Efficacy and safety of tyrosine kinase inhibitors for advanced metastatic thyroid cancer: A systematic review and network meta-analysis of randomized controlled trials.

BACKGROUND: Tyrosine kinase inhibitors (TKIs) have been approved for treating patients with clinically advanced metastatic thyroid cancer. However among the many TKIs, it remains unknown which regimen is the best choice for these patients. METHODS: We conducted a systematic review and network meta-analysis to compare the survival benefits and efficacy of the available first-line regimens. We conducted an active search for phase II, III, or IV randomized controlled trials (RCTs) in the PubMed, Embase, and Cochrane databases to compare the effects of at least 2 drugs in the systemic treatment of advanced or metastatic thyroid cancer up to May 2023. The network meta-analysis model was adjusted using Bayesian Network model. Twelve trials with 2535 patients were included in our meta-analysis. The overall survival (OS), progression-free survival (PFS), and serious adverse events (SAEs) were taken as reference indicators. We also performed subgroup analyses of OS and PFS in medullary thyroid cancer (MTC) and radioiodine-refractory differentiated thyroid cancer (RR-DTC) to explore the variations of TKIs in different groups. RESULTS: As a result, apatinib had the best effect on overall survival (OS) (hazards ratio [HR] = 0.42, 95% confidence interval [CI] = 0.18-0.98), lenvatinib 18 mg/d has the best effect on progression-free survival (PFS) (HR = 0.13, 95% CI = 0.064-0.27), and cabozantinib 60 mg/d has the best safety profile. CONCLUSIONS: Our network meta-analysis showed that we believe that cabozantinib has the potential to become a widely used drug in clinical practice.

Semipinacol Rearrangement of Iododifluorohomoallyl Alcohols and Its Application in the Allylic C-H Esterification Reactions.

We herein present a study on the Ag(I)-mediated semipinacol rearrangement of iododifluorohomoallyl alcohols, the resulting allylic difluoromethyl ketones underwent oxidative allylic C-H esterification under palladium catalysis in the absence of external ligand. This process yielded a range of difluoromethyl ketones derived from allyl esters in a single operation. The reaction features broad scope of o-nitrobenzoic acids and homoallylic iododifluoroalcohols affording the targeted molecules in synthetically useful yields. Control experiments illustrated that the silver salt acted as not only a Lewis acid to promote the cleavage of a C-I bond and furnish the semipinacol rearrangement but also a co-oxidant in the catalytic cycle for the allylic C-H esterification.

SHMT2 promotes papillary thyroid cancer metastasis through epigenetic activation of AKT signaling.

Cancer cells alter their metabolism and epigenetics to support cancer progression. However, very few modulators connecting metabolism and epigenetics have been uncovered. Here, we reveal that serine hydroxymethyltransferase-2 (SHMT2) generates S-adenosylmethionine (SAM) to epigenetically repress phosphatase and tensin homolog (PTEN), leading to papillary thyroid cancer (PTC) metastasis depending on activation of AKT signaling. SHMT2 is elevated in PTC, and is associated with poor prognosis. Overexpressed SHMT2 promotes PTC metastasis both in vitro and in vivo. Proteomic enrichment analysis shows that AKT signaling is activated, and is positively associated with SHMT2 in PTC specimens. Blocking AKT activation eliminates the effects of SHMT2 on promoting PTC metastasis. Furthermore, SHMT2 expression is negatively associated with PTEN, a negative AKT regulator, in PTC specimens. Mechanistically, SHMT2 catalyzes serine metabolism and produces activated one-carbon units that can generate SAM for the methylation of CpG islands in PTEN promoter for PTEN suppression and following AKT activation. Importantly, interference with PTEN expression affects SHMT2 function by promoting AKT signaling activation and PTC metastasis. Collectively, our research demonstrates that SHMT2 connects metabolic reprogramming and epigenetics, contributing to the poor progression of PTC.

