Endovascular aneurysm repair (EVAR) is routinely used for treatment of abdominal aortic aneurysm (AAA). In 2018, draft guidance from the National Institute for Clinical Excellence (NICE) suggested EVAR was not cost-effective compared to open surgical repair. The analysis was driven by clinical inputs from randomized control trials which may not reflect current clinical practice. Data from registries may inform more robust economic modelling. The Global Registry for Endovascular Aortic Treatment (GREAT) was initiated to collect contemporary real-world data on the performance of GORE® aortic endografts and includes long-term data on survival, re-interventions and resource use. This study compares the real-world values for mortality and resource use following elective EVAR as collected by GREAT with the 2018 NICE AAA draft guidance.

A total of 1,348 patients (88.7% men; mean age 73.1 years) undergoing elective AAA repair with the GORE® EXCLUDER device. Mortality, re-intervention and resource use was compared with the economic inputs for 2018 NICE draft guidance cost-utility analysis.

All patients survived EVAR compared to the 0.4 percent mortality indicated in the NICE analysis. All-cause mortality was lower through 1, 3 and 5 years with values of 6.9, 14.8 and 16.2 percent respectively compared to the NICE base case. The average length of stay was 3.7 days in GREAT compared to 8.34 days in the NICE analysis. Short- and long-term re-interventions were also lower with real-world data (3.6% versus 7.3% and 5.5% versus 8.3%).

GREAT provides conflicting data on survival and resource use associated with EVAR compared to inputs of the 2018 NICE draft guidance These differences are likely to significantly alter incremental cost-effectiveness ratios. Robust cost-effectiveness modelling in health technology assessments should consider contemporary data, as it is likely more reflective of current clinical practice and more informative for clinical and economic decision making for AAA.

China's National Reimbursement Drug List (NRDL) covers medicines that are included in national health insurance schemes. NRDL updates take into account evidence and recommendations of experts from the fields of medicine, health economics, pharmacy and health policy. A negotiation mechanism between the government and manufacturers was introduced in 2017 to include a more detailed evaluation and negotiation for high cost drugs. However, the values that are considered in NRDL decision making are not well-understood. This study aims to investigate the influence of available evidence and other factors on coverage decisions.

Outcomes of the 2017 and 2018 NRDL negotiations were analyzed. Logistic regression was used to investigate factors associated with listing decisions. Ordinary least squares and Tobit regression were used to investigate factors associated with negotiated price discounts. Independent variables were published cost-effectiveness analysis (CEA), incremental cost-effectiveness ratio (ICER), disease area, burden of disease (disability-adjusted life years), company ownership (domestic or foreign) and regulatory approval year.

Twenty-eight out of sixty-two negotiated drugs had one or more published CEA studies in the English or Chinese language, although neither the presence of a study nor the central ICER estimates were predictive of price discount or listing. A longer time since regulatory approval was a significant predictor of listing (p < 0.05). Disease area (oncology) and ownership (foreign) were significant predictors of a higher price discount (p < 0.01).

The NRDL plays a key role in providing access to healthcare for the 95 percent of China's population that is covered by public insurance. We found several factors that were associated with reimbursement decisions. Many of the medicines in the NRDL negotiation have CEA evidence, although the role of CEA in reimbursement decision making in China remains inconclusive.

The Cochrane Handbook of Systematic Reviews contains two search filters to find randomized controlled trials (RCT) in Ovid MEDLINE: a sensitivity maximizing RCT filter and a sensitivity and precision maximizing RCT filter. The RCT search strategies were originally published in 1994 have been adapted and updated, most recently in 2008. To determine whether the Cochrane filters are still performing adequately to inform Cochrane reviews, we tested the performance of the Cochrane filters and 36 other MEDLINE filters in a large new gold standard set of relevant records.

We identified a gold standard set of RCT reports published in 2016 from the Cochrane CENTRAL database of controlled clinical trials. We retrieved the records in Ovid MEDLINE using their PubMed identifiers. Each RCT filter was run in MEDLINE and combined with the gold standard set of records, to determine their sensitivity, precision and f-scores.

