Risk stratification for radioactive iodine refractoriness using molecular alterations in distant metastatic differentiated thyroid cancer

Objective: Patients with radioactive iodine-refractory differentiated thyroid cancer(RAIR-DTC) are often diagnosed with delay and constrained to limited treatment options. The correlation between RAI refractoriness and the underlying genetic characteristics has not been extensively studied.Methods: Adult patients with distant metastatic DTC were enrolled and assigned to undergo next-generation sequencing of a customized 26-gene panel(Thyro Lead). Patients were classified into RAIR-DTC or non-RAIR groups to determine the differences in clinicopathological and molecular characteristics. Molecular risk stratification(MRS) was constructed based on the association between molecular alterations identified and RAI refractoriness, and the results were classified as high, intermediate or low MRS.Results: A total of 220 patients with distant metastases were included, 63.2% of whom were identified as RAIRDTC. Genetic alterations were identified in 90% of all the patients, with BRAF(59.7% vs. 17.3%), TERT promoter(43.9% vs. 7.4%), and TP53 mutations(11.5% vs. 3.7%) being more prevalent in the RAIR-DTC group than in the non-RAIR group, except for RET fusions(15.8% vs. 39.5%), which had the opposite pattern. BRAF and TERT promoter are independent predictors of RAIR-DTC, accounting for 67.6% of patients with RAIR-DTC. MRS was strongly associated with RAI refractoriness(P<0.001), with an odds ratio(OR) of high to low MRS of 7.52 [95%confidence interval(95% CI), 3.96-14.28;P<0.001] and an OR of intermediate to low MRS of 3.20(95% CI,1.01-10.14;P=0.041).Conclusions: Molecular alterations were associated with RAI refractoriness, with BRAF and TERT promoter mutations being the predominant contributors, followed by TP53 and DICER1 mutations. MRS might serve as a valuable tool for both prognosticating clinical outcomes and directing precision-based therapeutic interventions.

Relational Turkish Text Classification Using Distant Supervised Entities and Relations

Text classification,by automatically categorizing texts,is one of the foundational elements of natural language processing applications.This study investigates how text classification performance can be improved through the integration of entity-relation information obtained from the Wikidata(Wikipedia database)database and BERTbased pre-trained Named Entity Recognition(NER)models.Focusing on a significant challenge in the field of natural language processing(NLP),the research evaluates the potential of using entity and relational information to extract deeper meaning from texts.The adopted methodology encompasses a comprehensive approach that includes text preprocessing,entity detection,and the integration of relational information.Experiments conducted on text datasets in both Turkish and English assess the performance of various classification algorithms,such as Support Vector Machine,Logistic Regression,Deep Neural Network,and Convolutional Neural Network.The results indicate that the integration of entity-relation information can significantly enhance algorithmperformance in text classification tasks and offer new perspectives for information extraction and semantic analysis in NLP applications.Contributions of this work include the utilization of distant supervised entity-relation information in Turkish text classification,the development of a Turkish relational text classification approach,and the creation of a relational database.By demonstrating potential performance improvements through the integration of distant supervised entity-relation information into Turkish text classification,this research aims to support the effectiveness of text-based artificial intelligence(AI)tools.Additionally,it makes significant contributions to the development ofmultilingual text classification systems by adding deeper meaning to text content,thereby providing a valuable addition to current NLP studies and setting an important reference point for future research.

Risk factors,prognostic factors,and nomograms for distant metastasis in patients with diagnosed duodenal cancer:A population-based study

