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Objective: This study aims to elucidate the therapeutic efficacy and safety of a taxane-based chemotherapy in combination with immune checkpoint inhibitors regimen in patients diagnosed with recurrent or metastatic head and neck squamous cell carcinoma (HNSCC). Methods: We retrospectively collected clinical data from 154 patients who received at least two cycles of PD-1 inhibitors in combination with a taxane-based chemotherapy as first-line treatment in seven hospitals in Hunan Province, between December 2018 and December 2023. These patients were subjected to long-term follow-up. Results: The study included 154 eligible patients, with a median follow-up period of 21.5 months. The median PFS was 8.7 months, while the median OS was 16.7 months. The 12-month PFS rate was 43.6%, and the 12-month OS rate was 60.1%. At 24 months, the PFS rate was 34.4%, and the OS rate was 36.9%. With 26 complete responses (16.9%) and 52 partial responses (33.8%), the ORR was 50.6%. Stable disease was observed in 54 patients (35.1%), resulting in a disease control rate of 85.7%, while 22 patients showed progressive disease. In the univariate analysis, the distant organ metastasis had a statistically significant impact on both PFS and OS. Subsequent radiotherapy following this protocol also showed a statistically significant effect on PFS and OS. However, radiotherapy before recurrent metastasis did not significantly affect PFS, though it did have a significant impact on OS. Other factors analyzed did not show a statistically significant effect on PFS and OS. Multivariate analysis indicated that the distant organ metastasis and subsequent radiotherapy following this protocol were independent prognostic factors for PFS in patients with R/M HNSCC, and the latter was also an independent prognostic factor for OS in these patients. Regarding safety, during treatment anemia was observed in 97 patients, leukopenia in 64, neutropenia in 33, thrombocytopenia in 28, transaminase elevation in 46, hypothyroidism in 46 patients, and one patient stopped taking the medication due to a serious adverse reaction. No treatment-related deaths occurred. Conclusion: The combination of PD-1 inhibitors with a a taxane-based chemotherapy regimen as a first-line treatment for R/M HNSCC patients demonstrates good therapeutic efficacy and acceptable safety profiles. [ABSTRACT FROM AUTHOR]

Background: Osteosarcoma is a malignant tumor originating from mesenchymal bone tissue, characterized by high malignancy and poor prognosis. Despite progress in comprehensive treatment approaches, the five-year survival rate remains largely unchanged, highlighting the need to clarify its underlying mechanisms and discover new therapeutic targets. Methods: This study utilized RNA sequencing data from multiple public databases, encompassing osteosarcoma samples and healthy controls, along with single-cell RNA sequencing data. Various methods were utilized, such as differential expression analysis of genes, analysis of metabolic pathways, and weighted gene co-expression network analysis (WGCNA), to pinpoint crucial genes. Using this list of genes, we developed and validated a prognostic model that incorporated risk signatures, and we evaluated the effectiveness of the model through survival analysis, immune cell infiltration examination, and drug sensitivity evaluation. Results: We analyzed gene expression and metabolic pathways in nine samples using single-cell sequencing data. Initially, we performed quality control and clustering, identifying 21 statistically significant cell subpopulations. Metabolic analyses of these subpopulations revealed heterogeneous activation of metabolic pathways. Focusing on the osteoblastic cell subpopulation, we further subdivided it into six groups and examined their gene expression and differentiation capabilities. Differential expression and enrichment analyses indicated that tumor tissues were enriched in cytoskeletal and structural pathways. Through WGCNA, we identified core genes negatively correlated with four highly activated metabolic pathways. Using osteosarcoma patient data, we developed a risk signature model that demonstrated robust prognostic predictions across three independent cohorts. Ultimately, we performed a thorough examination of the model, which encompassed clinical and pathological characteristics, enrichment analysis, pathways associated with cancer markers, and scores of immune infiltration, highlighting notable and complex disparities between high-risk and low-risk populations. Conclusion: This research clarifies the molecular mechanisms and metabolic features associated with osteosarcoma and how they relate to patient outcomes, offering novel perspectives and approaches for targeted therapy and prognostic assessment in osteosarcoma. [ABSTRACT FROM AUTHOR]

Background: Peripheral T-cell lymphomas (PTCL) are an aggressive group of mature T-cell neoplasms, often associated with poor outcomes, in part, due to frequent relapsed/refractory disease. The objective of this study was to assess the prognostic impact of disease progression within 24 months (POD24) on overall survival (OS) for patients diagnosed with PTCL. Methods: A retrospective analysis was conducted on a cohort of patients with newly diagnosed PTCL who underwent chemotherapy at the Affiliated Hospital of Xuzhou Medical University between January 2010 and September 2021. Prognostic assessment was limited to patients who were evaluable for POD24. Results: Records were reviewed for 106 patients with PTCL, of whom 66 patients experienced POD24 (referred to as the POD24 group) and 40 patients did not experience POD24 (referred to as the no POD24 group). Significant differences were observed between the POD24 group and the no POD24 group in regard to clinical stage, Eastern Cooperative Oncology Group (ECOG) performance status (PS), International Prognostic Index (IPI) score, lactate dehydrogenase (LDH) levels, β2-microglobulin (β2-MG) levels, prealbumin and albumin levels. Patients in the POD24 group had a significant shorter median OS compared to the no POD24 group (11.9 months vs not reached, respectively; P < 0.001). Non response (NR) to treatment and POD24 were identified as independent negative prognostic factors for survival in patients with PTCL. Conclusion: POD24 is a prognostic factor associated with unfavorable outcomes in patients with PTCL and can be used to identify high-risk patients and guide treatment decisions. [ABSTRACT FROM AUTHOR]

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Abstract Objectives To analyze the risk factors for developing dysphagia after occipitocervical fusion (OCF) and investigate possible mechanisms and prognosis. Methods The case data of 43 patients who underwent OCF were retrospectively reviewed. Patients were divided into group A (dysphagia group) and group B (non-dysphagia group) based on Bazaz scoring criteria. Baseline data and imaging parameters were collected: O-C2 angle, C2-7 angle, pharyngeal inlet angle (PIA), posterior occipital cervical angle (POCA), O-EA angle, Oc-Ax angle, Atlas-dens interval, C2-7 sagittal vertical axis (SVA), T1 slope, narrowest oropharyngeal airway space (nPAS), and thickness of the prevertebral soft tissue. Potential risk factors were identified via one-way intergroup comparisons and included in multivariable logistic regression analysis. Pearson or Spearman correlation analysis was performed to assess associations between dnPAS% and each parameter and inter-parameter correlations. Predictors were selected to plot receiver operating characteristic (ROC) curves for diagnostic evaluation. Prognosis was analyzed using the Kaplan-Meier method and curvilinear regression. Results Dysphagia occurred in 17 of 43 patients (39.53%). By the final follow-up (≥ 12 months), 11 patients (25.58%) had residual symptoms. Baseline factors, including dyspnea (P = 0.028), operative segment (P = 0.021), operative time (P = 0.006), anesthesia time (P = 0.025), solitude (P = 0.019), and satisfaction (P -8° being less likely to develop dysphagia. However, only ~ 30% of patients achieve full recovery.

Abstract Background Heart failure (HF) significantly impacts quality of life and healthcare systems worldwide. Assessing left ventricular mechanical dyssynchrony (LVMD) is crucial for understanding cardiac function and optimizing treatments like cardiac resynchronization therapy (CRT). Phase analysis using gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has shown promise in predicting outcomes, yet recent comprehensive reviews are lacking. Objective To systematically assess the prognostic value of phase analysis by gated SPECT MPI in the HF population through a systematic review. Methods We conducted a systematic review by collecting studies from databases including PubMed, CINAHL, and Web of Science. Two reviewers independently performed study selection, data extraction, and risk of bias assessment. Systematic reviews were conducted using Review Manager Software 5.4 and STATA 16.0. Results A total of 2004 patients from seven studies were included in our review and analysis. The systematic review indicated that patients with predetermined clinical events had higher PSD [MD = 6.45, 95% CI (5.83, 7.07), p

Abstract Multiple myeloma (MM) is a common hematological malignancy, and its prognostic factors have been extensively studied. Progression of disease within 24 months (POD24) suggests a poor prognosis in many malignancies, but is rarely mentioned in MM. This study aimed to investigate the prognostic value of POD24 in MM and risk factors of POD24, and to evaluate the predictive value of existing MM prognostic models for POD24. The research retrospectively analyzed the clinical data of MM patients and found that the occurrence of POD24 is an independent prognostic factor affecting overall survival in MM, while non-transplantion and genetic abnormality are independent risk factors for the occurrence of POD24. The existing prognostic models are not effective in predicting POD24. Therefore, it’s still necessary to explore a prognostic model that can predict POD24 more accurately.

