Search Results (2,850)

Background and Objectives: Metastatic renal cell carcinoma (mRCC) remains a lethal disease despite advances with immune checkpoint inhibitors such as nivolumab. However, a substantial proportion of patients exhibit primary resistance or early progression, highlighting the need for reliable and easily accessible prognostic biomarkers. The C-reactive protein–albumin–lymphocyte (CALLY) index is a novel immunonutritional biomarker integrating systemic inflammation, nutritional status, and immune competence. Materials and Methods: In this retrospective single-center study, 91 patients with mRCC treated with nivolumab were analyzed. Patients were stratified into low and high CALLY index groups based on a receiver operating characteristic-derived cut-off (0.322). Survival outcomes were assessed using Kaplan–Meier analysis and Cox regression models. Results: Patients with a low CALLY index demonstrated significantly shorter progression-free survival (4.5 vs. 13.5 months, p < 0.001) and overall survival (9.1 vs. 25.5 months, p = 0.003). Multivariate analysis confirmed the CALLY index as an independent prognostic factor for both progression-free survival (HR: 2.63, p = 0.002) and overall survival (HR: 1.88, p = 0.035). Conclusions: The CALLY index is a simple, cost-effective, and reproducible biomarker that independently predicts survival in nivolumab-treated mRCC. It may serve as a practical tool for risk stratification and personalized treatment planning in the immunotherapy era. Full article

Background: Although immune checkpoint inhibitors (ICIs) have improved survival in advanced melanoma, predicting individual responses remains challenging; thus, practical and inexpensive biomarkers are needed. In this study, we investigated the prognostic value of the neutrophil percentage–albumin ratio (NPAR) in patients with advanced melanoma receiving ICI therapy. Methods: Fifty patients treated in our clinic were included, with a mean age of 53.3 years and 66% being male. Visceral metastases were present in 76% of the cohort. Through conducting Receiver Operating Characteristic (ROC) analysis, we determined an NPAR cut-off value of 1.81, with patients categorized into low (<1.81, n = 27)- and high (≥1.81, n = 23)-NPAR groups. The progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan–Meier and Cox regression analyses. Results: High NPAR (≥1.81) significantly shortened both PFS and OS. In the univariate analysis, high NPAR emerged as a strong risk factor for PFS (HR: 2.68, p = 0.002) and OS (HR: 3.70, p < 0.001), while multivariate analysis confirmed NPAR as an independent negative prognostic factor for PFS (HR: 2.45, p = 0.006) and OS (HR: 2.82, p = 0.003), regardless of clinical variables. Additionally, visceral metastasis was an independent negative predictor of survival. Conclusions: Pre-treatment NPAR levels may be an independent and potential predictor of survival in advanced melanoma patients receiving ICIs. This easily calculable ratio could provide a practical guide for risk stratification. Full article

Background/Objectives: Heart failure (HF) remains a major cause of global mortality and morbidity; it is, therefore, of paramount importance that diagnosis and prognostication are made timely in order to better improve outcomes and reduce healthcare expenditure. This research presents a novel predictive model of heart failure that combines clinical criteria with demographic factors in order to maximize predictive performance and act as a reliable tool for individualized healthcare intervention. Methods: Complex machine learning techniques, including decision trees, random forest, and deep learning, are applied in analyzing a large dataset of subjects with heart failure. We collected a diverse dataset comprising clinical indicators such as echocardiographic data, biomarkers, electrocardiogram (ECG) features, and demographic information. Data preprocessing techniques, such as feature normalization and handling of missing values, were applied to ensure the integrity and reliability of the dataset. Results: The results indicate that integrating both clinical indicators and demographic characteristics significantly improves the predictive power of the model, compared to models based on clinical indicators alone. Specifically, the hybrid model demonstrated a superior ability to predict short- and long-term outcomes in heart failure patients, offering enhanced accuracy in risk stratification and prognosis prediction. Conclusions: This research highlights the potential of artificial intelligence (AI) and machine learning in revolutionizing heart failure care by providing healthcare professionals with more accurate, data-driven decision support tools. The proposed model not only holds promise for clinical applications but also offers insights for future research into personalized medicine. Full article