BACKGROUND Duodenal cancer is one of the most common subtypes of small intestinal cancer,and distant metastasis(DM)in this type of cancer still leads to poor prognosis.Although nomograms have recently been used in tumor areas,no studies have focused on the diagnostic and prognostic evaluation of DM in patients with primary duodenal cancer.AIM To develop and evaluate nomograms for predicting the risk of DM and person-alized prognosis in patients with duodenal cancer.METHODS Data on duodenal cancer patients diagnosed between 2010 and 2019 were extracted from the Surveillance,Epidemiology,and End Results database.Univariate and multivariate logistic regression analyses were used to identify independent risk factors for DM in patients with duodenal cancer,and univariate and multivariate Cox proportional hazards regression analyses were used to determine independent prognostic factors in duodenal cancer patients with DM.Two novel nomograms were established,and the results were evaluated by receiver operating characteristic(ROC)curves,calibration curves,and decision curve analysis(DCA).RESULTS A total of 2603 patients with duodenal cancer were included,of whom 457 cases(17.56%)had DM at the time of diagnosis.Logistic analysis revealed independent risk factors for DM in duodenal cancer patients,including gender,grade,tumor size,T stage,and N stage(P<0.05).Univariate and multivariate COX analyses further identified independent prognostic factors for duodenal cancer patients with DM,including age,histological type,T stage,tumor grade,tumor size,bone metastasis,chemotherapy,and surgery(P<0.05).The accuracy of the nomograms was validated in the training set,validation set,and expanded testing set using ROC curves,calibration curves,and DCA curves.The results of Kaplan-Meier survival curves(P<0.001)indicated that both nomograms accurately predicted the occurrence and prognosis of DM in patients with duodenal cancer.CONCLUSION The two nomograms are expected as effective tools for predicting DM risk in duodenal cancer patients and offering personalized prognosis predictions for those with DM,potentially enhancing clinical decision-making.

Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports

BACKGROUND Development of distant metastasis(DM)is a major concern during treatment of nasopharyngeal carcinoma(NPC).However,studies have demonstrated im-proved distant control and survival in patients with advanced NPC with the addition of chemotherapy to concomitant chemoradiotherapy.Therefore,precise prediction of metastasis in patients with NPC is crucial.AIM To develop a predictive model for metastasis in NPC using detailed magnetic resonance imaging(MRI)reports.METHODS This retrospective study included 792 patients with non-distant metastatic NPC.A total of 469 imaging variables were obtained from detailed MRI reports.Data were stratified and randomly split into training(50%)and testing sets.Gradient boosting tree(GBT)models were built and used to select variables for predicting DM.A full model comprising all variables and a reduced model with the top-five variables were built.Model performance was assessed by area under the curve(AUC).RESULTS Among the 792 patients,94 developed DM during follow-up.The number of metastatic cervical nodes(30.9%),tumor invasion in the posterior half of the nasal cavity(9.7%),two sides of the pharyngeal recess(6.2%),tubal torus(3.3%),and single side of the parapharyngeal space(2.7%)were the top-five contributors for predicting DM,based on their relative importance in GBT models.The testing AUC of the full model was 0.75(95%confidence interval[CI]:0.69-0.82).The testing AUC of the reduced model was 0.75(95%CI:0.68-0.82).For the whole dataset,the full(AUC=0.76,95%CI:0.72-0.82)and reduced models(AUC=0.76,95%CI:0.71-0.81)outperformed the tumor node-staging system(AUC=0.67,95%CI:0.61-0.73).CONCLUSION The GBT model outperformed the tumor node-staging system in predicting metastasis in NPC.The number of metastatic cervical nodes was identified as the principal contributing variable.

Conditional survival probability of distant-metastatic hepatocellular carcinoma: A population-based study