The gold standard comprised 27,617 records and the searches were run on 16 July 2019. The most sensitive RCT filter was Duggan (sensitivity 0.99). The Cochrane sensitivity maximizing RCT filter had a sensitivity of 0.96, but was more precise than Duggan (0.14 compared to 0.04 for Duggan). The most precise RCT filter was Chow, Glanville/Lefebvre, Royle/Waugh, Dumbrique (precision 0.97, sensitivity 0.83). The best precision Cochrane filter was the sensitivity and precision maximising RCT filter.

The Cochrane MEDLINE sensitivity maximizing RCT filter can continue to be used by Cochrane reviewers and CENTRAL compilers as it has very high sensitivity but a more acceptable precision than many higher sensitivity filters. Slightly more sensitive filters are available, but with lower precision than the Cochrane sensitivity maximizing RCT filter. These other filters may be preferred when combining with a subject search when record numbers may be more manageable than searching the whole of MEDLINE.

Data from randomized controlled trials (RCTs) are the primary source for health technology assessment (HTA) however these are limited by strict patient inclusion criteria, leading to concerns about whether treatment benefit estimates are accurate for all patients (generalizability). Real-World Data (RWD) have been proposed as a solution however as these are observational data there is additional potential for bias when estimating treatment effectiveness. To maximize the utility of RWD it is useful to consider the whole process of evidence generation and robustly address issues of feasibility and validity.

A series of complementary studies investigated whether population-based routinely collected health data from Scotland are suitable for estimating the effectiveness of chemotherapy for early breast cancer. Firstly, a prognostic score was validated in this population. Secondly, a comparison of RWD and randomized trial effectiveness estimates was made to investigate feasibility and validity of several methods – Propensity Score Matching (PSM), Instrumental variables (IV) and Regression Discontinuity. Finally, effectiveness estimates in trial underrepresented groups were produced.

PSM and IV were feasible and produced results in relatively close agreement with randomized data. Effectiveness estimates in trial underrepresented groups (women over 70 years and women with high comorbidity) were consistent with an approximate one-third reduction in the risk of death from breast cancer. This is equivalent to approximately a 3–4 percentage point difference in all cause mortality over 10 years in these groups.

RWD are a feasible for generating estimates of effectiveness of adjuvant chemotherapy in early stage breast cancer. The process of using RWD for this purpose should include careful assessment of data quality and comparison of alternative strategies for causal identification in the context of available randomized data.

NICE is undergoing transformational change aiming to improve consistency across the different types of guidance and to bring together related guidance in a more accessible way (NICE Connect). Currently, NICE publishes myriad guidance with different language and formats, which may lead to stakeholder confusion and gaps in the provision of information. Here, the consistency of the format and language of a subset of NICE guidance was assessed to understand where and how guidance could be better aligned. This preliminary investigation is important to determine the extent of inconsistencies and whether a more detailed analysis is warranted.

Ten randomly selected pieces of guidance published (or updated) April 2018 – March 2019 from three programs were assessed (two pieces of guidance or ten percent of guidance per program, whichever was greatest): Medical Technologies (n = 2); Diagnostics (n = 2); Technology Appraisals (n = 6). Guidance was assessed on aspects listed on the guidance webpage (for example, summary type, additional sections, links to other resources, format) and the guidance pdf (for example, table of contents and language). Observed data and trends are described.

The webpage summary and additional sections were consistent within and between programs. Additional information on the webpages showed themes which are not currently standardized (for example, guidance history). In the table of contents only one section was consistently included in all guidance, and the terminology was not consistent across different types of guidance. The format used to present evidence differed between programs (webpage tab or within the pdf), as did terminology for the external assessment groups.

These descriptive data highlight inter- and intra-program inconsistencies in the content and format of NICE guidance, especially in the guidance table of contents and the format and language regarding the provision of evidence. These inconsistencies contribute to the inaccessibility of NICE guidance, making it potentially difficult for patients and professionals to understand guidance, conditions and treatments as a whole.

A more comprehensive analysis is warranted to extend and validate these conclusions. Future research of this kind could constructively direct the resources and priorities of NICE transformational projects, and could lead to an improvement in the accessibility of NICE Guidance.

