Questionnaire survey and analysis of drug clinical research implementation capabilities of breast cancer treatment departments in Chinese hospitals.

BACKGROUND: Clinical research competence determines the quality of clinical research and the reliability of research findings. We aimed to explore the clinical research implementation capabilities of breast cancer treatment departments in China. METHODS: This was a department-based cross-sectional study conducted in the form of electronic questionnaires on the Wenjuanxing platform from 7th August to 31st August 2023 among hospitals from the first batch of breast cancer standardized diagnosis and treatment quality control pilot centers in China. RESULTS: A total of 127 questionnaires from 122 hospitals were ultimately included in the analysis. Medical personnel involved in the clinical research of 118 (92.9 %) departments received good clinical practice (GCP) training. The steps of the approval process from research initiation to completion lasted 2-4 weeks or longer. The majority of departments initiated or participated in 2 or fewer clinical research projects over the past year. Among the differences between different departments, the Department of Medical Oncology had a better qualification profile and process and greater number of initiated and participated clinical studies than did the Department of Surgical Oncology. For needs and problems, most of the departments were strongly willing to undertake clinical research and receive professional training; the most common problem in the process of conducting studies was patient recruitment. CONCLUSIONS: Most departments generally exhibited complete capabilities for implementing clinical research. Improvements in implementation efficiency, quality of research and patient recruitment are still needed. Professional training and communication, as well as the recommendation of clinical research, are required in future development.

Serum Concentration of CD137 and Tumor Infiltration by M1 Macrophages Predict the Response to Sintilimab plus Bevacizumab Biosimilar in Advanced Hepatocellular Carcinoma Patients.

PURPOSE: This study aimed to investigate the biomarkers of sintilimab (anti-PD-1) plus IBI305 (a bevacizumab biosimilar) in advanced hepatocellular carcinoma (HCC), as well as their safety and efficacy. PATIENTS AND METHODS: A total of 50 patients with advanced HCC received sintilimab (200 mg) plus IBI305 (7.5 or 15 mg/kg), treated every 3 weeks in a phase Ib clinical study. We performed baseline serum cytokine analysis using bead-based multiplex immunoassay and multiplex immunofluorescence on tissue specimens to discover novel biomarkers of response to VEGF/PD-1 combination therapy in HCC. RESULTS: The overall response rate was 34.0% (17/50). The median progression-free survival (PFS) and the median overall survival were 10.5 and 20.2 months, respectively. The incidence of grade 3 to 5 adverse events was lower in the 7.5 mg/kg (13.8%) than in the 15 mg/kg (28.6%) dose groups. Biomarker analysis showed that the serum CD137 concentration was significantly higher in patients with clinical benefit (CB) than in those without CB (median, 32.8 pg/mL vs. 19.8 pg/mL, P = 0.034). A markedly longer PFS was observed in patients with high CD137 concentrations compared with those with low concentrations (median, 14.2 months vs. 4.1 months, P = 0.001). The higher density of M1 macrophages (CD68+CD163-) in the stroma was also associated with higher efficacy (P = 0.033) and a longer PFS (P = 0.024). CONCLUSIONS: Sintilimab plus IBI305 was well tolerated and was effective therapy for advanced HCC. Both serum concentrations of CD137 and tumor infiltration of M1 macrophages may serve as potential predictive biomarkers. See related commentary by Cappuyns and Llovet, p. 3405.

Advanced development of biomarkers for immunotherapy in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common liver cancer and one of the leading causes of cancer-related deaths in the world. Mono-immunotherapy and combination therapy with immune checkpoint inhibitors (ICIs) and multitargeted tyrosine kinase inhibitors (TKIs) or anti-vascular endothelial growth factor (anti-VEGF) inhibitors have become new standard therapies in advanced HCC (aHCC). However, the clinical benefit of these treatments is still limited. Thus, proper biomarkers which can predict treatment response to immunotherapy to maximize clinical benefit while sparing unnecessary toxicity are urgently needed. Contrary to other malignancies, up until now, no acknowledged biomarkers are available to predict resistance or response to immunotherapy for HCC patients. Furthermore, biomarkers, which are established in other cancer types, such as programmed death ligand 1 (PD-L1) expression and tumor mutational burden (TMB), have no stable predictive effect in HCC. Thus, plenty of research focusing on biomarkers for HCC is under exploration. In this review, we summarize the predictive and prognostic biomarkers as well as the potential predictive mechanism in order to guide future research direction for biomarker exploration and clinical treatment options in HCC.

Longitudinal Average Glucose Levels and Variance and Risk of Stroke: A Chinese Cohort Study.