BACKGROUND The prognosis of many patients with distant metastatic hepatocellular carcinoma(HCC)improved after they survived for several months.Compared with tradi-tional survival analysis,conditional survival(CS)which takes into account changes in survival risk could be used to describe dynamic survival probabilities.AIM To evaluate CS of distant metastatic HCC patients.METHODS Patients diagnosed with distant metastatic HCC between 2010 and 2015 were extracted from the Surveillance,Epidemiology and End Results database.Univariate and multivariate Cox regression analysis were used to identify factors for overall survival(OS),while competing risk model was used to identify risk factors for cancer-specific survival(CSS).Six-month CS was used to calculate the probability of survival for an additional 6 mo at a specific time after initial diagnosis,and standardized difference(d)was used to evaluate the survival differences between subgroups.Nomograms were constructed to predict CS.Positiveα-fetoprotein expression,higher T stage(T3 and T4),N1 stage,non-primary site surgery,non-chemotherapy,non-radiotherapy,and lung metastasis were independent risk factors for actual OS and CSS through univariate and multivariate analysis.Actual survival rates decreased over time,while CS rates gradually increased.As for the 6-month CS,the survival difference caused by chemotherapy and radiotherapy gradually disappeared over time,and the survival difference caused by lung metastasis reversed.Moreover,the influence of age and gender on survival gradually appeared.Nomograms were fitted for patients who have lived for 2,4 and 6 mo to predict 6-month conditional OS and CSS,respectively.The area under the curve(AUC)of nomograms for conditional OS decreased as time passed,and the AUC for conditional CSS gradually increased.CONCLUSION CS for distant metastatic HCC patients substantially increased over time.With dynamic risk factors,nomograms constructed at a specific time could predict more accurate survival rates.

中远海区域水雷威胁分析

根据布雷作战方在远离大陆港岸依托的较远大陆架和一岛链海区及一岛链以外中远海区域的布雷作战形式,针对海区环境特点对中远海主要水雷威胁区的水雷类型和障碍样式进行分析,可为海上编队中远海对水雷防御需求提供依据,对中远海反水雷能力建设具有重要意义。

远缘杂交仁用杏新品种京仁5号的选育

京仁5号通过仁用杏品种龙王帽与扁桃品种意大利2号远缘杂交育成。果实卵圆形,果顶圆凸,在北京地区7月中下旬成熟;成熟时果皮底色黄色,阳面着片状红色,平均单果质量30.5 g;果核卵圆形,壳面较平滑,平均单核质量2.54 g,纵横侧径分别为3.28 cm、2.12 cm、1.23 cm;核仁饱满,离核,甜仁,平均单仁鲜质量1.05 g、干质量0.90 g,出仁率37.02%;杏仁脂肪含量(w,后同)435.63 g·kg^(-1),蛋白质含量269.84 g·kg^(-1),钙含量1.26 g·kg^(-1),铁含量24.08 mg·kg^(-1)。丰产稳产,适应性强,综合性状优良。

通消阳和颗粒联合环磷酰胺对4T1乳腺癌荷瘤小鼠移植瘤的影响

目的:观察通消阳和颗粒联合环磷酰胺对4T1乳腺癌荷瘤小鼠的作用。方法:选取BALB/c雌性小鼠建立4T1乳腺癌荷瘤模型,随机分成模型组、通消阳和颗粒组(颗粒组)、通消阳和颗粒^(+)环磷酰胺组(联合组)及环磷酰胺组,每组8只,另选取8只作为空白组。监测各组荷瘤小鼠肿瘤生长情况,绘制乳腺肿瘤时间-生长曲线;计算各组小鼠肿瘤抑制率;检测外周血白细胞计数及中性粒细胞、淋巴细胞和单核细胞的比例;测定肝、肾功能的生化指标;检测脾脏免疫细胞数量及CD4^(+)T和CD8^(+)T细胞比例;培养各组小鼠肺、脑、肝及外周血细胞,用于检测肿瘤细胞远处器官转移情况。结果:与模型组相比,联合组小鼠移植瘤增长速度最缓慢(P<0.01),抑瘤率最高(P<0.01),白细胞计数显著降低(P<0.01);与环磷酰胺组相比,联合组小鼠淋巴细胞比例明显升高(P<0.01),中性粒细胞及单核细胞比例降低,差异有统计学意义(P<0.01),肝肾功能指标正常,无早期损害,T、B淋巴细胞升高、MDSCs细胞降低及CD4^(+)T和CD8^(+)T细胞比例升高,差异有统计学意义(P<0.05),乳腺癌细胞无远处器官转移情况。结论:通消阳和颗粒联合环磷酰胺可显著抑制乳腺癌荷瘤小鼠移植瘤生长;通消阳和颗粒可以减少环磷酰胺所致的小鼠肝肾功能损害、免疫功能减低等毒性反应,联合环磷酰胺可以明显提高乳腺癌小鼠的免疫功能并抑制肿瘤细胞的远处转移。

