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Results for “Risk-based stratification”

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PubMed2026

Circulating IGF2BP3 enables risk stratification and predicts treatment response in Ewing sarcoma.

Ewing sarcoma (EWS), the second most common pediatric bone tumor, presents with a markedly heterogeneous clinical spectrum and optimal risk stratification is therefore crucial for improving treatment outcomes. The RNA-binding protein IGF2BP3 is a critical oncogenic driver of EWS malignancy. This study evaluates the clinical utility of circulating IGF2BP3 as a biomarker to predict treatment response and risk of disease progression in patients with EWS. Plasma samples from 60 patients with EWS diagnosed and treated at the IRCCS Rizzoli Orthopedic Institute (Bologna, Italy) were collected at diagnosis before treatment initiation and/or after induction chemotherapy. For 51 of these patients, blood was collected at diagnosis, prior to any treatments. For 25 patients, blood samples were available at diagnosis and before surgical intervention, allowing longitudinal analysis in the same patient. For 9 patients, blood was collected only after preoperative chemotherapy, before surgical intervention. Circulating IGF2BP3 levels were quantified using a highly specific and sensitive ELISA assay. Plasma samples from healthy donors served as controls. IGF2BP3 plasma levels were correlated with IGF2BP3 tumor tissue expression, established clinical risk factors, and cumulative incidence of relapse using univariable and multivariable analyses. Plasma IGF2BP3 levels were significantly elevated in patients with EWS compared with healthy controls, with a subset of patients (22/51, 43.2%) exhibiting clinically relevant concentrations. Circulating IGF2BP3 levels reflected tumor expression of the molecule and provided additional prognostic information beyond standard clinicopathologic features. The prognostic impact of circulating IGF2BP3 was primarily observed in patients with localized disease, in whom elevated levels were identified as a significant adverse prognostic factor for disease-specific survival (hazard ratio, 10.63; 95% CI, 1.27-88.62; P = 0.029). Longitudinal monitoring demonstrated that persistence of IGF2BP3 in plasma after induction chemotherapy was a strong predictor of poor clinical outcomes. Circulating IGF2BP3 represents a valuable biomarker for early risk stratification in EWS, particularly in patients with localized disease. Although this is single-marker assay, the expression of the molecule may impact on the fate of many mRNAs. We present an accurate, simple, cost-effective and easy clinical applicable tool to support risk-adapted therapeutic interventions. The limited number of employed patients warrants the need of larger cohorts for validation.

Humans↗
PubMed2026

Measurement of low-density lipoprotein cholesterol and other circulating lipids in Brazil: a systematic literature review.

Accurate laboratory assessment of circulating lipids underpins cardiovascular risk stratification, yet clinical interpretation depends not only on the assays but on the formula chosen to estimate low-density lipoprotein cholesterol (LDL-C). This review integrates the 2019-2025 evidence on laboratory methods for triglycerides (TG), total cholesterol (TC), and high-density lipoprotein cholesterol (HDLC), and on the formulas estimating LDL-C, VLDL-C, and non-HDL cholesterol, to determine how these should be measured, reported, and harmonized in Brazil, where lipid thresholds are adapted from international consensus. A PRISMA 2020 systematic search (PROSPERO CRD420251241064) of PubMed/MEDLINE, Scopus, SciELO, LILACS, Web of Science, and Embase retrieved 57,915 records; after removing 38,210 duplicates, 19,705 titles/abstracts were screened, 312 full texts assessed, and 25 sources included. Enzymatic colorimetric assays remain standard for TG, TC, and HDLC. For LDL-C, Martin/Hopkins classifies more accurately than Friedewald (89.6% vs 83.2% correct categorization in 5,051,467 patients), particularly at high TG and low LDL-C, while Sampson/NIH and modified Sampson/NIH extend reliable estimation into hypertriglyceridemia and very low LDL-C; direct measurement is reserved for TG beyond the validated range. Although the review centers on the Friedewald, Martin/Hopkins, and Sampson/NIH families that dominate guideline practice, other published equations exist and are addressed in context. In Brazil, atherogenic-lipid thresholds are risk-based decision limits rather than reference intervals; national surveys describe lipid distributions but were not designed to establish them. Analytical standardization through traceability programs, multicenter validation of formulas, and-where the distribution-based construct applies (HDLC, pediatrics)-nationally derived reference intervals are priorities for equitable cardiovascular risk assessment in Brazil.

Humans↗
PubMed2026

Machine learning-based clinical prediction model and multi-omics integration for assessing pancreatic cancer risk in new-onset diabetes.

