上市后药品不良反应信号检测方法的进展与思考

国内外大量惨痛的药源性事件提醒人们需关注药品的安全性.药品监管部门和上市许可持有人要尽可能早地开始收集药品不良反应信息,针对不同的药品制订不同的风险管理计划,以最大程度地保障患者的用药安全.在药品全生命周期管理上,药品不良反应信号检测是上市后安全性监测的重要环节.本文介绍了上市后药品不良反应信号检测常用的不相称测定分析...     

上海市药品不良反应自发呈报数据库定量信号检测系统的建立

目的建立上海市药品不良反应自发呈报数据库定量信号检测系统。方法借鉴目前国际上五种针对自发呈报数据库的定量信号检测方法,采用PowerBuilder与SQL2000编程,建立了信息编码、信号检测和报表生成三个模块,并应用于上海市2003—2004年自发呈报数据库．验证其检测效果。结果1．该系统能准确检出已知信号;2．不同定量信号检测方法联合使用能够提高信号检测的准确性;3．本系统可以早期检出两种新的药品不良反应信号（莲必治致急性肾功能衰竭,头孢拉定致血尿）。结论不良反应定量信号检测系统的建立可以极大地提高药品不良反应监测工作的效率。     

DDIWAS: High-throughput electronic health record-based screening of drug-drug interactions

ObjectiveWe developed and evaluated Drug-Drug Interaction Wide Association Study (DDIWAS). This novel method detects potential drug-drug interactions (DDIs) by leveraging data from the electronic health record (EHR) allergy list.Materials and MethodsTo identify potential DDIs, DDIWAS scans for drug pairs that are frequently documented together on the allergy list. Using deidentified medical records, we tested 616 drugs for potential DDIs with simvastatin (a common lipid-lowering drug) and amlodipine (a common blood-pressure lowering drug). We evaluated the performance to rediscover known DDIs using existing knowledge bases and domain expert review. To validate potential novel DDIs, we manually reviewed patient charts and searched the literature.ResultsDDIWAS replicated 34 known DDIs. The positive predictive value to detect known DDIs was 0.85 and 0.86 for simvastatin and amlodipine, respectively. DDIWAS also discovered potential novel interactions between simvastatin-hydrochlorothiazide, amlodipine-omeprazole, and amlodipine-valacyclovir. A software package to conduct DDIWAS is publicly available.ConclusionsIn this proof-of-concept study, we demonstrate the value of incorporating information mined from existing allergy lists to detect DDIs in a real-world clinical setting. Since allergy lists are routinely collected in EHRs, DDIWAS has the potential to detect and validate DDI signals across institutions.     

我院128例药品不良反应报告分析

目的了解我院药品不良反应(ADR)发生情况和特点。方法分别从患者性别、年龄、引起ADR的药品、给药途径以及临床具体表现等方面对我院2005~2007年上报的128例ADR报告进行统计分析。结果128例ADR报告中,老年患者65例,占总例数的50.78%;抗微生物药物引起的ADR最多,占总例数的40.63%(52例);以静脉滴注方式给药引发的ADR最多,占总例数的75%(96例);临床表现以皮肤及附件损伤最为常见,占总例数的47.13%(71例);严重的ADR报告1例,占总例数的0.78%。结论医护药人员应正确理解ADR,加强ADR监测和报告工作,减少或避免ADR的发生。     

Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning

ObjectiveAutomated analysis of vaccine postmarketing surveillance narrative reports is important to understand the progression of rare but severe vaccine adverse events (AEs). This study implemented and evaluated state-of-the-art deep learning algorithms for named entity recognition to extract nervous system disorder-related events from vaccine safety reports.Materials and MethodsWe collected Guillain-Barré syndrome (GBS) related influenza vaccine safety reports from the Vaccine Adverse Event Reporting System (VAERS) from 1990 to 2016. VAERS reports were selected and manually annotated with major entities related to nervous system disorders, including, investigation, nervous_AE, other_AE, procedure, social_circumstance, and temporal_expression. A variety of conventional machine learning and deep learning algorithms were then evaluated for the extraction of the above entities. We further pretrained domain-specific BERT (Bidirectional Encoder Representations from Transformers) using VAERS reports (VAERS BERT) and compared its performance with existing models.Results and ConclusionsNinety-one VAERS reports were annotated, resulting in 2512 entities. The corpus was made publicly available to promote community efforts on vaccine AEs identification. Deep learning-based methods (eg, bi-long short-term memory and BERT models) outperformed conventional machine learning-based methods (ie, conditional random fields with extensive features). The BioBERT large model achieved the highest exact match F-1 scores on nervous_AE, procedure, social_circumstance, and temporal_expression; while VAERS BERT large models achieved the highest exact match F-1 scores on investigation and other_AE. An ensemble of these 2 models achieved the highest exact match microaveraged F-1 score at 0.6802 and the second highest lenient match microaveraged F-1 score at 0.8078 among peer models.     

A systematic review to evaluate the accuracy of electronic adverse drug event detection

Objective

Adverse drug events (ADEs), defined as adverse patient outcomes caused by medications, are common and difficult to detect. Electronic detection of ADEs is a promising method to identify ADEs. We performed this systematic review to characterize established electronic detection systems and their accuracy.

Methods

We identified studies evaluating electronic ADE detection from the MEDLINE and EMBASE databases. We included studies if they contained original data and involved detection of electronic triggers using information systems. We abstracted data regarding rule characteristics including type, accuracy, and rationale.

Results

Forty-eight studies met our inclusion criteria. Twenty-four (50%) studies reported rule accuracy but only 9 (18.8%) utilized a proper gold standard (chart review in all patients). Rule accuracy was variable and often poor (range of sensitivity: 40%–94%; specificity: 1.4%–89.8%; positive predictive value: 0.9%–64%). 5 (10.4%) studies derived or used detection rules that were defined by clinical need or the underlying ADE prevalence. Detection rules in 8 (16.7%) studies detected specific types of ADEs.

Conclusion

Several factors led to inaccurate ADE detection algorithms, including immature underlying information systems, non-standard event definitions, and variable methods for detection rule validation. Few ADE detection algorithms considered clinical priorities. To enhance the utility of electronic detection systems, there is a need to systematically address these factors.     

Research and applications: Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care

Background

Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment.

Objective

This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs.

Methods

From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported.

Results

Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting.

Conclusions

Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect.     

基于药物论坛中潜在不良反应与适应症的知识发现体系构建

目的：基于用户反馈信息,构建药物论坛中潜在不良反应与适应症的知识发现体系。方法：利用BIO序列标注方法和BiLSTM-CRF命名实体识别方法,从药物论坛的评论数据中识别不良反应与适应症的实体。结果：对不良反应与适应症进行过滤,得到26种药物共180种不良反应和26种适应症,并以此构建模型。结论：基于药物论坛构建的知识发现体系为挖掘中文领域内基于评论信息药物潜在不良反应与适应症可提供一种新的研究思路方案。     

新疆医科大学附属肿瘤医院200例药品不良反应报告分析

目的探讨新疆医科大学附属肿瘤医院医院药品不良反应(ADR)发生的相关因素与特点,促进临床合理用药,预防或减少ADR的发生。方法依据2010年1月-2013年3月上报的200例ADR报告,分别按照患者年龄、性别、引起ADR的药品、给药途径及ADR的临床表现等方面进行统计分析。结果 200例ADR报告中,ADR发生集中在40～49岁年龄段;女性患者发生ADR例次远高于男性患者;引发ADR的药品中,以抗肿瘤药为主(30.50%),其次为中药制剂(22.50%);主要给药途径是静脉给药(93.5%);引起ADR的前10种药品中,以注射用奈达铂为主(7.0%),其次为奥沙利铂注射液(6.5%)和紫杉醇注射液(4.0%);ADR以全身性损害为主。结论 ADR的发生与多种因素相关,应加强抗肿瘤药物ADR的监测工作,做好相应的防治工作,以保证用药安全。     