基于地基测量数据的月球DRO轨道定轨精度分析

针对地月空间DRO探测,基于中国深空探测任务的现有测量条件,仿真分析月球DRO轨道探测器定轨预报精度。采用批处理定轨方法,选择以地球为中心天体进行轨道积分,并增加了月球非球形引力摄动。计算分析表明,在目前的测量条件下,2天短弧测距单独定轨精度为km量级,速度精度优于3cm/s,预报7天三维位置最大差异为数10km量级,速度差异小于6 cm/s;测距联合VLBI定轨精度为百米量级,速度精度优于0.4 cm/s,预报7天三维位置最大差异为千米量级,速度差异小于2cm/s,VLBI数据的加入能显著提高DRO短弧定轨预报精度。5天长弧测距单独定轨精度优于1km,速度精度优于1cm/s,预报7天三维位置最大差异小于2km,三维速度最大差异小于1cm/s,增加定轨弧长对测距数据单独定轨预报精度有显著提高。

大辟缘蝽触角感器的扫描电镜观察

为了解大辟缘蝽(Prionolomia gigas Distant)触角感器与其嗅觉感受机制的关系,采用扫描电镜观察大辟缘蝽雌、雄成虫触角感器类型、超微形态及其分布。结果表明:大辟缘蝽雌、雄成虫触角均呈线状,由柄节、梗节和鞭节3部分组成;雌、雄成虫触角上共观察到6种类型感器,分别为毛形感器、刺形感器、锥形感器、腔形感器、腔锥形感器和具弯钩型感器,其中,以毛型感器数量最多、分布范围最广,鞭节上的感器类型较柄节和梗节丰富,雌虫的感器类型多于雄虫,表现出明显的性二型现象。

基于BERT的两次注意力机制远程监督关系抽取

针对词向量语义信息不完整以及文本特征抽取时的一词多义问题,提出基于BERT(Bidirectional Encoder Representation from Transformer)的两次注意力加权算法(TARE)。首先,在词向量编码阶段,通过构建Q、K、V矩阵使用自注意力机制动态编码算法,为当前词的词向量捕获文本前后词语义信息;其次,在模型输出句子级特征向量后,利用定位信息符提取全连接层对应参数,构建关系注意力矩阵;最后,运用句子级注意力机制算法为每个句子级特征向量添加不同的注意力分数,提高句子级特征的抗噪能力。实验结果表明:在NYT-10m数据集上,与基于对比学习框架的CIL(Contrastive Instance Learning)算法相比,TARE的F1值提升了4.0个百分点,按置信度降序排列后前100、200和300条数据精准率Precision@N的平均值(P@M)提升了11.3个百分点;在NYT-10d数据集上,与基于注意力机制的PCNN-ATT(Piecewise Convolutional Neural Network algorithm based on ATTention mechanism)算法相比,精准率与召回率曲线下的面积(AUC)提升了4.8个百分点,P@M值提升了2.1个百分点。在主流的远程监督关系抽取(DSER)任务中,TARE有效地提升了模型对数据特征的学习能力。

通过远缘杂交培育郁金香新品种‘雪域湘妃’

为了利用中国野生郁金香资源的优良基因,实现选育适合中国气候条件的“中华郁金香新品种群”的目标,开展了以郁金香栽培品种‘波兰心’为母本,以原产于中国的郁金香野生种阿尔泰郁金香为父本的远缘杂交研究。结果表明:‘波兰心’×阿尔泰郁金香杂交组合具有较高的亲和性,杂交结实率80%,获得杂交种子1080粒。对杂交后代进行筛选,最终选育出郁金香新品种‘雪域香妃’。‘雪域湘妃’株高32.67 cm,极显著低于母本‘波兰心’,与父本阿尔泰郁金香差异不显著。花径大小与花冠高度分别为5.55 cm和5.34 cm,与母本‘波兰心’差异不显著,与父本阿尔泰郁金香差异极显著。‘雪域湘妃’萌芽期为3月下旬,4月中旬现蕾,始花期为4月下旬,盛花期13d。该研究将为中国分布的野生郁金香资源的杂交利用提供参考。