Dexmedetomidine Prevents Chronic Incisional Pain After Brain Tumor Resection: A Secondary Analysis of the Randomized Control Trial.

BACKGROUND: Dexmedetomidine was reported to reduce postoperative acute pain after neurosurgery. However, the efficacy of dexmedetomidine for preventing chronic incisional pain is uncertain. METHODS: This article is a secondary analysis of a randomized, double-blind, placebo-controlled trial. Eligible patients were randomly allocated to either the dexmedetomidine group or the placebo group. Patients assigned to the dexmedetomidine group were given a 0.6 µg kg -1 dexmedetomidine bolus followed by a 0.4 µg kg -1 h -1 maintenance dose until dural closure; placebo patients were given comparable amounts of normal saline. The primary end point was the incidence of incisional pain at 3 months after craniotomy evaluated by numerical rating scale scores and defined as any score >0. The secondary end points were postoperative acute pain scores, sleep quality, and Short-Form McGill Pain Questionnaire (SF-MPQ-2) at 3 months after craniotomy. RESULTS: From January 2021 to December 2021, a total of 252 patients were included in the final analysis: the dexmedetomidine group (n = 128) and the placebo group (n = 124). The incidence of chronic incisional pain was 23.4% (30 of 128) in the dexmedetomidine group versus 42.7% (53 of 124) in the placebo group (risk ratio, 0.55; 95% confidence interval, 0.38-0.80; P = .001). The overall severity of chronic incisional pain was mild in both groups. Patients in the dexmedetomidine group had lower acute pain severity on movement than those in the placebo group for the first 3 days after surgery (all adjusted P < .01). Sleep quality did not differ between groups. However, the SF-MPQ-2 total sensory ( P = .01) and neuropathic pain descriptor ( P = .023) scores in the dexmedetomidine group were lower than those in the placebo group. CONCLUSIONS: Prophylactic intraoperative dexmedetomidine infusion reduces the incidence of chronic incisional pain as well as acute pain score after elective brain tumor resections.

Surgical techniques and effectiveness of laparoscopic resection of abdominal wall desmoid-type fibromatosis and defect reconstruction: a single-center retrospective analysis.

PURPOSE: Although the treatment of abdominal wall desmoid-type fibromatosis (DF) has evolved over the past decades, surgical treatment remains an important approach. Previously, surgeries for abdominal DF were mostly performed by laparotomy, which involves massive dissection and significant trauma. Here, we report our single-center experience of the laparoscopic management of abdominal wall DF in young female patients. METHODS: The clinical data of nine patients diagnosed with abdominal wall DF during January 2020-April 2022 at the Qilu Hospital of Shandong University were retrospectively analyzed. All patients underwent laparoscopic resection of abdominal wall DF and immediate abdominal wall reconstruction (AWR) with mesh augmentation via the intraperitoneal onlay mesh (IPOM) technique. RESULTS: Laparoscopic DF resection and AWR were successfully performed in all patients. The mean operation time was 175.56 ± 46.20 min. The width of abdominal wall defect was 8.61 ± 3.30 cm. Full- and partial-thickness myofascial closure and reapproximation were performed in five, two, and two patients, respectively. The average mesh size was 253.33 ± 71.01 cm2. The total and postoperative lengths of hospital stay were 11.00 ± 3.46 and 4.89 ± 2.03 days, respectively. Tumor recurred in one patient after 20 months of the resection. Nonetheless, death, herniation, or bulging were not observed in any patient during a mean follow-up of 16.11 ± 8.43 months. CONCLUSION: Laparoscopic resection of abdominal wall DF and immediate AWR with IPOM mesh reinforcement is safe and reliable for young female patients. Management of such patients should be decided according to the biological behavior, size, and location of tumors.

Identification and validation of key biomarkers associated with macrophages in nonalcoholic fatty liver disease based on hdWGCNA and machine learning.

