The integrated patient-centered, evidence-based approach to care recognizes the role of patient preferences. A discrete choice experiment (DCE) was developed with the aim of identifying the preferences of men with prostate cancer in Italy regarding the different risk-benefit factors of various treatment options.

The DCE was developed with the support of prostate cancer patients and oncologists and was based on a targeted scoping review. The final DCE included 26 choice sets divided into two blocks. The first block focused on all prostate cancer patients (both metastatic and non-metastatic), while the second block aimed to assess preferences for patients with metastatic hormone-sensitive prostate cancer (mHSPC). Patients were asked to choose from ten attributes in the first block and six in the second block. The aim was to identify attributes and levels with a statistically significant impact on patient preferences. Preference estimates were calculated using a conditional logit regression model and the results were stratified by cancer stage (metastatic or non-metastatic) in the first block.

A total of 202 patients (mean age 72 years) completed the DCE. In the first block, the most important attribute was quality of life (QoL), particularly for patients with metastatic cancer. The other three attributes found to be significant, in order of relevance to patients, were the risks of experiencing cognitive impairment, hematologic complications, and fatigue. For patients with mHSPC, QoL was the strongest determinant of preference. The risk of experiencing fatigue was also a relevant attribute, followed by skin irritation.

This study shows that the effect of treatment on QoL was the most important attribute for patients diagnosed with prostate cancer. Specific risk factors play a different role in the choice of treatment depending on cancer type, with the risk of experiencing fatigue being valued by all groups. Identifying and understanding patients’ preferences related to treatments for prostate cancer will help physicians identify the best treatment strategy.

It is estimated that approximately 1.1 million cases of prostate cancer (PCa) are diagnosed in the world every year. In general, PCa is a slow-onset cancer and less than 10 percent of cases are detected in the metastatic phase. In order to identify patients at risk of suffering from clinically significant prostate cancer (csPCa), as well as to avoid unnecessary biopsies, overdiagnosis and overtreatment, a variety of molecular biomarker detection tests have been developed.

We undertook a systematic review with meta-analyses on the effectiveness of diagnostic tests based on biomarkers in blood or urine samples for the identification of men at risk of csPCa. A cost-effectiveness analysis was conducted using a decision tree model for the short term and a Markov model for the long term, both from the social and the National Health System perspectives. The effectiveness measure was quality-adjusted life years (QALYs). We ran extensive sensitivity analyses, including a probabilistic sensitivity analysis.

Sixty-five studies were included with a total of 34,287 participants. The diagnostic tests analyzed were: PHI, Progensa® PCA3, SelectMDx, MyProstateScore, 4Kscore®, TMPRSS2: ERG, Stockholm3, ExoDx Prostate IntelliScore and Proclarix®. All studies included biopsy as comparator. The sensitivity and specificity of diagnostic tests depended on the test itself and the threshold chosen, and ranged from 42 percent to 99 percent and from 13 percent to 87 percent, respectively. In the cost-effectiveness analysis, the alternative that includes the biomarker, specifically the SelectMDx, led to higher QALYs and healthcare costs with an estimated incremental cost-effectiveness ratio (ICER) of 6,640.21 EUR per QALY. The sensitivity analyses confirmed that the results were robust.

Biomarker testing to select men at risk of csPCa who should undergo prostate biopsy can be a cost-effective strategy depending on its cost per determination and its sensitivity/specificity. The analyses carried out indicate that the SelectMDx biomarker is cost-effective at a cost of EUR 375 per determination.

Next-generation sequencing (NGS) can be run in-house or outsourced to an independent laboratory. It has enabled wider use of deoxyribonucleic acid/ribonucleic acid (DNA + RNA) sequencing in clinical practice. Within oncology, NGS has paved the way for more effective treatment, including personalized medicine. There are, however, large variations in access and reimbursement across Europe. The aim is to understand the European NGS landscape and barriers to access.

Structured telephone interviews covered topics on NGS perception, guidelines, use-cases, benefits, costs, and future expectations. Twelve experts per country (France, Germany, Italy, Spain): two payers, five oncologists, and five pathologists were interviewed between June and August 2021. Responses were translated into English for qualitative analysis.

NGS was considered most useful when there were approved, targeted treatments. Although often noted that there was a lack of published evidence to support a beneficial link, respondents perceived that NGS has the potential to improve patient quality of life (QoL) and reduce resource use through avoiding suboptimal treatment. All of the payer respondents expected the role of NGS to increase, though it may be held back by lack of reimbursement. Respondents favored in-house NGS over outsourcing in terms of clinical benefit: “Advantages of in-house NGS are turnaround time, results and lean processes” … “you build the expertise in-house. If you have urgent samples, it’s easy to prioritize them”. Reasons for not having in-house NGS included “costs, lack of personnel. Basically, organizational and financial issues.” In-house NGS was perceived to be associated with high setup-costs (acquisition, setup, training), but lower running costs (per-test costs). There was a view that in-house solutions are mainly suitable in larger centers undertaking many tests.

