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Information regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on cervical cancer in mainland China is lacking. We explored its impact on the hospital attendance of patients with primary cervical cancer. We included 1918 patients with primary cervical cancer who initially attended Harbin Medical University Cancer Hospital between January 23, 2019, and January 23, 2021. Attendance decreased by 31%, from 1135 in 2019 to 783 in 2020, mainly from January to June (𝜒2 = 73.362, P < .001). The percentage of patients detected by screening decreased from 12.1% in January-June 2019 to 5.8% in January-June 2020 (𝜒2 = 7.187, P = .007). Patients with stage I accounted for 28.4% in 2020 significantly lower than 36.6% in 2019 (𝜒2 = 14.085, P < .001), and patients with stage III accounted for 27.1% in 2020 significantly higher than 20.5% in 2019 (𝜒2 = 11.145, P < .001). Waiting time for treatment was extended from 8 days (median) in January-June and July-December 2019 to 16 days in January-June (𝜒2 = 74.674, P < .001) and 12 days in July-December 2020 (𝜒2 = 37.916, P < .001). Of the 179 patients who delayed treatment, 164 (91.6%) were for the reasons of the healthcare providers. Compared to 2019, the number of patients in Harbin or non-Harbin in Heilongjiang Province and outside the province decreased, and cross-regional medical treatment has been hindered. The COVID-19 pandemic has negatively impacted cervical cancer patient attendance at the initial phase. These results are solid evidence that a strategy and mechanism for the effective attendance of cervical cancer patients in response to public health emergencies is urgently needed.  相似文献   
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Previous studies on the immunogenicity of SARS-CoV-2 mRNA vaccines showed a reduced seroconversion in cancer patients. The aim of our study is to evaluate the immunogenicity of two doses of mRNA vaccines in solid cancer patients with or without a previous exposure to the virus. This is a single-institution, prospective, nonrandomized study. Patients in active treatment and a control cohort of healthy people received two doses of BNT162b2 (Comirnaty, BioNTech/Pfizer, The United States) or mRNA-1273 (Spikevax, Moderna). Vaccine was administered before starting anticancer therapy or on the first day of the treatment cycle. SARS-CoV-2 antibody levels against S1, RBD (to evaluate vaccine response) and N proteins (to evaluate previous infection) were measured in plasma before the first dose and 30 days after the second one. From January to June 2021, 195 consecutive cancer patients and 20 healthy controls were enrolled. Thirty-one cancer patients had a previous exposure to SARS-CoV-2. Cancer patients previously exposed to the virus had significantly higher median levels of anti-S1 and anti-RBD IgG, compared to healthy controls (P = .0349) and to cancer patients without a previous infection (P < .001). Vaccine type (anti-S1: P < .0001; anti-RBD: P = .0045), comorbidities (anti-S1: P = .0274; anti-RBD: P = .0048) and the use of G-CSF (anti-S1: P = .0151) negatively affected the antibody response. Conversely, previous exposure to SARS-CoV-2 significantly enhanced the response to vaccination (anti-S1: P < .0001; anti-RBD: P = .0026). Vaccine immunogenicity in cancer patients with a previous exposure to SARS-CoV-2 seems comparable to that of healthy subjects. On the other hand, clinical variables of immune frailty negatively affect humoral immune response to vaccination.  相似文献   
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目的探讨乙肝相关性肝癌临床病理学特征与溶血磷脂酸(LPA)和高敏C反应蛋白(hs-CRP)表达的相关性。方法选取2019年1月至2020年1月间河南省驻马店市中心医院收治的198例乙肝相关性肝癌患者作为乙肝组,198例酒精相关性肝癌患者作为酒精组。两组患者都进行血清hs-CRP和LPA表达检测,调查患者的病理学特征并进行相关性分析。结果乙肝组患者血清hs-CRP和LPA含量均高于酒精组,差异均有统计学意义(均P <0.05)。两组患者血清ALP、AFP、ALT、AST和GGT含量比较,差异均无统计学意义(P> 0.05)。乙肝组不同临床分期和组织学分化患者的血清hs-CRP和LPA含量比较,差异均有统计学意义(均P <0.05)。乙肝组患者的临床分期和组织学分化与血清hs-CRP和LPA表达均存在相关性,差异均有统计学意义(均P <0.05)。患者的临床分期和组织学分化均为影响hs-CRP和LPA表达的重要因素,差异均有统计学意义(均P <0.05)。结论相对于酒精相关性肝癌,乙肝相关性肝癌的血清hs-CRP和LPA呈现高表达,与患者的临床病理学特征存在相关性。  相似文献   
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Objective: Hepatocellular carcinoma (HCC) microenvironment has been recognized as a key contributor for cancer progression, metastasis, and drug resistance. The crosstalk between tumor cells, the vascular endothelial growth factor (VEGF), and the chemokine (C-C motif) ligand 2 (CCL2) signaling networks mediates immunoinhibitory impact and facilitates tumor angiogenesis. The current investigation aimed at exploring the potent anti-cancer activity of the newly designed nano-based anti-cancer therapy comprising anti-VEGF drug, avastin (AV), and CCR2 antagonist (CR) to counteract HCC and tracking its mode of action in vivo. Methods: The prepared AV, CR, and AVCR nanoprototypes were characterized by nanoscale characterization techniques in our previous work. Here, they are applied for unearthing their anti-cancer properties / mechanisms in hepatic cancer-induced rats via analyzing protein levels and genetic expression of the elements incorporated in the angiogenesis, apoptosis, and metastasis signalling pathways. Results: The present results revealed a significant down-regulation in the angiogenesis, survival and metastasis indices along with up-regulation in the pro-apoptotic mediators upon treatment of hepatic cancer-bearing rats with the novel synthesized nanomaterials when compared with the untreated counterparts. We showed across HCC model that anti-VEGF in combination with CCR2 antagonism therapy leads to sensitization and enhanced tumor response over anti-VEGF or CCR2 antagonism monotherapy, particularly in its nanoscale formulation. Conclusion: The present approach provides new mechanistic insights into the powerful anti-hepatic cancer advantage of the novel nanoprototypes which is correlated with modulating critical signal transduction pathways implicated in tumor microenviroment such as angiogenesis, apoptosis and metastasis. This research work presents a substantial foundation for future studies focused on prohibiting cancer progression and recovery by targeting tumor microenviroment.  相似文献   