BACKGROUND: NAFLD has attracted increasing attention because of its high prevalence and risk of progression to cirrhosis or even hepatocellular carcinoma. Therefore, research into the root causes and molecular indicators of NAFLD is crucial. METHODS: We analyzed scRNA-seq data and RNA-seq data from normal and NAFLD liver samples. We utilized hdWGCNA to find module-related genes associated with the phenotype. Multiple machine learning algorithms were used to validate the model diagnostics and further screen for genes that are characteristic of NAFLD. The NAFLD mouse model was constructed using the MCD diet to validate the diagnostic effect of the genes. RESULTS: We identified a specific macrophage population called NASH-macrophages by single-cell sequencing analysis. Cell communication analysis and Pseudo-time trajectory analysis revealed the specific role and temporal distribution of NASH-macrophages in NAFLD. The hdWGCNA screening yielded 30 genes associated with NASH-macrophages, and machine learning algorithms screened and obtained two genes characterizing NAFLD. The immune infiltration indicated that these genes were highly associated with macrophages. Notably, we verified by RT-qPCR, IHC, and WB that MAFB and CX3CR1 are highly expressed in the MCD mouse model and may play important roles. CONCLUSIONS: Our study revealed a macrophage population that is closely associated with NAFLD. Using hdWGCNA analysis and multiple machine learning algorithms, we identified two NAFLD signature genes that are highly correlated with macrophages. Our findings may provide potential feature markers and therapeutic targets for NAFLD.

Construction and validation of a PANoptosis-related lncRNA signature for predicting prognosis and targeted drug response in thyroid cancer.

Thyroid cancer (TC) is the most prevalent malignancy of the endocrine system. PANoptosis, a newly discovered cell death pathway, is of interest in tumor research. However, the relationship between PANoptosis-related lncRNAs (PRlncRNAs) and TC remains unclear. The study aimed to develop a prognostic model based on PRlncRNAs in TC. Gene expression data of PANoptosis-associated genes and clinical information on TC from The Cancer Genome Atlas (TCGA) database were analyzed by Pearson correlation analysis, univariate/multivariate Cox analysis, and Lasso Cox regression analysis. A PRlncRNA signature was constructed and used to develop a nomogram to predict overall survival (OS). We further explored the correlation between the risk score and tumor immune microenvironment, immune checkpoints, and drug sensitivity. Moreover, we verified the expression and biological function of lncRNAs in TC cell lines. Finally, seven PRlncRNAs were used to construct a prognostic model for predicting the OS of TC patients. We found that the risk score was associated with the tumor microenvironment (TME) and the expression of critical immune checkpoints. In addition, we screened for drugs that high- or low-risk TC groups might be sensitive to. Quantitative real-time polymerase chain reaction (qRT-PCR) results showed differential expression of four PRlncRNAs (GAPLINC, IDI2-AS1, LINC02154, and RBPMS-AS1) between tumor and normal tissues. Besides, a GEO database (GSE33630) was used to verify the expression differences of PRLncRNAs in THCA tissues and normal tissues. Finally, RBPMS-AS1 was found to inhibit the proliferation and migration of TC cells. In conclusion, we developed a PANoptosis-related lncRNA prognostic risk model that offers a comprehensive understanding of TME status in patients with TC and establishes a foundation for the choice of sensitive medications and immunotherapy.

Development and validation of a deep learning survival model for cervical adenocarcinoma patients.

BACKGROUND: The aim was to develop a personalized survival prediction deep learning model for cervical adenocarcinoma patients and process personalized survival prediction. METHODS: A total of 2501 cervical adenocarcinoma patients from the surveillance, epidemiology and end results database and 220 patients from Qilu hospital were enrolled in this study. We created our deep learning (DL) model to manipulate the data and evaluated its performance against four other competitive models. We tried to demonstrate a new grouping system oriented by survival outcomes and process personalized survival prediction by using our DL model. RESULTS: The DL model reached 0.878 c-index and 0.09 Brier score in the test set, which was better than the other four models. In the external test set, our model achieved a 0.80 c-index and 0.13 Brier score. Thus, we developed prognosis-oriented risk grouping for patients according to risk scores computed by our DL model. Notable differences among groupings were observed. In addition, a personalized survival prediction system based on our risk-scoring grouping was developed. CONCLUSIONS: We developed a deep neural network model for cervical adenocarcinoma patients. The performance of this model proved to be superior to other models. The results of external validation supported the possibility that the model can be used in clinical work. Finally, our survival grouping and personalized prediction system provided more accurate prognostic information for patients than traditional FIGO stages.