NGS can save costs and provide QoL benefit through enabling optimized, personalized therapy, but published evidence establishing the outcomes link is lacking. From the hospital perspective, investing in NGS requires understanding the cost of NGS over its entire lifecycle, likely entailing a health-technology assessment including health-economic analysis.

Pelvic floor diseases (PFD) often affect the adult population, with approximately 50 percent of women aged 50 years and older suffering from PFD. The condition has complex symptoms that may lead to stress and a negative impact on the quality of life. The USA spends about USD 1 billion annually on inpatient costs as a result of more than 700,000 emergency department visits and 50,000 hospitalizations associated with PFD. Defecography is currently the most commonly used method of diagnostic imaging used to evaluate PFD. This technology is not available in the Republic of Kazakhstan, despite its high diagnostic value.

In order to assess the clinical effectiveness of defecography, we have conducted a literature search in the MEDLINE database. We selected articles with pairwise comparisons of defecography with other tests: anorectal manometry; balloon expulsion test; electromyography; magnetic resonance imaging (MRI); and, ultrasound.

The findings are primarily based on two meta-analysis (91 studies representing 10,768 cases). The results have been evaluated according to the detection frequency and omission of the following signs: cystocele, middle compartment descent, rectocele, intussusception, rectal prolapse, enterocele, and perineal descent. The literature review did not reveal significant difference in diagnostic value between MR defecography and defecography based on X-ray. However, the imaging endpoints (detection rate of structural and functional abnormalities) for defecography based on X-ray were significantly better than plain radiography.

The defecography is currently considered the gold standard and the most commonly used tool of diagnosis. The implementation does not require an expensive equipment purchase (MR defecography) and is reproducible on conventional X-ray equipment if the necessary inventory is available.

Osteoarthritis (OA) is a heterogeneous group of diseases of various etiologies based on the defeat of all components of the joint. OA is one of the main causes of disability in older people. To date, joint replacement is the most clinical and cost-effective method of the terminal stage treatment. The short and long-term success of total joint replacement is closely related to the accuracy of the prosthesis implantation. Published studies show that the accuracy of prosthesis implantation can be intraoperatively controlled by computed navigation and robotic systems better than by traditional methods.

In order to assess the clinical effectiveness of the technologies, we have conducted a literature search in the MEDLINE database. We included studies that reported a comparison of outcomes between conventional methods, computer navigation and robot-assisted surgery.

The results of this literature review are based on six systematic reviews with meta-analyses (101 studies representing 482,367 cases) and one national joint replacement registry. The outcomes compared included Knee Society Score (KSS)-function, alignment correction, mechanical axis (varus and vagus deviance >3°), prosthesis positioning, soft tissues balancing and functional outcomes. Thus, the cumulative success rate in the computed navigation and robotic systems group was reported to be 86.7 percent, which is crucial considering its lowered rate of revision (3%), correct mechanical axis (≤3%) and functional status.

The literature review demonstrates a high potential of the computed navigation and robotics systems in the intraoperative monitoring of important surgical parameters for achieving the best intervention outcomes. All the clinical endpoints were significantly better by comparison with conventional method.

Risk prediction models, using either machine learning or statistical algorithms, can act as inputs of a cost-effectiveness model when predicting costs and effectiveness of an intervention. This systematic review has two objectives: to evaluate methodological quality of the published models to predict diabetic coronary heart disease (CHD) risk; to evaluate whether the models were sufficiently reported to judge their applicability to the cost-effectiveness modelling.

A targeted review of journal articles published in English, Dutch, Chinese, or Spanish was undertaken in PubMed, Embase, Scopus, Web of Science, and IEEE Explore from 1 January, 2016 to 31 May, 2021. To assess the methodological quality and reporting of the models, we used PROBAST (Prediction model Risk Of Bias Assessment Tool), CHARMS (a Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies), and a checklist (Betts 2019) summarizing the application of cardiovascular risk prediction models to health technology assessment.

Our search retrieved 6,579 hits, of which 18 models were eligible for inclusion. Among them, four studies developed machine learning models (2 recurrent neural networks, 1 random forest models, and 1 multi-task learning model) while 14 studies developed statistical models (8 Cox models, 5 logistic models, and 1 microsimulation model). More than 70 percent of models were of high methodological quality in aspects of participants (89%), predictors (72%), and outcomes (72%), while only five models (28%) in aspects of statistical analysis. For the reporting, only two models provided sufficient evidence in all aspects (i.e., participants, predictors, and outcomes) for judging their applicability to the cost-effectiveness modelling. Most models were reported sufficiently regarding participants (78%) and outcomes (72%), but only three models regarding predictors (17%).