Background: Human epidermal growth factor receptor 2 (HER2) alterations have been implicated as mechanisms of resistance to anti-epidermal growth factor receptor (anti-EGFR) therapy in metastatic colorectal cancer (mCRC). We aimed to evaluate the predictive and prognostic significance of HER2 expression in patients with RAS wild-type mCRC in a real-world setting. Methods: We conducted a multicenter retrospective cohort study across ten oncology centers in Turkey, including patients with RAS wild-type mCRC treated between 2015 and 2022. Clinical outcomes, including progression-free survival (PFS) and overall survival (OS), were compared between HER2-positive and HER2-negative groups. Multivariable Cox proportional hazards models were used to identify independent predictors of survival outcomes. Results: Among 204 patients, 28 (13.7%) were HER2-positive. Baseline characteristics were generally comparable; however, HER2-positive patients showed a trend toward higher-grade tumors and were significantly less likely to receive anti-EGFR therapy. HER2-positive patients had significantly shorter PFS compared to HER2-negative patients (median 10 vs. 13 months; p = 0.006). In multivariable analysis, HER2 positivity remained an independent predictor of shorter PFS (HR 1.76, 95% CI 1.01–3.07; p = 0.045). In the subgroup of 144 patients receiving anti-EGFR therapy, HER2-positive patients also demonstrated significantly shorter PFS (median 9.0 vs. 14.0 months; p = 0.023). No significant differences in OS were observed between groups. Conclusions: HER2 positivity is associated with reduced response to anti-EGFR therapy and independently predicts shorter PFS in patients with RAS wild-type mCRC. These findings further support the role of HER2 as a clinically relevant biomarker in RAS wild-type mCRC, particularly in predicting response to anti-EGFR therapy, while highlighting the need for optimized patient selection strategies in the era of HER2-targeted treatments. Full article

Purpose: Prostate cancer is one of the most common malignancies in men, yet current prognostic methods remain suboptimal. Emerging evidence indicates that microRNAs (miRNAs) play critical roles in prostate cancer progression. This study aimed to identify miRNAs associated with adverse clinical outcomes by comparing miRNA expression profiles between prostate tumors with unfavorable versus favorable prognostic features. Materials and Methods: High-throughput next-generation sequencing (NGS) was used to analyze miRNA expression in formalin-fixed, paraffin-embedded prostate cancer tissue samples. Patients were classified into favorable or unfavorable prognosis groups based on risk stratification scores, Gleason grade group, and biochemical recurrence. Differentially expressed miRNAs were identified using a fold-change threshold ≥2 and a false discovery rate (FDR) <0.05. Predicted target genes and pathway analyses were conducted to generate candidate regulatory hypotheses rather than confirm mechanistic relationships. Results: Several miRNAs were differentially expressed according to prognostic category. miR-206 was significantly downregulated in high-risk tumors compared with low-risk tumors. High-Gleason-grade tumors showed reduced expression of miR-7704 and miR-4454, while miR-25-3p and let-7f-5p were upregulated. In patients with early biochemical recurrence, miR-7704 and miR-10400-5p were downregulated relative to those with prolonged recurrence-free survival. Target prediction analysis identified CPEB3, HAND1, PTAR1, and SPRYD4 as shared candidate targets, with CPEB3 emerging as a prioritized candidate supported by consistency in external datasets rather than a confirmed molecular target. Conclusions: Distinct miRNA expression patterns correlate with prostate cancer aggressiveness and clinical outcomes. miR-206, miR-7704, miR-4454, miR-25-3p, and let-7f-5p represent candidate prognostic biomarkers. Their shared target CPEB3 should be interpreted as a prioritized candidate for future investigation. Given the very small sample size and the lack of qRT-PCR and functional validation, these findings should be considered preliminary and hypothesis-generating, requiring validation in larger independent cohorts and experimental studies. Full article

Melanoma adjuvant therapy has substantially improved recurrence-free and distant metastasis-free survival in patients with resected high-risk disease, and more recently, these advances have extended to earlier stages. However, important unmet needs remain, including the management of stage IIIA disease, the optimal treatment strategy after relapse on adjuvant therapy, and the identification of biomarkers capable of refining patient selection. This review summarizes recent advances and unresolved questions in the adjuvant and neoadjuvant treatment of melanoma. We discuss novel systemic strategies, including immune checkpoint inhibitor combinations and personalized neoantigen mRNA vaccines, together with the expanding role of neoadjuvant approaches. We also examine prognostic and predictive tools—such as clinicopathologic models, circulating tumor DNA, serum biomarkers, tumor microenvironment features, and gene expression profiling—that may help better define recurrence risk and therapeutic benefit. Current evidence suggests that although modern therapies have changed the natural history of resected melanoma, a substantial proportion of patients are still overtreated or undertreated when treatment decisions are based on stage alone. Future progress will depend on integrating biological risk stratification with clinical staging and optimizing treatment sequencing across adjuvant and neoadjuvant settings. Full article