In 2019, the Norwegian Institute for Public Health and Canadian Agency for Drugs and Technologies in Health (CADTH) received support from HTAi to produce a quarterly current awareness alert for the HTAi Disinvestment and Early Awareness Interest Group in collaboration with the HTAi Information Retrieval Interest Group. The alert focuses on methods and topical issues, and broader forecasts of potentially disruptive technologies that may be of interest to those involved in horizon scanning and disinvestment initiatives in health technology assessment (HTA).

Information specialists at both agencies developed search strategies for disinvestment and for horizon scanning in PubMed and Google. The template for the alert was based on an e-newsletter developed by the Information Retrieval Interest Group. Information specialists and researchers reviewed the monthly (PubMed) and weekly (Google) search results and selected potentially relevant publications. Additional sources were also identified through regular HTA and horizon scanning work.

Alerts are posted quarterly on the HTAi Interest Group website; members receive an email notice when new alerts are available. While the revised PubMed searches are identifying relevant information, Google alerts have been disappointing, and this search may need to be revised further or dropped. When the one-year pilot project ends, in Fall 2020, interest group members will be surveyed to see if the alerts were useful, and whether they have suggestions for improving them.

Collaborating on this alert service reduces duplication of effort between agencies, and makes new research in horizon scanning and disinvestment more accessible to colleagues in other agencies working in these areas.

The National Institute for Health Research (NIHR) Innovation Observatory (NIHRIO) is the national Horizon Scanning (HS) organization in England, and the National Institute for Health and Care Excellence (NICE) is its key health technology assessment (HTA) stakeholder. NIHRIO has a remit to notify NICE of innovative technologies with a time horizon of three years prior to regulatory approval in the European Union (EU)/United Kingdom (UK). The notification process produces an initial ‘filtration form’ followed by a ‘technology briefing’ produced 17–20 months prior to licence for those technologies that NICE will consider for appraisal. Since April 2017, NIHRIO has produced ~400 technology briefings. We present an analysis of how this has fed into the NICE HTA process so far.

The analysis mapped NIHRIO's technology briefings (April 2017 – June 2020) with relevant NICE technology appraisal/highly specialized technologies (TA/HST) guidance during the time period. The analysis followed the timeline of technologies from identification during the horizon scanning process to filtration to briefing submission to NICE and entering the TA/HST process to outcome/recommendation given by NICE.

Until June 2020, 496 technology briefings entered the NICE TA/HST scoping process. Forty per cent are in progress, four per cent have had a TA/HST recommendation and three per cent that entered the NICE TA/HST scoping process did not complete it. On average it took less time from briefing submission to NICE recommendation for cancer indications. The time from discovery to NICE recommendation ranged from 115 months to 22 months.

HS for TA/HST is a lengthy process from identification to final recommendation and there is considerable variation in time duration from identification to briefing submission to NICE recommendation. Average time taken from briefing submission to NICE recommendation is shorter for cancer indications and repurposed medicines. A full TA/HST may not be recommended for all technology briefings, rather they may update existing guidance or find different routes of evaluation. Technologies that enter the TA/HST scoping process might be terminated, suspended or discontinued for several reasons which may include lack of company engagement, change in development or regulatory plans by the company. Timely notification is key in achieving TA/HST recommendation at the time of market authorization but not the only influencing factor.

While horizon-scanning systems aim to identify innovative and potentially disruptive health technologies in development, a key challenge is variation in information collation and tracking of the pace of change prior to regulatory approval. An active and efficient monitoring process is crucial for timely notification of health technology assessment (HTA) stakeholders to enhance faster market and patient access. The National Institute for Health Research Innovation Observatory (NIHRIO) identifies and notifies its key HTA stakeholders in England of technologies that are within three to five-year timeframe to regulatory approval. Regular review of each technology is required to meet this remit.

A standardized monitoring framework was developed based on the knowledge and experience of the evidence synthesis specialists in NIHRIO, supplemented by literature to ensure consistency of setting review periods. This framework used predefined criteria that integrated the technology innovation (advanced therapies, orphan status, regulatory awards), trial data (phase, status, completion date, preliminary results) and estimated approval timelines obtained from the company or other sources (for example, press releases).