To apply the CHD risk prediction models to cost-effectiveness modelling, concerns remain regarding the potential risk of bias due to inappropriate use of analysis methods, and regarding insufficient reporting on how to measure and assess the predictors.

In 2019, the German government established a new evaluation procedure for digital health applications (DiGAs) to facilitate their reimbursement by statutory health insurance. The procedure involves the assessment of a DiGA’s “positive healthcare effect”, which is defined as a medical benefit and/or “a patient-relevant improvement of structure and processes”. If the available clinical evidence is insufficient to prove the manufacturer’s claim on the positive healthcare effect, but the claim seems plausible, the DiGA is provisionally reimbursed, and further clinical evidence within twelve months must be generated. DiGAs eligible for provisional or permanent reimbursement are publicly listed in the DiGA directory.

In contrast to the usual pathways for reimbursement of healthcare technologies which involve IQWiG as the national HTA agency and the G-BA (Federal Joint Committee) as the decision-making body, the DiGA procedure is currently carried out by the national competent authority (BfArM) and thus outside the joint self-government. Furthermore, legal evidence requirements for DiGAs are comparatively low.

This work analyzed the suitability of clinical studies that intended to prove a DiGA’s medical benefit. For this purpose, the key elements for clinical studies published in the DiGA directory and clinical trial registries were extracted and compared with the usual evidence requirements in the reimbursement context.

As of October 2020, 20 DiGAs have successfully undergone the application procedure. Fourteen DiGAs (70%) were provisionally accepted. A randomized controlled study (RCT) design was chosen for all clinical studies to be conducted for further evidence generation. However, in four cases (28%), it is questionable whether the clinical study is suitable to demonstrate a medical benefit mainly due to the choice or operationalization of the primary endpoint (n=2), the timing of the endpoint survey (n=2) and/or the choice of the control intervention (n=1).

Even though all currently ongoing or planned clinical studies with DiGAs are RCTs, not all of them are adequate to demonstrate a medical benefit according to the usual evidence requirements.

The use of mobile applications in the treatment of health issues is more frequently becoming common practice. Apps are fast, versatile, and manageable tools that allow the empowerment of patients and professionals, and can reduce the possible stigmatization suffered by some patients, mainly in mental health. There are more than 325,000 health apps on the market, but their impact remains unclear. There are several initiatives to define how health applications should be assessed, however, all of them address only partial aspects of the evaluation. The theoretical frameworks existing to date highlight the need to develop new tools and methodologies to assess mobile applications whose objective is the management of specific pathologies.

The primary goal of the EvalDepApps project is to develop and pilot an assessment tool for mobile applications whose main objectives are the treatment, monitoring or social support of people suffering from depression. The project is inspired by the results and lessons learnt from a previous project, EVALAPPS, whose central aim was to develop a tool to assess health apps targeted toward the management of overweight and obesity. The first steps of the EvalDepApps project are: (i) to explore and characterize the current landscape of mobile applications available in the market to treat depression through a systematic appraisal, and (ii) to review the existing evidence about the effectiveness and safety of these applications through systematic research of the existing evidence.

Preliminary results show that all the depression management studies were by design based on cognitive-behavioral therapy (CBT) interventions (n=17) and the main management tools included in the services (web or apps) are psychoeducation and coaching (14), together with self-monitoring and feedback messaging (13).

Moreover, although health apps seem to be an interesting strategy to treat depression, there are very few apps available on the markets (30) and the supporting evidence is very limited. This result uncovers a need for further systematic and clinically oriented validation and testing of such apps.

In the context of the COVID-19 pandemic, which required urgent responses from health systems, and ongoing decision making in a context of limited and evolving evidence, modeling played a significant role in supporting public policy making. Nonetheless, particularly in low and middle-income countries, modeling groups are scarce, and usually not routinely involved in supporting public health policy making. We aimed to appraise COVID-19 modeling work in Brazil during the pandemic.

We performed a scoping review following PRISMA guidelines to identify groups conducting COVID-19 modeling to support health decision-making in Brazil. Search strategies were applied to MEDLINE, LILACS, Embase, ArXiv, and also included National data repositories and gray literature. We excluded reports of models without modeling results. Titles, abstracts, data repository descriptions and full-text articles identified were read and selected by two reviewers. Data extracted included modeling questions, model characteristics (structure, type, and programming), epidemiologic data sources, main outcomes reported, and parameters. To further identify modeling groups that might have not yet published results, snowball sampling was performed, and a short survey was sent electronically. Investigators and policymakers were invited to an online interview, to obtain further information on how they interacted, communicated, and used modeling results.