Background: Predicting postoperative recurrence of prostate cancer (PCa) after robot-assisted radical prostatectomy (RARP) remains challenging. Endogenous testosterone density (ETD) has emerged as a potential biomarker, though its exact prognostic value remains underexplored in specific surgical cohorts. To evaluate preoperative ETD, the ratio of endogenous testosterone to prostate volume (PV; mL), as a predictor of both unfavorable tumor grade and disease progression in clinically localized low-grade (ISUP 1) and high-grade (ISUP 4/5) prostate cancer (PCa). Methods: Between November 2014 and December 2019, 186 patients were selected according to the study criteria. Statistical methods evaluated associations of ETD with study endpoints. Results: In the surgical specimen, 63 cases (33.9%) were low grade (ISUP 1) and 123 (66.1%) high grade (ISUP 4/5). Median (IQR) follow-up was 40 (25–50). PCa progression occurred in 48 subjects (25.8%). Patients presenting with increased ETD levels above 10 ng/(mL × dL) were more likely to associate with high-grade cancer in the surgical specimen (OR = 2.098; 95% CI: 1.028–4.124; p = 0.021) than to undergo disease progression (HR 2.278; 95%CI: 1.258–4.124; p = 0.007). Conclusions: Preoperative ETD was an independent parameter for stratifying clinically localized PCa. ETD levels increased according to the risk of unfavorable tumor grade and disease progression. Full article

Triple-negative breast cancer is an aggressive and heterogeneous type of invasive breast cancer (BC) in which the cancer cells lack estrogen and progesterone receptors, as well as expression of the human epidermal growth factor 2 protein. This cancer tends to grow and spread faster than other BC subtypes, and is associated with a poor prognosis due to early visceral and neurological recurrences. Multidisciplinary management includes surgery, chemotherapy, radiation therapy, and immunotherapy with targeted immune checkpoint inhibitors (ICIs). The introduction of ICIs has improved outcomes in patients with TNBC, particularly in the metastatic and neoadjuvant settings. Despite these advances, a significant proportion of patients either do not respond to treatment or develop resistance to it. TNBC mortality remains high, underscoring the urgent need to identify novel prognostic and predictive biomarkers to overcome resistance to immunotherapy. Following a brief overview of the clinical features and established biomarkers of TNBC, the current review focuses on immune checkpoint proteins (ICPs) beyond PD-1 and PD-L1, and on the potential use of soluble ICPs rather than the well-established membrane-bound assays. These soluble ICPs are produced through the alternative splicing of messenger (m)RNA or the cleavage/shedding of membrane-bound proteins. This is followed by an overview of current treatment and novel predictive targets in TNBC. Additionally, the involvement of the B- and T-lymphocyte attenuator (BTLA)/herpes virus entry mediator (HVEM)/CD160 pathway and its role in the pathogenesis of BC and TNBC are reviewed, highlighting the potential use of BTLA and HVEM as biomarkers. Full article

