基于CT的三维数字化导航技术在肺癌介入微波消融治疗中的应用价值

目的 在肺癌微波消融治疗中探究基于CT的三维数字化导航技术的应用价值。方法 回顾性分析我院收治的92例肺癌患者,随机进行三维数字化导航微波消融或传统CT引导下微波消融,分为三维导航组和传统组,依据肿瘤位置、大小（最大径差值≤2 mm）及微波消融条件不同两两配对,共46对,比较2组手术时间、微波针穿刺次数、CT剂量指数、术中并发症发生率、术后病灶控制情况。结果 三维导航组与传统组的手术时间分别为（30.07 ± 6.36）min、（47.20 ± 9.65）min、穿刺次数分别为（1.72 ± 0.69）次、（7.13 ± 3.00）次、CT剂量指数分别为（11.16 ± 2.20）mGy、（26.67 ± 8.72）mGy、术中并发症发生率分别为10.87%、34.78%,以上3个指标三维导航组均低于传统组,三维导航组治疗有效率（93.48%）高于传统组（71.74%）,差异均有统计学意义（P < 0.05）。结论 CT引导下利用三维数字化导航技术行肺癌微波消融治疗,使介入穿刺手术的操作更加精准安全。     

国际学术出版技术商面向科技期刊的业务特征分析及启示

【目的】 研究国际主要学术出版技术服务商面向科技期刊服务的业务特征,为国内科技期刊行业发展提供参考。【方法】 通过对13家典型的国际学术出版技术服务商进行信息收集和整理,总结其业务范围及产品和服务方案,并结合国内同类机构进行比较分析。结合文献探讨专业化的学术出版技术服务商的发展趋势。【结果】 国际学术出版技术服务商的业务范围覆盖学术出版全过程,近年来呈现服务领域不断延伸、服务内容更加分工细化的趋势。国际学术出版技术服务商充分运用数字信息技术,其规模和业务范围大于国内同类企业。【结论】 利用好技术手段,发展成熟完善的学术出版技术服务产业,有利于科技期刊将资源集中于核心内容,有利于提高科技期刊整体质量。     

Reported Challenges in Health Technology Assessment of Complex Health Technologies

ObjectivesWith complex health technologies entering the market, methods for health technology assessment (HTA) may require changes. This study aimed to identify challenges in HTA of complex health technologies.MethodsA survey was sent to European HTA organizations participating in European Network for HTA (EUnetHTA). The survey contained open questions and used predefined potentially complex health technologies and 7 case studies to identify types of complex health technologies and challenges faced during HTA. The survey was validated, tested for reliability by an expert panel, and pilot tested before dissemination.ResultsA total of 22 HTA organizations completed the survey (67%). Advanced therapeutic medicinal products (ATMPs) and histology-independent therapies were considered most challenging based on the predefined complex health technologies and case studies. For the case studies, more than half of the reported challenges were “methodological,” equal in relative effectiveness assessments as in cost-effectiveness assessments. Through the open questions, we found that most of these challenges actually rooted in data unavailability. Data were reported as “absent,” “insufficient,” “immature,” or “low quality” by 18 of 20 organizations (90%), in particular data on quality of life. Policy and organizational challenges and challenges because of societal or political pressure were reported by 8 (40%) and 4 organizations (20%), respectively. Modeling issues were reported least often (n = 2, 4%).ConclusionsMost challenges in HTA of complex health technologies root in data insufficiencies rather than in the complexity of health technologies itself. As the number of complex technologies grows, the urgency for new methods and policies to guide HTA decision making increases.     

Assessing the Economic Value of Clinical Artificial Intelligence: Challenges and Opportunities

ObjectivesClinical artificial intelligence (AI) is a novel technology, and few economic evaluations have focused on it to date. Before its wider implementation, it is important to highlight the aspects of AI that challenge traditional health technology assessment methods.MethodsWe used an existing broad value framework to assess potential ways AI can provide good value for money. We also developed a rubric of how economic evaluations of AI should vary depending on the case of its use.ResultsWe found that the measurement of core elements of value—health outcomes and cost—are complicated by AI because its generalizability across different populations is often unclear and because its use may necessitate reconfigured clinical processes. Clinicians’ productivity may improve when AI is used. If poorly implemented though, AI may also cause clinicians’ workload to increase. Some AI has been found to exacerbate health disparities. Nevertheless, AI may promote equity by expanding access to medical care and, when properly trained, providing unbiased diagnoses and prognoses. The approach to assessment of AI should vary based on its use case: AI that creates new clinical possibilities can improve outcomes, but regulation and evidence collection may be difficult; AI that extends clinical expertise can reduce disparities and lower costs but may result in overuse; and AI that automates clinicians’ work can improve productivity but may reduce skills.ConclusionsThe potential uses of clinical AI create challenges for health technology assessment methods originally developed for pharmaceuticals and medical devices. Health economists should be prepared to examine data collection and methods used to train AI, as these may impact its future value.     