Ovarian cancer ranks among the deadliest gynecological malignancies, with high-grade serous adenocarcinoma (HGSA) constituting 75 % of ovarian cancer cases and accounting for 80 %–90 % of ovarian cancer-related fatalities. Accurate prognosis prediction for ovarian HGSA is of critical clinical significance. However, existing prognostic analysis methods exhibit suboptimal performance in identifying prognostically relevant pathological markers, making it challenging, even for experienced pathologists, to forecast the prognosis of ovarian HGSA patients accurately. Deep learning holds promise in enhancing prognostic prediction accuracy. However, a significant challenge in this field arises from the impracticality of directly inputting histopathology whole-slide images with millions to billions of pixels into existing deep learning networks for training and inference. To address this issue, we propose a prognostic analysis network for ovarian cancer based on hierarchical sampling and fine-grained recognition. This network comprises a two-stage hierarchical sampling sub-network, a fine-grained image recognition sub-network, and a prognostic analysis sub-network. We assess the system's performance using a pathological dataset of 450 cases of ovarian HGSA diagnosed and treated at the Pathology Department of the West China Second University Hospital of Sichuan University. Results indicate that: (1) The proposed prognostic analysis network based on two-stage hierarchical sampling sub-network can effectively analyze the histopathology whole-slide image; (2) the use of fine-grained image recognition and the introduction of clinical information can improve the performance of HGSA prognosis analysis method, with an improvement range of 4.77–10.66%; and (3) the proposed method can be used for the model analysis of pathological datasets of HGSA. Moreover, this method can be used to explore effective characteristics from the multi-modal dataset through automatic learning with prediction recall, accuracy, and precision rates of 80.0%, 81.1%, and 81.8%, respectively, underscoring its clinical potential. This study reveals the reliability and effectiveness of the proposed prognosis evaluation method of HGCA. Conclusions can help clinicians precisely evaluate the recurrence risk of patients, take the initiative to master the diagnosis and treatment, and increase the long-term survival rate of patients.

Background: Heart failure (HF) significantly impacts quality of life and healthcare systems worldwide. Assessing left ventricular mechanical dyssynchrony (LVMD) is crucial for understanding cardiac function and optimizing treatments like cardiac resynchronization therapy (CRT). Phase analysis using gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has shown promise in predicting outcomes, yet recent comprehensive reviews are lacking. Objective: To systematically assess the prognostic value of phase analysis by gated SPECT MPI in the HF population through a systematic review. Methods: We conducted a systematic review by collecting studies from databases including PubMed, CINAHL, and Web of Science. Two reviewers independently performed study selection, data extraction, and risk of bias assessment. Systematic reviews were conducted using Review Manager Software 5.4 and STATA 16.0. Results: A total of 2004 patients from seven studies were included in our review and analysis. The systematic review indicated that patients with predetermined clinical events had higher PSD [MD = 6.45, 95% CI (5.83, 7.07), p < 0.00001] and PBW [MD = 7.91, 95% CI (5.64, 10.19), p < 0.00001]. The diagnosis of LVMD determined by PSD [HR = 1.05, 95% CI (1.01, 1.08), p = 0.007] was a strong predictor of endpoint events compared to PBW [HR = 1.95, 95% CI (0.48, 7.89), p = 0.35]. Conclusions: The analysis demonstrated that phase information obtained from gated SPECT MPI is of significant prognostic value in patients with heart dysfunction. It effectively enhances clinical risk models, providing reliable guidance for patient treatment. [ABSTRACT FROM AUTHOR]

Objective Method Results Conclusion To search for a new biomarker that can predict the efficacy and prognosis of tumor immunotherapy.FOXK2 genes were analyzed using single‐cell sequencing in pan‐cancer bulk RNA‐seq from the TCGA database. We used algorithms to predict their immune infiltration. Functional enrichment and ChIP‐seq identified potential downstream gene, FBXO32. FBXO32's role in cancer immune response was explored through analysis.Significant up‐regulation of FOXK2 was observed in prostate adenocarcinoma (PRAD), uterine corpus endometrial carcinoma (UCEC), bladder urothelial carcinoma (BLCA), colorectal cancer (CRC), pancreatic ductal adenocarcinoma (PDAC), and stomach adenocarcinoma (STAD), while no such increase was found in lung cancer (lung adenocarcinoma [LUAD], lung squamous cell carcinoma [LUSC]) or thyroid carcinoma (THCA) tumor and adjacent tissues. FOXK2 expression correlated with patient prognosis, with lower expression associated with better immune response and survival and higher expression of its downstream gene FBXO32 linked to worse overall survival (OS) and immune infiltration. FOXK2 has the potential to be used as a prognostic indicator and target for treatment in individuals with cancer.Our research provides insights into the significance of FOXK2 in cancer and indicates its potential as both a prognostic indicator and target for treatment. The ribosome‐associated pathways involving FOXK2 and FBXO32 could be pivotal in the advancement of tumors, offering possible avenues for targeted and individualized immunotherapy approaches. Additional research is required to completely understand the mechanisms that are responsible for the participation of FOXK2 and its subsequent gene FBXO32 in cancer, as well as to explore the possible advantages of focusing on FOXK2 for cancer treatment. [ABSTRACT FROM AUTHOR]

Objective: Diagnosis and treatment of gastroenteropancreatic high-grade neuroendocrine neoplasms (GEP-HG-NENs), particularly G3 well-differentiated neuroendocrine tumours (NETs) and poorly differentiated neuroendocrine carcinomas (NECs) relies on histopathological morphology, immunohistochemistry, and molecular biological markers, which are lacking especially in cases with ambiguous histomorphology. In this study to contribute to the development of more targeted treatment strategies, we examined various immunohistochemical and molecular biologicalmarkers and their associationwith clinicopathological features in GEP-HG-NENs. Methods: We included 38 patients with GEP-HG-NENs in this study, with their retrospective follow-up data. The expression of tumour protein p53 (TP53), RB transcriptional corepressor 1 (RB1), somatostatin receptor 2 (SSTR2), clusterin (CLU), and marker of proliferation Ki-67 (MKI67) was immunohistochemically analysed. KRAS proto-oncogene, GTPase (KRAS) and B-Raf proto-oncogene, serine/threonine kinase (BRAF) V600E expression was evaluated using quantitative real-time polymerase chain reaction (qRT-PCR). The relationships between immunohistochemical and molecular biological markers and clinicopathological characteristics were examined using a Cox risk regression model, receiver operating characteristic (ROC) curve, and Kaplan-Meier survival analyses. Results: SSTR2, RB, TP53, and CLU expression differed between NET G3 and NECs, with variations among the NET G3 and small- and large-cell NEC (SCNEC and LCNEC, respectively) groups (p < 0.05). The median MKI67 proliferative index was approximately 40% and 70% in G3 NETs and NECs, respectively. The NET G3 group exhibited a median survival of 25 months, indicating a relatively better prognosis than that of the NECs group (median survival, 11 months). Both Kaplan-Meier survival analysis and the Cox risk regression model indicated a statistical correlation among treatment methods, CLU expression, and prognosis (p < 0.05). The BRAF V600E mutation rate was 32.4% in G3 NETs and SCNEC, demonstrating a significant difference between both types (p = 0.0086). Furthermore, ROC curve analysis highlighted the diagnostic significance of the positive expression of the immunohistochemical markers CLU, SSTR2, and RB in identifying NET G3. Conclusion: To guide more suitable treatment strategies, it is essential to develop and apply valuable and more targeted immunohistochemical and molecular pathological markers for a comprehensive analysis. [ABSTRACT FROM AUTHOR]

Background: The Nottingham prognostic index (NPI) has been shown to negatively impact survival in breast cancer (BC). However, its ability to predict the locoregional recurrence (LRR) of BC remains still unclear. This study aims to determine whether a higher NPI serves as a significant predictor of LRR in BC. Methods: In total, 238 patients with BC were included in this analysis, and relevant clinicopathological features were collected. Correlation analysis was performed between NPI scores and clinicopathological characteristics. The optimal nomogram model was determined by Akaike information criterion. The accuracy of the model's predictions was evaluated using receiver operating characteristic curves (ROC curves), calibration curves and goodness of fit tests. The clinical application value was assessed through decision curve analysis. Results: Six significant variables were identified, including age, body mass index (BMI), TNM stage, NPI, vascular invasion, perineural invasion (P<0.05). Two prediction models, namely a TNM-stage-based model and an NPI-based model, were constructed. The area under the curve (AUC) for the TNM-stageand NPI-based models were 0.843 (0.785,0.901) and 0.830 (0.766,0.893) in training set and 0.649 (0.520,0.778) and 0.728 (0.610,0.846) in validation set, respectively. Both models exhibited good calibration and goodness of fit. The Fmeasures were 0.761vs 0.756 and 0.556 vs 0.696, respectively. Clinical decision curve analysis showed that both models provided clinical benefits in evaluating risk judgments based on the nomogram model. Conclusions: a higher NPI is an independent risk factor for predicting LRR in BC. The nomogram model based on NPI demonstrates good discrimination and calibration, offering potential clinical benefits. Therefore, it merits widespread adoption and application. [ABSTRACT FROM AUTHOR]