Based on ARASENS trial: efficacy and safety of darolutamide as an emerging option of endocrinotherapy for metastatic hormone-sensitive prostate cancer-an updated systematic review and network meta-analysis.

PURPOSE: The newly published ARASENS trial has demonstrated the clinical efficacy of darolutamide for metastatic hormone-sensitive prostate cancer (mHSPC). However, the use of darolutamide as the latest first-line androgen receptor pathway inhibitor for mHSPC has not been compared with other androgen receptor targeted agents (ARTAs). Given the lack of head-to-head randomized trials, we performed this updated meta-analysis to conduct indirect comparison for the efficacy and safety of darolutamide with other new-generation ARTAs. METHODS: By searching the databases of PubMed, Scopus, Cochrane Library, and Embase, 9 large randomized controlled trials evaluating ARTAs for mHSPC patients were eventually screened according to PRISMA. We extracted data from overall survival, castration-resistant progression, and adverse events for network meta-analysis using the Bayesian and standard frequentist models. RESULTS: Darolutamide combination emerged with superiority (HR = 0.68, 95%CrI = 0.57-0.81) among four androgen receptor inhibitors for patients with high Gleason score (HR = 0.71, 95%CrI = 0.59-0.86). Darolutamide was best tolerated in several androgen suppression-related adverse events (AEs). CONCLUSION: Darolutamide appears to be an optional androgen receptor inhibitor for mHSPC patients, especially for patients with Gleason score ≥ 8. Its well-tolerated characteristic may provide a preferred drug option for patients with poor cardiovascular function and bone health.

Construction of a prognostic model based on eight ubiquitination-related genes via machine learning and potential therapeutics analysis for cervical cancer.

Introduction: Ubiquitination is involved in many biological processes and its predictive value for prognosis in cervical cancer is still unclear. Methods: To further explore the predictive value of the ubiquitination-related genes we obtained URGs from the Ubiquitin and Ubiquitin-like Conjugation Database, analyzed datasets from The Cancer Genome Atlas and Gene Expression Omnibus databases, and then selected differentially expressed ubiquitination-related genes between normal and cancer tissues. Then, DURGs significantly associated with overall survival were selected through univariate Cox regression. Machine learning was further used to select the DURGs. Then, we constructed and validated a reliable prognostic gene signature by multivariate analysis. In addition, we predicted the substrate proteins of the signature genes and did a functional analysis to further understand the molecular biology mechanisms. The study provided new guidelines for evaluating cervical cancer prognosis and also suggested new directions for drug development. Results: By analyzing 1,390 URGs in GEO and TCGA databases, we obtained 175 DURGs. Our results showed 19 DURGs were related to prognosis. Finally, eight DURGs were identified via machine learning to construct the first ubiquitination prognostic gene signature. Patients were stratified into high-risk and low-risk groups and the prognosis was worse in the high-risk group. In addition, these gene protein levels were mostly consistent with their transcript level. According to the functional analysis of substrate proteins, the signature genes may be involved in cancer development through the transcription factor activity and the classical P53 pathway ubiquitination-related signaling pathways. Additionally, 71 small molecular compounds were identified as potential drugs. Conclusion: We systematically studied the influence of ubiquitination-related genes on prognosis in cervical cancer, established a prognostic model through a machine learning algorithm, and verified it. Also, our study provides a new treatment strategy for cervical cancer.

Dexmedetomidine administration during brain tumour resection for prevention of postoperative delirium: a randomised trial.