Three-dimensional aspects of formulation excipients in drug discovery: a critical assessment on orphan excipients,matrix effects and drug interactions

Formulation/pharmaceutical excipients play a major role in formulating drug candidates, with the objectives of ease of administration, targeted delivery and complete availability. Many excipients used in pharmaceutical formulations are orphanized in preclinical drug discovery. These orphan excipients could enhance formulatability of highly lipophilic compounds. Additionally, they are safe in preclinical species when used below the LD₅₀ values. However, when the excipients are used in formulating compounds with diverse physico-chemical properties, they pose challenges by modulating study results through their bioanalytical matrix effects. Excipients invariably present in study samples and not in the calibration curve standards cause over-/under- estimation of exposures. Thus, the mechanism by which excipients cause matrix effects and strategies to nullify these effects needs to be revisited. Furthermore, formulation excipients cause drug interactions by moderating the pathways of drug metabolizing enzymes and drug transport proteins. Although it is not possible to get rid of excipient driven interactions, it is always advised to be aware of these interactions and apply the knowledge to draw meaningful conclusions from study results. In this review, we will comprehensively discuss a) orphan excipients that have wider applications in preclinical formulations, b) bioanalytical matrix effects and possible approaches to mitigating these effects, and c) excipient driven drug interactions and strategies to alleviate the impacts of drug interactions.     

基于Apriori算法分析2021年山东省医疗器械不良事件的关联性

目的 医疗器械不良事件监测是医疗器械上市后风险管理的重要手段。本研究旨在基于Apriori算法分析2021年山东省医疗器械不良事件的关联性。方法 对2021年山东省各监测机构上报的63 041起不良伤害事件,按广义医疗器械分类划分为三类(无源医疗器械、有源医疗器械以及体外诊断试剂)医疗器械不良事件进行描述分析。采用关联规则挖掘中的Apriori模型,挖掘出与不良事件相关的器械类别、使用科室、医院类别、是否超期使用以及上报单位所属地区,探索医疗器械不良事件关联风险。结果 不良事件中包含有源医疗器械20 564起、无源医疗器械42 181起及体外诊断试剂296起。其中,无源医疗器械不良事件发生最多的地级市为烟台市(5 711起)、科室为手术室(835起)、医院类别为二级综合医院(5 320起);有源医疗器械不良事件发生最多的地级市为济南市(2 271起)、科室为手术室(196起)、医院类别为三级综合医院(1 108起);体外诊断试剂不良事件发生最多的地级市为烟台市(42起)、科室为儿科(6起)、医院类别为一级医院(42起)。根据关联规则可知,一级医院中卫生院使用未超期无源器械关联规则支持度...     

A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data

Background Venous thromboembolisms (VTEs), which include deep vein thrombosis (DVT) and pulmonary embolism (PE), are associated with significant mortality, morbidity, and cost in hospitalized patients. To evaluate the success of preventive measures, accurate and efficient methods for monitoring VTE rates are needed. Therefore, we sought to determine the accuracy of statistical natural language processing (NLP) for identifying DVT and PE from electronic health record data.Methods We randomly sampled 2000 narrative radiology reports from patients with a suspected DVT/PE in Montreal (Canada) between 2008 and 2012. We manually identified DVT/PE within each report, which served as our reference standard. Using a bag-of-words approach, we trained 10 alternative support vector machine (SVM) models predicting DVT, and 10 predicting PE. SVM training and testing was performed with nested 10-fold cross-validation, and the average accuracy of each model was measured and compared.Results On manual review, 324 (16.2%) reports were DVT-positive and 154 (7.7%) were PE-positive. The best DVT model achieved an average sensitivity of 0.80 (95% CI 0.76 to 0.85), specificity of 0.98 (98% CI 0.97 to 0.99), positive predictive value (PPV) of 0.89 (95% CI 0.85 to 0.93), and an area under the curve (AUC) of 0.98 (95% CI 0.97 to 0.99). The best PE model achieved sensitivity of 0.79 (95% CI 0.73 to 0.85), specificity of 0.99 (95% CI 0.98 to 0.99), PPV of 0.84 (95% CI 0.75 to 0.92), and AUC of 0.99 (95% CI 0.98 to 1.00).Conclusions Statistical NLP can accurately identify VTE from narrative radiology reports.     

