基于SEER数据库的上皮性卵巢癌肝转移预后分析及列线图构建

目的:分析上皮性卵巢癌肝转移的独立预后因素,构建并验证预测患者癌症特异性生存率(CSS)的列线图。方法:回顾性分析SEER数据库中2010年至2013年确诊的329例卵巢癌肝转移患者的临床资料,应用Kaplan-Meier法绘制生存曲线,Log-rank检验评价各因素不同亚组生存期的差别,通过COX多因素回归分析获得独立预后因素,运用R软件绘制列线图。列线图的预测性能由校准图和ROC曲线下面积(AUC)进行内部验证。一致性指数(C-index)评估模型的精确性。结果:年龄≥73岁、黏液性癌、透明细胞癌和癌肉瘤是CSS的独立危险因素;T3期、仅细胞减灭术、细胞减灭术联合Ⅱ期肝切除术和化疗是CSS的独立保护因素。列线图内部验证C-index为0.692(95%CI:0.651～0.733)。所建列线图预测确诊后1、3年CSS的预测区分度分别为0.802和0.723。校准曲线均呈现出良好的一致性。结论:基于SEER数据库确立了上皮性卵巢癌肝转移患者的独立预后因素,列线图预测效果良好,具有快速准确评估患者生存预后的应用价值。     

子宫颈腺癌患者总生存列线图预测模型的建立和验证

目的:探讨影响子宫颈腺癌(ECA)患者总生存预后的影响因素,并建立预测ECA患者总生存的列线图模型并验证。方法:检索SEER数据库中2004～2015年的子宫颈癌患者,纳入符合标准的模型组中ECA患者5952例及子宫颈鳞癌(CSCC)患者15593例,采用倾向性评分进行1∶1配对(各4941例),采用单因素和多因素Cox回归模型分析ECA对子宫颈癌预后的影响及ECA预后的影响因素,并基于Cox回归模型建立列线图预测模型。选择安徽医科大学第一附属医院ECA患者共122例进行验证,通过ECA患者模型组(5952例)和验证组(122例)验证的C指数、受试者工作特征曲线下面积(AUC)、校准曲线和决策曲线分析评估列线图的预测能力和临床应用价值。结果:(1)ECA是影响子宫颈癌预后的独立危险因素(HR 1.183,95%CI 1.096～1.277,P<0.001),其发病占比随时间的推移呈上升趋势。(2)年龄、种族、婚姻状况、分化程度、肿瘤大小、分期、手术、放疗和化疗均是影响ECA预后的影响因素。(3)列线图的模型组、国际妇产科联盟(FIGO)分期及验证组的C指数分别为0.863、0.761及0.792,均大于0.750。列线图模型组的1、3、5年曲线下面积(AUC)分别为0.927、0.902、0.886,验证组的AUC分别为0.872、0.739、0.870。决策曲线分析表明,在较宽的阈值概率范围内,列线图的净收益大于FIGO分期预测模型。结论:对影响ECA总生存的9个独立预后因素经过内外部验证,建立的ECA总生存列线图预测模型具有良好的预测能力和临床应用价值。     

基于SEER数据库子宫颈癌发病率的分析及预后预测模型的构建

目的:探讨子宫颈癌发病率变化和预后影响因素，构建用于预测患者预后的列线图。方法:收集并整理SEER数据库2000～2018年子宫颈癌数据。评估子宫颈癌的发病率变化；采用Kaplan-Meier法计算患者总体生存率(OS);使用单因素和多因素Cox回归筛选预后影响因素。构建预测模型并使用列线图可视化，使用受试者工作特征(ROC)曲线、校准曲线和决策曲线分析评估其预测效能。结果:子宫颈癌发病率总体呈下降趋势，中青年和黑种人发病率最高，亚洲和太平洋岛国人发病率逐渐下降。本研究共纳入20194例子宫颈癌患者，其1年、3年、5年和10年OS分别为90.1%、75.5%、69.4%和61.9%。单因素和多因素Cox回归分析结果提示年龄、婚姻状态、种族、肿瘤最大径、病理分级、病理类型、FIGO分期和区域淋巴结转移情况是患者预后的影响因素(P<0.05)。自身验证和内部验证结果显示，构建的列线图具有良好的预测准确性和临床适用性。结论:子宫颈癌发病率总体呈下降趋势，基于独立影响因素构建的列线图可在治疗前良好地预测患者预后。     

