Background/Objectives: Accurate preoperative discrimination between benign and malignant testicular masses remains challenging. Lesion size has been suggested as a predictor, but robust cutoffs and the role of contralateral biopsy remain uncertain. Methods: We retrospectively analyzed a prospectively maintained single-center database of 387 patients treated for testicular lesions between December 2013 and November 2024. Patients with malignant non-germ cell histologies or prior systemic GCT therapy were excluded. Lesion size was evaluated as a predictor of malignancy using ROC analysis, logistic regression, and predefined cutoffs (5, 8, 10, 15 mm). Associations between contralateral biopsy results and clinical variables were assessed using uni- and multivariable analyses. Results: Of 387 patients, 284 (73.4%) had malignant GCTs. Malignant lesions were significantly larger than benign ones (median 25.0 vs. 5.5 mm, p < 0.001). Lesion size showed good discrimination between benign and malignant lesions (AUC 0.829, 95% CI 0.784–0.874), with a Youden-derived optimal cutoff of 12.5 mm. Internal bootstrap validation (2000 resamples) yielded a median optimal cutoff of 12.5 mm (95% percentile interval 7.45–19.5 mm), indicating uncertainty regarding the exact threshold. Among 360 patients with complete clinical and tumor-marker data, combining lesion size with age, AFP, β-HCG, and LDH significantly improved discrimination compared with lesion size alone (AUC 0.863 vs. 0.818; DeLong p = 0.003). Contralateral biopsy was performed in 249 patients, with 7 (2.8%) positive for GCNIS. Younger age was associated with contralateral GCNIS, while tumor size, serum markers, and histology were not predictive. Multivariable analysis showed no significant predictors. Conclusions: Lesion size is a strong predictor of malignant histology, although the optimal size threshold remains subject to uncertainty. Combining lesion size with readily available clinical and biochemical parameters may further improve preoperative risk stratification. Contralateral GCNIS was rare and not reliably predicted, supporting individualized biopsy strategies.
Background/Objectives: Baseline magnetic resonance imaging (MRI) findings may provide prognostic information beyond existing clinical scoring systems in primary central nervous system lymphoma (PCNSL). This study evaluated whether baseline MRI findings predict survival in immunocompetent PCNSL and assessed the clinical implications of subependymal enhancement for treatment decision-making. Methods: Fifty immunocompetent PCNSL patients treated at a single institution (2010–2024) were retrospectively analyzed. Baseline MRI features, including subependymal enhancement, leptomeningeal spread, and ventricular involvement, were evaluated. Univariate and multivariate Cox analyses were performed for progression-free survival (PFS) and overall survival (OS), and the relationship between subependymal enhancement and chemoradiotherapy outcome was assessed by log-rank and interaction testing. Results: Median PFS and OS were 21.1 and 23.6 months, respectively. On multivariate analysis, subependymal enhancement was the strongest independent predictor of both PFS (hazard ratio [HR] 2.447, 95% confidence interval [CI] 1.164–5.145; p = 0.018) and OS (HR 2.607, 95% CI 1.279–5.313; p = 0.008), and leptomeningeal spread was independently associated with worse OS (HR 3.418, 95% CI 1.473–7.932; p = 0.004). Among patients with subependymal enhancement, chemoradiotherapy was associated with markedly improved PFS (33.5 vs. 3.0 months; p = 0.029) and OS (39.8 vs. 13.4 months; p = 0.029) and a higher complete response rate (100% vs. 0%) compared with chemotherapy alone. No significant chemoradiotherapy benefit was observed in patients without subependymal enhancement (PFS p = 0.332; OS p = 0.907). Conclusions: Subependymal enhancement and leptomeningeal spread independently predict survival in PCNSL. Although subependymal enhancement marks a poor-risk subgroup overall, patients with this feature who received chemoradiotherapy achieved markedly better outcomes, suggesting a role for early chemoradiotherapy in this population. Systematic MRI assessment at diagnosis may guide individualized treatment decisions beyond existing clinical scoring systems.
