), with a predisposition of approximately 10 %.</p><p><strong>Conclusions: </strong>Our results confirm that, similarly to other more studied tumors, predictive genomic medicine can play a crucial role in the early identification of germline mutations in head and neck cancers. This approach should be considered for the early detection of OSCC particularly for individuals at increased risk, e.g., those with a family history of the disease, who may also be candidates for targeted molecular therapies based on their genetic profile.</p>","PeriodicalId":10390,"journal":{"name":"Clinical chemistry and laboratory medicine","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145079745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Value is equal to outcome/costs: how to apply to laboratory medicine.","authors":"Rossella Tomaiuolo, Giuseppe Banfi","doi":"10.1515/cclm-2025-0691","DOIUrl":"https://doi.org/10.1515/cclm-2025-0691","url":null,"abstract":"<p><p>The concept of value, defined as health outcomes achieved per monetary unit spent, has profoundly reshaped modern healthcare delivery. While Value-Based Healthcare models have permeated many clinical disciplines, laboratory medicine has been slow to integrate this paradigm shift. In this opinion paper, we argue for a strategic repositioning of clinical laboratories as core enablers of value in healthcare systems. Laboratory diagnostics, long considered ancillary, should be reframed as pivotal tools that support outcome-based, cost-effective decision-making. We explore how laboratory parameters contribute to clinical value through predictive accuracy, diagnostic specificity, and operational appropriateness - factors that directly influence patient outcomes and resource allocation. Examples such as vitamin D testing, albumin as a biomarker of biological age, and NT-proBNP in heart failure demonstrate the potential and pitfalls of volume-driven laboratory utilization. Beyond technical excellence, we emphasize the importance of interpretive collaboration, health literacy, and ethical stewardship of diagnostic resources. Structural challenges, including commoditization, delocalization via point-of-care testing, and the limited use of patient-reported outcomes in laboratory settings, are critically examined. Finally, we highlight emerging policy frameworks across Europe that align reimbursement models with measurable outcomes, advocating for the integration of laboratories in clinical governance and value-based procurement. In this renewed perspective, laboratories are not merely data providers but agents of personalized, sustainable, and patient-centered care.</p>","PeriodicalId":10390,"journal":{"name":"Clinical chemistry and laboratory medicine","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145074608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sara Contu, Manon Launay, Hélène Bouges Le Royer, Laurence Simon, Audrey Mignot, Eva Seutin, Renaud Schiappa, Philippe Follana, Anne Creisson, Ludovic Evesque, Marie-Christine Etienne-Grimaldi
{"title":"Impact of renal and hepatic function on dihydropyrimidine dehydrogenase phenotype assessed by enzyme activity in peripheral blood mononuclear cells and uracilemia.","authors":"Sara Contu, Manon Launay, Hélène Bouges Le Royer, Laurence Simon, Audrey Mignot, Eva Seutin, Renaud Schiappa, Philippe Follana, Anne Creisson, Ludovic Evesque, Marie-Christine Etienne-Grimaldi","doi":"10.1515/cclm-2025-0949","DOIUrl":"https://doi.org/10.1515/cclm-2025-0949","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the relationship between uracilemia (U) and dihydropyrimidine dehydrogenase (DPD) activity in peripheral blood mononuclear cells (PBMC) and whether they are influenced by renal or hepatic impairment.</p><p><strong>Methods: </strong>This retrospective study included 176 cancer patients with pre-treatment U (UPLC-MSMS assay) and PBMC-DPD (radioenzymatic assay) analyzed the same day (routine phenotyping). Blood renal (creatinine, BUN) and hepatic (ALT, AST, GGT, ALP, albumin, bilirubin) work-up was performed within 15 days before or up to 4 days after DPD phenotyping. Biochemical markers were categorized according to CTCAEv5.0 grade (G). Glomerular filtration rate (eGFR) was estimated (CKD-EPI and EKFC). Non-parametric statistical tests were used.