细读、粗读与远读:从传统阅读到数字人文的范式演变

阅读是人类获取知识文化与接续文明的重要手段。技术、物质、思想等的瞬息万变,使得阅读主体、阅读载体及阅读媒介也发生变革,由此而引发了阅读方法的范式演变。在传统纸媒阅读时代,崇尚逐字逐句的“细读”,同时辅以概览式的“粗读”。但在屏幕阅读时代,随着计算技术的突飞猛进,开展大数据阅读的“远读”方法,不知不觉地影响了大众的阅读生活。文章拟就细读、粗读与远读的关系与内涵进行梳理与探讨,试图揭示阅读范式生成与演变的内在逻辑,以及如何在数字人文语境下理性应对阅读方法的时代变革。

远处转移性甲状腺乳头状癌生化进展的影响因素研究

背景晚期甲状腺乳头状癌(PTC),尤其是远处转移性甲状腺乳头状癌(DM-PTC)的病情变化主要从甲状腺球蛋白(Tg)等血清学指标和CT等影像学两方面进行监测。由于CT等影像学手段本身的局限性如辐射、价格昂贵及转移病灶分布的复杂性,实体瘤疗效评估标准(RECIST 1.1)常无法及时捕捉DM-PTC患者的病情变化,而整合了时间维度的Tg倍增时间(TgDT)已显示其在灵敏监测PTC疾病变化中的作用。目的以TgDT为结局变量,探索DM-PTC的生化进展及其影响因素。方法回顾性纳入2018年1月—2023年6月北京协和医院核医学科就诊的61例DM-PTC患者为研究对象,通过门诊病历系统收集研究对象的基线资料并进行基因突变检测,基因突变检测内容包括鼠类肉瘤滤过性毒菌致癌同源体B1(BRAF)突变、端粒酶反转录酶(TERT)突变、转染重排(RET)融合、大鼠肉瘤病毒(RAS)突变。末次^(131)I治疗后4个月到1年时间内行外周血T细胞亚群、自然杀伤细胞(NK细胞)及淋巴细胞检测。计算TgDT,以TgDT 3年为界,将研究对象分为<3年组(n=16)和≥3年组(n=45)。末次^(131)I治疗后4个月到1年时间内,计算TgDT的初次Tg时间点的T细胞亚群、NK细胞百分比及淋巴细胞绝对值被定义为淋巴细胞亚群的初始值,计算TgDT的末次Tg时间点的T细胞亚群、NK细胞百分比及淋巴细胞绝对值被定义为淋巴细胞亚群的末次值,淋巴细胞亚群随时间纵向变化情况以淋巴细胞亚群变化率表示,淋巴细胞亚群变化率=(末次值-初始值)/初始值×100%。比较两组淋巴细胞亚群初始值及变化率的差异情况。采用多因素Logistic逐步向后回归分析探究DM-PTC生化进展的影响因素。结果≥3年组确诊年龄、末次^(131)I治疗前局部手术次数、碘难治(RAIR)、TERT突变、BRAF与TERT共同突变比例低于<3年组,RET融合比例高于<3年组(P<0.05)。≥3年组CD_(3)^(+)T细胞百分比、CD_(8)^(+)T细胞百分比高于<3年组,NK细胞百分比、CD4/CD8低于<3年组(P<0.05)。多因素Logistic回归分析结果显示CD_(8)^(+)T细胞百分比降低(OR=0.879,95%CI=0.792~0.975)、BRAF与TERT共同突变(OR=7.044,95%CI=1.368~36.265)是DM-PTC生化进展的影响因素(P<0.05)。结论低CD_(8)^(+)T细胞比例的免疫状态、BRAF与TERT共同突变等多种因素可影响DM-PTC的生化进展,淋巴细胞亚群及多基因联合检测对于DM-PTC病情监测及预后评价具有重要意义。