Objective: Immune checkpoint inhibitor monotherapy has shown limited efficacy in platinum-resistant ovarian cancer (PROC), although a small subset of patients experiences durable disease control. We evaluated the association between baseline systemic inflammatory markers and the clinical outcomes of pembrolizumab monotherapy. Materials and Methods: We included 95 patients with PROC who received pembrolizumab monotherapy at Samsung Medical Center between 2018 and 2023. Durable disease control was defined as a progression-free survival (PFS) ≥ 6 months. The systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII) were calculated from the pretreatment complete blood count. Associations with the PFS and overall survival (OS) were evaluated using multivariable Cox regression. Results: Among 94 patients evaluable for 6-month durable disease control, 10 (10.6%) achieved this endpoint. The patients with durable disease control had a lower baseline SIRI than those without durable disease control (median, 0.7 vs. 1.6; p = 0.019). In multivariable analyses, a higher log-transformed SIRI was associated with a shorter PFS (HR, 1.44; 95% CI, 1.13–1.83; p = 0.003) and OS (HR, 2.02; 95% CI, 1.53–2.67; p < 0.001). Conclusions: The baseline SIRI was associated with the PFS and OS in heavily pretreated patients with PROC receiving pembrolizumab monotherapy, and a lower SIRI was associated with durable disease control. The SIRI may provide readily available prognostic information in this setting; however, the data-derived cutoff requires prospective external validation and should not be interpreted as a predictor of the pembrolizumab-specific benefit.
Background/Objectives: Major pathological response (MPR) has been suggested as a potential surrogate marker for assessing the efficacy of neoadjuvant therapy. However, its prognostic value and association with postoperative recurrence patterns remain unclear in patients with locally advanced oesophageal squamous cell carcinoma (ESCC) treated with neoadjuvant immunochemotherapy. This multicentre study aimed to investigate the relationship between MPR status, survival outcomes, and recurrence characteristics in this population. Methods: A total of 305 patients with locally advanced ESCC who received neoadjuvant immunochemotherapy followed by surgical resection at four medical centres in China between December 2019 and April 2024 were retrospectively enrolled in this study. Prognostic factors for overall survival (OS) and recurrence-free survival (RFS) were analyzed using Cox proportional hazards regression models. Propensity score matching (PSM) was performed to balance baseline characteristics between patients with and without MPR, and survival outcomes and postoperative recurrence patterns were subsequently compared. Results: Among the 305 patients, 115 (37.7%) achieved MPR. Multivariate analysis identified MPR and the number of neoadjuvant treatment cycles as independent prognostic factors for both OS and RFS (p < 0.05). After PSM, patients with MPR showed significantly improved OS and RFS compared with those without (p < 0.05). Postoperative recurrence occurred less frequently in the MPR group than in the non-MPR group (13.9% vs. 42.1%, respectively; p < 0.05), with reductions in both locoregional and distant recurrence. Conclusions: In patients with locally advanced ESCC receiving neoadjuvant immunochemotherapy and surgery, achieving MPR is associated with improved survival outcomes and a lower risk of postoperative recurrence. MPR may serve as a useful prognostic indicator for this population.
Background/Objectives: Uterine adenosarcoma is a rare uterine malignancy with limited evidence on prognostic factors and long-term outcomes. We aimed to evaluate clinicopathological characteristics, treatment patterns, oncologic outcomes, and prognostic factors associated with disease-free survival (DFS) and overall survival (OS) in patients with uterine adenosarcoma. Methods: This multicenter retrospective cohort study included 43 patients with histopathologically confirmed uterine adenosarcoma who underwent primary surgery at seven tertiary referral centers in Türkiye between 2016 and 2026. Clinicopathological features, treatment modalities, recurrence patterns, and survival outcomes were assessed. Survival was analyzed using Kaplan–Meier and log-rank methods, and multivariable Cox proportional hazards regression was performed to identify independent prognostic factors. Results: The mean age at diagnosis was 59.1 ± 10.8 years, and 83.7% of patients were postmenopausal. Pelvic pain (62.8%) and abnormal uterine bleeding (60.5%) were the most common presenting symptoms. Most patients (79.1%) underwent laparotomy, and 79.1% had stage I disease. Sarcomatous overgrowth (SO) was present in 44.1% and lymphovascular space invasion (LVSI) in 18.6%. During a median follow-up of 72 months, 34.9% experienced recurrence, most commonly in the pelvis. The five-year DFS and OS rates were 59.9% and 80.4%, respectively. SO was independently associated with DFS (HR 4.41, 95% CI 1.21–16.08; p = 0.025) and OS (HR 10.23, 95% CI 1.16–89.80; p = 0.036), while LVSI was independently associated with OS (HR 11.17, 95% CI 1.34–93.14; p = 0.026). Conclusions: Uterine adenosarcoma showed favorable long-term survival but substantial recurrence risk. SO and LVSI may have potential prognostic relevance and could contribute to postoperative risk assessment and individualized follow-up.