The framework has been piloted and early findings showed improved consistency in the monitoring process between different analysts. It ensures that each technology is reviewed at least once a year; review timelines are set at three, six, nine or twelve months based on the predefined criteria. Estimated timeframes obtained from the companies are used to triangulate and streamline review periods, improving efficiency of the monitoring process.

Findings from the pilot work with the framework demonstrated improved consistency and efficiency of the technology monitoring process, which can be easily implemented to provide early awareness in an accurate and timely manner for HTA. This framework was designed using a systematic and transparent approach that integrated different data sources to set review periods. While most of the data used in defining the criteria are publicly available, commercially sensitive information provided by companies were also used which may not always be readily available. Implications for horizon-scanning organizations will be discussed.

Opposition parties in Germany are allowed to send formal requests to the government to control actions and pass important political debates to the parliament. These formal requests include a comprehensive analysis report issued by the scientific service of the German parliament. A systematic overview of these reports would support a deeper understanding about healthcare topics and assessments discussed by parties in the highest German decision body, particularly in the field of nursing.

We conducted a review using the German parliament “Bundestag” database for all formal requests since 1949. To systemize the formal requests we performed a quantitative category analysis using descriptive statistics.

We identified 26,197 formal requests with 146 reports related to nursing issued between 1978 and 2019. The 146 reports related to nursing accounted for 0.54 percent of all requests. Almost 30 percent of these requests were related to recruitment and qualification. The second major topic, with 15 percent, was financing of the nursing sector. Of all 146 formal requests in the history of the Bundestag, 55 percent (n = 81) were issued in the last 10 years.

Nursing is an emerging topic in the German parliament, highlighting the demographic shift in Germany and the growing pressure in the nursing care sector. Health Technology Assessment bodies should be informed and work together with the scientific services of parliamentary bodies. This would support a more transparent and evidence based healthcare system, aside from lobbyism.

Premature mortality affects the economy directly due to the loss of productivity of individuals who die, thus ceasing to contribute economically to the country. The one-third reduction in premature mortality (30–69 years) from chronic noncommunicable diseases is goal 3.4 of the United Nations Sustainable Development Goals (UN SDG). Although cancer is a chronic disease, it comprises more than 100 different conditions, with different risk factors and prognosis. This study aimed to calculate current and predicted premature mortality by 2030 for Brazil and regions, compared with the SDG 3.4 target and identify regional progress and future needs.

Mortality data were extracted from the National Mortality Information System of Brazil (SIM) and subsequently corrected for ill-defined causes. Crude and age-standardized mortality rates per 100,000 inhabitants were calculated. NordPred package by software R was used to calculate predictions up to 2030 and compared with the goal of one-third reduction of premature deaths.

Comparison of observed (2011–2015) and predicted (2026–2030) mortality rates show a 12.0% reduction in the likelihood of death among men and 4.6 percent among women nationally. Although predicted rates for 2026–2030 are lower than those observed in 2011–2015, the predicted number of deaths increases by 75,341 for men and 90,513 for women. Lung cancer mortality rates are predicted to decrease more among men than women, while colorectal cancer mortality will increase for both sexes.

The profile of cancer premature mortality is diverse in Brazil. Nationally, only male lung cancer will be close to reaching the SDG 3.4 target, endorsing the government's long-term efforts to reduce tobacco consumption. Colorectal cancer mortality increases in most regions, reflecting the epidemiological transition. Despite progress in cervical cancer control, it will continue to be a major challenge, especially in the North and Northeast. Our results provide a baseline for public policies for both prevention and access to treatment to reduce premature mortality in Brazil. Differences in cancer patterns show the need to plan and to adapt regionally for each reality.

Both patient composition and medical care received in clinical trials may not be representative of clinical practice, yet health technology assessments (HTAs) commonly use extrapolation results from trials to estimate incremental benefit. Due to data limitations, external validation of trial extrapolations are uncommon. With the goal of better estimating the benefit of new therapies in practice, we compared long-term survival estimated from real-world patients who received therapy similar to the comparator arm of the OAK trial, a phase III study of patients with advanced non-small cell lung cancer (aNSCLC) who progressed following initial chemotherapy, to standard estimation approaches.