Ovarian cancer ranks among the deadliest gynecological malignancies, with high-grade serous adenocarcinoma (HGSA) constituting 75 % of ovarian cancer cases and accounting for 80 %–90 % of ovarian cancer-related fatalities. Accurate prognosis prediction for ovarian HGSA is of critical clinical significance. However, existing prognostic analysis methods exhibit suboptimal performance in identifying prognostically relevant pathological markers, making it challenging, even for experienced pathologists, to forecast the prognosis of ovarian HGSA patients accurately. Deep learning holds promise in enhancing prognostic prediction accuracy. However, a significant challenge in this field arises from the impracticality of directly inputting histopathology whole-slide images with millions to billions of pixels into existing deep learning networks for training and inference. To address this issue, we propose a prognostic analysis network for ovarian cancer based on hierarchical sampling and fine-grained recognition. This network comprises a two-stage hierarchical sampling sub-network, a fine-grained image recognition sub-network, and a prognostic analysis sub-network. We assess the system's performance using a pathological dataset of 450 cases of ovarian HGSA diagnosed and treated at the Pathology Department of the West China Second University Hospital of Sichuan University. Results indicate that: (1) The proposed prognostic analysis network based on two-stage hierarchical sampling sub-network can effectively analyze the histopathology whole-slide image; (2) the use of fine-grained image recognition and the introduction of clinical information can improve the performance of HGSA prognosis analysis method, with an improvement range of 4.77–10.66%; and (3) the proposed method can be used for the model analysis of pathological datasets of HGSA. Moreover, this method can be used to explore effective characteristics from the multi-modal dataset through automatic learning with prediction recall, accuracy, and precision rates of 80.0%, 81.1%, and 81.8%, respectively, underscoring its clinical potential. This study reveals the reliability and effectiveness of the proposed prognosis evaluation method of HGCA. Conclusions can help clinicians precisely evaluate the recurrence risk of patients, take the initiative to master the diagnosis and treatment, and increase the long-term survival rate of patients. [ABSTRACT FROM AUTHOR]

PurposeTo investigate the impact of the product of preoperative platelet count and C-reactive protein (P-CRP) on the postoperative prognosis of patients with non-muscle invasive bladder cancer (NMIBC), and to construct a Nomogram to predict the recurrence-free survival (RFS) of NMIBC patients based on pathological data.MethodsA retrospective analysis was conducted on the clinical data of 164 NMIBC patients who underwent transurethral resection of bladder tumors (TURBT) at the Second Affiliated Hospital of University of South China from January 2013 to December 2019. The endpoint of the study was the RFS. Kaplan-Meier (KM) method and Cox regression were used for analysis to identify independent factors affecting RFS. Then, the Nomogram was used to visualize the results of the multivariate analysis that were statistically significant and related to the RFS of NMIBC patients. Finally, the predictive ability of the model was evaluated using the concordance index (C-index) and calibration curves.ResultsBefore the end of the follow-up, the RFS was 88.3% at 1 year, 75.5% at 2 years, and 58.5% at 3 years. KM curves showed that P-CRP (HR=0.357, 95% CI: 0.204-0.625, P

BackgroundOsteosarcoma is a malignant tumor originating from mesenchymal bone tissue, characterized by high malignancy and poor prognosis. Despite progress in comprehensive treatment approaches, the five-year survival rate remains largely unchanged, highlighting the need to clarify its underlying mechanisms and discover new therapeutic targets.MethodsThis study utilized RNA sequencing data from multiple public databases, encompassing osteosarcoma samples and healthy controls, along with single-cell RNA sequencing data. Various methods were utilized, such as differential expression analysis of genes, analysis of metabolic pathways, and weighted gene co-expression network analysis (WGCNA), to pinpoint crucial genes. Using this list of genes, we developed and validated a prognostic model that incorporated risk signatures, and we evaluated the effectiveness of the model through survival analysis, immune cell infiltration examination, and drug sensitivity evaluation.ResultsWe analyzed gene expression and metabolic pathways in nine samples using single-cell sequencing data. Initially, we performed quality control and clustering, identifying 21 statistically significant cell subpopulations. Metabolic analyses of these subpopulations revealed heterogeneous activation of metabolic pathways. Focusing on the osteoblastic cell subpopulation, we further subdivided it into six groups and examined their gene expression and differentiation capabilities. Differential expression and enrichment analyses indicated that tumor tissues were enriched in cytoskeletal and structural pathways. Through WGCNA, we identified core genes negatively correlated with four highly activated metabolic pathways. Using osteosarcoma patient data, we developed a risk signature model that demonstrated robust prognostic predictions across three independent cohorts. Ultimately, we performed a thorough examination of the model, which encompassed clinical and pathological characteristics, enrichment analysis, pathways associated with cancer markers, and scores of immune infiltration, highlighting notable and complex disparities between high-risk and low-risk populations.ConclusionThis research clarifies the molecular mechanisms and metabolic features associated with osteosarcoma and how they relate to patient outcomes, offering novel perspectives and approaches for targeted therapy and prognostic assessment in osteosarcoma.

Hyponatremia, a prevalent electrolyte imbalance among tumor patients, has often been overlooked regarding its prognostic significance for immunotherapy. In this study, we delved into the prognostic ramifications of hyponatremia in advanced gastric cancer (AGC) patients undergoing immunotherapy. Enrolling AGC patients diagnosed between December 2014 and May 2021, we extracted pertinent data from electronic medical records, with a median follow-up of 35.8 months. Kaplan–Meier curves illuminated patients’ progression-free survival (PFS) and overall survival (OS), while survival disparities were tested using the Mantel–Haenszel log rank test. COX and logistic regressions were employed to scrutinize the correlation between serum sodium levels and prognosis in 268 AGC patients, both at baseline and during treatment. Notably, patients with hyponatremia exhibited shorter PFS (4.7 vs 2.1 months, p = .001*) and OS (12.5 vs 3.9 months, p

AIM: To explore the prognostic factors for lacrimal gland adenoid cystic carcinoma (LGACC) in Chinese patients. METHODS: Clinical and histopathological data were reviewed in patients with pathologically confirmed LGACC. Local recurrence, metastasis, and disease-specific death were the main outcome measures. Univariate and multivariate analyses were performed by the Kaplan-Meier method and a Cox proportional hazard model. RESULTS: This retrospective cohort study included 45 patients with pathologically confirmed LGACC between January 2008 and June 2022. Tumor (T) classification (P=0.005), nodal metastasis (N) classification (P=0.018) and positive margin (P=0.008) were independent risk factors of recurrence; T (P=0.013) and N (P=0.003) classification and the basaloid tumor type (P=0.032) were independent risk factors for metastasis; T classification (P

Abstract Background Accurate prognostic assessment is vital for the personalized treatment of endometrial cancer (EC). Although radiomics models have demonstrated prognostic potential in EC, the impact of region of interest (ROI) delineation strategies and the clinical significance of peritumoral features remain uncertain. Our study thereby aimed to explore the predictive performance of varying radiomics models for the prediction of LVSI, DMI, and disease stage in EC. Methods Patients with 174 histopathology-confirmed EC were retrospectively reviewed. ROIs were manually delineated using the 2D and 3D approach on T2-weighted MRI images. Six radiomics models involving intratumoral (2Dintra and 3Dintra), peritumoral (2Dperi and 3Dperi), and combined models (2Dintra + peri and 3Dintra + peri) were developed. Models were constructed using the logistic regression method with five-fold cross-validation. Area under the receiver operating characteristic curve (AUC) was assessed, and was compared using the Delong’s test. Results No significant differences in AUC were observed between the 2Dintra and 3Dintra models, or the 2Dperi and 3Dperi models in all prediction tasks (P > 0.05). Significant difference was observed between the 3Dintra and 3Dperi models for LVSI (0.738 vs. 0.805) and DMI prediction (0.719 vs. 0.804). The 3Dintra + peri models demonstrated significantly better predictive performance in all 3 prediction tasks compared to the 3Dintra model in both the training and validation cohorts (P

Currently, there is a scarcity of reliable biomarkers that can accurately forecast the outcome and prognosis of transarterial chemoembolization (TACE). In this study, we assessed the diagnostic efficacy of serum glutathione reductase (GR) as a biomarker for hepatocellular carcinoma (HCC) and its practicality in predicting TACE treatment response. The baseline positive rate and level of serum GR were analyzed and compared between HCC group and control group. Serum GR levels were assessed at three specific time points in 181 patients with unresectable HCC who underwent TACE (HCC-TACE). The correlation between serum GR levels and clinical pathological factors, tumor reactivity, and prognosis was investigated. The modified Response Evaluation Criteria in Solid Tumors (mRECIST) was utilized for assessing the treatment response to TACE. A nomogram for predicting the response to TACE treatment efficacy was developed. Serum GR demonstrated superior diagnostic performance in HCC patients. The baseline levels of serum GR were associated with the patient's age, tumor size, BCLC staging, and tumor thrombi of the portal vein (TTPV) (p < 0.05). Elevated baseline levels of serum GR were also identified as independent prognostic factors for predicting lower overall survival (OS) and shorter time to radiological progression (TTP) (p < 0.001). Moreover, it is worth noting that non-responders group exhibited a substantial increase in median GR level in the fourth week following TACE treatment (p < 0.0001), whereas the median GR level of responders group did not display a significant augmentation (p > 0.05). Lastly, the changes in serum GR t1-t3 were negatively correlated with TTP (p < 0.001). The nomogram developed to predict the risk of mRECIST responsiveness in patients with HCC-TACE demonstrated excellent discriminatory ability. Serum GR can serve as a valuable biomarker for the diagnosis of HCC and for predicting the therapeutic efficacy and prognosis of TACE treatment. [Display omitted] • Evaluate the value of serum glutathione reductase (GR) as a diagnostic biomarker for hepatocellular carcinoma (HCC). • The usefulness of GR in predicting the effectiveness and prognosis of transarterial chemoembolization (TACE) treatment. • Develop a nomogram for predicting response to TACE. [ABSTRACT FROM AUTHOR]