Background: Gliomas are characterized by a high degree of molecular heterogeneity, which impairs the reproducibility of predictive biomarkers derived from bulk-based molecular profiling due to immune/stromal contamination of tumors and the high prevalence of the IDH mutation signature. Methods: In this study, we used MOFA+ to derive intrinsic molecular signatures from transcriptional, methylation, and genomic profiles of a cohort of 667 diffuse gliomas in the Cancer Genome Atlas database. Thereafter, factor scores were derived for two separate Chinese Glioma Genome Atlas batches (Batch 1, n = 325; Batch 2, n = 693) without any retraining on the model. The prognostic independence of identified molecular signatures was assessed using multivariable Cox regression adjusted for IDH mutation status and tumor purity; purity-residualized survival analyses; IDH-stratified Cox regression in each cohort; validation by concordance index against established molecular signatures; and survival extreme profiling. To characterize the biological significance of factor signatures, we projected gene set signatures corresponding to each factor signature onto a single-cell RNA-seq dataset of GBM (GSE131928). Results: MOFA+ identified 12 latent factors, of which a vascular–extracellular matrix (ECM) remodeling axis (Factor 1) explained the highest multi-omics variance (24.9%) and was the strongest independent prognostic factor. In multivariable Cox regression adjusting for IDH status and tumor purity, Factor 1 remained independently prognostic (HR = 1.67, 95% CI 1.27–2.20, p = 0.0002); in a fully-adjusted model additionally including age, WHO grade, MGMT methylation, and 1p/19q codeletion (plus radiotherapy and chemotherapy status in the CGGA cohorts), Factor 1 remained prognostic in both CGGA cohorts (CGGA1: HR = 1.50, p = 3.8 × 10⁻⁵; CGGA2: HR = 1.18, p = 0.003) but lost significance in TCGA (HR = 1.04, p = 0.83), consistent with the cohort-dependent magnitude reported in the IDH-stratified and meta-regression analyses below. Purity-residualized survival analysis showed negligible attenuation of the Factor 1 signal (raw HR = 3.57 vs. residualized HR = 3.72; concordance 96.5%). Within IDH-wildtype gliomas, Factor 1 was significant in both external validation cohorts (CGGA1: HR = 1.64, FDR = 4.6 × 10⁻⁶; CGGA2: HR = 1.20, FDR = 0.02), though the TCGA IDH-wildtype subgroup showed a trend that did not survive FDR correction (FDR = 0.060). All validation was performed without model retraining. Within IDH-mutant gliomas, Factor 1 was strongly prognostic in both CGGA cohorts but was not significant in TCGA (HR = 1.17, FDR = 0.33). These findings should therefore be interpreted as consistent in directionality across cohorts but not uniformly replicated at the FDR-adjusted significance threshold in the TCGA discovery dataset. Concordance index benchmarking on a matched subset (n = 503) showed Factor 1 achieved discrimination comparable to the Mesenchymal signature (C = 0.797 vs. 0.801; ΔC = −0.004) while outperforming four other established classifiers. Factor 1 consistently separated patients with extreme survival phenotypes (OS < 6 vs. >15 months) across all three cohorts (all log-rank p < 0.001). Projection onto a single-cell GBM atlas (GSE131928), supported by inferCNV-based malignant-cell classification, localized the Vascular–ECM program to malignant cells and the Immune–ECM axis to myeloid compartments. Conclusions: The Vascular–ECM axis is a consistent, prognostic program robust to purity adjustment for diffuse gliomas that remains relevant across IDH-defined subgroups in three independent datasets comprising 1685 patients. The Vascular–ECM axis is a reproducible, purity-robust prognostic program in diffuse glioma, with directionally consistent adverse effects across TCGA, CGGA Batch 1, and CGGA Batch 2 (pooled n = 1685). Given the strong co-loading of endothelial, ECM, and myeloid genes observed in the single-cell projection, Factor 1 is best interpreted as a vascular/ECM-associated tumor–microenvironment ecosystem program rather than a malignant-cell-autonomous signature. Its FDR-adjusted significance within IDH-stratified subgroups is cohort-dependent and robust in both CGGA cohorts but attenuated in the TCGA IDH-wildtype (FDR = 0.060) and TCGA IDH-mutant (FDR = 0.33) strata. The pooled signal should therefore be interpreted as evidence of a generalizable biological program rather than a uniformly replicated subgroup-specific biomarker. It is possible to calculate factor scores based on RNA sequencing alone using fixed loadings (Z = XWᵀ), which may have implications for future translational applications. All findings are correlative; a causal role for the Vascular–ECM program in glioma progression, invasion, or therapy resistance remains to be established through functional perturbation experiments. Full article

Upper tract urothelial carcinoma (UTUC) presents distinct diagnostic and therapeutic challenges because of its rarity, anatomic constraints, frequent understaging at biopsy, and risk of systemic recurrence after radical nephroureterectomy. Current perioperative management is driven primarily by clinicopathologic risk factors, which may be insufficient to identify occult molecular residual disease (MRD) or to determine which patients are most likely to benefit from systemic therapy. This narrative review summarizes available evidence on circulating tumor DNA (ctDNA) in UTUC and related urothelial carcinoma settings, classifies the level of evidence supporting each application, and proposes a research framework for prospective evaluation. The strongest UTUC-specific evidence supports ctDNA as a prognostic biomarker associated with recurrence risk, whereas predictive validity for selecting chemotherapy, immune checkpoint inhibitors, antibody-drug conjugates, targeted therapy, or surveillance intensity remains unproven. Evidence from muscle-invasive bladder cancer, including ctDNA-correlative and ctDNA-guided perioperative trials, provides biologic rationale but should not be directly translated into routine UTUC care without disease-specific validation. We outline key implementation questions, including target population, assay selection, timing, false-positive and false-negative results, lead-time bias, and integration of plasma ctDNA with utDNA. Prospective UTUC-specific trials are needed to determine whether ctDNA-guided perioperative strategies improve survival, reduce unnecessary toxicity, and are cost-effective. Full article