Do Cost-Effectiveness Analyses Account for Drug Genericization? A Literature Review and Assessment of Implications

ObjectivesWe investigated how health technology assessment (HTA) organizations around the world have handled drug genericization (an allowance for future generic drug entry and subsequent drug price declines) in their guidelines for cost-effectiveness analyses (CEAs). We also analyzed a large sample of published CEAs to examine prevailing practices in the field.MethodsWe reviewed 43 HTA guidelines to determine whether and how they addressed drug genericization in their CEAs. We also selected a sample of 270 US-based CEAs from the Tufts Medical Center’s CEA Registry, restricting the sample to studies on pharmaceuticals published from 1991 to 2019 and to analyses taking a lifetime time horizon. We determined whether each CEA examined genericization (and if so, whether in base case or sensitivity analyses), and how inclusion of genericization influenced the estimated incremental cost-effectiveness ratios.ResultsFourteen (33%) of the 43 HTA guidelines mention genericization for CEAs and 4 (9%) recommend that base case analyses include assumptions about future drug price changes due to genericization. Most published CEAs (95%) do not include assumptions about future generic prices for intervention drugs. Only 2% include such assumptions about comparator drugs. Most studies (72%) conduct sensitivity analyses on drug prices unrelated to genericization.ConclusionsThe omission of assumptions about genericization means that CEAs may misrepresent the long run opportunity costs for drugs. The field needs clearer guidance for when CEAs should account for genericization, and for the inclusion of other price dynamics that might influence a drug’s cost-effectiveness.     

Development of an EQ-5D Value Set for India Using an Extended Design (DEVINE) Study: The Indian 5-Level Version EQ-5D Value Set

ObjectivesThis study aimed to develop the Indian 5-level version EQ-5D (EQ-5D-5L) value set, which is a key input in health technology assessment for resource allocation in healthcare.MethodsA cross-sectional survey using the EuroQol Group’s Valuation Technology was undertaken in a representative sample of 3548 adult respondents, selected from 5 different states of India using a multistage stratified random sampling technique. The participants were interviewed using a computer-assisted personal interviewing technique. This study adopted a novel extended EuroQol Group’s Valuation Technology design that included 18 blocks of 10 composite time trade-off (c-TTO) tasks, comprising 150 unique health states, and 36 blocks of 7 discrete choice experiment (DCE) tasks, comprising 252 DCE pairs. Different models were explored for their predictive performance. Hybrid modeling approach using both c-TTO and DCE data was used to estimate the value set.ResultsA total of 2409 interviews were included in the analysis. The hybrid heteroscedastic model with censoring at ?1 combining c-TTO and DCE data yielded the most consistent results and was used for the generation of the value set. The predicted values for all 3125 health states ranged from ?0.923 to 1. The preference values were most affected by the pain/discomfort dimension.ConclusionsThis is the largest EQ-5D-5L valuation study conducted so far in the world. The Indian EQ-5D-5L value set will promote the effective conduct of health technology assessment studies in India, thereby generating credible evidence for efficient resource use in healthcare.     

Diagnostics and Treatments of COVID-19: A Living Systematic Review of Economic Evaluations

ObjectivesAs healthcare systems continue to respond to the COVID-19 pandemic, cost-effectiveness evidence will be needed to identify which tests and treatments for COVID-19 offer value for money. We sought to review economic evaluations of diagnostic tests and treatments for COVID-19, critically appraising the methodological approaches used and reporting cost-effectiveness estimates, using a “living” systematic review approach.MethodsKey databases (including MEDLINE, EconLit, Embase) were last searched on July 12, 2021. Gray literature and model repositories were also searched. Only full economic evaluations published in English were included. Studies were quality assessed and data were extracted into standard tables. Results were narratively summarized. The review was completed by 2 reviewers independently, with disagreements resolved through discussion with a senior reviewer.ResultsOverall, 3540 records were identified, with 13 meeting the inclusion criteria. After quality assessment, 6 were excluded because of very severe limitations. Of the 7 studies included, 5 were cost-utility analyses and 2 were cost-effectiveness analyses. All were model-based analyses. A total of 5 evaluated treatments (dexamethasone, remdesivir, hypothetical) and 2 evaluated hypothetical testing strategies. Cost-effectiveness estimates were sensitive to the treatment effect on survival and hospitalization, testing speed and accuracy, disease severity, and price.ConclusionsPresently, there are few economic evaluations for COVID-19 tests and treatments. They suggest treatments that confer a survival benefit and fast diagnostic tests may be cost effective. Nevertheless, studies are subject to major evidence gaps and take inconsistent analytical approaches. The evidence may improve for planned updates of this “living” review.     