卵巢上皮性癌患者预后列线图预测模型的建立与应用

目的:探讨影响卵巢上皮性癌（卵巢癌）患者预后的相关因素,构建列线图预测模型,对卵巢癌患者的预后进行评估。方法:回顾性分析2016年8月11日至2018年7月11日在陆军军医大学第一附属医院进行初始治疗的208例卵巢癌患者的临床病理资料,包括年龄、术前有无腹水、有无新辅助化疗、手术方式、病理类型、病理分化程度、手术病理分...     

基于真实世界大数据构建及验证子宫颈癌患者的手术预后预测模型

目的:构建并验证子宫颈癌手术患者无病生存率(DFS)和总生存率(OS)的列线图预测模型，为评估子宫颈癌手术患者预后提供参考依据。方法:回顾性分析2013年3月至2018年10月在空军军医大学西京医院行子宫颈癌根治性手术患者的临床、病理及随访资料。基于Cox回归分析、贝叶斯信息准则的向后逐步选择法和R2筛选变量，使用净重新分类指数和综合判别改进指数比较后，选取预测效能较好的列线图作为预测模型。使用一致性指数和受试者工作特征曲线(ROC)检验该预测模型的效能。结果:共纳入950例子宫颈癌患者。构建DFS列线图的危险因素为国际妇产科联盟(FIGO)分期(2018)、宫旁浸润、浸润深度和肿瘤最大径线，训练集和验证集的一致性指数(C-index)分别为0.754和0.720,训练集1、3、5年的ROC曲线下面积(AUC)分别为0.74(95%CI 0.65～0.82)、0.77(95%CI 0.71～0.83)、0.79(95%CI 0.74～0.85),验证集1、3、5年的AUC分别为0.72(95%CI 0.58～0.87)、0.75(95%CI 0.64～0.86)、0.72(95%CI 0.61～0.84)。构建OS列线图的危险因素为FIGO分期(2018)、组织学类型、淋巴脉管间隙浸润(LVSI)、宫旁浸润、手术切缘和浸润深度，训练集和验证集的一致性指数分别为0.737和0.759,训练集3、5年的AUC分别为0.76(95%CI 0.69～0.83)、0.78(95%CI 0.72～0.84),验证集3、5年的AUC分别为0.76(95%CI 0.65～0.87)、0.79(95%CI 0.69～0.88)。结论:本研究基于真实世界大数据构建的子宫颈癌1、3、5年DFS的列线图和3、5年OS的列线图，具有理想的预测效果，有助于临床医师正确评估子宫颈癌手术患者的预后，对患者诊疗和预后评价提供有力的参考依据。     

基于SEER数据库的育龄期女性Ⅰ期卵巢透明细胞癌不同治疗方式生存率分析和术后生存预测模型构建

目的:探讨Ⅰ期卵巢透明细胞癌(OCCC)患者不同治疗方式之间的长期预后差异,构建列线图预测术后Ⅰ期OCCC患者的预后。方法:从SEER数据库中筛选2010年至2019年组织学诊断为OCCC的患者。使用Kaplan-Meier评估根治性手术与保留子宫手术联合或不联合化疗对OCCC患者总生存期(OS)和癌症特异性生存期(CSS)的影响。Cox比例风险模型评估临床病理因素与OS和CSS的相关性。使用与OS和CSS显著相关的参数构建列线图,通过内部验证评估列线图的性能。结果:共纳入824例OCCC患者,173例单独接受子宫切除术(HRT),430例子宫切除术后辅助化疗(HRT+CT),54例选择保留子宫的术式(NHRT),167例选择NHRT+CT。与其余三者相比,接受NHRT患者拥有最好的CSS和OS(P=0.0077,0.0078)。单独接受NHRT治疗的患者比接受NHRT+CT治疗的患者具有更好的生存率(CSS:P=0.0052;OS:P=0.0062)。多变量Cox回归分析表明,年龄、婚姻状态、肿瘤分期、治疗方案是CSS和OS的独立预后因素。根据结果建立了Ⅰ期OCCC患者术后预后列线图...     