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BackgroundDissection of lymph nodes at the roots of the inferior mesenteric artery (IMAN) should be offered only to selected patients at a major risk of developing IMAN involvement. The aim of this study is to present the first artificial intelligence (AI) models to predict IMAN metastasis risk in the left colon and rectal cancer patients.MethodsA total of 2891 patients with descending colon including splenic flexure, sigmoid colon and rectal cancer undergoing major primary surgery and IMAN dissection were included as a study cohort, which was then split into a training set (67%) and a testing set (33%). Feature selection was conducted using the least absolute shrinkage and selection operator (LASSO) regression model. Seven AI algorithms, namely Support Vector Machine (SVM), Logistic Regression (LR), Extreme Gradient Boosting (XGB), Light Gradient Boosting (LGB), Decision Tree Classifier (DTC), Random Forest (RF) classifier, and Multilayer Perceptron (MLP), as well as traditional multivariate LR model were employed to construct predictive models. The optimal hyperparameters were determined with 5 fold cross-validation. The predictive performance of models and the expert surgeon was assessed and compared in the testing set independently.ResultsThe IMAN involvement incidence was 4.6%. The optimal set of features selected by LASSO included 10 characteristics: neoadjuvant treatment, age, synchronous liver metastasis, synchronous lung metastasis, signet ring adenocarcinoma, neural invasion, lymphovascular invasion, CA199, endoscopic obstruction, T stage evaluated by MRI. The most accurate model derived from MLP showed excellent prediction power with area under the receiver operating characteristic curve (AUROC) of 0.873 and produced 81.0% recognition sensitivity and 82.5% specificity in the testing set independently. In contrast, the judgment of IMAN metastasis by expert surgeon yield rather imprecise and unreliable results with a significantly lower AUROC of 0.509. Additionally, the proposed MLP had the highest net benefits and the largest reduction of unnecessary IMAN dissection without the cost of additional involved IMAN missed.ConclusionMLP model was able to maintain its prediction accuracy in the testing set better than other models and expert surgeons. Our MLP model could be used to help identify IMA nodal metastasis and to select candidates for individual IMAN dissection.  相似文献   
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AimsTreatment decisions for older patients with breast cancer are complex and evidence is largely extrapolated from younger populations. Frailty and comorbidity need to be considered. We studied the baseline characteristics and treatment decisions in older patients in Christchurch with breast cancer and assessed survival outcomes and prognostic/discriminatory performance of several tools.Materials and methodsWe searched the Canterbury Breast Cancer Registry and identified patients aged 70 years or older at diagnosis with invasive, non-metastatic breast cancer between 1 June 2009 and 30 June 2015. We retrieved demographics, treatment and outcome information. Overall survival and breast cancer-specific survival were estimated. Tools analysing performance status and comorbidity were assessed for their prognostic and discriminatory power.ResultsIn total, 440 patients were identified. Primary surgery was carried out for 362 patients (82.3%): breast-conserving surgery in 114 (of whom 88.6% received radiation therapy); mastectomy in 248 (of whom 24.6% received radiation). Hormone therapy was given for 265 (71.1%) patients with oestrogen receptor-positive cancers. Two hundred and seventy-four (62.3%) patients received full standard treatment, which was associated with significantly improved 5-year survival and 5-year breast cancer-specific survival. The median estimated overall survival was 8.2 years (95% confidence interval 7.3–9.1 years). Of those who died, 71.3% of deaths were due to causes other than breast cancer or unknown causes. The comorbidity-adjusted life expectancy (CALE) showed partial prognostic accuracy. CALE, Charlson and Eastern Cooperative Oncology Group tools all showed discriminatory value.ConclusionIn this population-based series of older patients with breast cancer, showing high levels of primary and adjuvant treatment, patients were more likely to die of causes other than breast cancer. Performance status and comorbidity tools showed prognostic and discriminatory potential in this population supporting their use in treatment decision making. CALE showed the most potential to improve treatment decisions but requires validation in this population to improve prognostic accuracy.  相似文献   
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