We estimated long-term survival from: (i) direct extrapolation of trial survival curves; and (ii) aNSCLC patients from the United States Flatiron Health Electronic Health Record ()-derived de-identified database diagnosed between January 2011 and August 2019 who received docetaxel monotherapy after platinum-doublet and had adequate organ function as well as functional status. Patients with unknown organ function and functional status were also included. Standard parametric extrapolations were applied and selected based on visual inspection and goodness-of-fit tests for each cohort.

Using a log-logistic model to extrapolate the trial comparator arm (N = 425), estimated lifetime mean overall survival was 19.2 months (95% confidence interval [95% CI]: 16.5–22.6), and 14.4 months (95% CI: 12.4–17.0) for the real-world cohort (N = 415). Estimated 5-year overall survival rates were 5.4 percent (95% CI: 3.9–7.3) for the trial patients, compared to 3.7 percent (95% CI: 2.6–5.0) among real-world cohort patients.

Our results suggest that directly extrapolating observed survival for trial patients may overestimate the long-term survival compared to the experience of patients treated in routine practice. Our findings have implications for those wishing to estimate the incremental benefit for novel versus established treatments. We plan to compare our results to a generic patient cohort from national cancer registry. Further EHR-based studies utilizing real world data are needed to confirm our findings and to extend beyond this use case for other cancer types and anti-neoplastic therapies.

Early death from cancer is potentially preventable. In developing countries, it is not only a human tragedy but also an economic tragedy. In Latin America and the Caribbean, the estimated number of deaths for people 15–64 years in 2018 was 262,141, with Brazil being the country with the largest number of cases in the region (38.2%). The mortality rate for cancer in Brazil was 68.7/100,000. The analysis of causes impacting premature mortality is an essential function of public health surveillance. This study aims to estimate Potential Productive Life Years of Lost (YPPLL) due to cancer from 2000 to 2016, according to the region, sex and cancer site.

Official data from the Brazilian government were used for the period 2000–2016 for the 15–64 age group (economically active population). For each cancer death in working-age people, potential years of productive life lost (YPPLL) were calculated as the difference between pensionable age and age at death from cancer (based on the age group mid-point). The limit considered as pensionable age was 65 years for men and 60 years for women.

The total of cancer deaths among working-age people was 61,547 in 2000 and increased to 93,551 in 2016. The correspondent YPPLL was 717,883 and 944,565, respectively (increase of 31.6%), mostly coming from males (56.8%). Highest individual YPPLL were observed in the North and Northeast and Midwest, for both sexes. The most substantial changes observed from 2000 to 2016 in total YPPLL were for colorectal cancer, which moved from sixth to the second position nationally.

The YPPLL due to cancer is increasing in Brazil and present different patterns by sex and geographic regions. While in the South and Southeast lung cancer has the highest impact among males, in the North and Northeast most YPPLL come from stomach cancer. Among females, a clear pattern is observed with breast cancer being responsible for most YPPLL excepting in the North, where cervical cancer still having a major impact compared to other tumors.

Omics technologies enable the measurements of genes (genomics), mRNA (transcriptomics), proteins (proteomics) and metabolites (metabolomics) and thus proved to be valuable tools for personalized decision-making in clinical practice. For their evaluation, a health technology assessment (HTA) framework is not standardized and accepted, yet. Therefore, we aim at designing an omics-technologies HTA evaluation framework to facilitate their assessment, through a mixed-method approach. This work is part of the ExACT project, which aims to produce a range of tools to facilitate the implementation of precision health in clinical practice.

A systematic review was conducted to identify the existing HTA frameworks used for the evaluation of omics-technologies. Desk research on the HTA agencies’ websites was performed to identify the reports on omics-technologies HTA evaluation frameworks used by these agencies. A questionnaire evaluating HTA agencies’ experience on evaluation of omics-technologies was designed. The new framework will be elaborated based on the findings from the three methodological steps, and will be validated through a Delphi process.

Twenty-three articles were included in the systematic review. The main identified HTA frameworks were ACCE and “Evaluation of Genomic Applications in Practice and Prevention” (EGAPP). The desk research showed that these frameworks were seldom used by HTA agencies, which for the evaluation of omics-technologies mostly refer to the HTA Core Model®, mainly assessing the following domains: clinical effectiveness and economic evaluation. Data collection process of the questionnaire HTA agencies’ experience is in progress.