高敏C反应蛋白水平对预测急性ST段抬高心肌梗死心脏不良事件的临床价值

目的:探讨高敏C反应蛋白(hsCRP)水平对预测急性ST段抬高心肌梗死(STEMI)心脏不良事件的临床价值。方法:选取我院2008年5月至2009年9月收治的240例STEMI的患者为研究对象,入院后测定hsCRP的水平,随访12个月,观察终点为心肌梗死新发或再发、心力衰竭和心源性死亡,采用多元Logistic回归分析方法对各种潜在危险因素与主要不良心脏事件(MACE)的相关性进行分析。结果:年龄>70岁、糖尿病、吸烟、左室射血分数(LVEF)<50%、肌钙蛋白I>0.1μg.L-1、B型钠尿肽>80 ng.L-1、hsCRP>4 mg.L-1都与发生MACE有关(P<0.05)。MACE组的hsCRP水平显著高于非MACE组(P<0.05);hsCRP>4 mg.L-1组的MACE发生率显著高于hsCRP≤4 mg.L-1组(P<0.05);多因素回归分析表明年龄>70岁、糖尿病、LVEF<50%、hsCRP>4 mg.L-1是预测MACE的独立危险因素(P<0.05)。结论:hsCRP是STEMI患者MACE的独立危险预测因子,对患者的近期预后有重要的临床价值。     

基于质量编码探针的质谱多联检测研究进展

质量编码探针是一类以质量标签分子对待测物进行特异性识别标记并输出其特征离子信号的探针工具,其在疾病标志物多元分析和药物靶点筛选等方面都发挥着重要的作用。近年来,研究者基于各类质谱分析方法,开发了不同结构与功能的质量编码探针,为生理环境中生物分子的多重检测以及组织样本的质谱成像提供了有力的技术工具。本文从探针结构组成、质谱分析方法以及在生化分析中的应用3个方面综述了质量编码探针在质谱多联检测方面的最新研究进展,并对其未来的发展方向进行了展望。     

多重实时荧光定量PCR检测急性肝炎患者HBV和HCV方法的建立与意义分析

目的建立一种新的可以快速筛查急性肝炎患者HBV和HCV感染的多重实时荧光定量PCR方法。方法收集596例急性肝炎患者血清或血浆样本,应用自主构建的多重实时荧光定量PCR方法同时检测HBV和HCV,同时应用HBV和HCV单管检测试剂进行检测分析。结果新建立的多重实时荧光定量PCR体系,可以有效地检测HBV和HCV的阳性质控品及阳性样本。多重实时荧光定量PCR体系特异性较好,检测HBV和HCV时,两者之间无交叉反应,且以多种血浆病毒的核酸样品为模板进行检测时结果全为阴性;多重实时荧光定量PCR体系检测HBV、HCV的灵敏度分别为20 IU/ml、50 IU/ml;多重实时荧光定量PCR体系精密度好,检测HBV、HCV的CV值分别为0.11%、0.096%。在检测临床样本时,多重复合体系检测血清或血浆中HBV和HCV的检出率与单独检测HBV和HCV具有很好的一致性,且HBV和HCV的一致率分别达到97.7%(k=0.952)、98.8%(k=0.976);同时有6例样本出现HBV和HCV共感染。结论新型多重实时荧光定量PCR方法对快速检测及筛查HBV和HCV较快捷,而且特异性好、灵敏度高、精密度好。因此多重实时荧光定量PCR方法对2种肝炎病毒的检测具有重要意义。     

建立我国药物研发专利预警机制的SWOT分析

运用SWOT分析方法,分析了目前我国建立药物研发专利预警机制具备的优势条件、不足之处以及面临的外部机会和不利条件,并对预警机制的建立提出了参考建议.     