The association between anal fistula patients and colorectal cancer, as well as the potential pathophysiological mechanisms, remains unclear. To explore the relationship between anal fistula and colorectal cancer and its potential mechanisms. Analysis of GEO and TCGA databases. Disease‐related genes were also referenced from Coremine Medical, GeneCard and OMIM. Core hub genes were identified through protein–protein interaction analysis by intersecting differentially expressed genes from the datasets with disease data. On one hand, a prognostic model was developed using genes and its prognostic role was validated. On the other hand, the optimal diagnostic genes were selected through machine learning. Mendelian randomization (MR) analysis was conducted to explore the potential causal link between anal fistula and colorectal cancer. Thirteen core genes were identified (TMEM121B, PDGFRA, MID2, WNT10B, HOXD13, BARX1, SIX2, MMP1, SNAL1, CDKN2A, ITGB3, TIMP1, CALB2). Functional enrichment analysis revealed that the intersecting genes between anal fistula and colorectal cancer were associated with extracellular matrix components, signalling pathways, cell growth, protein modification, as well as important roles in cellular activities, tissue and organ development, and biological function maintenance. These genes were also involved in pathways related to Wnt signalling and colorectal cancer development. Prognostic analysis and immune infiltration analysis indicated a close relationship between core hub genes and the prognosis and immune infiltration in colorectal cancer. Machine learning showed that core genes played an essential role in the diagnostic differentiation of colorectal cancer. MR results suggested no causal relationship between anal fistula and colorectal cancer. This study identified shared core genes between anal fistula and colorectal cancer, involved in various pathways related to tumour development. These genes play crucial roles in prognosis and diagnosis. [ABSTRACT FROM AUTHOR]

Background: As a common soft tissue sarcoma, liposarcoma (LPS) is a heterogeneous malignant tumor derived from adipose tissue. Due to the high risk of metastasis and recurrence, the prognosis of LPS remains unfavorable. To improve clinical treatment, a robust risk prediction model is essential to evaluate the prognosis of LPS patients. Methods: By comprehensive analysis of data derived from GEO datasets, differentially expressed genes (DEGs) were obtained. Univariate and Lasso Cox regressions were subsequently employed to reveal distant recurrence-free survival (DRFS)-associated DEGs and develop a prognostic gene signature, which was assessed by Kaplan–Meier survival and ROC curve. GSEA and immune infiltration analyses were conducted to illuminate molecular mechanisms and immune correlations of this model in LPS progression. Furthermore, a correlation analysis was involved to decipher the therapeutic significance of this model for LPS. Results: A six-gene signature was developed to predict DRFS of LPS patients and showed higher precision performance in more aggressive LPS subtypes. Then, a nomogram was further established for clinical application based on this risk model. Via GSEA, the high-risk group was significantly enriched in cell cycle-related pathways. In the LPS microenvironment, neutrophils, memory B cells and resting mast cells exhibited significant differences in cell abundance between high-risk and low-risk patients. Moreover, this model was significantly correlated with therapeutic targets. Conclusion: A prognostic six-gene signature was developed and significantly associated with cell cycle pathways and therapeutic target genes, which could provide new insights into risk assessment of LPS progression and therapeutic strategies for LPS patients to improve their prognosis. [ABSTRACT FROM AUTHOR]

Background: Clear Cell Renal Cell Carcinoma (ccRCC) is the most common type of kidney cancer, characterized by high heterogeneity and complexity. Recent studies have identified mitochondrial defects and autophagy as key players in the development of ccRCC. This study aims to delve into the changes in mitophagic activity within ccRCC and its impact on the tumor microenvironment, revealing its role in tumor cell metabolism, development, and survival strategies. Methods: Comprehensive analysis of ccRCC tumor tissues using single cell sequencing and spatial transcriptomics to reveal the role of mitophagy in ccRCC. Mitophagy was determined to be altered among renal clear cells by gene set scoring. Key mitophagy cell populations and key prognostic genes were identified using NMF analysis and survival analysis approaches. The role of UBB in ccRCC was also demonstrated by in vitro experiments. Results: Compared to normal kidney tissue, various cell types within ccRCC tumor tissues exhibited significantly increased levels of mitophagy, especially renal clear cells. Key genes associated with increased mitophagy levels, such as UBC, UBA52, TOMM7, UBB, MAP1LC3B, and CSNK2B, were identified, with their high expression closely linked to poor patient prognosis. Particularly, the ubiquitination process involving the UBB gene was found to be crucial for mitophagy and its quality control. Conclusion: This study highlights the central role of mitophagy and its regulatory factors in the development of ccRCC, revealing the significance of the UBB gene and its associated ubiquitination process in disease progression. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is one of the most common digestive tract malignant tumors, which has a high mortality rate especially for patients with CRC recurrence. However, the pathological mechanism of recurrence of CRC is unclear. In this study, we integrated multiple cohort datasets and databases to clarify and verify potential key candidate biomarkers and signal transduction pathways in recurrence of CRC. As results, 628 DEGs were identified from GSE33113 and GSE2630 datasets and their function and pathway were analyzed. 14 hub genes related to CRC recurrence were screened from and their influence on survival were analyzed. Two key genes (IL1B and DDAH1) regarded as prognostic factors were further screened. Relapse-free survival results indicated the interaction between IL1B and DDAH1 genes and B cells was the most obvious and correlated with survival, with statistical significance (P < 0.05). Specially, cox regression analysis suggested that patients with T1 and N0 stages had a higher risk of recurrence than patients with T2 and N1. This work would provide potential value for prognosis, and would promote molecular targeting therapy for CRC recurrence. [ABSTRACT FROM AUTHOR]

Objective To investigate the clinical characteristics and long-term prognosis of patients aged under 25 years with acute myocardial infarction(AMI). Methods We enrolled the patients aged under 25 years(young group)who were diagnosed with AMI at The First Affiliated Hospital of Xi'an Jiaotong University from February 2013 to July 2023. And the patients who were admitted to the hospital during the same period and aged 25-44 years with the same gender and the same infarct sites were selected as the control group(young and middle-aged group)(1:2). The clinical data of the two groups including comorbidities, high risk factors and biochemical indicators were collected and compared, and prognostic factors were analyzed. Results In this study, we enrolled a total of 84 AMI patients: 28 in the young group and 56 in the young and middle-aged group. The patients in young group had single-vessel disease(15/26, 57.7%)and no obvious culprit vessel(7/26, 26.9%); their white blood cell count and uric acid level were significantly higher than those of the young and middle-aged group. The median follow-up was 72.4(25.5, 110.2)months in this study. The results of univariate and multivariate Cox proportional hazards regression model analysis showed that the younger group(HR=7.925, 95% CI: 1.861-33.749, P=0.005), length of hospital stay(HR=1.183, 95% CI: 1.001-1.398, P=0.048), and complicated typical angina symptoms(HR=0.090, 95%CI: 0.015-0.544, P=0.009)were independent factors affecting the patients' overall surivival. Conclusion Compared to middle-aged and young AMI patients, the younger AMI ones have a worse prognosis. Young patients(under 25 years), length of hospital stay and atypical angina symptoms are the most important risk factors for patients with AMI. Therefore, early detection and identification of AMI in young patients is helpful for improving the patients' prognosis. [ABSTRACT FROM AUTHOR]