基于自适应损失函数的句子级远程监督关系抽取

远程监督关系抽取是一种关系抽取方法,现有方法主要采用多实例学习,在具有相同实体对的样例包上进行关系抽取。但是,包级方法只能缓解却并不能完全解决错误标签问题。基于此,文中首先分析了干净数据和噪声数据的分布,提出了一种新的自适应损失函数;在此基础上,提出了一种基于自适应损失函数的句子级远程监督关系抽取方法。在公开数据集NYT-10以及基于TACRED的合成数据集上的实验结果表明:文中提出的方法优于对比文献中的方法,能够更有效地区分错误标签噪声样例和干净样例,提高了句子级远程监督关系抽取的准确率。

基于注意力机制和提示学习联合训练的上下位关系识别研究

专利术语间的上下位关系是一种重要的语义关系,专利文本中术语间的上下位关系识别在专利检索、查询扩展、知识图谱构建等多个领域发挥着重要作用。然而,专利文本领域的多样性、语言表述的复杂性使得术语间的上下位关系识别仍然面临许多挑战。文中提出一种融合提示学习和注意力机制的术语上下位关系识别方法,该方法基于远程监督框架,将术语之间的最短依存路径作为辅助特征融入提示模板,使用图神经网络将术语间的共现信息融入提示学习和注意力机制联合训练过程。在专利文本测试数据集上的实验结果表明,所提方法的AUC值、F1值达到94.94%和89.33%,相较于PARE模型分别提升了3.82%和3.17%。该方法有效地去除了使用远程监督方法标注的数据集的噪声,避免了掩码语言模型的训练目标和下游任务的不匹配问题,充分利用了预训练语言模型中存在的语言知识信息。

汉至唐宋琴的士人化与琴学的审美倾向

琴在先秦就进入宫廷,成为宫廷主要乐器之一。汉代以后,有流行于民间、盛行于士人的倾向。这是因为琴不同于八音中的其他乐器,从一产生,就因为其便于携带和琴曲适于独奏的特点,很适合私人备用和演奏。所以琴极容易成为士人常备的乐器,蓄琴至晚到汉代就已经成为士人的雅趣,自汉至宋名士善琴者甚多。更为重要的是魏晋士人个体意识的觉醒,琴因此而成为士人隐居以求志、独居而养心、标榜士人风流的工具。蓄琴私人化和琴事的士人化,必不可免地使琴学染上士人的观念和情趣,形成了崇尚琴的中和之美、欣赏琴曲清远风格的取向。

基于多层级注意力机制和动态阈值的远程监督关系抽取

远程监督关系抽取面临着数据质量的问题,即生成的数据集存在多类噪声,包括噪声词、噪声句和噪声包。现有研究主要集中在噪声句方面,忽略了其他噪声的影响,无法彻底消除噪声。为此,提出一种基于多层级注意力机制和动态阈值的远程监督关系抽取模型(MADT)。该模型首先采用预训练语言模型获取实体对语义表示,再通过双向门控循环单元和自注意力机制获得蕴涵关键词信息的语义特征,然后结合句子深层上下文表示依次处理三种噪声问题。此外,还提出一种动态阈值方法进一步剔除噪声句,增强正例句对包表示的贡献,并采用基于语义相似性的注意力机制降低噪声包的影响。在NYT10d和NYT10m数据集上的实验表明,MADT模型能够解决远程监督关系抽取中各个层面的噪声,有效提升关系的抽取性能。