Background/Objectives: Proton therapy provides superior dose conformity and better normal tissue sparing than conventional radiotherapy but is limited by its relatively low relative biological effectiveness (RBE). Nanoparticles have emerged as promising proton radiosensitizers capable of enhancing physical dose deposition and biological responses. Methods: A narrative literature review was conducted using PubMed, Scopus, Web of Science, and Google Scholar. Results: Gold nanoparticles were the most extensively studied radiosensitizers, while platinum, gadolinium, hafnium oxide, titanium dioxide, iron oxide, and other nanoparticles also demonstrated promising radiosensitizing effects. Evidence indicates that nanoparticles enhance local dose deposition, increase LET and ROS production, promote DNA damage, and improve tumor control. Conclusions: Nanoparticle-assisted proton therapy represents a promising strategy for improving cancer treatment by increasing therapeutic efficacy while preserving healthy tissues. Although preclinical studies demonstrate significant improvements in therapeutic efficacy, challenges related to tumor targeting, biodistribution, safety, and clinical validation remain. Further research is required to facilitate clinical implementation.
Background: Adjuvant radiotherapy (RT) may improve in-field regional tumor control in melanoma following resection of lymph node macrometastases. However, no significant effect on recurrence-free survival or overall survival has been demonstrated. The approval of adjuvant systemic immune checkpoint inhibitors and targeted therapies has significantly impacted the role of adjuvant RT. Its use in clinical practice has decreased, with heterogeneous treatment indications and approaches observed across institutions and regions. Objectives: The aim of the present study was to characterize the population of melanoma patients still undergoing adjuvant RT in the era of modern adjuvant systemic treatments, and to outline potential clinical scenarios in which it may continue to play a role in the future. Patients and methods: Fifty-eight patients treated with adjuvant RT were identified in five participating Austrian and Swiss dermato-oncologic centers. Treatment timing, toxicity, recurrence patterns, and survival outcomes were analyzed, and compared to 88 stage-matched, non-irradiated patients from a German cohort of patients who met formal RT criteria. Results: The majority of irradiated patients (53.5%) received RT before systemic therapy. The concurrent administration of adjuvant systemic therapy and radiotherapy did not increase the frequency of RT-associated toxicities (77.8% vs. 74.2%, p = 0.456). No significant differences in recurrence-free survival or overall survival were observed between irradiated and non-irradiated patients (p = 0.725 and p = 0.986, respectively). Conclusions: Although still recommended in certain melanoma guidelines, adjuvant RT is infrequently performed in the era of modern systemic treatments. Due to its exclusively locoregional efficacy, the application of adjuvant RT should be limited to clearly defined scenarios where systemic treatment options are limited and locoregional control is most important. The concurrent administration of adjuvant RT and systemic therapy is safe and should be preferred if a combined treatment strategy is chosen.
Background and Aims: Hepatocellular carcinoma (HCC) is frequently diagnosed at an advanced stage, and serum alpha-fetoprotein (AFP), the most widely used biomarker for HCC surveillance, exhibits substantial interpatient variability. However, longitudinal AFP patterns preceding HCC diagnosis and their clinical correlates remain incompletely characterized. We aimed to characterize pre-diagnostic AFP trajectories and identify clinical features associated with rising versus non-rising AFP patterns. Methods: We analyzed 529 patients with newly diagnosed HCC at Songklanagarind Hospital, each with at least three serum AFP measurements obtained within five years before diagnosis. Log-transformed AFP values were modeled using latent class mixed models with natural cubic splines and linear fixed and random effects. The optimal model was selected based on Bayesian Information Criterion (BIC), entropy, and clinical interpretability. Multinomial logistic regression and Cox proportional hazards models were used to evaluate associations between AFP trajectory class, baseline characteristics, and overall survival. Results: A two-class natural spline model (df = 3) provided the optimal fit (BIC = 9003). The non-rising trajectory (n = 440; 83.2%) showed stable AFP levels throughout follow-up, whereas the rising trajectory (n = 89; 16.8%) demonstrated exponential increase beginning 18–24 months before diagnosis. Compared to the non-rising group, patients in the rising group were significantly more likely to present with tumors >2 cm (78% vs. 62%; p = 0.009). The rising trajectory was associated with shorter overall survival in univariable analysis (hazard ratio [HR] 1.33, 95% confidence interval [CI] 1.02–1.73; p = 0.033), but not after adjustment for clinical and tumor characteristics, including Barcelona Clinic Liver Cancer stage (adjusted HR 1.01, 95% CI 0.77–1.33; p = 0.920). Conclusions: Two distinct AFP trajectories precede HCC diagnosis. Most patients did not demonstrate a substantial rise in AFP, underscoring the need for complementary surveillance biomarkers. Prospective validation in independent cohorts is required before AFP trajectory-based approaches can be incorporated into HCC surveillance practice. These findings are exploratory and hypothesis-generating rather than a validated clinical prediction tool.