Heart failure with preserved ejection fraction (HFpEF) is a prevalent and heterogeneous syndrome with limited therapeutic options, making accurate risk stratification essential yet challenging. Traditional tools such as the H2FPEF and HFA-PEFF scores incorporate few variables and demonstrate modest prognostic performance. Machine learning (ML) offers enhanced risk prediction by integrating multidimensional clinical, imaging, biomarker, and molecular data. This review summarizes current ML applications in HFpEF, including random forests, gradient boosting, support vector machines, and deep learning, highlighting their superior discrimination and ability to reveal phenotypic subgroups with distinct outcomes. We also address practical considerations such as interpretability, real-world validation, and integration into clinical workflows, as well as challenges related to data bias, generalizability, and regulatory requirements. Future opportunities include real-time clinical decision support, digital health integration, and interventional ML to guide personalized therapy. ML holds significant potential to advance precision care and improve outcomes in HFpEF. Full article

Background and Objectives: Neoadjuvant chemotherapy (NAC) followed by radical cystectomy is the standard of care for eligible patients with locally advanced bladder cancer (LABC). However, adjuvant chemotherapy (AC) remains widely used in real-world practice. Host-related inflammatory and nutritional biomarkers may also influence survival outcomes. This study aimed to compare survival outcomes between NAC and AC and to identify independent prognostic factors for overall survival (OS) and progression-free survival (PFS), with particular emphasis on the Prognostic Nutritional Index (PNI). Methods: This multicenter retrospective study included 262 patients with locally advanced bladder cancer. The median age was 66 years, and 84% of patients were male. Patients were treated with neoadjuvant chemotherapy followed by radical cystectomy or adjuvant chemotherapy after surgery between August 2021 and March 2025. The Prognostic Nutritional Index (PNI) was calculated using pretreatment laboratory values. ROC analysis was used to determine the optimal PNI cut-off for predicting mortality, and the derived threshold (49.97) was applied for stratification in all survival analyses. Survival outcomes were evaluated using the Kaplan–Meier method and compared using the log-rank test. Multivariate Cox proportional hazards regression was used to identify independent prognostic factors. Results: Among 262 patients, 138 (52.7%) received NAC, and 124 (47.3%) received AC. Median follow-up was 33.6 months (95% CI: 29.4–37.8). No statistically significant differences in OS (p = 0.388) or PFS (p = 0.499) were observed between treatment groups. In univariate analyses, nodal stage, pathological complete response (pCR), and PNI were significantly associated with both OS and PFS. In multivariate analysis, low PNI (≤49.97) remained an independent predictor of mortality (HR 1.78, 95% CI 1.04–3.38; p = 0.044), while N3 nodal stage independently predicted disease progression (HR 5.92, 95% CI 1.06–32.84; p = 0.042). Conclusions: In this multicenter real-world cohort, nodal stage and systemic inflammatory-nutritional status were key determinants of prognosis in patients with locally advanced bladder cancer receiving perioperative chemotherapy. PNI emerged as an independent predictor of overall survival, suggesting that host-related biomarkers may improve prognostic stratification beyond traditional clinicopathological factors. Full article

Colon adenocarcinoma (COAD) is a common malignancy with substantial morbidity and mortality, and the identification of new therapeutic targets remains essential for improving patient outcomes. In this study, we investigated SHC SH2-domain binding protein 1 (SHCBP1) in COAD through two complementary components with distinct evidentiary scopes. The first component comprised expression profiling, prognostic and methylation analyzes, bioinformatic characterization, and functional validation in vitro and in vivo. The second component comprised exploratory computational analyses, including predicted interaction network analysis and structure-based virtual screening. Public databases were used to analyze SHCBP1 expression, prognosis, and promoter methylation status. Co-expression and functional enrichment analyses were performed to explore the biological context of SHCBP1. In vitro and in vivo experiments were then conducted to evaluate the effects of SHCBP1 knockdown on tumor growth. SHCBP1 was significantly upregulated in COAD and was associated with poor patient prognosis. Promoter hypomethylation may contribute to its increased expression. Bioinformatic analyses suggested that SHCBP1 is associated with DNA replication and cell-cycle-related pathways. Experimental studies demonstrated that SHCBP1 knockdown suppressed cell proliferation and tumor growth. In the exploratory computational component, predicted interaction network analysis and virtual screening prioritized several in silico candidate interactions and two compounds with favorable predicted binding scores. These computational findings require independent biochemical and cellular validation. Overall, our findings suggest that SHCBP1 may represent a candidate biomarker associated with COAD proliferation and unfavorable prognosis, as well as a putative molecular target that warrants further validation. Full article