BACKGROUND: Delirium is common, especially after neurosurgery. Dexmedetomidine might reduce delirium by improving postoperative analgesia and sleep quality. We tested the primary hypothesis that dexmedetomidine administration during intracerebral tumour resection reduces the incidence of postoperative delirium. METHODS: This randomised, double-blind, placebo-controlled trial was conducted in two tertiary-care hospitals in Beijing. We randomised 260 qualifying patients to either dexmedetomidine (n=130) or placebo (n=130). Subjects assigned to dexmedetomidine were given a loading dose of 0.6 µg kg-1 followed by continuous infusion at 0.4 µg kg-1 h-1 until dural closure; subjects in the placebo group were given comparable volumes of normal saline. The primary outcome was the incidence of delirium, which was assessed with the Confusion Assessment Method twice daily during the initial 5 postoperative days. RESULTS: The average (standard deviation) age of participating patients was 45 (12) yr, duration of surgery was 4.2 (1.5) h, and patients assigned to dexmedetomidine were given an average of 126 (45) µg of dexmedetomidine. There was less delirium during the initial 5 postoperative days in patients assigned to dexmedetomidine (22%, 28 of 130 patients) than in those given placebo (46%, 60 of 130 patients) with a risk ratio of 0.51 (95% confidence interval: 0.36-0.74, P<0.001). Postoperative pain scores with movement, and recovery and sleep quality were improved by dexmedetomidine (P<0.001). The incidence of safety outcomes was similar in each group. CONCLUSIONS: Prophylactic intraoperative dexmedetomidine infusion reduced by half the incidence of delirium during the initial 5 postoperative days in patients recovering from elective brain tumour resection. CLINICAL TRIAL REGISTRATION: NCT04674241.

Analysis of prognostic factors for cervical mucinous adenocarcinoma and establishment and validation a nomogram: a SEER-based study.

Up to now, there are no relevant studies on prognostic factors of cervical mucinous adenocarcinoma. Therefore, we explored the prognostic factors for cervical mucinous adenocarcinoma, and established and validated the prognostic model using the SEER database. We selected the independent factors through univariate and multivariate analyses. LASSO regression analysis was conducted to identify potential risk factors. In conjunction with LASSO and multivariate analysis, the nomogram incorporated three variables, including age, tumour size, and AJCC stage for OS. The c-index was 0.794 and 0.831 in development and validated cohorts, indicating that this prediction model showed adequate discriminative ability in the development cohort. Besides, calibration curves showed good concordance for the development cohort, as well as the validation cohort. We constructed a first-of-its-kind nomogram to predict cervical mucinous adenocarcinomas OS and it showed better performance than AJCC and FIGO stages. Patients with cervical mucinous adenocarcinoma might benefit from using this model to develop tailored treatments.IMPACT STATEMENTWhat is already known on this subject? Cervical cancer has a variety of pathological types. The biological behaviour of each type is different, and the prognosis is quite different.What do the results of this study add? We analysed and explored the relevant factors affecting the prognosis of cervical mucinous adenocarcinoma.What are the implications of these findings for clinical practice and/or further research? Through the analysis of the SEER dataset, the prognostic factors affecting cervical mucinous adenocarcinoma were identified, and the first predictive model was created to predict the prognosis to help doctors develop individualised treatment plans and follow-up plans.

Development of a Novel Deep Learning-Based Prediction Model for the Prognosis of Operable Cervical Cancer.

