A retrospective study on the analysis of influencing factors of neutropenia in endometrial cancer with adjuvant chemoradiotherapy.

OBJECTIVE: This retrospective study aimed to investigate the factors influencing the occurrence of neutropenia in patients with endometrial cancer (EC) following adjuvant chemoradiotherapy (CRT). METHODS: Retrospective analysis of EC patients who underwent adjuvant CRT from January 2012 to June 2023 in the Department of Gynecology and Oncology of the First Affiliated Hospital of Shandong First Medical University. Neutropenia was defined as an Absolute Neutrophil Count (ANC) of peripheral blood neutrophils below 2 × 109/L. Factors affecting neutropenia in EC patients treated with CRT using Generalized Estimating Equation (GEE), and Logistic regression was used to further analyze the effect of adding radiotherapy to different chemotherapy cycles on neutropenia, so that patients receive optimal adjuvant CRT while the risk of neutropenia is appropriately controlled. RESULTS: A total of 144 patients met the inclusion criteria. They underwent 330 cycles of adjuvant chemotherapy, of whom 96 (66.7%) developed neutropenia, which occurred 140 times. The results of one-way GEE analysis showed that before CRT, White Blood Cell (WBC) (OR = 0.827; 95%CI, 0.701-0.976), ANC (OR = 0.749; 95%CI, 0.586-0.957), Absolute Monocyte Count (AMC) (OR = 0.047; 95%CI, 0.008-0.283), Blood Urea Nitrogen (BUN) (OR = 0.857; 95%CI, 0.741-0.991), platinum and docetaxel (platinum/docetaxel) dosing regimen (OR = 2.284; 95%CI, 1.130-4.618) were associated with neutropenia with adjuvant CRT for EC (p < 0.05), results of multifactorial GEE analysis showed that before adjuvant CRT ANC (OR = 0.552; 95%CI, 0.973-2.231), AMC (OR = 0.047; 95%CI, 0.004-0.052), platinum/docetaxel (OR = 2.437; 95%CI, 1.087-5.464) were an independent influence on neutropenia in adjuvant CRT for EC (p < 0.05). Multifactorial Logistic regression shows addition of radiotherapy to the first cycle of chemotherapy (OR = 4.413; 95%CI, 1.238-18.891) was an independent influence of neutropenia (p < 0.05). CONCLUSIONS: Patients with low pre-CRT ANC and AMC, platinum/docetaxel dosing regimens need to be closely monitored during each cycle of CRT. Also, the concurrent addition of radiotherapy should be avoided during the first cycle of chemotherapy.

Risk factors associated with false negative rate of sentinel lymph node biopsy in endometrial cancer: a systematic review and meta-analysis.

Objective: Currently, sentinel lymph node biopsy (SLNB) is increasingly used in endometrial cancer, but the rate of missed metastatic lymph nodes compared to systemic lymph node dissection has been a concern. We conducted a systematic review and meta-analysis to evaluate the false negative rate (FNR) of SLNB in patients with endometrial cancer and to explore the risk factors associated with this FNR. Data sources: Three databases (PubMed, Embase, Web of Science) were searched from initial database build to January 2023 by two independent reviewers. Research eligibility criteria: Studies were included if they included 10 or more women diagnosed with International Federation of Gynecology and Obstetrics (FIGO) stage I or higher endometrial cancer, the study technique used sentinel lymph node localization biopsy, and the reported outcome metrics included false negative and/or FNR. Study appraisal and synthesis methods: Two authors independently reviewed the abstracts and full articles. The FNR and factors associated with FNR were synthesized through random-effects meta-analyses and meta-regression. The results: We identified 62 eligible studies. The overall FNR for the 62 articles was 4% (95% CL 3-5).There was no significant difference in the FNR in patients with high-risk endometrial cancer compared to patients with low-risk endometrial cancer. There was no difference in the FNR for whether frozen sections were used intraoperatively. The type of dye used intraoperatively (indocyanine green/blue dye) were not significantly associated with the false negative rate. Cervical injection reduced the FNR compared with alternative injection techniques. Indocyanine green reduced the FNR compared with alternative Tc-99m. Postoperative pathologic ultrastaging reduced the FNR. Conclusions: Alternative injection techniques (other than the cervix), Tc-99m dye tracer, and the absence of postoperative pathologic ultrastaging are risk factors for a high FNR in endometrial cancer patients who undergo SLNB; therefore, we should be vigilant for missed diagnosis of metastatic lymph nodes after SLNB in such populations. Systematic review registration: http://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023433637.