</p><p><strong>Results: </strong>Prevalence of partial deficiency was 3.4 % based on PBMC-DPD (i.e. ≤100 pmol/min/mg) and 6.3 % based on U (i.e. ≥16 μg/L). No complete deficiency was observed. Fifteen patients out of 176 (8.5 %) exhibited discordant DPD status between PBMC activity and U. The correlation between PBMC-DPD and U was significant but weak (r= -0.309, p<0.001). PBMC-DPD (mean 246, median 235, range 62-926 pmol/min/mg prot) was not influenced by renal or hepatic impairment. U (mean 9.6, median 8.5, range 1.7-57.8 μg/L) was significantly higher in patients with elevated BUN (normal vs. >1-UNL, p=0.009), GGT (G0 vs. G1 vs. G2 vs. G3, p<0.001), AST (G0 vs. G≥1, p=0.015), or with hypoalbuminemia (G0 vs. G ≥ 1, p=0.045). Categorized creatinine or eGFR did not influence U.</p><p><strong>Conclusions: </strong>It remains unclear whether renal and/or hepatic impairment acts as a confounding factor affecting the accuracy of uracilemia testing, or whether truly impacts DPD activity, suggesting caution in U interpretation.</p>","PeriodicalId":10390,"journal":{"name":"Clinical chemistry and laboratory medicine","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145074610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Comparison of seven different enzymatic methods for serum glycated albumin in pregnant women: a multicenter study.","authors":"Dandan Sun, Zheng Cao, Mingyuan Jiao, Xiuzhi Guo, Ran Gao, Chaochao Ma, Ying Zhu, Lian Hou, Ying Meng, Meng Wang, Songlin Yu, Yicong Yin, Ling Qiu","doi":"10.1515/cclm-2025-0530","DOIUrl":"https://doi.org/10.1515/cclm-2025-0530","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the consistency of seven enzymatic glycated albumin (GA) assays in pregnant women based on a multicenter study.</p><p><strong>Methods: </strong>Samples were collected from pregnant women at three different gestational stages: 4-13 weeks (n=150), 24-28 weeks (n=300, including 150 GDM subjects), and 29-40 weeks (n=300, including 150 GDM subjects), across three hospitals between July 2022 and December 2023 in China. These samples were analyzed using seven enzymatic GA methods (Lucica, Norudia, BSBE, Maccura, Meikang, Reebio, and Zybio assays). Spearman correlation analysis, Passing-Bablok regression, and Bland-Altman plots were used to evaluate the consistency between the Lucica used in our laboratory and the other selected assays. The effects of albumin concentration and gestational stage on the consistency of GA were evaluated through stratified analyses.</p><p><strong>Results: </strong>The correlation coefficients between Lucica and the other six assays for GA% measurement ranged from 0.741 to 0.906 (p<0.0001), with the mean relative biases ranging from -15.5 to +6.7 %. In trimester-stratified analysis, the highest correlation coefficient was observed in the first trimester for all assays except Maccura, and the bias increased with advancing gestational age for all assays except BSBE. In albumin-stratified analysis (30-45 g/L), the correlation increased with increasing albumin concentration for all assays, while the bias decreased except for BSBE and Maccura assays.</p><p><strong>Conclusions: </strong>Poor analytical consistency was observed in enzymatic GA assays for pregnant women, with discrepancies varying across gestational stages and albumin concentrations. Reference intervals for pregnant women should be established based on trimester-stratified and manufacturer-specific criteria.</p>","PeriodicalId":10390,"journal":{"name":"Clinical chemistry and laboratory medicine","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145074617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"16th Congress of the Portuguese Society of Clinical Chemistry, Genetics and Laboratory Medicine.","authors":"","doi":"10.1515/cclm-2025-0675","DOIUrl":"https://doi.org/10.1515/cclm-2025-0675","url":null,"abstract":"","PeriodicalId":10390,"journal":{"name":"Clinical chemistry and laboratory medicine","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145074669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}