Objectives: Lung cancer is the leading cause of cancer death, and 80-85% of all lung cancer cases are non-small cell lung cancer (NSCLC). Surgical resection is the standard treatment for early-stage NSCLC. However, lung resection, a surgical procedure, can result in complications and increased mortality. Recent studies have shown a significant correlation between complications after lung resection and right ventricular dysfunction. Methods: Transthoracic echocardiography-derived right ventricular-pulmonary artery coupling (RV-PAC) was utilized to assess right ventricular function in these patients. Multivariate logistic regression analysis was also conducted to assess risk factors independently associated with RV-PA uncoupling. The 3- and 5-year cumulative survival rates were estimated with Kaplan-Meier curves, and differences between groups were analyzed using the Mantel-Cox log-rank test. Results: RV-PA uncoupling was defined as a TAPSE/PASP value < 0.67 mm/mm Hg according to spline analysis. The results of multivariable logistic regression analysis indicated that diabetes is an independent risk factor for right ventricular dysfunction after lung resection in patients with NSCLC. Kaplan-Meier analysis revealed a significant decrease in the survival rate of patients with RV-PA uncoupling at both the 3-year follow-up (73% vs 40%, p < 0.001) and 5-year follow-up (64% vs 37%, p < 0.001). Conclusions: After lung resection for NSCLC, the patient's right ventricular function predicts prognosis. Patients with right ventricular dysfunction, particularly those with diabetesmellitus, have a worse prognosis. It is crucial to actively prevent and correct risk factors to reduce the mortality rate in these patients. [ABSTRACT FROM AUTHOR]

The prognostic analysis for high grade serous adenocarcinoma (HGSC) holds significant clinical importance. However, current prognostic analysis primarily relies on statistical techniques like logistic regression and chi-square analysis alongside traditional machine learning methods based on pattern recognition. These approaches face challenges in addressing the limited reliability and validity of evaluation results, as well as the absence of reliable prognostic indicators. To identify a reliable prognostic evaluation method for high grade serous adenocarcinoma, a novel prognostic evaluation method was constructed using multi-modal deep learning techniques and compared with existing methods using data from 210 patients with high grade serous adenocarcinoma (stage III). The experimental results showed that the accuracy of this method for prognostic analysis was 80.0%, and the detection rate for poor prognosis cases was 82.87%, which was superior to current methods. Our proposed method could also automatically extract key features from different datasets and efficiently predict patient outcomes. Overall, this study laid the groundwork to overcome the difficulties in the prognostic evaluation of HGSC, help clinicians better understand the pathogenesis, and improve the long-term survival rates of this patient population. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) are associated with colorectal cancer (CRC); however, CRC-related linc00239 functions have not been fully elucidated. Prognostic analysis of patients with CRC with linc00239 overexpression was performed using data from The Cancer Genome Atlas database. Cell Counting Kit-8 and Transwell were used to determine linc00239 functions for CRC cells. The lncRNA–miRNA–mRNA interaction network was used to screen target miRNAs and mRNAs regulated by linc00239. Quantitative real-time polymerase chain reaction and western blotting were used to confirm the miRNA and mRNA expression. Furthermore, a miRNA inhibitor was transfected into CRC cells, and cell function was evaluated. Results indicated a high linc00239 expression in the tumor tissue of patients with CRC. Transfection of linc00239 siRNA into SW480 and LOVO cells decreased cell proliferation, cell migration, and invasion. MiR-182-5p/metadherin (MTDH) axis is a downstream pathway of linc00239. MTDH expression, the activity of cell proliferation, migration, and invasion, which were suppressed by linc00239 siRNA, were partially attenuated when linc00239 siRNA and miR-182-5p inhibitor were co-transfected into the CRC cells. Furthermore, miR-182-5p expression was decreased and MTDH expression was promoted in CRC tissues. Altogether, linc00239 may promote CRC development through the miR-182-5p/MTDH axis. [ABSTRACT FROM AUTHOR]

Abstract Purpose Immune checkpoint inhibitors-related myocarditis (ICI-M) is one of the immune-related adverse events (irAEs), which is rare and highly lethal. This study aimed to establish nomograms based on ratio biomarkers to predict the severity and prognosis of ICI-M. Methods We retrospectively examined patients with advanced cancers who were also diagnosed with ICI-M at the Fourth Hospital of Hebei Medical University. The patients of ICI-M were divided into mild and severe groups and a 40-day following up was carried out. The major adverse cardiovascular events(MACEs) were regarded as the endpoint. Nomogram-based models were established and validated. Results Seventy-seven patients were involved, including 31 severe cases(40.3%). Lactate dehydrogenase-to-albumin ratio(LAR) combined with the change rate from baseline to onset of LAR( $$\triangle$$ ▵ LAR) which performed best to diagnose the severe ICI-M was identified to establish the nomogram-based model. The bootstrap-corrected concordance index [0.752 95% confidence interval (CI): 0.635 $$-$$ - 0.866] and calibration plot with good degree of fitting confirmed this diagnostic model. Neutrophil-to-high-density lipoprotein cholesterol ratio(NHR) and LAR were also screened into the nomogram-based model for 40-day MACEs after ICI-M, which performed well by validating for concordance index(0.779 95% CI: 0.677 $$-$$ - 0.865)and calibration plots after being bootstrap-corrected. Moreover, a $$\ge$$ ≥ 101% increase in LAR significantly separated patients in MACE-free survival. Conclusion Ratio indexes at onset and their change rates from baseline showed good diagnostic value for the severity of ICI-M and prognostic value for subsequent MACEs, particularly LAR, NHR and their change rates. The nomogram-based models of ratio indexes could provide a potential choice for early detection and monitor of the severe ICI-M and subsequent MACEs. Graphical abstract

Abstract Background Radiation-induced liver damage (RILD) occasionally occurs following carbon-ion radiotherapy (CIRT) for liver tumors, such as hepatocellular carcinoma (HCC), in patients with impaired liver function disease. However, the associated risk factors remain unknown. The present study aimed to determine the risk factors of RILD after CIRT. Methods We retrospectively analyzed 108 patients with HCC treated with CIRT at the Osaka Heavy Ion Therapy Center between December 2018 and December 2022. RILD was defined as a worsening of two or more points in the Child–Pugh score within 12 months following CIRT. The median age of the patients was 76 years (range 47–95 years), and the median tumor diameter was 41 mm (range 5–160 mm). Based on the pretreatment liver function, 98 and 10 patients were categorized as Child–Pugh class A and B, respectively. We analyzed patients who received a radiation dose of 60 Gy (relative biological effectiveness [RBE]) in four fractions. The median follow-up period was 9.7 months (range 2.3–41.1 months), and RILD was observed in 11 patients (10.1%). Results Multivariate analysis showed that pretreatment Child–Pugh score B (p = 0.003, hazard ratio [HR] = 6.90) and normal liver volume spared from

Objectives. The aim of this study was to explore the clinicopathological characteristics, prognostic factors, recurrence patterns and survival analysis of triple negative breast cancer patients compared to non-triple negative breast cancer patients. Materials and methods. The cohort included 420 patients who were diagnosed with breast cancer. The patients were evaluated based on the molecular classification and grouped into TNBC and non-TNBC. Data was explored using SPSS Version 29.0.0.0. Patient and tumor characteristics were studied. Univariate and multivariate Cox Regression was used to analyze prognostic factors. Kaplan Meier method with the logrank test was performed to observe DFS and OS. Outcomes. The triple negative subtype was observed in 57(13.6%) patients. Patients with TNBC had a greater proportion of grade 3 tumors compared to those with non-TNBC (43.9% vs. 5.5%, p

Background: Mutations in STK11 (STK11Mut) gene may present a negative impact on survival in Non-small Cell Lung Cancer (NSCLC) patients, however, its relationship with immune related genes remains unclear. This study is to unveil whether overexpressed- and mutated-STK11 impact survival in NSCLC and to explore whether immune related genes (IRGs) are involved in STK11 mutations. Methods: 188 NSCLC patients with intact formalin-fixed paraffin-embedded (FFPE) tissue available for detecting STK11 protein expression were included in the analysis. After immunohistochemical detection of STK11 protein, patients were divided into high STK11 expression group (STK11High) and low STK11 expression group (STK11Low), and then Kaplan-Meier survival analysis and COX proportional hazards model were used to compare the overall survival (OS) and progression-free survival (PFS) of the two groups of patients. In addition, the mutation data from the TCGA database was used to categorize the NSCLC population, namely STK11 Mutated (STK11Mut) and wild-type (STK11Wt) subgroups. The difference in OS between STK11Mut and STK11Wt was compared. Finally, bioinformatics analysis was used to compare the differences in IRGs expression between STK11Mut and STK11Wt populations. Results: The median follow-up time was 51.0 months (range 3.0 - 120.0 months) for real-life cohort. At the end of follow-up, 64.36% (121/188) of patients experienced recurrence or metastasis. 64.89% (122/188) of patients ended up in cancer-related death. High expression of STK11 was a significant protective factor for NSCLC patients, both in terms of PFS [HR=0.42, 95% CI= (0.29-0.61), P<0.001] and OS [HR=0.36, 95% CI= (0.25, 0.53), P<0.001], which was consistent with the finding in TCGA cohorts [HR=0.76, 95%CI= (0.65, 0.88), P<0.001 HR=0.76, 95%CI= (0.65, 0.88), P<0.001]. In TCGA cohort, STK11 mutation was a significant risk factor for NSCLC in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) histology in terms of OS [HR=6.81, 95%CI= (2.16, 21.53), P<0.001; HR=1.50, 95%CI= (1.00, 2.26), P=0.051, respectively]. Furthermore, 7 IRGs, namely CALCA, BMP6, S100P, THPO, CGA, PCSK1 and MUC5AC, were found significantly overexpressed in STK11-mutated NSCLC in both LUSC and LUAD histology. Conclusions: Low STK11 expression at protein level and presence of STK11 mutation were associated with poor prognosis in NSCLC, and mutated STK11 might probably alter the expression IRGs profiling. [ABSTRACT FROM AUTHOR]