Although two main HTA frameworks for the evaluation of omics-technologies have been identified, these frameworks are sporadically used by HTA agencies in their practice. The particular interest of HTA agencies on clinical effectiveness and economic evaluation, might potentially reflect the uncertainty and difficulties when evaluating omics-technologies. This could indicate that these HTA frameworks are not feasible and practical to be used in routine HTA agency processes for omics technologies, emphasizing the need for a new framework. Our methodological approach might contribute to the development of a new HTA framework, feasible and practical to use not only for HTA agencies.

In Canada, individuals test for HIV commonly through clinic-based screening services (CBSS). However, gay, bisexual and other men who have sex with men (GBMSM) may face barriers accessing such services due to, for example, feeling discomfort disclosing their sexual history or fearing judgment from healthcare providers. To reduce barriers and increase uptake and frequency of screening for sexually-transmitted infections (STIs) including HIV, the British Columbia Centre for Disease Control implemented an internet-based screening service, GetCheckedOnline.com (GCO), in September 2014 in Vancouver, Canada. We assessed the cost-effectiveness of GCO at different uptake scenarios compared to CBSS in Vancouver GBMSM.

Cost-utility analyses were conducted from a healthcare payer's perspective using an established dynamic GBMSM HIV compartmental model. The model estimated the probability of becoming infected with HIV, progressing through diagnosis, disease stages, and treatment over a 30-year time horizon. The base case assumed 4.7 percent uptake of GCO, and 74 percent of high-risk and 44 percent of low-risk infrequent testers becoming regular testers in five years. Scenario analyses tested GCO 10 and 15 percent uptakes.

Compared with the conventional CBSS alone, a 4.7 percent GCO uptake increased the costs by CAD90,059 (USD75,680; 95% confidence interval (CI): -CAD420,836, CAD273,987) and gained 3 (95% CI: 0, 6) quality-adjusted life years (QALYs) in a 30-year time horizon. There was a 71 percent probability that GCO was cost-effective at a cost-effectiveness threshold of CAD50,000 (USD42,000) per QALY. The results were consistent in other two uptake scenarios.

Expanding HIV screening for GBMSM through increasing uptake of GCO is a cost-effective alternative to expanding the conventional CBSS. We noted that difference in total costs might be smaller if a battery of STI tests is considered, which in turn may affect our cost-effectiveness estimate. For the next phase of cost-utility analysis, we will expand our model to include testing for other STIs.

Demonstrating the value of medicines through health technology assessment (HTA) systems is becoming increasingly complex. Innovative therapies – such as immuno-oncology (IO) agents – are testing limits of methodological approaches in markets with established HTA systems. The objective of this study is to understand how requirements, approaches, and decision-making differ between select HTA agencies with a focus on specific PD-1/PD-L1 (programmed death receptor-1/programmed death-ligand 1) agents and cancer indications, and to describe how this variation impacts patient access. To achieve this objective, we conducted a detailed HTA dossier review for several recently launched IO products across Australia (AU), Canada (CA), France (FR), and the United Kingdom (UK).

Content experts reviewed HTA dossiers for pembrolizumab, nivolumab, and atezolizumab for non-small cell lung cancer (NSCLC) first-line monotherapy, NSCLC combination therapy, and adjuvant melanoma. A systematic analytic framework was developed to understand best-practice methodology across systems. Information on submitted data, patient/expert input, and access decisions were extracted; key themes were identified and refined through workshop discussion, and probed further through blinded primary research with eight individuals with current or recent experience of HTA systems.

We identified six major elements of variation impacting decision-making: evidentiary expectations for biomarkers, use/impact of patient-centered data; use/impact of real-world data, acceptance of surrogate endpoints, approaches for clinical data extrapolation, and accepted time horizons. Considerable variation in time to access was observed; for pembrolizumab (NSCLC first-line monotherapy), time from product registration to HTA decision ranged from 42 (CA) to 487 (AU) days; time from registration to listing ranged from 189 (CA) to 605 (AU) days.