输卵管妊娠破裂患者并发失血过多风险预测模型构建及验证

目的:构建并验证输卵管妊娠破裂患者失血过多风险预测模型，对输卵管妊娠破裂患者病情变化评估提供依据和工具。方法:回顾性分析2014年1月至2021年7月在东莞市妇幼保健院妇科行手术治疗的输卵管妊娠破裂住院患者的临床数据。以术中发现盆腔积血量是否≥750 ml为依据分为失血过多组和非失血过多组。通过单因素分析、Lasso回归和多因素Logistic逐步回归筛选出发生失血过多的影响因素并建立模型。采用受试者工作特征曲线下面积(AUC)评价预测模型的区分度，通过校准曲线及拟合优度检验评价模型的一致性，通过决策分析曲线评价及验证模型的临床效用，最后绘制列线图。结果:(1)共纳入386例输卵管妊娠破裂患者，其中124例(32.12%)失血量≥750 ml。(2)筛选出预测输卵管妊娠破裂患者并发失血过多的最优预测因素包括：腹痛天数、头晕、面色苍白、神疲乏力、宫旁包块最大径、人绒毛膜促性腺激素(β-hCG)、血红蛋白(Hb),据此构建模型和列线图。(3)预测模型AUC为0.827(95%CI 0.781～0.873);界值为0.391,特异度和灵敏度分别为68.55%和84.35%,通过重抽样后模型内...     

基于多指标建立妊娠期糖尿病列线图模型

目的:建立基于多指标的妊娠期糖尿病(GDM)风险预测模型并予验证。方法:纳入2020年4月至2023年2月在南京医科大学附属南京医院(南京市第一医院)产检并分娩的484例孕妇，其中231例GDM孕妇，253例正常孕妇，按7∶3比例分为训练集与验证集。采用单因素分析两组数据的差异性，将有统计学意义的变量纳入多因素logistic回归模型，分析GDM相关危险因素。筛选出的危险因素使用R软件建立列线图预测模型，并以一致性指数(C-index)、标准校正曲线评价模型的效能，验证其准确性。结果:血红蛋白(Hb)、平均血小板体积(MPV)、血清肌酐、碱性磷酸酶(ALP)和空腹血糖是GDM的独立危险因素。基于筛选出的5项独立危险因素，建立GDM的预测模型。列线图模型预测效果较好，具有良好的精准度及区分度。C-index在训练集为0.829(95%CI为0.785～0.871),在验证集为0.817(95%CI为0.745～0.888)。校正曲线显示预测结果与实际结果的相关性良好。决策曲线(DCA)分析显示该列线图模型具有良好的临床实用性。结论:基于多指标构建的列线图，能较准确地预测GDM发生，可作为...     

预测宫腔粘连患者妊娠概率列线图模型建立的研究

目的:探讨宫腔粘连(IUA)妊娠预后的影响因素,构建预测IUA妊娠概率的列线图模型。方法:选择2010年1月至2017年1月在我院诊断并进行综合治疗的105例IUA患者,通过Cox模型分析影响IUA妊娠预后的影响因素,并建立预测IUA患者综合治疗后妊娠概率的列线图模型。结果:患者年龄(RR=0.480,P=0.045)、粘连性质(RR=0.652,P=0.015)和治疗效果(RR=0.508,P=0.004)是影响IUA妊娠预后的独立因素,预测治疗后2年内妊娠概率列线图模型的准确性为0.697。结论:基于年龄、粘连性质、产次和治疗效果等4个因素构建的列线图有助于个体化预测IUA患者综合治疗后的妊娠概率,为临床治疗提供更有力的指导。     