两种不同剂量碘-131对非远处转移性高危分化型甲状腺癌全切术后患者DTC的应用效果

目的探讨两种不同剂量碘-131对非远处转移性高危分化型甲状腺癌(DTC)全切术后患者的应用效果。方法回顾性分析86例非远处转移性高危DTC患者的临床资料,所有患者均行DTC全切术,并按照碘-131治疗剂量的不同分成低剂量组(100~150 mCi)和高剂量组(150~200 mCi),前者为45例,后者为41例,治疗3个月,随访1年。比较两组相关临床治疗指标(清甲成功率、无病生存率、住院隔离时间)、甲状腺癌特异性生命质量量表(THYCA-QoL)和不良反应发生情况的差异。结果治疗及随访结束后,两组的清甲成功率无明显差异(P<0.05),低剂量组的无病生存率(95.56%)高于高剂量组(80.49%),且住院隔离时间短于高剂量组(P<0.05);两组生理功能和活动、心理功能、症状或对生活影响评分均高于同组治疗前,且低剂量组THYCA-QoL评分均高于高剂量组(P<0.05);低剂量组不良反应发生率(8.89%)低于高剂量组(29.27%)(P<0.05)。结论低剂量和高剂量碘-131对于非远处转移性高危DTC全切术后患者的治疗效果相当,但前者更有利于缩短住院隔离时间,提高无病生存率,减少不良反应的发生,进而提高生存质量。

miR-891a-5p及miR-383-5p与激素受体阳性早期乳腺癌术后发生远处转移的关系探讨

目的探讨微小RNAs(miRNAs,miR)-891a-5p及miR-383-5p与激素受体(HR)阳性早期乳腺癌术后发生远处转移的关系。方法62例HR阳性早期(T1~2N0M0期)乳腺癌患者,根据术后是否出现远处转移分为远处转移组(28例,出现远处转移)和未远处转移组(34例,未出现远处转移)。收集两组的临床乳腺癌标本,并检测组织的miRNAs表达水平。比较两组miR-891a-5p、miR-383-5p、miR-1295a表达水平,分析miR-891a-5p、miR-383-5p、miR-1295a对乳腺癌远处转移的诊断效能;比较两组miR-661、miR-296-3p、miR-128-3p表达水平,分析miR-891a-5p、miR-383-5p、miR-1295a表达水平与无远处转移生存率(DMFS)之间的关系。结果远处转移组miR-891a-5p、miR-383-5p、miR-1295a表达水平明显较未远处转移组减少,差异倍数分别为-2.519、-1.812和-1.443;远处转移组miR-891a-5p表达(1.099±0.899)明显低于未远处转移组的(2.768±2.194)(P<0.05)。miR-891a-5p低表达(<1.12)预测远处转移的敏感度和特异度分别为71.4%和82.4%,曲线下面积(AUC)为0.825(P=0.0000<0.01);miR-383-5p低表达(<1.15)预测远处转移的敏感度和特异度分别为53.4%和85.3%,AUC为0.738(P=0.0013<0.01);而miR-1295a低表达(<2.08)预测远处转移的敏感度和特异度分别为82.1%和50.0%,AUC仅为0.677(P=0.0175<0.05)。在诊断效能上,miR-891a-5p诊断乳腺癌远处转移的AUC、敏感度、阳性预测值、阴性预测值均优于miR-383-5p,miR-1295a诊断效能最差,表明miR-891a-5p、miR-383-5p低表达能预测HR阳性早期乳腺癌的远处转移。远处转移组的miR-661、miR-296-3p、miR-128-3p表达水平均低于未远处转移组,差异具有统计学意义(P<0.05)。62例患者的随访时间为59~131个月,中位随访时间为81个月。miR-891a-5p低表达患者的中位DMFS时间为48个月,5年DMFS仅为38.5%,低于miR-891a-5p高表达的86.1%(P<0.01)。miR-383-5p低表达患者的中位DMFS时间为52个月,5年DMFS为35.0%,低于miR-383-5p高表达的73.8%(P<0.01);miR-1295a低表达患者的中位DMFS时间为65个月,miR-1295a高、低表达患者的5年DMFS无明显差别(P>0.05)。结论miR-891a-5p、miR-383-5p有可能成为HR阳性乳腺癌的一个有价值的预后相关的生物标志物和治疗肿瘤的靶点。