This study aimed to develop and validate a nomogram using clinical variables to guide personalized treatment strategies for adenoid cystic carcinoma of the head and neck (ACCHN). Data from 1069 patients with ACCHN diagnosed between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were used to construct the nomogram. External validation was performed using an independent cohort of 70 patients from Fujian Cancer Hospital. Multivariate Cox regression analysis was conducted using IBM SPSS version 26.0 and R Software version 4.2.3. The concordance index (C-index) and receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the nomogram. Age, tumor site, surgery, N stage, M stage, and TNM stage were identified as independent prognostic factors through univariate and multivariate Cox analyses. The nomogram demonstrated superior predictive performance compared to the TNM staging system, effectively stratifying patients into high-risk and low-risk groups. This nomogram offers a valuable tool for predicting overall survival in patients with ACCHN and tailoring individualized treatment approaches.
Background Choledochal cyst perforation is extremely rare, and early diagnosis or prediction is important for the immediate therapeutic intervention of perforations. This study aimed to define the predictor(s) of an impending or complete spontaneous perforation of choledochal cyst and establish the optimal operative timing. Methods All 429 consecutive choledochal cyst patients from January 2015 to December 2021, were included. A retrospective study was performed based on Kaplan-Meier analysis, and Cox univariate and multivariate analyses. Results A total of 429 patients were included, among which, 21 had choledochal cyst perforations (group A), and 408 did not (group B). Compared to group B, the serum alanine aminotransferase, aspartate aminotransferase, direct bilirubin, gamma-glutamyl transpeptidase, indirect bilirubin, total bilirubin, and alkaline phosphatase were significantly higher in group A ( p = 0.025, 0.006, < 0.0001, 0.0001, 0.001, < 0.0001, and 0.033). High serum gamma-glutamyl transpeptidase was negatively associated with perforation-free preoperative survival, and multivariate Cox regression revealed that serum gamma-glutamyl transpeptidase was an independent predictive factor for an impending or complete perforation ( p = 0.042). Conclusions A gamma-glutamyl transpeptidase level ≥ 346.5 U/L accompanied with significantly elevated liver enzymes and bilirubin levels was indicative of the possibility of an impending or complete choledochal cyst perforation, and a proactive surgical approach should be considered.
Although radiation therapy (RT) plays a critical role in the treatment of low-grade glioma (LGG), many patients suffer from adverse effects without experiencing survival benefits.In various carcinomas, long non-coding RNAs (lncRNAs) contribute to pathogenic processes, including tumorigenesis, metastasis, chemoresistance, and radioresistance.Currently, the role of lncRNAs in the radiosensitivity of LGG is largely unknown.Here, we downloaded clinical data for 167 LGG patients from The Cancer Genome Atlas database and divided them between radiosensitive and radioresistant groups based on their clinical outcomes after receiving radiotherapy.We identified 37 lncRNAs that were differentially expressed (DElncRNAs) between the groups.Functional enrichment analysis revealed that their potential target mRNAs were mainly enriched in the PI3K-Akt and MAPK signaling pathways and in DNA damage response.Kaplan-Meier survival analysis revealed that increased expression of six lncRNAs was significantly associated with radiosensitivity.We then developed a risk signature based on three of the DElncRNAs that served as an independent biomarker for predicting LGG patient outcomes after radiotherapy.In vitro experiments further validated the biological function of these lncRNAs on low-grade glioma radiation response.
Robotic surgery is becoming increasingly widely used in the field of pediatric surgery. The present study aimed to evaluate the safety and feasibility of robot-assisted resection of benign pediatric splenic tumors and to discuss the technical points.A total of 32 patients who were diagnosed with benign splenic tumors and underwent minimally invasive surgery from January 2017 to September 2023 were included in the study. The clinical data including demographic criteria, operative details, and postoperative outcomes were analyzed retrospectively.Thirteen patients underwent robot-assisted surgery, and 19 patients underwent laparoscopic surgery. The median operation time was 150 min, with an interquartile range (IQR) of 120 to 200 min for the robot-assisted group and 140 min with an IQR of 105 to 180 min in the laparoscopic group (P = 0.318). Despite four cases in the laparoscopic group (21%) being converted to laparotomy because of intraoperative bleeding, compared with none in the robot-assisted group, there was no significant difference between two groups (P = 0.128). The intraoperative volume of blood loss was significantly less (P = 0.041), and the hospitalization expense was significantly higher (P = 0.000) in the robot-assisted group than for the laparoscopic group. There was no significant difference in patients' age, tumor size, postoperative feeding time, and the postoperative hospitalization time between two groups (P > 0.05).Robot-assisted benign splenic tumor resection was safe and feasible, and it reduced surgical trauma for the pediatric patient.
Few studies have assessed the comprehensive associations among comorbid diseases in elderly patients with nasopharyngeal carcinoma (NPC). This study sought to identify potential comorbidity patterns and explore the relationship of comorbidity patterns with the mortality risk in elderly patients with NPC.
Metabolic reprogramming contributes to patient prognosis. Here, we aimed to reveal the comprehensive landscape in metabolism of head and neck squamous carcinoma (HNSCC), and establish a novel metabolism-related prognostic model to explore the clinical potential and predictive value on therapeutic response. We screened 4752 metabolism-related genes (MRGs) and then identified differentially expressed MRGs in HNSCC. A novel 10-MRGs risk model for prognosis was established by the univariate Cox regression analysis and the least absolute shrinkage and selection operator (Lasso) regression analysis, and then verified in both internal and external validation cohort. Kaplan-Meier analysis was employed to explore its prognostic power on the response of conventional therapy. The immune cell infiltration was also evaluated and we used tumor immune dysfunction and exclusion (TIDE) algorithm to estimate potential response of immunotherapy in different risk groups. Nomogram model was constructed to further predict patients’ prognoses. We found the MRGs-related prognostic model showed good prediction performance. Survival analysis indicated that patients suffered obviously poorer survival outcomes in high-risk group ( p < 0.001). The metabolism-related signature was further confirmed to be the independent prognostic value of HNSCC (HR = 6.387, 95% CI = 3.281-12.432, p < 0.001), the efficacy of predictive model was also verified by internal and external validation cohorts. We observed that HNSCC patients would benefit from the application of chemotherapy in the low-risk group ( p = 0.029). Immunotherapy may be effective for HNSCC patients with high risk score ( p < 0.01). Furthermore, we established a predictive nomogram model for clinical application with high performance. Our study constructed and validated a promising 10-MRGs signature for monitoring outcome, which may provide potential indicators for metabolic therapy and therapeutic response prediction in HNSCC.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)