山药配方颗粒溶化性差的原因分析与解决策略

山药配方颗粒由山药饮片经水煎煮提取、分离、浓缩、干燥、制粒而成,具有调剂简单、使用方便、免煎易服等优势。然而,因山药富含淀粉与黏液质类成分,其提取物粉末与配方颗粒溶化性差,在5 min内难以完全溶化或分散,不溶物即使在水中静置24 h也难以完全溶散,影响了配方颗粒的质量评价与患者的服药心理。因此,通过研究山药提取物及其配方颗粒的溶化过程与机制,发现山药特殊的化学组成、高温提取过程中淀粉的变性及其与蛋白质等物质的复合、喷雾干燥过程中“衣膜”的收缩形成等因素综合叠加,最终形成“衣膜”包覆淀粉粒的特殊微观结构,是山药配方颗粒溶化性差的根本原因。基于课题组前期对粉体结构-性质-功能的研究,笔者提出采用粉体改性工艺改善山药配方颗粒溶化性的技术策略,并通过实验证明改性处理后的山药配方颗粒能在2 min内实现全部溶散,解决了该技术难题,可为其他类似品种的溶化性改善提供借鉴,推动中药配方颗粒产业的高质量发展。     

基于混合测序策略的两品种当归中类黄酮调控基因差异分析

目的 比较2个不同茎叶色当归品种岷归1号与岷归2号转录水平差异。方法 以2种颜色当归的新鲜叶片（带叶柄）和上端茎为材料,采用混合测序策略,应用全长转录组技术构建当归无参全长转录本文库,利用RNA-seq技术对两品种进行差异基因表达分析,再利用公共数据库对差异基因的生物学功能进行注释和精细分类,筛选调控当归茎叶色差异的主要候选基因。结果 当归转录本的测序结果良好,测序数据质量较高,当归全长转录本的34 528条序列在非冗余蛋白（NR）、京都基因与基因组百科全书（KEGG）、SwissProt及KOG数据库中分别注释到33 947、33 241、29 150和22 601条。对两品种当归差异表达基因（DEGs）进行精细分类,具有生物学功能和分子功能的705个DGEs可分为11类,主要富集在初级代谢（17.87%）、逆境响应（14.47%）、次级代谢（11.49%）等功能上,与颜色有关的差异表达基因主要集中在类黄酮生物合成途径上。结论 两品种当归茎叶颜色差异的主要原因可能与调控类黄酮的生物合成基因的表达差异有关,可为后续进行功能验证,进一步明确与当归主要药效成分之间的联系奠定基础。     

电子鼻技术应用于白及及其近似饮片快速辨识的可行性分析

目的：探讨电子鼻技术应用于白及及其近似饮片快速辨识的可行性。方法：收集134批白及及其近似饮片（白及45批、天麻30批、玉竹30批、黄花白及29批）作为待测样品,使用PEN3型电子鼻采集样品嗅觉感官数据作为自变量X,基于2020年版《中华人民共和国药典》和地方标准的鉴别结果,以及各饮片高效液相色谱法（HPLC）指纹图谱和原始采购信息,获得辨识模型的标杆数据Y,分别采用主成分分析-判别分析（PCA-DA）、偏最小二乘法-判别分析（PLS-DA）、最小二乘法-支持向量机（LS-SVM）及K-最近邻（KNN）4种化学计量学方法建立45批白及与89批非白及的二分类辨识模型和上述4种饮片的四分类辨识模型Y=F(X)。结果：经留一法交互验证,在二分类辨识中,上述4种模型分类正判率分别为97.01%、97.01%、98.51%和97.01%;在四分类辨识中,这4种模型分类正判率分别为97.76%、89.55%、98.51%和97.01%。二分类和四分类辨识模型的最高正判率均可达到98.51%,且均以LS-SVM算法为最优,最优核函数分别选择径向基核函数和线性核函数。最优模型判别结果良好,没有未分类样...