Background: Prostate cancer (PC) is a heterogeneous disease in which the histopathological grade does not always reflect underlying biological behavior. While transcriptomic studies have provided insight into tumor biology, grade-associated molecular changes remain incompletely defined, particularly in underrepresented populations such as those from the Middle East and North Africa (MENA) region. Methods: In this study, we used a pathology-guided transcriptomic approach to examine gene expression patterns across PC grades in a MENA cohort. RNA sequencing was performed on formalin-fixed paraffin-embedded (FFPE) tissues, including benign prostatic hyperplasia (BPH, n = 7), low-grade tumors (Gleason 6–7 [3 + 4]; LG; n = 7), and high-grade tumors (Gleason 7 [4 + 3]–10; HG; n = 7). Differential expressions, pathway-level enrichment analyses and the estimation of immune cell composition were carried out, followed by comparison with publicly available datasets (TCGA-PRAD, n = 496), including LG tumors (n = 292) and HG tumors (n = 204), using the GEPIA2 and UALCAN platforms. Selected genes were further assessed using qRT-PCR in an independent set of samples (n = 21). Representative immunohistochemical images from the Human Protein Atlas were reviewed to provide descriptive protein-level context across tumor grades. Results: Transcriptomic comparisons of tumor samples with benign controls identified a set of shared transcriptional changes present in both low- and high-grade disease. Among these, SLC29A2 and IL2RA showed consistent upregulation across tumor grades and similar expression trends in external datasets. Direct comparison between HG and LG tumors revealed distinct transcriptional profiles with patterns indicative of increased proliferative activity and altered immune-related signaling in higher-grade disease. Pathway-level analyses showed the enrichment of cell-cycle and metabolic gene signatures in HG tumors, whereas inflammatory and NF-κB-associated transcriptional signatures showed a comparatively reduced expression. Additional genes, including AAMDC, ASAH2, TNFRSF1B, NFKBIL1, and NFKBIZ, were associated with these grade-dependent differences. qRT-PCR findings were generally consistent with the RNA-seq results for selected targets. Conclusions: This study describes transcriptional patterns associated with the PC grade in a MENA cohort using a pathology-guided framework. The findings highlight candidate genes associated with tumor presence and grade progression and provide a foundation for further investigation in larger, well-annotated cohorts, particularly in populations that remain underrepresented in transcriptomic studies.
Background: Secondary acute promyelocytic leukemia (sAPL) is a very rare subtype of acute myeloid leukemia that develops following exposure to chemotherapy, radiotherapy, or immunosuppressive agents. The treatment results and survival outcomes of sAPL patients are still not precisely defined. Methods: A search of the Polish Adult Leukemia Group (PALG) database identified 29 cases of sAPL (median age 57 years; 62.1% female) among 437 APL patients (6.7%) diagnosed between 2006 and 2024. Each sAPL case was matched to a de novo APL patient by sex, age, year of diagnosis, and treatment protocol (LPA (Leucemia Promielocítica Aguda) 2005, LPA 2012, or LPA 2017). Results: All sAPL cases occurred following chemo- and/or radiotherapy, most commonly for breast cancer. The sAPL cases demonstrated higher CD15 expression than the de novo APL cases (median 27.6% vs. 7%, p = 0.04). The two groups exhibited comparable complete remission rates (82.8% sAPL vs. 75.9% de novo; p = 0.75) and early mortality rates (17.2% vs. 20.7%, p = 1.0). However, relapse-free survival was significantly shorter in sAPL (median 94.7 months vs. not reached; HR 7.23, 95% CI 1.63–32.02, p = 0.030), whereas overall survival did not differ significantly between groups. Multivariate analysis identified Eastern Cooperative Oncology Group performance status ≥3 and CD15 expression > 20% as independent predictors of inferior survival. Conclusions: These findings suggest that sAPL shares many clinical features with de novo APL but carries a higher risk of relapse, highlighting the need for further prospective studies and the potential implementation of tailored therapeutic strategies.