BACKGROUND: Given that pancreatic cancer (PC) is typically diagnosed at an advanced stage but is often preceded by new-onset diabetes mellitus (NODM), providing a window for early detection, we sought to develop and validate an interpretable machine-learning model integrated with multi-omics profiling to identify early biomarkers of NODM-associated PC. METHODS: In a population-based cohort, individuals with NODM-associated PC and NODM without PC were identified and randomly divided (70:30) into training and validation sets after feature selection. Eight machine learning (ML) classifiers were compared using fivefold cross-validation, and model performance was evaluated in terms of discrimination, calibration, and decision curve–based clinical utility. We evaluated interpretability using the Shapley additive explanations (SHAP) analyses. Mechanistically, Olink proteomic profiling and metabolomics were analyzed through clinical classifications and model-defined risk strata. RESULTS: Categorical boosting achieved the best performance in the independent validation set (AUROC = 0.844). The NODM cohort was stratified into high- (n = 2,362) and low-risk (n = 5,030) groups, and internal validation together with SHAP analyses demonstrated consistent model performance and identified clinically interpretable predictors. Proteomic and metabolomic analyses under clinical and risk-based grouping identified 39 overlapping differentially expressed proteins and 145 overlapping metabolites with enriched across 11 shared KEGG pathways. Cross-platform validation highlighted PLTP, CRTAC1, and ITGAV as serum biomarkers with a strong potential for early NODM-PC detection. CONCLUSIONS: We developed an interpretable ML framework centered on NODM enables practical risk stratification for early PC detection by multi-omics and provides a pathway of ML-based triage followed by biomarker confirmation for earlier detection and diagnosis.

Humans↗
PubMed2026

Clinical Relevance of Genomics Defined WHO5 Subtypes of Pediatric B-ALL in the Context of Measurable Residual Disease-Directed Risk-Based Therapy.

PURPOSE: WHO5 (2022) classification of B-lymphoblastic leukemia (B-ALL) incorporates several novel entities requiring high-throughput sequencing for their accurate characterization. The clinical relevance of this classification in the context of contemporary measurable residual disease (MRD)-directed therapy is unclear. METHODS: We analyzed 533 pediatric B-ALL uniformly treated with Indian Collaborative Childhood Leukaemia group (ICiCLe)-ALL-14 protocol as defined by WHO-2016 and reclassified them as per WHO5 using targeted sequencing, FISH, and cytogenetics. RESULTS: Subtype-defining genomic abnormalities were identified in 81.2% of the cohort as per the WHO5 classification. Among the new subtypes, PAX5alt and MEF2D-r were associated with a trend toward an inferior 3-year event-free survival (EFS) of 32.8% (P = .003) and 33.7% (P = .091), respectively. We developed a three-tier genomic risk stratification model incorporating 15 genomic subtypes and the IKZF1 deletion. Children with standard (SGR), intermediate (IGR), and high genomic risk (HGR) demonstrated 3-year EFS of 80.4%, 59.3%, and 45.8% (P < .0001), and 3-year overall survival of 89.6%, 75.3%, and 62.3% (P < .0001), respectively. Genomic risk further identified heterogeneous outcomes among ICiCLe risk groups (P < .0001). SGR was associated with superior EFS irrespective of MRD status (3-year EFS 80.5% in postinduction [PI] MRD-negative v 80.8% PI-MRD-positive patients, P = .530). On multivariable analysis, genomic risk (hazard ratio [HR], 1.7 [95% CI, 1.41 to 2.01]; P < .0001), initial ICiCLe risk (HR, 1.3 [95% CI, 1.06 to 1.49]; P = .009), and PI-MRD (HR, 2.2 [95% CI, 1.66 to 2.90]; P < .0001) independently predicted EFS. CONCLUSION: The study demonstrates the potential role of genomic risk stratification, in conjunction with MRD, in stratifying patients into clinically relevant risk categories.

Humans↗
PubMed2025

A Prospective Validation of the Decipher Genomic Classifier in Men With Early Localized Prostate Cancer: The VANDAAM Study.

BACKGROUND: The emergence of genomic precision oncology has advanced personalized care for some patients with prostate cancer (PCa), while threatening to widen existing disparities due to the historically low recruitment of African American men (AAM), who have the highest disease burden. Here, we report the first prospective validation of a genomic classifier (GC) to predict rapid-onset biochemical recurrence (BCR) in AAM. METHODS: Between 2016 and 2021, this multicenter prospective validation study recruited 243 patients with low- or intermediate-risk PCa who received treatment for their disease. Patients were recruited on a 1:1 basis (AAM:White) and matched by CAPRA score. Patients who elected active surveillance were ineligible for participation. Decipher GC testing was ordered for all patients using their biopsy and/or radical prostatectomy (RP) tumor tissue. The primary outcome was to determine whether the GC could predict 2-year BCR rates-used as a surrogate for disease aggressiveness-following standard treatment. The secondary outcome evaluated the concordance between biopsy- and RP-derived GC risk scores for treatment recommendations. RESULTS: The final analytical cohort included 226 matched patients with genomic information, and 207 evaluable cases (104 AAM, 103 White) with both genomic and complete clinical outcome data. Overall, a high genomic-risk GC score was associated with a 5.25-fold increase in the odds of rapid-onset 2-year BCR compared with the low-risk group (odds ratio, 5.25 [95% CI, 1.27-21.66]; P=.021). In a subset of the surgical cohort (n=74), biopsy- and RP-derived GC scores exhibited a 77% concordance rate, defined as no reclassification in GC risk-based categories. CONCLUSIONS: This study represents the first prospective validation of GC performance in predicting early 2-year BCR in both AAM and White men. The findings provide strong evidence supporting the integration of the GC into clinical practice guidelines to improve risk stratification and management of AAM with early-stage PCa. CLINICALTRIALS: gov identifier: NCT02723734.

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