Evaluated HTA systems demonstrate a large degree of variability in approaches to decision-making for novel IO medicines; resultant access decisions and time to access are also highly variable. Inconsistency between systems and duplication of effort when assessing similar clinical/economic data could be contributing to limited or delayed patient access; the relationship merits further exploration. Assessed HTA systems are currently undergoing process revisions but expert input suggests that this is not expected to reduce variation, and could further increase complexity. The influence of parallel scientific advice programs between HTA agencies and regulatory bodies in reducing variation must also be determined.

Artificial Intelligence (AI) is an important product of the rapid development of computer technology today. It has a far-reaching impact on the development of medical diagnostic technology especially in combination with medical imaging. The aim of this study was to analyze the diagnostic accuracy of AI-assisted diagnosis technology for classification of benign and malignant lung nodules on Computerized Tomography (CT) images.

A meta-analysis was conducted of published research articles on diagnostic accuracy of AI-assisted diagnosis technology for lung nodules classification between 2010 and 2019 in the databases of PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and China Bio-medicine Database. Statistical analysis was performed with the software SAS 9.4 and Stata 12.0, and the summary receiver operating characteristic (SROC) curve was drawn to evaluate accuracy of the method.

A total of 27 studies with 5,701 lung nodules were considered. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and the area under the curve of SROC for AI-assisted diagnosis technology for lung nodules classification respectively were 0.892 (95% confidence interval [CI]: 0.854–0.920), 0.876 (95% CI: 0.833–0.909), 7.190 (95% CI: 5.194–9.955), 0.124 (95% CI: 0.089–0.171), 58.102 (95% CI: 32.391–104.219) and 0.95 (95%CI: 0.92–0.96).

Of note, several limitations should be considered when interpreting the findings of this meta-analysis. Data acquisition is not comprehensive enough because the language of the literature search was limited to Chinese and English. Furthermore,heterogeneity caused due to the difference of lung nodule size affected the study results. Despite these limitations, our study suggests that AI-assisted diagnosis technology for benign-malignant lung nodule classification on CT images obtains high diagnostic accuracy, and it can be used as a novel method to differentiate benign and malignant pulmonary nodules.

Quantitative flow ratio (QFR) is a novel approach to derive fractional flow reserve (FFR) from coronary angiography. QFR based on 3-dimensional reconstruction of angiographic images assesses the significance of coronary artery disease (CAD) without using an invasive pressure wire. This study aimed to evaluate the diagnostic accuracy of quantitative flow ratio in myocardial ischemia of coronary artery disease.

A meta-analysis was conducted of published research articles on diagnostic accuracy of QFR between January 2016 and September 2019 in the databases of PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and China Bio-medicine Database. Statistical analysis was performed with software Meta-Disc 1.4 and Stata 12.0, and the summary receiver operating characteristic (SROC) curve was drawn to evaluate accuracy of the method.

A total of 11 articles were retreived, including 1,782 patients and 2,054 vessels. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio for quantitative flow ratio respectively, were 0.86 (95% confidence interval [CI]: 0.85-0.89), 0.89 (95%CI: 0.87–0.91), 7.51(95%CI: 6.40–8.82), 0.15 (95%CI: 0.10–0.23), 54.18 (95%CI: 34.09–86.12), and the pooled AUC was 0.9458.

Several limitations should be considered when interpreting the findings of this meta-analysis. First, despite the extensive literature search, the number of included studies was small; however, the number of patients and vessels enrolled was satisfactory, thereby decreasing type II error. Furthermore, data acquisition is not comprehensive enough because the language of the literature search was limited to Chinese and English. Despite these limitations, our study suggests with a definition of ischemia as FFR ≤ 0.8, the QFR obtains high diagnostic efficacy in myocardial ischemia of CAD. It can be used as a non-invasive novel method to screen CAD patients with myocardial ischemia.

Artificial Intelligence (AI) is an important product of the rapid development of computer technology today. It has a far-reaching impact on the development of medical diagnostic technology especially in combination with medical imaging. The aim of this study was to analyze the diagnostic accuracy of AI-assisted diagnosis technology for classification of breast cancer in histopathological images.