Purpose: Immune checkpoint inhibitors-related myocarditis (ICI-M) is one of the immune-related adverse events (irAEs), which is rare and highly lethal. This study aimed to establish nomograms based on ratio biomarkers to predict the severity and prognosis of ICI-M. Methods: We retrospectively examined patients with advanced cancers who were also diagnosed with ICI-M at the Fourth Hospital of Hebei Medical University. The patients of ICI-M were divided into mild and severe groups and a 40-day following up was carried out. The major adverse cardiovascular events(MACEs) were regarded as the endpoint. Nomogram-based models were established and validated. Results: Seventy-seven patients were involved, including 31 severe cases(40.3%). Lactate dehydrogenase-to-albumin ratio(LAR) combined with the change rate from baseline to onset of LAR(▵ LAR) which performed best to diagnose the severe ICI-M was identified to establish the nomogram-based model. The bootstrap-corrected concordance index [0.752 95% confidence interval (CI): 0.635 - 0.866] and calibration plot with good degree of fitting confirmed this diagnostic model. Neutrophil-to-high-density lipoprotein cholesterol ratio(NHR) and LAR were also screened into the nomogram-based model for 40-day MACEs after ICI-M, which performed well by validating for concordance index(0.779 95% CI: 0.677 - 0.865)and calibration plots after being bootstrap-corrected. Moreover, a ≥ 101% increase in LAR significantly separated patients in MACE-free survival. Conclusion: Ratio indexes at onset and their change rates from baseline showed good diagnostic value for the severity of ICI-M and prognostic value for subsequent MACEs, particularly LAR, NHR and their change rates. The nomogram-based models of ratio indexes could provide a potential choice for early detection and monitor of the severe ICI-M and subsequent MACEs. [ABSTRACT FROM AUTHOR]

Background: Radiation-induced liver damage (RILD) occasionally occurs following carbon-ion radiotherapy (CIRT) for liver tumors, such as hepatocellular carcinoma (HCC), in patients with impaired liver function disease. However, the associated risk factors remain unknown. The present study aimed to determine the risk factors of RILD after CIRT. Methods: We retrospectively analyzed 108 patients with HCC treated with CIRT at the Osaka Heavy Ion Therapy Center between December 2018 and December 2022. RILD was defined as a worsening of two or more points in the Child–Pugh score within 12 months following CIRT. The median age of the patients was 76 years (range 47–95 years), and the median tumor diameter was 41 mm (range 5–160 mm). Based on the pretreatment liver function, 98 and 10 patients were categorized as Child–Pugh class A and B, respectively. We analyzed patients who received a radiation dose of 60 Gy (relative biological effectiveness [RBE]) in four fractions. The median follow-up period was 9.7 months (range 2.3–41.1 months), and RILD was observed in 11 patients (10.1%). Results: Multivariate analysis showed that pretreatment Child–Pugh score B (p = 0.003, hazard ratio [HR] = 6.90) and normal liver volume spared from < 30 Gy RBE (VS30 < 739 cm3) (p = 0.009, HR = 5.22) were significant risk factors for RILD. The one-year cumulative incidences of RILD stratified by Child–Pugh class A or B and VS30 < 739 cm3 or ≥ 739 cm3 were 10.3% or 51.8% and 39.6% or 9.2%, respectively. Conclusion: In conclusion, the pretreatment Child–Pugh score and VS30 of the liver are significant risk factors for RILD following CIRT for HCC. [ABSTRACT FROM AUTHOR]

Objective: Double pituitary adenomas (DPA) are a rare clinical condition, and our knowledge of them is limited. Missing the second lesion leading to incomplete biochemical remission after surgery is an important challenge in DPA management. This study aims to analyze independent prognostic factors in DPA patients and summarize clinical experiences to prevent surgical failure. Methods: Two cases of DPA patients with Cushing's disease diagnosed and surgically treated at Peking Union Medical College Hospital are reported. A literature review was performed on the online database Pubmed, and 57 DPA patients from 22 retrieved articles were included. Demographic characteristics, endocrine manifestations, diagnostic methods, tumor size, and immunohistochemical features of 59 patients were analyzed. Binary logistic regression models were used to identify independent prognostic factors affecting postoperative biochemical remission. Results: Among 59 DPA patients, the mean ± SD age was 43.64 ± 14.42 years, with 61.02% being female (n = 36). The most common endocrine manifestations were Cushing's syndrome (23/59, 38.98%) and acromegaly (20/59, 33.90%). The most prevalent immunohistochemical types were ACTH-immunopositive (31/ 118, 26.27%) and GH-immunopositive (31/118, 26.27%) tumors. Microadenomas (<1cm) were the most frequent in terms of tumor size (62/92, 67.39%). The detection rate for double lesions on 3.0T MRI was 50.00% (14/28), which significantly higher than 1.5T MRI (P = 0.034). Univariate analysis revealed that female, Cushing's syndrome and only single lesion detected by surgical exploration were associated with significantly worse prognosis (P<0.05). Multivariate analysis identified double lesion detected by surgical exploration (OR = 0.08, P = 0.003) and contiguous type tumor (OR = 0.06, P = 0.017) as independent protective factors for DPA patients. Conclusions: The double lesion detected by surgical exploration is independently associated with a better prognosis for DPA patients. Comprehensive intraoperative exploration are crucial measures to avoid missing causative lesions. [ABSTRACT FROM AUTHOR]

Background: Nodal T-follicular helper cell lymphomas (nTFHLs) represent a new family of peripheral T-cell lymphomas (PTCLs), and comparative studies of their constituents are rare. Methods: This study retrospectively enrolled 10 patients with nTFHL-F and 30 patients with nTFHL-NOS diagnosed between December 2017 and October 2023 at six large comprehensive tertiary hospitals; 188 patients with nTFHL-AI were diagnosed during the same period at the First Affiliated Hospital of Zhengzhou University for comparison. Results: Compared with nTFHL-AI, nTFHL-NOS patients exhibited better clinical manifestations, lower TFH expression levels, and a lower Ki-67 index. However, no differences in clinicopathological features were observed between nTFHL-F and nTFHL-AI patients as well as nTFHL-NOS patients. According to the survival analysis, the median OS for patients with nTFHL-NOS, nTFHL-AI, and nTFHL-F were 14.2 months, 10 months, and 5 months, respectively, whereas the median TTP were 14 months, 5 months, and 3 months, respectively. Statistical analysis revealed differences in TTP among the three subtypes(P=0.0173). Among the population of patients receiving CHOP-like induction therapy, there were significant differences in the OS and TTP among the nTFHL-NOS, nTFHL-AI, and nTFHL-F patients (P=0.0134, P=0.0205). Both the GDPT and C-PET regimens significantly improved the ORR, OS, and PFS in nTFHL patients. Conclusion: There are significant differences in the clinical manifestations, pathology, and survival outcomes among the three subtypes of nTFHLs. However, further research with a larger sample size, and involving clinical pathology and molecular genetics is needed to determine the distinctive biological characteristics of these tumors. [ABSTRACT FROM AUTHOR]

Purpose: The present study aimed to develop nomograms based on the SEER database to predict the prognosis for patients with primary sarcomatoid carcinoma of the urinary bladder (SCUB). Materials and Methods: Patients with primary SCUB were identified in the Surveillance, Epidemiology, and End Results (SEER) database, between 1975 and 2017. Univariate and multivariable Cox analysis were conducted to identify the independent prognostic factors for developing the overall survival (OS) and cancer-specific survival (CSS) nomograms. Then, concordance index (C-index), receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the accuracy of the nomogram model. In addition, the model was further compared with TNM staging system. Results: A total of 238 eligible patients with primary SCUB were selected from the SEER database. As suggested by Cox-analysis, age, sex, T stage, M stage, tumor size, and surgery type of primary site were identified as the independent factors for predicting both OS and CSS. We developed OS and CSS nomograms with a favorable C-index by using these prognostic factors. The C-indexes of the OS and CSS nomogram in the present study were 0.738 (0.701-0.775) and 0.763 (0.724-0.802), which were superior to those of the AJCC TNM staging with 0.621 (0.576-0.666) and 0.637 (0.588-0.686) respectively, showing better discriminatory ability. Subsequently, the ROC curves showed that the 1-, 3- and 5-year AUCs (area under the curve) of OS nomogram (i.e., 0.793, 0.807 and 0.793) were higher than those of the TNM stage((i.e., 0.659, 0.676, 0.659). Similarly, as for CSS model, them ((i.e., 0.823, 0.804 and 0.804) were aslo exceed those of TNM stage((i.e., 0.683, 0.682, 0.682). Furthermore, the calibration curves indicated a good consistency between the predictive survival and the actual survival. Finally, patients were stratified by risk, and Kaplan-Meier survival curve suggested that the prognosis of the low-risk group was significantly better than that of the high-risk group. Conclusion: We developed nomograms with the SEER database, which could help predict the prognosis of SCUB individuals more accurately. [ABSTRACT FROM AUTHOR]

