Abstract The clinical evidence of applying programmed cell death-ligand 1 (PD-L1) inhibitors in the first-line setting to treat esophageal squamous cell carcinoma (ESCC) remains scarce. In this multicenter, randomized, double-blinded phase 3 trial, a total of 540 adults (aged 18-75 years) with unresectable, locally advanced, recurrent or metastatic ESCC who had not received systemic treatment were enrolled. All patients were randomized at 2:1 to receive sugemalimab (an anti-PD-L1 antibody; 1200 mg) or placebo every 3 weeks for up to 24 months, plus chemotherapy (cisplatin 80 mg/m 2 on day 1 plus 5-fluorouracil 800 mg/m 2 /day on days 1-4) every 3 weeks for up to 6 cycles. At the prespecified interim analysis, this study has met its dual primary endpoints. With a median follow-up of 15.2 months, the prolongation of progression-free survival (PFS) was statistically significant with sugemalimab-chemotherapy compared with placebo-chemotherapy (median 6.2 v 5.4 months, hazard ratio [HR] 0.67 [95% confidence interval [CI] 0.54 to 0.82], P =0.0002) as assessed by blinded independent central review (BICR). Overall survival (OS) was also superior with sugemalimab-chemotherapy (median 15.3 v 11.5 months, HR 0.70 [95% CI 0.55 to 0.90], P =0.0076. A significantly higher objective response rate (60.1% v 45.2%) assessed by BICR was observed with sugemalimab-chemotherapy. The incidence of Grade 3 or above treatment-related adverse events (51.3% v 48.4%) was comparable between the two groups. Sugemalimab plus chemotherapy significantly prolonged PFS and OS in treatment-naïve patients with advanced ESCC, with no unexpected safety signal. This study is registered on ClinicalTrials.gov (NCT04187352).
Denosumab (Xgeva®) is a standard treatment for the prevention of skeletal-related events (SREs) in patients with bone metastases (BM). This trial was designed to assess the equivalence of LY01011 to denosumab in terms of efficacy and safety. Eligible patients with BM from solid tumors were randomized at a 1:1 ratio to receive 120 mg of LY01011 or 120 mg of denosumab subcutaneously every four weeks during a 12-week double-blind treatment period, and then all enrolled patients continued to receive LY01011 until week 53. The primary endpoint was the natural logarithm of change of the urinary N-terminal crosslinked telopeptide of type I collagen level normalized to the urine creatinine level (uNTX/uCr) at week 13 from baseline. Other endpoints included the uNTX/uCr ratio, serum bone-specific alkaline phosphatase level alteration, status of anti-drug antibodies and neutralizing antibodies, adverse events and SREs. 850 eligible patients were randomized into the LY01011 group (n = 424) or the denosumab group (n = 426). The least-squares means (SEs) of the natural logarithms of the changes in the uNTX/uCr ratios at week 13 from baseline were -1.810 (0.0404) in the LY01011 group and -1.791 (0.0406) in the denosumab group. The LSM difference [90 % CI] between two arms was -0.019 [-0.110, 0.073] within the equivalence margins (-0.135, 0.135) and met the predetermined primary endpoint. The AEs, ADAs and the PK data showed no statistically significant difference. This study demonstrated the equivalent efficacy and safety of LY01011 to denosumab in patients with BM.
article: Cannulated screw internal fixation combined with quadratus femoris muscle bone flap transplantation in the treatment of femoral neck fracture in young adults - Minerva Pediatrics 2022 June;74(3):383-5 - Minerva Medica - Journals
Radiomics was proposed by Lambin et al. in 2012 and since then there has been an explosion of related research. There has been significant interest in developing high-throughput methods that can automatically extract a large number of quantitative image features from medical images for better diagnostic or predictive performance. There have also been numerous radiomics investigations on intrahepatic cholangiocarcinoma in recent years, but no pertinent review materials are readily available. This work discusses the modeling analysis of radiomics for the prediction of lymph node metastasis, microvascular invasion, and early recurrence of intrahepatic cholangiocarcinoma, as well as the use of deep learning. This paper briefly reviews the current status of radiomics research to provide a reference for future studies.