Background: Cervical cancer ranks as the 4th most common female cancer worldwide. Early stage cervical cancer patients can be treated with operation, but clinical staging system is not a good predictor of patients' survival. We aimed to develop a novel prognostic model to predict the prognosis for operable cervical cancer patients with better accuracy than clinical staging system. Methods: A total of 13,952 operable cervical cancer patients were retrospectively enrolled in this study. The whole dataset was randomly split into a training set (n = 9,068, 65%), validation set (n = 2,442, 17.5%), and testing set (n = 2,442, 17.5%). Cox proportional hazard (CPH) model and random survival forest (RSF) model were used as baseline models for the prediction of overall survival (OS). Then, a deep survival learning model (DSLM) was developed for OS prediction. Finally, a novel prognostic model was explored based on this DSLM. Results: The C-indexes for the CPH and RSF model were 0.731 and 0.753, respectively. DSLM, which had four layers that had 50 neurons in each layer, achieved a C-index of 0.782 in the validation set and a C-index of 0.758 in the testing set. The novel prognostic model based on DSLM showed better performances than the conventional clinical staging system (area under receiver operating curves were 0.826 and 0.689, respectively). Personalized survival curves for individual patient using this novel model also showed notably different survival slopes. Conclusions: Our study developed a novel, practical, personalized prognostic model for operable cervical cancer patients. This novel prognostic model may have the potential to provide a more prognostic information to oncologists.

Use of Nomogram to Predict the Risk of Lymph Node Metastasis among Patients with Cervical Adenocarcinoma.

Background: The objective of this study was to develop a nomogram that can predict lymph node metastasis (LNM) in patients with cervical adenocarcinoma (cervical AC). Methods: A total of 219 patients with cervical AC who had undergone radical hysterectomy and lymphadenopathy between 2005 and 2021 were selected for this study. Both univariate and multivariate logistic regression analyses were performed to analyze the selected key clinicopathologic features and develop a nomogram and underwent internal validation to predict the probability of LNM. Results: Lymphovascular invasion (LVI), tumor size ≥ 4 cm, and depth of cervical stromal infiltration were independent predictors of LNM in cervical AC. However, the Silva pattern was not found to be a significant predictor in the multivariate model. The Silva pattern was still included in the model based on the improved predictive performance of the model observed in the previous studies. The concordance index (C-index) of the model increased from 0.786 to 0.794 after the inclusion of the Silva pattern. The Silva pattern was found to be the strongest predictor of LNM among all the pathological factors investigated, with an OR of 4.37 in the nomogram model. The nomogram developed by incorporation of these four predictors performed well in terms of discrimination and calibration capabilities (C - index = 0.794; 95% confidence interval (CI), 0.727-0.862; Brier score = 0.127). Decision curve analysis demonstrated that the nomogram was clinically effective in the prediction of LNM. Conclusion: In this study, a nomogram was developed based on the pathologic features, which helped to screen individuals with a higher risk of occult LNM. As a result, this tool may be specifically useful in the management of individuals with cervical AC and help gynecologists to guide clinical individualized treatment plan.

Effect of anesthesia on the outcome of high-grade glioma patients undergoing supratentorial resection: study protocol for a pragmatic randomized controlled trial.

BACKGROUND: High-grade glioma (HGG) is the most malignant brain tumor with poor outcomes. Whether anesthetic methods have an impact on the outcome of these patients is still unknown. Retrospective study has found no difference between intravenous and inhalation anesthesia on the overall survival (OS) of the HGG patients, however, intravenous anesthesia with propofol might be beneficial in a subgroup of patients with a Karnofsky Performance Status (KPS) Scale less than 80. Further prospective studies are needed to evaluate the results. METHODS: This is a single-centered, randomized controlled, parallel-group trial. Three hundred forty-four patients with primary HGG for tumor resection will be randomly assigned to receive either intravenous anesthesia with propofol or inhalation anesthesia with sevoflurane. The primary outcome is the OS of the patients within 18 months. Secondary outcomes include progression-free survival (PFS), the numerical rating scale (NRS) of pain intensity and sleep quality, the postoperative encephaloedema volume, complications, and the length of hospital stay of the patients. DISCUSSION: This is a randomized controlled trial to compare the effect of intravenous and inhalation anesthesia maintenance on the outcome of supratentorial HGG patients. The results will contribute to optimizing the anesthesia methods in these patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT02756312. Registered on 29 April 2016 and last updated on 9 Sep 2020.