预测复苏周期单囊胚移植临床妊娠的列线图模型的开发和验证

目的:开发和验证复苏周期单囊胚移植临床妊娠的列线图预测模型,以根据预测临床妊娠的概率,更好地开展IVF-ET咨询,进行临床决策和患者选择。方法:选取2015年1月到2018年12月首次行冷冻复苏单囊胚移植的1378例患者作为开发组,2019年1月到2019年5月首次行冷冻复苏单囊胚移植的292例患者为验证组。采用单因素和多因素logistic回归分析筛选与临床妊娠相关的独立影响因素,根据回归系数绘制相应的列线图预测模型,分别通过受试者工作特征曲线(ROC)及曲线下面积(AUC)和Hosmer-Lemeshow检测对模型的区分度和校准度进行评价。结果:通过多因素Logistic回归分析,最终预测模型共纳入女方年龄、不孕类型、主要不孕因素、不孕年限、移植日子宫内膜厚度和囊胚扩张状态6个影响因素。开发组和验证组ROC曲线下面积分别为0.640(95%CI 0.610～0.669)和0.629(95%CI 0.564～0.693)。拟合优度检验Hosmer-Lemeshowχ~2=12.701,P>0.05,提示模型预测概率与实际观测概率之间差异无统计学意义,预测模型有较好的校准度。结论:复苏周期单囊胚移植临床妊娠结局列线图预测模型有助于更好地开展单囊胚移植,具有一定的临床应用价值。     

External validation of a nomogram predicting overall survival of patients diagnosed with endometrial cancer

Objectives

Nomograms are predictive models that provide the overall probability of a specific outcome. Nomograms have shown better individual discrimination than currently used staging systems in numerous tumor entities. Recently, a nomogram for predicting overall survival (OS) in women with endometrial cancer was introduced by Memorial Sloan-Kettering Cancer Center (MSKCC). The aim of this study was to test the validity of the MSKCC endometrial cancer nomogram using an independent, external patient cohort.

Methods

The MSKCC nomogram is based on five readily available clinical characteristics. A multi-institutional endometrial cancer database was used to test the nomogram's validity. All consecutive patients treated for endometrial cancer between December 1995 and May 2011 and who had all nomogram variables documented were identified for analysis.

Results

Seven hundred sixty-five eligible patients were identified and used for external validation analysis. In the Austrian patient cohort, median OS was 134 months, and 3-year and 5-year OS rates were 83.8% (95% CI, 80.6-86.5%) and 77.2% (95% CI, 43.5-80.5%), respectively. The nomogram concordance index was 0.71 (SE = 0.017; 95% CI, 0.68-0.74). The correspondence between the actual OS and the nomogram predictions suggests a good calibration of the nomogram in the validation cohort.

Conclusion

The MSKCC endometrial cancer nomogram was externally validated and was shown to be generalizable to a new and independent patient population. The nomogram provides a more individualized and accurate estimation of OS for patients diagnosed with endometrial cancer following primary therapy. The nomogram can be used for counseling patients more accurately and for better stratifying patients for clinical trials.     

A prognostic nomogram to predict overall survival in women with recurrent ovarian cancer treated with bevacizumab and chemotherapy

Objective

To develop a nomogram to predict overall survival (OS) in women with recurrent ovarian cancer treated with bevacizumab and chemotherapy.

Methods

A multicenter retrospective study was conducted. Potential prognostic variables included age; stage; grade; histology; performance status; residual disease; presence of ascites and/or pleural effusions; number of chemotherapy regimens, treatment-free interval (TFI) prior to bevacizumab administration, and platinum sensitivity. Multivariate analysis was performed using Cox proportional hazards regression. The predictive model was developed into a nomogram to predict five-year OS.