The difficulties of early detection for infectious disease outbreak in China：A qualitative investigation

Objective： To make intensified analysis upon the existing difficulties in early detection for the infectious diseases outbreak in China and put forward some effective measures to improve it. Methods： Field investigation and in-depth interview were applied in 23 interviewees from different-level CDC. Results：The study findings suggest that although the timeliness of outbreak detection has been improved since SARS epidemic in China, some problems still exist, such as： ① lacking syndrome surveillance; ② report quality of infectious disease should be improved; ③ difficulties of identifying the cases at lower social economic status; ④a definite financial compensation mechanism for the operation of web-based report system is absent; ⑤insufficient information exchange among different branches. Conclusion：Some effective measures must be taken including developing syndrome surveillance system; affording more education and txaining for related staff; increasing payout on surveillance and establishing an information exchange platform for early detection of disease outbreak.     

Comparison of polymerase chain reaction and catalyzed signal amplification in situ hybridization methods for human papillomavirus detection in paraffin-embedded cervical preneoplastic and neoplastic lesions

BACKGROUND: Two molecular methods for HPV genotyping in formalin-fixed, paraffin-embedded tissue were evaluated: in house polymerase chain reaction assay (PCR) with consensus and type-specific primers and a novel procedure of in situ hybridization-a catalyzed signal amplification system (CSA-ISH, Genpoint, DAKO, Glostrup, Denmark). The number of HPV positive cases and detected viral types were compared in cervical biopsies and cone specimens according to histopathological diagnosis. Primer efficiency in detecting various types of HPV by PCR method was evaluated. METHODS: DNA samples (101) were used as a template to amplify with three pairs of consensus (MY09/11, GP5+/6 +, CPI/IIG) and four type-specific HPV primers (HPV-6/11, 18, 16 and 33). The according histological tissue sections were analyzed with CSA-ISH method, using commercial HPV biotinylated probes HPV-6/11, 16/18 and 31/33/51. RESULTS: The degree of concordance for PCR and CSA-ISH was 64.4%. In 63 of 101 samples (62.4%), HPV was detected by PCR, while only 35 (34.7%) were positive using CSA-ISH. CSA-ISH found lower percentages for all HPV types, except HPV-6/11. A lower percentage of positive results in all high-grade lesions was detected by CSA-ISH. Multiple infections were detected by PCR in only one sample and in three samples by CSA-ISH. Detection with My09/11 primers followed by Gp5+/6+ primers, in nested reaction, gave the highest number of positive results: 58 of 63 (92%). None of the samples diagnosed as condylomata planum or CIN I was positive for HPV-6/11 (low risk type), which was detected exclusively in condylomata acuminatum group. CONCLUSIONS: A significantly higher number of positive samples was detected with PCR than with CSA-ISH method. CSA-ISH method should be improved, especially in detecting HPV in high-grade lesions. CSA-ISH may be more accurate in detection of multiple infections. GP5+/6+ in nested reaction after MY09/11 detected the highest number of positive results. Samples diagnosed as benign lesions positive on HPV-X must be monitored as possible candidates for progression. CIN I lesions, which were HPV negative, probably will not progress. This finding may be important in planning therapy and avoiding unnecessary treatment.     

基于运动和声音同步记录的动物行为活动监测系统

目的　研制一套新颖的基于运动和声音同步记录的动物活动监测系统。方法　采用视频记录和图象分析技术确定动物每一时刻在笼内的几何位置和在相邻时间内身体的位移面积，同时持续记录笼内与运动有关的声音信号。结果　初步研究结果表明运动与声音的同步监测能够更精细全面地反映动物的活动，有助于动物行为的识别。结论　系统具有数据压缩率高（512×5124）、在线分析（1sec）和储存时间长（可达持续数周）等特点。