Background: Accurate pancreatic tumor segmentation on contrast-enhanced computed tomography (CECT) is important for staging, treatment planning, and response assessment in pancreatic ductal adenocarcinoma (PDAC). Although foundation models have shown promise for medical image segmentation, their effectiveness for disease-specific tumor delineation remains uncertain. This study evaluated whether fine-tuning a Segment Anything Model (SAM)-based framework on the target cohorts improves pancreatic tumor segmentation compared with directly applied foundation models. Methods: In this retrospective multicenter study, CECT examinations from patients with pathologically confirmed PDAC acquired between 2015 and 2025 were included. Two foundation model baselines, nnInteractive and MedSAM2, were compared with three TAGS-based configurations representing increasing levels of adaptation: TAGS (Zero-Shot), SAM-TAGS (fine-tuned from SAM weights), and MSD-TAGS (fine-tuned from a pancreas-specific checkpoint). Performance was assessed using patient-level five-fold cross-validation with the Dice Similarity Coefficient (DSC) and Normalized Surface Dice (NSD). A leave-one-center-out analysis was additionally performed to evaluate generalization to institutions absent from training. Results: A total of 500 patients with PDAC from four independent centers were included. MSD-TAGS achieved the highest overall segmentation performance, with a mean DSC of 0.703 and a mean NSD of 0.835. SAM-TAGS achieved a mean DSC of 0.691 and a mean NSD of 0.822. In comparison, nnInteractive achieved a mean DSC of 0.632 and a mean NSD of 0.782; MedSAM2, 0.585 and 0.792; and TAGS (Zero-Shot), 0.496 and 0.639, respectively. Compared with each competing method, MSD-TAGS achieved significantly higher DSC and NSD values (all Holm-adjusted p < 0.001). It also achieved the highest DSC across all four centers and the highest NSD in three of the four centers. Under leave-one-center-out evaluation, MSD-TAGS declined by 0.025 DSC and SAM-TAGS by 0.089. Conclusions: Task-specific adaptation improved pancreatic tumor segmentation with foundation models, and fine-tuned TAGS outperformed two publicly released promptable models applied without adaptation. Models initialized from a pancreas-specific checkpoint showed greater robustness under center-held-out evaluation. These findings support the importance of organ-specific initialization and target-cohort fine-tuning for disease-specific segmentation and warrant further validation before clinical translation. The multicenter pancreatic tumor CT segmentation dataset, including de-identified images and expert segmentation annotations, is publicly available to facilitate future research.
Background: Approximately 13% of NSCLC cases have KRAS G12C mutations. As therapeutic strategies targeting KRAS G12C-mutant NSCLC evolve, it is important to understand clinical presentation and current outcomes for these patients. Methods: This retrospective study used data from two US nationwide databases, an electronic health records (EHR) database and a clinico-genomic database (CGDB) of EHR data linked to data from comprehensive genomic profiling tests. Eligible patients had advanced NSCLC, initiated first-line therapy from August 2018 to December 2022, and had KRAS test results. Clinicopathologic characteristics, treatments, real-world progression-free survival (rwPFS), and overall survival (OS) were analyzed. Results: There were 1227 patients with KRAS G12C-mutant NSCLC in the EHR database and 447 in the CGDB. First-line regimen was platinum-based chemotherapy plus pembrolizumab for 46% and pembrolizumab monotherapy for 20%. Less than 40% of patients received second-line therapy. Median (95% CI) OS for KRAS G12C-mutant NSCLC patients in the EHR was 17.0 (15.2–18.9) months. Variables significantly associated with shorter OS included PD-L1 <1%, brain metastases, STK11 co-mutation, and poor performance status. Patients treated with platinum-based chemotherapy plus pembrolizumab had median rwPFS of 5.3 (4.5–7.3) months and OS of 12.8 (11.1–17.3) months in the CGDB; median OS was 15.6 (12.5–18.6) months in the EHR. Patients with PD-L1 ≥ 50% treated with pembrolizumab monotherapy had median rwPFS of 4.6 (3.0–15.6) months and OS of 20.4 (10.3–38.5) months in the CGDB; median OS was 22.1 (18.7–30.7) in the EHR. Conclusions: These data provide a real-world benchmark of outcomes for patients with KRAS G12C-mutant NSCLC receiving the current standard of care and indicate an unmet need for more effective first-line therapies.