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Objective·To analyze the clinicopathologic characteristics, gene mutation profile, and prognostic factors of thyroid diffuse large B-cell lymphoma (DLBCL).Methods·From November 2003 to December 2021, a total of 66 patients with thyroid DLBCL [23 cases (34.8%) with primary thyroid DLBCL, and 43 cases (65.2%) with secondary thyroid DLBCL] admitted to Ruijin Hospital, Shanghai Jiao Tong University School of Medicine were retrospectively analyzed for their clinicopathological data, survival and prognostic factors. Gene mutation profiles were evaluated by targeted sequencing (55 lymphoma-related genes) in 40 patients.Results·Compared to primary thyroid DLBCL, secondary thyroid DLBCL had advanced ratio of Ann Arbor stage Ⅲ‒Ⅳ (P=0.000), elevated serum lactate dehydrogenase (LDH) (P=0.043), number of affected extranodal involvement ≥2 (P=0.000), non-germinal center B cell (non-GCB) (P=0.030), BCL-2/MYC double expression (DE) (P=0.026), and international prognostic index (IPI) 3‒5 -scores (P=0.000). The proportion of patients who underwent thyroid surgery (P=0.012) was lower than that of patients with primary thyroid DLBCL. The complete remission (CR) rate in primary thyroid DLBCL patients was higher than that in secondary thyroid DLBCL patients (P=0.039). Fifty-five patients (83%) received rituximab combined with cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP)-based first-line regimen. The estimated 5-year progression free survival (PFS) rate of primary thyroid DLBCL patients was 95.0%, higher than the 49.7% of the secondary patients (P=0.010). Univariate analysis showed that Ann Arbor Ⅲ‒Ⅳ (HR=4.411, 95%CI 1.373‒14.170), elevated LDH (HR=5.500, 95%CI 1.519‒19.911), non-GCB (HR=5.291, 95%CI 1.667‒16.788), and DE (HR=6.178, 95%CI 1.813‒21.058) were adverse prognostic factors of PFS in patients with thyroid DLBCL. Ann Arbor Ⅲ‒Ⅳ (HR=7.088, 95%CI 0.827‒60.717), elevated LDH (HR=6.982, 95%CI 0.809‒60.266), and DE (HR=18.079, 95%CI 1.837‒177.923) were adverse prognostic factors of overall survival (OS). Multivariate analysis showed that Ann Arbor Ⅲ‒Ⅳ (HR=4.693, 95%CI 1.218‒18.081) and elevated LDH (HR=5.058, 95%CI 1.166‒21.941) were independent adverse prognostic factors of PFS in patients with thyroid DLBCL. Targeted sequencing data showed mutation frequency >20% in TET2 (n=14, 35%), KMT2D (n=13, 32%), TP53 (n=11, 28%), GNA13 (n=10, 25%), KMT2C (n=9, 22%), and TP53 were adverse prognostic factors of PFS in patients with thyroid DLBCL (P=0.000).Conclusion·Patients with primary thyroid DLBCL have better PFS and OS than those with secondary thyroid DLBCL. Ann Arbor Ⅲ‒Ⅳ, elevated LDH, non-GCB, and DE (MYC and BCL2) are adverse prognostic factors in thyroid DLBCL. TET2, KMT2D, TP53, GNA13, and KMT2C are commonly highly mutated genes in thyroid DLBCL, and the prognosis of patients with TP53 mutations is poor.

Abstract Objective Lumbosacral vertebral osteoblastic metastasis is treated with percutaneous vertebroplasty (PVP) combined with 125I seed implantation and PVP alone. Compared to PVP alone, we evaluated the effects of combination therapy with PVP and 125I seed implantation on pain, physical condition, and survival and evaluated the clinical value of PVP combined with 125I particle implantation. Methods We retrospectively analyzed 62 patients with lumbosacral vertebral osseous metastases treated at our hospital between 2016 and 2019. All the patients met the inclusion criteria for 125I implantation, and they were randomly divided into a combined treatment group and a pure PVP surgery group. The visual analog pain scale (VAS), Karnofsky Performance Status (KPS), and survival time were recorded at different time points, including preoperative, postoperative 1 day, 1 month, 3 months, 6 months, 12 months, and 36 months in each group. The variation in clinical indicators and differences between the groups were analyzed using SPSS version 20.0. Correlations between different variables were analyzed using the nonparametric Spearman’s rank test. The Kaplan–Meier method was used to estimate the relationship between survival time and KPS score, VAS score, or primary tumor progression, and survival differences were analyzed using the log-rank test. Multivariate analyses were performed using a stepwise Cox proportional hazards model to identify independent prognostic factors. Results Compared to the PVP treatment group, the pain level in the combined treatment group was significantly reduced (P = 0.000), and the patient’s physical condition in the combination treatment group significantly improved. Kaplan–Meier analysis showed that the survival rate of the PVP group was significantly lower than that of the combination group (P = 0.038). We also found that the median survival of patients in both groups significantly increased with an increase in the KPS score (14 months vs. 33 months) (P = 0.020). Patients with more than three transfer sections had significantly lower survival rates than those with one or two segments of the section (P = 0.001). Further, Cox regression analysis showed that age (P = 0.002), the spinal segment for spinal metastasis (P = 0.000), and primary tumor growth rate (P = 0.005) were independent factors that affected the long-term survival of patients with lumbosacral vertebral osseous metastases. Conclusions PVP combined 125I seeds implantation surgery demonstrated superior effectiveness compared to PVP surgery alone in treating lumbosacral vertebral osseous metastases, which had feasibility in the clinical operation. Preoperative KPS score, spine transfer section, and primary tumor growth rate were closely related to the survival of patients with lumbosacral vertebral osteoblastic metastasis. Age, spinal segment for spinal metastasis, and primary tumor growth can serve as prognostic indicators and guide clinical treatment.

Abstract Background We aimed to investigate the factors influencing the cure, recurrence, and metastasis rates of stage IA lung adenocarcinoma, using a mixed cure model. Methods A total of 1,064 patients who underwent video-assisted thoracoscopic pulmonectomy were included. Variable screening was performed using the random forest algorithm and least absolute shrinkage and selection operator approaches. The mixed cure model was used to identify factors affecting patient cure and survival, and a sequential analysis was performed on 5%, 10%, and 20% of the presentational subtype concurrently. A receiver operating characteristics curve was used to determine the best model and construct a nomogram to predict the cure rate. Results The median follow-up time was 58 (range: 3–115) months. Results from the cure part of the mixed model indicated that the predominant subtype, presentational subtype, and tumor diameter were the main prognostic factors affecting cure rate. Therefore, the nomogram to predict the cure rate was constructed based on these factors. The survival part indicated that the predominant subtype was the only factor that influenced recurrence and metastasis. A sequential analysis of the presentational subtype showed it had no significant effect on survival (P > 0.05). Regardless of the recording mode, no significant improvement was observed in the model's discriminative ability. Only a few postoperative pathological specimens showed lymphovascular invasion (LVI); however, the survival curve suggested a significant effect on patient survival. Conclusions After excluding the existence of long-term survivors, the predominant tumor subtype was determined to be the only factor influencing recurrence and metastasis. Although LVI is rare in stage IA lung adenocarcinoma, its significance cannot be discounted in terms of determining patient prognosis.

Forkhead Box O1 (FOXO1) has been reported to play important roles in many tumors. However, FOXO1 has not been studied in pan-cancer. The purpose of this study was to reveal the roles of FOXO1 in pan-cancer (33 cancers in this study). Through multiple public platforms, a pan-cancer analysis of FOXO1 was conducted to obtained FOXO1 expression profiles in various tumors to explore the relationship between FOXO1 expression and prognosis of these tumors and to disclose the potential mechanism of FOXO1 in these tumors. FOXO1 was associated with the prognosis of multiple tumors, especially LGG (low grade glioma), OV (ovarian carcinoma), and KIRC (kidney renal clear cell carcinoma). FOXO1 might play the role of an oncogenic gene in LGG and OV, while playing the role of a cancer suppressor gene in KIRC. FOXO1 expression had a significant correlation with the infiltration of some immune cells in LGG, OV, and KIRC. By combining FOXO1 expression and immune cell infiltration, we found that FOXO1 might influence the overall survival of LGG through the infiltration of myeloid dendritic cells or CD4+ T cells. Functional enrichment analysis and gene set enrichment analysis showed that FOXO1 might play roles in tumors through immunoregulatory interactions between a lymphoid and a non-lymphoid cell, TGF-beta signaling pathway, and transcriptional misregulation in cancer. FOXO1 was associated with the prognosis of multiple tumors, especially LGG, OV, and KIRC. In these tumors, FOXO1 might play its role via the regulation of the immune microenvironment.