Results

312 women with recurrent ovarian cancer treated with bevacizumab and chemotherapy were identified; median age was 59 (range: 19–85); 86% women had advanced stage (III–IV) disease. The majority had serous histology (74%), high grade cancers (93.5%), and optimal cytoreductions (69.5%). Fifty-one percent of women received greater than two prior chemotherapeutic regimens. TFI (AHR = 0.98, 95% CI 0.97–1.00, p = 0.022) was the only statistically significant predictor in a multivariate progression-free survival (PFS) analysis. In a multivariate OS analysis, prior number of chemotherapy regimens, TFI, platinum sensitivity, and presence of ascites were significant. A nomogram to predict five-year OS was constructed and internally validated (bootstrap-corrected concordance index = 0.737).

Conclusion

Our multivariate model identified prior number of chemotherapy regimens, TFI, platinum sensitivity, and the presence of ascites as prognostic variables for OS in women with recurrent ovarian cancer treated with bevacizumab combined with chemotherapy. Our nomogram to predict five-year OS may be used to identify women who may benefit from bevacizumab and chemotherapy, but further validation is needed.     

Development and validation of a nomogram for predicting outcome of patients with vulvar cancer

OBJECTIVE: To construct and validate a nomogram to predict relapse-free survival of patients treated for vulvar cancer. METHODS: Data from 244 patients treated for vulvar cancer at a single institution (Creteil, France) were used as a training set to develop and calibrate a nomogram for predicting relapse-free survival and local relapse-free survival. We used bootstrap resampling for the internal validation and we tested the nomogram on an independent validation set of patients (Torino, Italy) for the external validation. RESULTS: The nomograms were based on a Cox proportional hazards regression model. Covariates for the relapse-free survival model included age, T stage, number of metastatic nodes, bilateral lymph node involvement, omission of the lymphadenectomy, margin status, lymphovascular space invasion, and depth of invasion. The concordance indices were 0.85 and 0.83 in the training set before and after bootstrapping, respectively, and 0.83 in the validation set. The predictions of our nomogram discriminated better than did the International Federation of Gynecology and Obstetrics stage (0.83 compared with 0.78, P = .01). The calibration of our nomogram was good. In the validation set, 2-year and 5-year relapse-free survival were well predicted with less than 5% difference between the predicted and observed survivals for each quartile. A nomogram for predicting local relapse was also developed. CONCLUSION: We have developed nomograms for predicting distant and local relapse of vulvar cancer at 2 and 5 years and validated them both internally and externally. These nomograms will be freely available on the International Society for the Study of Vulvovaginal Disease Web site. LEVEL OF EVIDENCE: III.     

A novel diagnostic nomogram based on serological and ultrasound findings for preoperative prediction of malignancy in patients with ovarian masses

ObjectiveTo develop a novel diagnostic nomogram model to predict malignancy in patients with ovarian masses.MethodsIn total, 1277 patients with ovarian masses were retrospectively analyzed. Receiver operating characteristic (ROC) analysis was performed to identify valuable predictive factors. Univariate and multivariate logistic regression analyses were used to identify risk factors for ovarian cancer. Subsequently, a predictive nomogram model was developed. The performance of the nomogram model was assessed by its calibration and discrimination in a validation cohort. Decision curve analysis (DCA) was applied to assess the clinical net benefit of the model.ResultsOverall, 496 patients (38.8%) had ovarian cancer. Eighteen parameters were significantly different between the malignant and benign groups. Five parameters were identified as being most optimal for predicting malignancy, including age, carbohydrate antigen 125, fibrinogen-to-albumin ratio, monocyte-to-lymphocyte ratio, and ultrasound result. These parameters were incorporated to establish a nomogram model, and this model exhibited an area under the ROC curve (AUC) of 0.937 (95% confidence interval [CI], 0.920–0.954). The model was also well calibrated in the validation cohort and showed an AUC of 0.925 (95%CI, 0.896–0.953) at the cut-off point of 0.298. DCA confirmed that the nomogram model achieved the best clinical utility with almost the entire range of threshold probabilities. The model has demonstrated superior efficacy in predicting malignancy compared to currently available models, including the risk of ovarian malignancy algorithm, copenhagen index, and the risk of malignancy index. More importantly, the nomogram established here showed potential value in identification of early-stage ovarian cancer.ConclusionThe cost-effective and easily accessible nomogram model exhibited favorable accuracy for preoperative prediction of malignancy in patients with ovarian masses, even at early stages.     