Background: South Asian Americans (SAAs) represent the fastest-growing U.S. immigrant group but remain underrepresented in breast cancer research. This study utilizes the National Cancer Database (NCDB) to evaluate differences in tumor characteristics, treatment patterns, and survival outcomes between SAAs and non-Hispanic Whites (NHWs). Materials and Methods: A retrospective cohort analysis was conducted using NCDB data from 2004–2021. Women with breast cancer were stratified by race/ethnicity (SAA vs. NHW), and demographic, clinical, and treatment variables were compared. Outcomes assessed were overall survival (OS) and treatment delays, defined as initiation of surgery, chemotherapy, or radiation therapy > 60 days after diagnosis. Multivariable Cox proportional hazards models assessed OS. Results: Among 2,363,627 patients, 20,561 (0.9%) were SAAs and 2,343,066 (99.1%) NHWs. SAAs were younger at diagnosis, with 37.6% aged 20–49 vs. 20.6% of NHWs (p < 0.001). Insurance coverage differed, with SAAs more likely privately insured (63.0% vs. 54.2%, p < 0.001), less likely on Medicare (17.2% vs. 37.9%), and more often uninsured (4.5% vs. 1.2%). Time to first treatment was longer for SAAs (39.55 vs. 37.17 days, p < 0.001). Surgical delays >60 days increased mortality by 59%, while chemotherapy delays raised it by 44%. SAAs demonstrated higher survival at 5, 10, and 15 years (93%, 87%, 81%) vs. NHWs (87%, 76%, 64%). Median survival was 225.8 months but not estimable for SAAs. SAAs presented with aggressive subtypes: triple-negative and HER2-positive tumors. Conclusions: SAAs present younger with aggressive subtypes and treatment delays yet maintain survival advantages; reducing care barriers and clarifying tumor biology are vital to improving outcomes.
Background/Objectives: Cutaneous squamous cell carcinoma (cSCC) is a highly prevalent malignancy. While Cemiplimab has transformed the treatment landscape across various disease stages, reliable pretreatment biomarkers for risk stratification remain lacking.. The Global Immune–Nutrition–Inflammation Index (GINI) is a composite biomarker integrating systemic inflammation and nutritional status into a single score. This study aimed to evaluate the prognostic value of the pretreatment GINI in patients with cSCC receiving Cemiplimab across all treatment settings. Methods: This retrospective cohort study evaluated 73 patients with unresectable, locally advanced, or metastatic cSCC treated with Cemiplimab between 2020 and 2023. Pretreatment laboratory parameters were extracted to calculate the GINI score. Receiver operating characteristic (ROC) curve analysis determined the optimal GINI cutoff to stratify patients into low- and high-GINI groups. Survival outcomes, including overall survival (OS) and progression-free survival (PFS), were analyzed using Kaplan–Meier curves and multivariable Cox proportional hazards models. Results: An optimal GINI cutoff of 74.4 divided the cohort into low-GINI (38%) and high-GINI (62%) groups. In the multivariable Cox regression models, a high pretreatment GINI remained independently associated with both inferior OS (adjusted HR 2.51, 95% CI 1.05–6.01, p = 0.039) and inferior PFS (adjusted HR 3.22, 95% CI 1.45–7.14, p = 0.004). When compared against five established inflammatory biomarkers (NLR, PLR, LMR, PNI, and CAR), the GINI consistently demonstrated comparable prognostic performance across multiple statistical approaches. Conclusions: The pretreatment GINI is a candidate prognostic marker for patients with cSCC undergoing Cemiplimab therapy. Given its cost-effectiveness and ready availability from routine clinical laboratory workups, the GINI score may improve prognostic risk stratification and could potentially inform risk assessment and clinical monitoring in real-world oncological practice.
Complete resection remains the only potentially curative treatment for localized intrahepatic cholangiocarcinoma (iCCA), yet postoperative recurrence is common, particularly in patients with high-risk disease. Neoadjuvant systemic therapy may permit earlier control of occult micrometastatic disease, optimize the delivery of systemic treatment, and provide an in vivo assessment of tumor biology prior to major hepatectomy. These potential benefits must be balanced against treatment-related toxicity, surgical delay, and the risk of disease progression precluding resection. Early evidence was primarily derived from retrospective studies, which yielded inconsistent survival outcomes and exhibited substantial vulnerability to confounding and treatment-selection bias. The single-arm NEO-GAP trial subsequently demonstrated the feasibility of administering neoadjuvant gemcitabine, cisplatin, and nab-paclitaxel followed by surgical resection. More recently, the randomized phase II–III ZSAB-neoGOLP trial showed that neoadjuvant gemcitabine–oxaliplatin, lenvatinib, and toripalimab followed by surgery prolonged median event-free survival compared with upfront surgery (median: 18.0 vs. 8.7 months) without substantially compromising surgical feasibility. However, the interim overall survival analysis was inconclusive, and the generalizability of these findings beyond selected, medically fit patients treated at Chinese centers remains uncertain. This narrative review critically appraises the evolving evidence, discusses patient selection and perioperative treatment, and identifies priorities for future research. Current evidence supports the selective consideration of neoadjuvant therapy in medically fit patients with technically resectable but oncologically high-risk iCCA, rather than its routine use in all resectable cases.