Effect of different interventions on the treatment of high-risk human papillomavirus infection: a systematic review and network meta-analysis.

Background: Persistent infection with high-risk human papillomavirus (HR-HPV) can lead to cervical intraepithelial neoplasia and cancer. At present, there is no medication that specifically targets HR-HPV infection. Objective: This study aimed to evaluate the effectiveness of different interventions in promoting HR-HPV regression using a MeSH meta-analysis method. Methods: A search for randomized controlled trials (RCTs) reporting different interventions for the treatment of HR-HPV infection included PubMed, Web of Science, Embase and Cochrane Library from the inception of the databases to March 8, 2023. Two researchers independently screened the articles, extracted data, and evaluated the quality. The literature that met the inclusion criteria was selected, the quality and risk of bias of the included studies were assessed according to the Cochrane 5.1 manual, and NMA was performed using Stata 16.0. The area under the cumulative ranking probability graph (SUCRA) represented the probability that each treatment would be the best intervention. Results: Nine studies involving 961 patients and 7 treatment options were included in the analysis. The results of the network meta-analysis indicated the following rank order in terms of promoting HR-HPV conversion: Anti-HPV biological dressing > vaginal gel > imiquimod > REBACIN® > interferon > probiotics > observation/placebo > Polyphenon E. Conclusion: Anti-HPV biological dressing treatment was found to be significantly effective in promoting HR-HPV conversion. However, further validation of the findings is necessary due to the limited number and quality of studies included in the analysis. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023413917.

GVDTI: graph convolutional and variational autoencoders with attribute-level attention for drug-protein interaction prediction.

MOTIVATION: Identifying proteins that interact with drugs plays an important role in the initial period of developing drugs, which helps to reduce the development cost and time. Recent methods for predicting drug-protein interactions mainly focus on exploiting various data about drugs and proteins. These methods failed to completely learn and integrate the attribute information of a pair of drug and protein nodes and their attribute distribution. RESULTS: We present a new prediction method, GVDTI, to encode multiple pairwise representations, including attention-enhanced topological representation, attribute representation and attribute distribution. First, a framework based on graph convolutional autoencoder is constructed to learn attention-enhanced topological embedding that integrates the topology structure of a drug-protein network for each drug and protein nodes. The topological embeddings of each drug and each protein are then combined and fused by multi-layer convolution neural networks to obtain the pairwise topological representation, which reveals the hidden topological relationships between drug and protein nodes. The proposed attribute-wise attention mechanism learns and adjusts the importance of individual attribute in each topological embedding of drug and protein nodes. Secondly, a tri-layer heterogeneous network composed of drug, protein and disease nodes is created to associate the similarities, interactions and associations across the heterogeneous nodes. The attribute distribution of the drug-protein node pair is encoded by a variational autoencoder. The pairwise attribute representation is learned via a multi-layer convolutional neural network to deeply integrate the attributes of drug and protein nodes. Finally, the three pairwise representations are fused by convolutional and fully connected neural networks for drug-protein interaction prediction. The experimental results show that GVDTI outperformed other seven state-of-the-art methods in comparison. The improved recall rates indicate that GVDTI retrieved more actual drug-protein interactions in the top ranked candidates than conventional methods. Case studies on five drugs further confirm GVDTI's ability in discovering the potential candidate drug-related proteins. CONTACT: zhang@hlju.edu.cn Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.