External validation of nomogram for the decline in serum anti-Müllerian hormone in women: a population study of 15,834 infertility patients

The value of anti-müllerian hormone (AMH) as a marker of the ovarian reserve is becoming clear in a range of clinical contexts.This study reports the external validation of a quadratic model-based AMH–age nomogram using a cohort of 15,834 US women. All models previously investigated for the decline in ovarian reserve (i.e. linear, bi-linear, decay curve, power and quadratic models) tended to overestimate AMH by approximately 11% versus the published nomogram, indicating some between-population heterogeneity. Bootstrapping of 1000 datasets indicated that the quadratic model provided the best fit, confirming the choice of this model in the AMH–age nomogram. This nomogram can therefore be used with confidence for the interpretation of AMH in clinical populations.     

XPG基因遗传变异与上皮性卵巢癌铂类化疗预后相关性研究

目的探讨XPG基因单核苷酸多态性(SNPs)与上皮性卵巢癌铂类化疗预后的关系。方法通过Haploview软件筛选出XPG基因9个标签SNPs(tag SNPs)。连接酶检测反应技术检测2002年3月至2009年12月在河北医科大学第四医院进行手术治疗的239例上皮性卵巢癌患者外周血DNA XPG基因9个tag SNPs的基因型频率分布情况。采用生存分析评估XPG基因SNPs与上皮性卵巢癌患者临床预后的关系。患者临床预后的判定指标包括患者对铂类化疗反应(TR)、疾病无进展生存期(PFS)和总生存期(OS)。结果统计学分析显示:XPG基因rs1047768C/T和rs2296147C/T多态可能与确诊时年龄≥50岁的卵巢癌患者临床预后相关。即与rs1047768 T/T基因型相比,rs1047768C等位基因降低了患者铂类抵抗、疾病复发和死亡的风险(TR:OR=0.49,95%CI 0.24~0.98;PFS:HR=0.57,95%CI 0.38~0.87;OS:HR=0.56,95%CI 0.34~0.94);与rs2296147 T/T基因型相比,rs2296147C等位基因降低上皮性卵巢癌患者疾病复发和死亡的风险(PFS:HR=0.63,95%CI 0.41~0.98;OS:HR=0.50,95%CI 0.28~0.87)。结论 XPG rs1047768C/T和rs2296147C/T多态可能是确诊时年龄≥50岁卵巢癌患者临床预后的分子标志物。     

Advanced ovarian cancer and cytoreductive surgery: Independent validation of a risk-calculator for perioperative adverse events

ObjectiveTo independently validate a published risk-calculator for adverse perioperative outcomes in patients with epithelial ovarian cancer undergoing debulking surgery at a high-volume surgical center.MethodsUsing our institution's curated prospective ovarian cancer database, we identified patients with epithelial ovarian cancer who underwent a debulking procedure from 7/2015 to 5/2019, to be used as the validation cohort. Variables used in the published nomogram were collected. These included American Society of Anesthesiology classification, preoperative albumin, history of bleeding disorder, presence of ascites on preoperative imaging, designation of elective or emergent surgery, age of the patient, and a procedure score. Patients were included if they had information available for all the variables used in the nomogram, and 30-day follow-up within our institution. The primary outcome was Clavien-Dindo Class IV with specific conditions (postoperative sepsis, septic shock, cardiac arrest, myocardial infarction, pulmonary embolism, ventilation >48 h, or unplanned intubation) and 30-day mortality. The combination of these endpoints is called the combined complication rate.ResultsA total of 700 patients who underwent debulking surgery for epithelial ovarian cancer during the timeframe met inclusion criteria. The combined complication rate was 11.7%; 9.9% of patients were readmitted; 2.7% required reoperation. Sepsis was the most common primary endpoint complication (4.4%), followed by septic shock (1.4%). There was no 30-day mortality in our cohort. The nomogram performed well, with a c index of 0.715 (95% CI 0.66–0.768), which was comparable to the published nomogram.ConclusionsWe independently validated a complication nomogram at a high-volume surgical center. This nomogram performs well at predicting a lower likelihood of serious postoperative complications. An enhanced nomogram would help identify patients at higher risk for serious complications.     