Background: Comorbidity is an important determinant of treatment selection and in-hospital complications in patients with head and neck cancer (HNC) and thyroid cancer (TC), yet population-based evidence on this relationship remains limited. Methods: We analyzed nationwide Diagnosis-Related Groups (DRG) data from 1,552,028 inpatient HNC and TC treatments of patients aged ≥30 years in Germany between 2005 and 2021. The aim was to characterize the association of comorbidity and severe treatment-related procedure-coded inpatient events (IEs) with gender, age, tumor subsite, and treatment type. Results: The largest proportion of treatments occurred in patients aged 60–69 years (33.5%). The most frequent tumor subsites were the oropharynx, thyroid gland, oral cavity, larynx, and hypopharynx, with 35.52, 33.84, 33.60, 26.12, and 15.76 treatments per 100,000 population per year, respectively. Overall, 38% of cases had a Charlson Comorbidity Index (CCI) ≥ 1, with the highest mean CCI observed for C14 (other sites of the lip, oral cavity and pharynx) and C12 (piriform sinus). IEs requiring additional in-hospital treatment occurred in 19.3% of cases. After adjustment for age, tumor location, and treatment type, men had a lower risk of IEs than women (OR 0.929; CI 0.919–0.939; p < 0.001). Increasing comorbidity was associated with a higher IE risk, reaching a plateau at CCI ≥ 4 (OR 2.135; CI 2.029–2.246; p < 0.001). IE risk was high during chemotherapy/immunotherapy (OR 29.527; CI 28.897–30.170; p < 0.001), followed by surgery (OR 3.465; CI 3.433–3.498; p < 0.001), whereas radiotherapy showed the lowest risk (OR 1.339; CI 1.313–1.366; p < 0.001). Conclusions: These findings highlight substantial heterogeneity in comorbidity and IE risk among patients with HNC or TC.
Background: Stage II/IIIA colorectal cancer (CRC) patients have a relatively high 5-year overall survival rate after surgical resection alone, but more than 50% of patients receive adjuvant chemotherapy. This study investigates a technology that applies artificial intelligence (AI) to conventional histopathology images to identify patients at risk of recurrence. Methods: HistoNav, a novel AI deep-learning algorithm based on Vision Transformer, Graph Neural Networks and Convolutional Neural Networks was designed to analyse H&E-stained formalin-fixed paraffin-embedded (FFPE) samples (n = 2095) to stratify Stage II/IIIA CRC patients into low-, intermediate-, and high-risk groups. Results: Data analysis revealed a 5-year disease-specific survival (DSS) of 93.2%, 84.3%, and 69.3% for low-, intermediate-, and high-risk groups, respectively. The hazard ratio for the high versus low-risk group (HR = 4.611, 95% CI: 2.776–7.662; p < 0.000001) was statistically significant, demonstrating HistoNav’s potential to stratify patients based on recurrence risk. Conclusions: HistoNav can effectively identify CRC patients with good prognosis using the digital images of H&E-stained resection samples and will support clinical decisions around the use of adjuvant chemotherapy.
This review aims to provide a comprehensive overview of the currently available therapies for primary vitreoretinal lymphoma (PVRL) and to evaluate emerging therapeutic strategies that may improve patient outcomes. A comprehensive literature search was conducted in databases including PubMed/MEDLINE, Embase, and Scopus for studies published up to 2026. Search terms included “primary vitreoretinal lymphoma”, “intravitreal methotrexate”, “rituximab”, “radiotherapy”, “targeted therapy”, and “immunotherapy”. Eligible publications included randomized controlled trials, prospective and retrospective studies, observational studies, systematic reviews, relevant clinical guidelines, case series, and case reports. Studies were independently screened and assessed by two reviewers. Current therapeutic strategies include intravitreal chemotherapy, systemic high-dose methotrexate-based regimens, and radiotherapy, either as monotherapy or in combination. While intravitreal approaches provide effective local disease control, they fail to address occult or subsequent central nervous system (CNS) dissemination, necessitating the use of systemic treatments in selected patients. In recent years, significant progress in the understanding of PVRL pathophysiology, including the role of MYD88 mutations and interleukin-10 signaling, has paved the way for the development of targeted and immunomodulatory therapies. Agents such as Bruton’s tyrosine kinase inhibitors, immunomodulatory drugs, and immune checkpoint inhibitors have demonstrated promising results in early clinical studies, particularly in relapsed or refractory disease. Despite advances in diagnostic techniques, the management of PVRL remains challenging due to its heterogeneous presentation, high relapse rates, and frequent progression to CNS involvement.