The study investigated the prognostic and immune predictive potential of major histocompatibility complex class I (MHC-I) in lung adenocarcinoma (LUAD). With The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus datasets (GSE26939, GSE72094) as the training and validation sets, respectively, we used Cox regression analysis to construct a prognostic model, and verified independence of riskscore. The predictive capacity of the model was assessed in both sets using the receiver operating characteristic curve and Kaplan-Meier survival curves. Immune analysis was performed by using ssGSEA. Additionally, immune checkpoint blockade therapy was assessed by using immunophenoscore, Tumor Immune Dysfunction and Exclusion score. Based on the cMAP database, effective small molecule compounds were predicted. A prognostic model was established based on 8 MHC-I-related genes, and the predictive capacity of the model was accurate. Immune analysis results revealed that patients classified as high-risk had lower levels of immune cell infiltration and impaired immune function. The low-risk group possessed a better response to immune checkpoint blockade therapy. Theobromine and pravastatin were identified as having great potential in improving the prognosis of LUAD. Overall, the study revealed MHC-I-related molecular prognostic biomarkers as robust indicators for LUAD prognosis and immune therapy response. [ABSTRACT FROM AUTHOR]

Objective To explore the influence of different marital status on cancer-specific survival (CSS) of pancreatic cancer patients. Methods The clinical data of pancreatic cancer patients from 2004 to 2016 were obtained from the SEER database. The patients were grouped according to different marital status, age, TNM stage and surgical conditions. Multivariate COX regression model was used to analyze the influence of marital status on CSS of pancreatic cancer patients. Results There were statistically significant differences in median CSS among patients with different marital status, age, race, TNM stage, Grade classification, and surgical status (P＜0. 01) . Marital status, age, Grade classification, TNM stage and operation were independent influencing factors of CSS in pancreatic cancer patients (P＜0. 01) . In the age group of ＜60 and ≥60 years old, marital status was an independent influencing factor of CSS in pancreatic cancer patients (P＜0. 05) . In the non-surgical group, marital status were independent influencing factors for CSS in pancreatic cancer patients (P＜0. 05) . In the surgical group, marital status was not independent factor affecting CSS in pancreatic cancer patients (P＞0. 05) . In the phase Ⅲ and Ⅳ groups, marital status was an independent influencing factor of CSS in pancreatic cancer patients (P＜0. 05) . In the stage Ⅰ and Ⅱ groups, marital status was not an independent influencing factor for CSS in pancreatic cancer patients (P＞0. 05) . Conclusion Marital status is related to the prognosis of pancreatic cancer patients. The CSS of married patients is better than that of unmarried and poor married patients. [ABSTRACT FROM AUTHOR]

Objective: To screen the interacting protein of ubiquitin-conjugating enzyme E2S (UBE2S) and construct the hepatocellular carcinoma (HCC) based on UBE2S interacting protein prognosis model (UIPM), and to discuss the value of UIPM in assessing the prognosis of the HCC patients. Methods: Coimmunoprecipitation (Co-IP) was used to screen the protein complexes binding to Flag-UBE2S. After validation by sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blotting methods；liquid chromatography-mass spectrometer (LC-MS) was used to identify the UBE2S interacting proteins； Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis were conducted on these proteins； the prognosis-related proteins from The Cancer Genome Atlas (TCGA) were cross-referenced with UBE2S interacting proteins by survival package of R software；the key proteins were extracted through LASSO regression analysis to build the UIPM； the prognostic model risk scoring formula was established. The HCC patients in TCGA were divided into high risk group and low risk group based on median value of the risk scores. The predictive accuracy of UIPM was evaluated by receiver operating characteristic curve (ROC), and the predictive accuracy was further validated by International Cancer Genome Consortium (ICGC) Database； univariate regression analysis and multivariate Cox regression analysis were used to detect whether the UIPM risk score was an independent prognostic factor for HCC. Furthermore, the nomogram model was built. Results: A total of 97 UBE2S interacting proteins were identified through Co-IP combined with LC-MS analysis. The GO functional enrichment analysis and KEGG signaling pathway enrichment analysis results showed that the interacting proteins were closely associated with cysteine-type endopeptidase activity, oxidative stress, and cell death. The TCGA revealed 5 163 HCC prognosis-related proteins；after intersecting with UBE2S interacting proteins, 40 prognosis-related interacting proteins were found. Seven key proteins were determined through LASSO regression analysis, including UBE2S, heat shock protein family A member 8 (HSPA8), heterogeneous nuclear ribonucleoprotein H1 (HNRNPH1), chaperonin containing TCP1 subunit 3 (CCT3), eukaryotic translation initiation factor 2 subunit 1 (EIF2S1), receptor for activated C kinase 1 (RACK1), and actin related protein 2/3 complex subunit 4 (ARPC4), and the UIPM was constructed. There was significant difference in survival rate of the patients between high risk group and low risk group (P<0. 05) . The ROC curve analysis results showed the area under ROC curve (AUC) values of UIPM for predicting 1-year, 2-year, and 3-year survival risk scores of the HCC patients were all greater than 0. 7, indicating the model had high predictive accuracy. This was also confirmed by ICGC Database data. The univariate and multivariate Cox regression analysis results showed that the UIPM risk score was an independent prognostic risk factor for the HCC patients (P<0. 05) . The nomogram results showed good consistency between predicted survival rate and actual survival rate of the patient. Conclusion : A total of 97 interacting proteins that interact with UBE2S may promote the occurence and development of HCC through oxidative stress and dysregulation of ferroptosis pathways. The UIPM risk score is an independent risk factor for the prognosis of HCC and can be used to predict the outcomes of the patients. UBE2S, HSPA8, HNRNPH1, CCT3, EIF2S1, RACK1, and ARPC4 could be regarded as the new biomarkers and therapeutic targets for HCC. [ABSTRACT FROM AUTHOR]

Survival analysis remains an important area in predictive modeling, especially in cases where event timing information is critical. This work presents a research effort to investigate the application of LightGBM, a high-performance highthroughput model, to conduct an improved fusion of decisions from multiple trees to reach survival analysis. Our objective is to address the challenge of developing correct predictive models while advancing computational effectiveness. Based on a case study of live disaster scenarios, the proposed approach applies and compares LightGBM with traditional prediction methods, which involve careful design engineering, and model training with LightGBM tree structure refinement. The results obtained from fair experimentation and comprehensive predictive performance evaluation demonstrate the robustness of LightGBM in increasing the accuracy of relevant classification tasks toward survival analysis. Furthermore, the findings highlighted that the combination of excellent tree depth for cutting and multi-thread optimization promotes efficient computational complexity and prediction accuracy. [ABSTRACT FROM AUTHOR]

Small-cell neuroendocrine carcinoma of the cervix (SCNCC) is a rare and aggressive tumor with a poor prognosis. Surgical resection followed by adjuvant therapy is the standard treatment for early-stage disease but the influence of different neo/adjuvant treatment approaches remains unclear. Retrospectively, we collected patients' characteristics and treatments in two medical centers. Disease status and survival outcomes were renewed through follow-up. Statistics analysis mainly included Kaplan-Meier methods for survival curve estimation, log-rank test for survival curve comparison, and Cox proportional hazards models for independent prognostic factors prediction. Finally, 51 patients treated by radical surgery between January 2010 and April 2020 were enrolled with a median age of 50 years (range: 32-68). 12 (23.5%) patients were at stage IIIC1 according to the International Federation of Gynecology and Obstetrics (FIGO) 2018 staging systems and the rest were at the early stage. The mean tumor size was 3.6±1.3 cm. Pathological examination found 24 cases with pure SCNCC and 27 cases with admixed SCCC. 29 (56.9%) patients had deep stromal infiltration and 19 (37.3%) patients had lymphovascular space invasion. 34 (66.7%) patients received neo/adjuvant chemotherapy and pelvic radiation was conducted in 41 (80.39%) patients with a median dose of 46 Gy (range: 40-50.4 Gy). The median follow-up time was 25.0 months. The median disease-free survival (DFS) time was 23.0 months. 27 (52.9%) patients developed distant metastasis and 14 (27.5%) experienced local failure. The median overall survival (OS) was 32.0 months. Univariate and multivariate analysis showed neoadjuvant chemotherapy as negative (HR=2.081, 95% CI 1.030-4.203, p=0.041) and adjuvant chemotherapy (HR=0.409, 95% CI 0.213-0.784, p=0.020) as positive independent prognostic factor for DFS. For OS, only lymph node metastasis was confirmed as an independent prognostic factor in both univariate analysis (HR=1.528, 95% CI 1.011-2.308, p=0.044) and multivariate analysis (HR=1.697, 95% CI 1.041-2.768, p=0.034). In conclusion, for surgically treated SCNCC, adjuvant chemotherapy showed a positive influence on DFS while neoadjuvant chemotherapy harmed DFS. OS was unaffected by either treatment choice. [ABSTRACT FROM AUTHOR]

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