BACKGROUND: Diabetes is a known independent risk factor for stroke. However, whether higher glucose levels (126-139.9 mg/dl) can increase the risk of stroke in people without diabetes is still unknown. Moreover, as a fluctuating parameter, long-term glucose levels may also be related to the risk of stroke outcome. It is important to explore the correlation between long-term average blood glucose, as well as its variability, and stroke. METHODS: We used 40,975 clinical measurements of glucose levels and 367 measurements of glycated hemoglobin A1c levels from 12,321 participants without stroke to examine the relationship between glucose levels and the risk of stroke. Participants were from the Weitang Geriatric Diseases study, including 5,707 men and 6,614 women whose mean age at baseline was 60.8 years; 1,011 participants had diabetes, and 11,310 did not. We estimated the long-term average blood glucose level based on the multilevel Bayesian model and fit in Cox regression models, stratified according to diabetes status. RESULTS: Over a median follow-up period of 5 years, stroke developed in 279 of the 12,321 participants (244 without diabetes and 35 with). For people with an average glucose level of 126-139.9 mg per deciliter, compared with 90-99.9 mg per deciliter, the adjusted hazard ratio (HR) for total stroke was 1.78 (95% confidence interval (CI), 1.16-2.75), and the HR for levels higher than 140 mg per deciliter was 1.89 (95% CI, 1.09-3.29). Among those without diabetes whose glucose level was higher than 140 mg per deciliter, compared with 90-99.9 mg per deciliter, the adjusted HRs for total stroke and fatal stroke were 3.66 (95% CI, 1.47-9.08) and 5 (95% CI, 1.77-14.15), respectively. For a glucose standard deviation level higher than 13.83 mg per deciliter, compared with that lower than 5.91 mg per deciliter, the adjusted HR for total stroke was 2.31 (95% CI, 1.19-4.48). CONCLUSIONS: Our results suggest that higher average glucose levels (126-139.9 mg/dl) and variance may be risk factors for stroke, even among people without diabetes diagnosis.

[Average blood glucose construction: a multi-level Bayes model approach and application].

OBJECTIVE: To explore the average blood glucose construction method based on the multi-level Bayes model and evaluate the example application. METHODS: We generate simulated data with multi-level Bayes model. Three methods were utilized to construct the average blood glucose at the same time, then we compared the result with each other. A cohort study method was used to select 12321 participants aged over 45 y who without stroke in a community in Suzhou and was followed up from 2011 to 2018, of which 53. 7% were male. Mean blood glucose calculated by the most accurate complete Bayesian method was divided into six groups. The Cox regression model was used to analyze the effect of mean blood glucose on the incidence of fatal stroke. RESULTS: 1000 times of simulation result showed that the average mean blood glucose estimation calculated by the complete Bayesian method was 0. 278, the average of blood glucose estimation was 0. 527 mmol/L, and the average correlation coefficient with the actual blood glucose was r=0. 898. During the follow-up period, 153 fatal strokes occurred. Association was found between the mean blood glucose and the risk of fatal stroke(P<0. 05). The average risk of blood glucose over 140 mg/dL was 2. 304 times that of 90-99 mg/dL(HR=2. 304, 95%CI 1. 151-4. 613) after the adjustment of effects. CONCLUSION: The complete Bayesian multi-level latent variable model can accurately estimate the average blood glucose.

Coagulation parameters predictive of polycystic ovary syndrome.

OBJECTIVE: To explore coagulation parameters in association with polycystic ovarian syndrome (PCOS) and establish a model for predicting the risk of PCOS. STUDY DESIGN: This study included 181 outpatients with PCOS. A total of 301 women who attempted to seek pre-pregnancy consultation at the Department of Gynecology of our hospital were included in the control group, and six coagulation parameters were measured for all included subjects. A logistic regression model was built based on the training dataset using the purposeful selection method to select important predictors. The performance of the established model was validated on the test dataset. RESULTS: There were statistically significant differences found among all coagulation parameters except D-Dimer (DD, P = 0.080). The purposeful selection method selected age (odds ratio [OR] = 0.89; p = 0.008), prothrombin time (PT, OR = 0.68, p < 0.0001), thrombin time (TT, OR = 3.30; p = 0.0005), and fibrin degradation products (FDP, OR = 0.24; p = 0.0002) as important predictors of PCOS risk. The receiver operating characteristic (ROC) curve analysis indicated that the area under the ROC curve (AUC) of the model was 0.81 for the training dataset with an optimal cut-off point of the predicted probability of 0.45, leading to a sensitivity of 0.71 and a specificity of 0.82. The AUC was 0.79 for the test data. CONCLUSIONS: It was found that the coagulation parameters, including PT, TT, and FDP, are predictive of PCOS. These results highlight the potential of anti-coagulation therapies to lower the risk of adverse outcomes in women with PCOS.

Characteristics of midluteal phase uterine artery hemodynamics in patients with recurrent pregnancy loss.

AIM: To study the association in resistance to uterine artery blood flow and recurrent pregnancy loss (RPL) and find its potential influencing factors. METHODS: A retrospective study was conducted in 870 RPL and 237 non-RPL patients visiting to the Clinic from January 2014 to February 2018. All participants underwent comprehensive examinations and were scanned by transvaginal Doppler ultrasonography during the midluteal phase to measure the pulsatility index (PI), resistance index (RI) and systolic/diastolic ratio (S/D) values of the left and right main uterine arteries. P value less than 0.05 was considered statistically significant. RESULTS: The mean PI, RI and S/D values for uterine arteries were significantly higher in RPL patients than in non-RPL patients (P < 0.001). When subjects were grouped according to the different etiologies of RPL, significant higher indices of uterine arteries were found in RPL patients with antiphospholipid syndrome (P < 0.001), autoimmune diseases (P < 0.001), endocrinological abnormalities (P < 0.05), thrombophilia (P < 0.001), uterine anomalies (P < 0.01) and unexplained RPL (P < 0.001). No differences were found between patients with chromosomal anomalies and uterine arteries blood flow (P > 0.05). In RPL patients, mean PI, mean RI and mean S/D values shows no difference among groups (P > 0.05). The Similar results were observed in age and number of spontaneous abortion (P > 0.05). CONCLUSION: Impaired uterine artery blood perfusion may be an underlying pathology to RPL, and it can be used as an independent risk factor for pregnancy failure.