Ultrasound-guided superficial cervical plexus block reduces opioid consumption in patients undergoing craniotomy via suboccipital retrosigmoid approach: a randomized controlled trial.

INTRODUCTION: The effectiveness of superficial cervical plexus block (SCPB) at decreasing opioid use and improving hemodynamic stability during suboccipital retrosigmoid craniotomy has not been established. The aim of this study is to evaluate the analgesic effect of preoperative ultrasound-guided SCPB for craniotomy via a suboccipital retrosigmoid approach. METHODS: This was a prospective, single-center, randomized, double-blind, parallel-group controlled trial. One hundred and six adult patients undergoing suboccipital retrosigmoid craniotomy were randomly allocated into either the SCPB group (n=53) to receive 10 mL of 0.5% ropivacaine or the control group (n=53) to receive 0.9% normal saline injected into the superficial layer of prevertebral fascia guided by ultrasound. The primary outcome was the cumulative consumption of sufentanil with patient-controlled intravenous analgesia (PCIA) within 24 hours. Secondary outcomes included the overall perioperative consumption of opioids, the area under the curve of the pain score from 1 hour to 48 hours (AUC1-48), intraoperative hemodynamic parameters, and anesthesia depth. RESULTS: The mean PCIA pump cumulative consumption of sufentanil in the first 24 hour postoperative period was significantly lowered by SCPB (5.0 µg vs 9.8 µg, 95% CI: -8.0 to -2.4; p=0.001). The total perioperative consumption of sufentanil (45.0 µg vs 54.5 µg, 95% CI: -14.8 to -4.1; p=0.001) was also significantly decreased by SCPB. The incidence of severe pain within 24 hours was decreased by SCPB (7.5% vs 26.4%, p=0.01). SCPB significantly decreased the AUC1-48 of the pain score. Intraoperative hemodynamic parameters and anesthesia depth were similar between groups (p>0.05). DISCUSSION: SCPB provides effective analgesia in patients undergoing craniotomy and tumor resection via suboccipital retrosigmoid approach. SCPB demonstrates an opioid-sparing effect and allows for the maintenance hemodynamic stability at an appropriate depth of anesthesia. TRIAL REGISTRATION NUMBER: NCT04036812.

Comparison of different treatment strategies in the management of endogenic caesarean scar pregnancy: a multicentre retrospective study.

BACKGROUND: The aim of this study was to evaluate the effectiveness and safety of different treatment strategies for endogenic caesarean scar pregnancy (CSP) patients. METHODS: According to Vial's standard, we defined endogenic-type CSP as (1) the gestational sac growing towards the uterine cavity and (2) a greater than 0.3 cm thickness of myometrial tissue at the caesarean scar. A total of 447 endogenic CSP patients out of 527 patients from 4 medical centres in China were enrolled in this study. A total of 120 patients were treated with methotrexate (MTX) followed by surgery, 106 received ultrasound-guided curettage directly and 221 received curettage combined with hysteroscopy. The clinical information and clinical outcomes of these patients were reviewed. Successful treatment was defined as (1) no additional treatment needed, (2) no retained mass of conception and (3) serum ß subunit of human chorionic gonadotropin (ß-hCG) level returning to a normal level within 4 weeks. The success rate was analysed based on these factors. RESULT: Among 447 patients, no significant difference was observed in baseline characteristics between groups except for foetal heartbeat. The success rate was significantly different (p<0.001) among the three groups. The highest success rate of 95.9% was noted in the hysteroscopy group, and the lowest success rate of 84.0% was noted in the curettage group. In addition, the MTX group reported the longest hospital stay and highest expenses, but the curettage group showed the shortest and lowest expenses, respectively. Nevertheless, no difference in blood loss was observed between the groups. CONCLUSION: The combination of curettage and hysteroscopy represents the most effective strategy. Pretreatment with MTX did not result in better clinical outcomes. Ultrasound-guided curettage directly should not be considered a first-line treatment choice for endogenic CSP patients.