Background: Multiple myeloma (MM) remains an incurable plasma cell malignancy characterized by marked clinical heterogeneity. Existing prognostic frameworks, including the International Staging System (ISS) and FISH-defined cytogenetic risk, are anchored at diagnosis and do not capture the evolutionary dynamics of disease or treatment response, leaving an unmet need for risk models that retain prognostic validity longitudinally. Methods: Using transcriptomic data from 762 CD138-selected MM plasma cells from newly diagnosed patient samples in the MMRF CoMMpass study (NCT01454297), we computed single-sample pathway activity scores for 469 curated cancer-relevant pathways (MSigDB Hallmark; Reactome) and learned a Bayesian causal network linking pathway activity to survival. The model was validated in five independent diagnostic cohorts (n = 1255) and in two independent treatment and relapsed/refractory cohorts (n = 319). Longitudinal risk tracking was additionally assessed in a 46-patient subset of the discovery cohort with serial pre- and post-treatment sampling. Results: The network identified five pathways associated with survival: unfolded protein response (UPR), FLT3 signaling through SRC family kinases, G2M DNA replication checkpoint, metabolism of selenium compound (SeMet), and nicotinate metabolism. The composite survival score stratified patients into high-risk (n = 76; 10%) and standard-risk groups with markedly divergent survival (median 1170 days vs. not reached; p < 0.0001). The score remained an independent prognostic factor after adjustment for age, sex, ISS stage, and KRAS, TP53, and UBR5 mutational status (HR 4.93; 95% CI 2.96–8.19; p < 0.001), and replicated across all five external diagnostic cohorts. Critically, the model retained prognostic discrimination in previously treated (GSE57317; p < 0.0001) and relapsed/refractory (GSE9782; p < 0.0001) settings, and patients transitioning from standard- to high-risk between serial samples exhibited significantly inferior survival compared to standard-risk patients. Conclusions: This pathway-based Bayesian network provides a reproducible, dynamically applicable risk model for MM that captures information complementary to ISS and FISH-defined cytogenetics. The framework supports longitudinal patient monitoring and may inform trial enrichment strategies and closer surveillance for high-risk subpopulations.
Background/Objectives: Renal mass biopsy (biopsy) is increasingly incorporated into the evaluation of localized renal masses, yet its role in guiding management remains variable among clinical practices. We evaluated the clinical association of biopsy using a simplified classification system categorizing biopsy results as Biopsy Actionable for Immediate Treatment (BAIT) or Biopsy Actionable for Active Surveillance (BAAS)—assessing how biopsy-derived histology influences real-world management. Methods: We identified all patients undergoing biopsy for a renal mass measuring 2–7 cm at a single academic center between 2010 and 2025. After excluding nondiagnostic biopsies, repeat biopsies, and biopsies performed for metastatic diagnosis, 1395 patients formed the analytic cohort. Histologic subtypes and initial treatment were evaluated. Multivariable logistic regression assessed predictors of (1) radical versus partial nephrectomy, (2) surgery versus thermal ablation, and (3) active surveillance versus intervention, adjusting for tumor diameter, age, and BAIT/BAAS status. Results: Of 1395 patients, 1119 (80.2%) had BAIT pathology and 276 (19.8%) had BAAS pathology. Initial management included surgery (36.3%), thermal ablation (36.3%), active surveillance (24.2%), no treatment (1.7%), and radiation (1.5%). BAAS pathology was strongly associated with the selection of active surveillance (OR 21.80, p < 0.001). Larger tumor diameter was the principal driver of radical nephrectomy (OR 2.04/cm, p < 0.001) and of choosing surgery over ablation (OR 2.05/cm, p < 0.001). Younger age was associated with selection of surgery over ablation (OR 0.93/year, p < 0.001). Biopsy histology showed a stronger association with surveillance selection than either tumor diameter or age. Conclusions: Biopsy provides actionable diagnostic information for patients with 2–7 cm renal masses, identifying benign or indolent pathology in nearly one in five patients. BAIT/BAAS categorization was strongly associated with the selection of active surveillance for renal masses.