晚期卵巢癌新辅助化疗的Meta分析

目的:评价新辅助化疗对晚期卵巢癌患者总生存期及无进展生存期的影响,探讨新辅助化疗在晚期卵巢癌的应用价值。方法:计算机检索PubMed数据库、Med-line数据库、EMbas数据库、Cochrane Library数据库、万方数据库、中国学术文献总库(CNKI)、中国生物医学文献数据库(CBM),手工检索《中华妇产科杂志》,《中国实用妇科与产科杂志》,《实用妇产科杂志》,《生殖与避孕》,《现代妇产科进展》5本妇产科杂志。语言种类为中文和英文,网上检索时间不限。试验组行新辅助化疗,即以铂类为基础的化疗后行细胞减灭术;对照组行传统治疗,即细胞减灭术后行规范性化疗。结果:共纳入3篇文献,提取数据后,Review Manager5.0软件进行Meta分析,两组的总生存期合并后的RR值为0.96(95%CI,0.90～1.03),两组的无进展生存期合并后的RR值为1.00(95%Cl 0.93～1.09),森林图菱形均与垂直线相交。结论:新辅助化疗并未改善晚期卵巢癌患者的预后。     

NTs家族成员及其受体Trk在卵巢癌中的表达及其与生存期的相关性

目的:分析神经营养素(NTs)家族成员及其酪氨酸激酶受体(Trk)在卵巢癌中的表达情况及其与患者总生存期(OS)的关系,评价其预后价值。方法:利用KaplanMeier plotter(KM plotter)在线数据库收集卵巢癌患者病理信息,分析NTs家族成员(NGF、BDNF、NT-3、NT-5)及其受体Trk(TrkA、TrkB、TrkC)表达与卵巢癌患者预后及临床病理参数的相关性。收集新鲜卵巢癌组织和癌旁组织各6例,Western blot法检测NTs及Trk蛋白表达。结果:BDNF mRNA高表达与卵巢癌患者较好的总生存期(OS)相关(危险比HR=0.78,95%CI为0.68~0.89,P0.001);NGF、NT-3、NT-5及受体TrkA、TrkB、TrkC表达与卵巢癌患者的总生存期(OS)无关(P0.05)。BDNF mRNA表达与临床分期Ⅰ、Ⅱ及Ⅲ期、病理分级Ⅱ级、组织学分型浆液性癌及TP53野生型的卵巢癌患者的OS密切相关(P0.05)。NGF、NT-3及TrkA表达均与卵巢癌患者的临床病理参数不相关(P0.05)。NT-5表达与病理分级Ⅱ级的卵巢癌患者的OS相关(P0.05)。TrkB及TrkC表达与临床分期Ⅲ期的卵巢癌患者的OS密切相关(P0.05)。Western blot法检测显示,NTs家族中NGF、BDNF、NT-5蛋白在卵巢癌组织中过表达,NT-3蛋白则为低表达;Trk家族中TrkA、TrkB及TrkC在卵巢癌组织中高表达。结论:BDNF表达与卵巢癌患者的预后密切相关,高表达患者的预后更好,可作为潜在的预后指标进行研究;NTs家族其他成员及受体Trk家族均无此预测作用。     

Systemic immune-inflammation index predicts prognosis in patients with epithelial ovarian cancer: A retrospective study

Objective

The study aimed to investigate the prognostic value of the systemic immune-inflammation index (SII) in patients with epithelial ovarian cancer (EOC).