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State-of-the-art response assessment of central nervous system lymphoma (CNSL) by magnetic resonance imaging is challenging and an insufficient predictor of treatment outcomes. Accordingly, the development of novel risk stratification strategies in CNSL is a high unmet medical need. We applied ultrasensitive circulating tumor DNA (ctDNA) sequencing to 146 plasma and cerebrospinal fluid (CSF) samples from 67 patients, aiming to develop an entirely noninvasive dynamic risk model considering clinical and molecular features of CNSL. Our ultrasensitive method allowed for the detection of CNSL-derived mutations in plasma ctDNA with high concordance to CSF and tumor tissue. Undetectable plasma ctDNA at baseline was associated with favorable outcomes. We tracked tumor-specific mutations in plasma-derived ctDNA over time and developed a novel CNSL biomarker based on this information: peripheral residual disease (PRD). Persistence of PRD after treatment was highly predictive of relapse. Integrating established baseline clinical risk factors with assessment of radiographic response and PRD during treatment resulted in the development and independent validation of a novel tool for risk stratification: molecular prognostic index for CNSL (MOP-C). MOP-C proved to be highly predictive of outcomes in patients with CNSL (failure-free survival hazard ratio per risk group of 6.60; 95% confidence interval, 3.12-13.97; P < .0001) and is publicly available at www.mop-c.com. Our results highlight the role of ctDNA sequencing in CNSL. MOP-C has the potential to improve the current standard of clinical risk stratification and radiographic response assessment in patients with CNSL, ultimately paving the way toward individualized treatment.
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http://dx.doi.org/10.1182/blood.2023022020 | DOI Listing |
Knee Surg Relat Res
September 2025
Florida Orthopaedic Institute, Gainesville, FL, 32607, USA.
Background: A clear understanding of minimal clinically important difference (MCID) and substantial clinical benefit (SCB) is essential for effectively implementing patient-reported outcome measurements (PROMs) as a performance measure for total knee arthroplasty (TKA). Since not achieving MCID and SCB may reflect suboptimal surgical benefit, the primary aim of this study was to use machine learning to predict patients who may not achieve the threshold-based outcomes (i.e.
View Article and Find Full Text PDFGeroscience
September 2025
Department of Emergency and Internal Medicine, Skåne University Hospital, Malmö, Sweden.
To evaluate a simplified version of the Clinical Frailty Scale (SCFS) among older adults presenting to the emergency department (ED) with acute dyspnea. In this retrospective single-center cohort study, we included patients from the Acute Dyspnea Study (ADYS) cohort. Severity of illness was assessed using the Medical Emergency Triage and Treatment System (METTS).
View Article and Find Full Text PDFGeroscience
September 2025
Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
This study aims to investigate the predictive value of combined phenotypic age and phenotypic age acceleration (PhenoAgeAccel) for benign prostatic hyperplasia (BPH) and develop a machine learning-based risk prediction model to inform precision prevention and clinical management strategies. The study analyzed data from 784 male participants in the US National Health and Nutrition Examination Survey (NHANES, 2001-2008). Phenotypic age was derived from chronological age and nine serum biomarkers.
View Article and Find Full Text PDFBr J Cancer
September 2025
Istituto Oncologico Veneto IOV-IRCCS, Padova, Italy.
The European Council recommends adopting risk-based screening when relevant. In triaging HPV-positive women, it can be an effective strategy to reduce overtreatment and referral to colposcopy. HPV genotyping and p16/ki67 expression may allow a better risk stratification than cytology.
View Article and Find Full Text PDFEur J Nutr
September 2025
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, PO Box 1627, 70211, Kuopio, Finland.
Purpose: To investigate how a group-based lifestyle intervention affects food choices and if the dietary patterns at the end of the intervention are associated with incidence type 2 diabetes (T2D). We also investigated if the possible associations between diet and T2D risk were modified by the genetic risk for T2D.
Methods: Participants in the T2D-GENE study were men with prediabetes aged 50-75 years, body mass index ≥ 25 kg/m, belonging in either low or high genetic risk score (GRS) tertile for T2D.