Abstract Background Tumor morphology, immune function, inflammatory levels, and nutritional status play critical roles in the progression of intrahepatic cholangiocarcinoma (ICC). This multicenter study aimed to investigate the association between markers related to tumor morphology, immune function, inflammatory levels, and nutritional status with the prognosis of ICC patients. Additionally, a novel tumor morphology immune inflammatory nutritional score (TIIN score), integrating these factors was constructed. Methods A retrospective analysis was performed on 418 patients who underwent radical surgical resection and had postoperative pathological confirmation of ICC between January 2016 and January 2020 at three medical centers. The cohort was divided into a training set ( n = 272) and a validation set ( n = 146). The prognostic significance of 16 relevant markers was assessed, and the TIIN score was derived using LASSO regression. Subsequently, the TIIN-nomogram models for OS and RFS were developed based on the TIIN score and the results of multivariate analysis. The predictive performance of the TIIN-nomogram models was evaluated using ROC survival curves, calibration curves, and clinical decision curve analysis (DCA). Results The TIIN score, derived from albumin-to-alkaline phosphatase ratio (AAPR), albumin–globulin ratio (AGR), monocyte-to-lymphocyte ratio (MLR), and tumor burden score (TBS), effectively categorized patients into high-risk and low-risk groups using the optimal cutoff value. Compared to individual metrics, the TIIN score demonstrated superior predictive value for both OS and RFS. Furthermore, the TIIN score exhibited strong associations with clinical indicators including obstructive jaundice, CEA, CA19-9, Child–pugh grade, perineural invasion, and 8th edition AJCC N stage. Univariate and multivariate analysis confirmed the TIIN score as an independent risk factor for postoperative OS and RFS in ICC patients ( p < 0.05). Notably, the TIIN-nomogram models for OS and RFS, constructed based on the multivariate analysis and incorporating the TIIN score, demonstrated excellent predictive ability for postoperative survival in ICC patients. Conclusion The development and validation of the TIIN score, a comprehensive composite index incorporating tumor morphology, immune function, inflammatory level, and nutritional status, significantly contribute to the prognostic assessment of ICC patients. Furthermore, the successful application of the TIIN-nomogram prediction model underscores its potential as a valuable tool in guiding individualized treatment strategies for ICC patients. These findings emphasize the importance of personalized approaches in improving the clinical management and outcomes of ICC.
Abstract This study aims to explore the risk factors associated with frozen shoulder (FS) and develop a predictive model for diagnosing FS, in order to facilitate early detection of the condition. A total of 103 patients diagnosed with FS and admitted to the Department of Joint Surgery at Suining Central Hospital between October 2021 and October 2023 were consecutively included in the study. Additionally, 309 individuals without shoulder joint diseases, matched for age and gender, who visited the department during the same time, were included as the control group.The complete recording of clinical data for all patients was followed by the utilization of statistical tests such as the Mann–Whitney U test, sample t test, and chi-square test to compare different groups. Additionally, multivariate binary logistic regression analysis was employed to identify risk factors associated with the occurrence of FS in patients, leading to the establishment of a prediction model and derivation of a simplified equation. The diagnostic effectiveness of individual indicators and prediction models was assessed through the use of receiver operating characteristic (ROC) curve analysis. In the sample of 103 individuals, 35 were identified as male and 68 as female, with an average age range of 40–70 years (mean age: 54.20 ± 6.82 years). The analysis conducted between different groups revealed that individuals with a low body mass index (BMI), in conjunction with other factors such as diabetes, cervical spondylosis, atherosclerosis, and hyperlipidemia, were more susceptible to developing FS. Logistic regression analysis further indicated that low BMI, diabetes, cervical spondylosis, and hyperlipidemia were significant risk factors for the occurrence of FS. These variables were subsequently incorporated into a predictive model, resulting in the creation of a simplified equation.The ROC curve demonstrated that the combined indicators in the predictive model exhibited superior diagnostic efficacy compared to single indicators, as evidenced by an area under the curve of 0.787, sensitivity of 62.1%, and specificity of 82.2%. Low BMI, diabetes, cervical spondylosis, and hyperlipidemia are significant risk factors associated with the occurrence of FS. Moreover, the utilization of a prediction model has demonstrated superior capability in forecasting the likelihood of FS compared to relying solely on individual indicators. This finding holds potential in offering valuable insights for the early diagnosis of FS.
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