A meta-analysis was conducted of published research articles on diagnostic accuracy of AI-assisted diagnosis technology for breast cancer classification between January 2010 and September 2019 in the databases of PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and China Bio-medicine Database. Statistical analysis was performed with software Meta-Disc 1.4 and Stata 12.0, and the summary receiver operating characteristic (SROC) curve was drawn to evaluate accuracy of the method.

A total of 18 studies with 13,573 breast histopathological images were considered for the analysis. The pooled sensitivity, specificity, diagnostic odds ratio and the area under the curve of the SROC for AI-assisted diagnosis technology for classification of breast cancer respectively, were 0.94 (95% confidence interval [CI]: 0.93–0.85), 0.84 (95% CI: 0.93–0.94), 255.47 (95% CI: 168.33–387.73) and 0.98 (95%CI: 0.96–0.99).

Several limitations should be considered when interpreting the findings of this meta-analysis. First, despite the extensive literature search, the number of included studies was small; however, the number of images enrolled was satisfactory, thereby decreasing type II error. Second, data acquisition is not comprehensive enough because the language of literature search was limited to Chinese and English. Furthermore, the heterogeneity caused due to different sources of data affected the study results. Despite these limitations, our study suggests AI-assisted diagnosis technology for breast cancer classification in histopathological images is a highly accurate and reliable diagnostic method for clinical application.

The Italian National Agency for Regional Health Services (AGENAS) participation in the European network (EUnetHTA) allowed capacity building and the spread of knowledge, tools and methodologies built by the network. In the latest Joint Action, AGENAS is implementing both EUnetHTA tools/methdologies and assessments. This was done both by the “adaptation” of most relevant EunetHTA assessments to Italian context or by “traslation” of EUnetHTA assessments’ Summeries. Language barriers have been highlighted from local HTA partners who aknowledged that contents written in italian could have a higher potential for dissemination.

To adapt a EUnetHTA report we evaluate if the PICOD fits our context with clinicians and stakeholders. We thus update systematic review and/or add other context specific domains. The EUnetHTA report summaries were translated into Italian and reviwed by clinicians. The HTA Core Model® was incorporated into national processes (Procedure Manual, HTA report templates, assessment elements, the Planned and On going Projects (POP) database was also used.

Implementation of EUnetHTA's tools and products consisted of i) Production of national assessment reports based on EUnetHTA assessments; ii) Dissemination of EUnetHTA assessment iii) Translation of EUnetHTA assessments summaries and publication on Agenas website iv) Use of EUnetHTA POP Database for the national HTA programme; v) Embedment Integration of the EUnetHTA HTA Core Model®

The use of the Core Model® allowed a better standardisation of AGENAS' outputs. The Assessement Element based structure assists authors with the choices of relevant research questions; and the Domain-based structure allowed an efficient division of work among the authors. The use of the Core Model® among European partners faciliated the adaptation of other national HTA reports to our context. The adaptation and translation of EUneHTA assessments provides more homogenous choices among Italian regions and European countries, and so does the use of the POP database as a source of information about technologies that are on other EU Countries agenda.

In the absence of direct evidence from randomized controlled trials (RCTs), real-world evidence (RWE) can play an important role in healthcare decision making. As part of a health technology assessment, we assessed the comparative risk of tuberculosis (TB) associated with using infliximab and etanercept in patients with rheumatoid arthritis.

We performed a systematic literature search using the PubMed database to identify relevant meta-analyses.

We located two relevant meta-analyses: one based on RCTs and one based on observational studies. Evidence from seven RCTs on infliximab (2,686 patients; 12 TB events) and two RCTs on etanercept (663 patients; 2 TB events) suggested no significant differences in the risk of TB between the two treatments, compared with placebo. In contrast, evidence from ten observational studies that directly compared the two treatments (443,941 patients; 253 TB events) indicated a significantly higher risk of TB with infliximab than with etanercept.

Although RWE is prone to confounding and bias, in this case it had the advantage of providing direct comparisons with larger sample sizes and longer follow up than evidence from RCTs. As a result, RWE was used to inform decision making on the risk of TB with infliximab and etanercept in patients with rheumatoid arthritis.