Long-term survival after solid organ transplantation remains limited by chronic remodeling, fibrosis, vascular complications, and malignancy despite advances in immunosuppressive therapy. Current monitoring strategies primarily rely on functional and immunological parameters that often identify complications only after irreversible injury has occurred. There is a critical need for earlier, mechanistically informative biomarkers that can predict survival outcomes. Many platelet-associated growth factors (PDGF, TGF-β, VEGF, EGF, and IGF-1) are stored in platelet α-granules but can also originate from immune, endothelial, and stromal cells, regulate angiogenesis, extracellular matrix deposition, immune modulation, and tissue repair—processes central to graft adaptation and chronic injury. In this review, we propose the growth factor signaling network as a conceptual framework that potentially links platelet biology, ischemia-reperfusion injury, alloimmune responses, and chronic immunosuppression to sustained growth factor signaling and maladaptive graft remodeling. This framework should be interpreted as a biologically plausible integrative model rather than a fully validated mechanistic pathway in transplant recipients. Importantly, direct clinical evidence linking platelet activation markers (e.g., P-selectin, PF4, β-thromboglobulin) with circulating growth factor levels and long-term transplant outcomes remains limited, highlighting a critical gap in current biomarker research. Emerging clinical evidence suggests their potential prognostic relevance in transplant outcomes. Elevated TGF-β levels have been associated with increased risk of opportunistic infections, while early postoperative IGF-1 concentrations predict short-term survival. Increased VEGF-A levels correlate with primary graft dysfunction and cardiac allograft vasculopathy, while PDGF isoforms contribute to fibrotic and vascular progression across transplanted organs. However, their clinical applicability is limited by methodological variability and lack of large-scale validation. Rather than serving solely as markers of rejection, platelet-associated growth factors may reflect dynamic processes involved in transplant remodeling and mortality risk. Incorporating growth factor profiling into multiparametric survival prediction models may improve early risk stratification and support precision post-transplant management strategies. Full article

Background: Accurate staging is vital for optimizing outcomes in pediatric rhabdomyosarcoma (RMS). While [¹⁸F]-FDG PET/CT is increasingly utilized, its specific impact on clinical management and its prognostic value compared to conventional imaging (CI) require further evaluation. Methods: In this retrospective single-center study, we reviewed 56 pediatric patients with RMS who underwent [¹⁸F]-FDG PET/CT at our center. Imaging findings were compared with CI (CT/MRI) and correlated with clinical management and survival outcomes. Results: In the total cohort (n = 56), PET/CT demonstrated high concordance with CI for nodal assessment, with an apparent sensitivity of 89.5% and specificity of 94.6%. PET/CT identified skeletal metastases in 5 patients (8.9%) and correctly characterized suspicious pulmonary nodules in one case, though it failed to detect a 0.6 cm lung nodule visualized on chest CT. Notably, PET/CT findings directly altered clinical management in 16.1% of patients (n = 9), primarily through radiotherapy adjustments, including field expansions (n = 4), field reductions (n = 3), and the initiation of previously unplanned radiotherapy (n = 2). At a median follow-up of 33.3 months, an exploratory analysis showed that patients with an SUVmax ≥3.6 had a lower 3-year EFS (57.6% vs. 71.6%; p = 0.51) and OS (60.4% vs. 71.6%; p = 0.63); neither comparison reached statistical significance. Conclusion: [¹⁸F]-FDG PET/CT is a powerful adjunct in pediatric RMS staging, particularly for nodal and skeletal evaluation. Its ability to refine radiotherapy planning in nearly one-sixth of cases underscores its clinical utility. SUVmax is not a validated prognostic or predictive biomarker in pediatric RMS; prospective, adequately powered multicenter studies, ideally incorporating volumetric PET parameters, are needed before any role in risk-stratified therapy can be defined. Full article