We retrieved 1,061 references. After removing duplicates (127), 1,016 abstracts and titles were screened. From an initial selection of 142 abstracts, 133 research groups were identified, of which 67 didn’t meet the eligibility criteria. Of these, 66 groups were invited for an interview, of which 24 were available, including 18 modeling groups from academic institutions, and four groups from State Health departments. Most models assessed the impact of mitigation measures in cases/hospitalization/deaths and healthcare service demand. Interaction and communication with decision-makers were not well established in most groups.

Despite a large number of modeling groups in Brazil, we observed a significant gap in modeling demand and communicating its results to support the decision-making process during the COVID-19 pandemic.

Scottish Medicine Consortium (SMC) meetings were suspended in March 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic. This led to a high number of submissions awaiting appraisal, prompting interim process changes to ensure minimal disadvantages to patient access. We expanded the eligibility criteria for the shorter (abbreviated) submissions process and expedited advice for submissions the New Drugs Committee (NDC) intended to accept. This study aimed to evaluate the impact of the COVID-19 pandemic and these interim process changes on the characteristics of submissions received, acceptance rates, and time to advice publication.

Data for all submissions received between January 2015 and November 2021 (n=720) were extracted from an organizational database. Characteristics of and acceptance rates for submissions received before and after the start of the pandemic were compared using chi-squared and one-proportion Z-tests, respectively. Additional analyses explored the number of submissions received per month and the time from receipt of submission to NDC and SMC decision.

The numbers of full and abbreviated submissions increased from March 2020 (6% in each case), with a corresponding decrease in the number of medicine-indication pairs (e.g., pembrolizumab for breast cancer) for which companies did not submit (8%; p=0.01). An increase in the SMC acceptance rate was also observed (62 to 72%; p=0.03). Fewer submissions were received in 2020 (n=65), compared with the pre-pandemic average (mean=79.6), whereas the total in 2021 to date was higher than average (n=92). Time series analysis suggested an increasing trend in monthly submissions (from approximately 6 to 9), which is the likely reason for the increase in average time to decision (146 versus 170 days).

Process changes in response to the pandemic have been effective in expediting advice for submissions with sufficiently robust evidence. This demonstrates agility and efficiencies for submitting companies and patient groups, with no perceived impact on process rigor. The average number of submissions has increased since March 2020, and further work is warranted to understand the influence of process improvements on reducing time to advice.

Health Technology Assessment (HTA) Process assists decision-making in health policies. The COVID-19 pandemic caused a high demand on protocol or guideline updates and incorporation of new drugs or therapies, overwhelming local agencies. A recent study reported that major HTA bodies in England, Scotland, Germany, and Canada reduced their number of drug recommendations in 2020, due to reprioritization of resources and COVID-related challenges. The present study aimed to evaluate the impact of the COVID-19 pandemic at the Brazilian National Committee for Health Technology Incorporation (Conitec) recommendation process.

This descriptive study evaluated all official recommendation reports available on the Government website in 2020 and 2021, extracting the data of disease category, technology type, the aim of the report, Public Involvement, and final result for the recommendation. The results were presented in tabular and graphical form using the machine learning, through the software R studio and excel.

A total of 168 documents were evaluated, including guidelines and recommendation reports, with no reduction in the number of evaluations considering 2019. In 2020, there was a more significant evaluation of guidelines, and in 2021, a report on the non-incorporation of technologies. There were four specific documents about COVID 19, including vaccines and hospital care guidelines. The most incorporated and non-incorporated technologies were medication, targeting rare and highly prevalent diseases in balance. The Brazilian government was the main proposer. These results are part of the study “A Survey about the core methods of the recommendation reports for Brazilian Ministry of Health carried out by Brazilian Health Technology Assessment Centers”, which will characterize and analyze the core methods of the recommendation reports conducted by the Brazilian HTA Centers.

The pandemic had a low impact on demands in the routine of the Conitec. Establish indicators and technological norms applicable to health services, contribute to the identification of possible new practices, methods or criteria.

Diabetic Macular Edema (DME) is an important complication of Diabetic Retinopathy (DR). Intravitreal steroids in slow-release systems represent a safe and effective therapeutic option for the management of DME, capable of improving patients’ quality of life by reducing the number of injections thus increasing the therapeutic adherence and the effectiveness of the treatment. This study aims to determine the economic impact of DME and the consequences, in terms of both expenditure and organizational impact, associated with a greater use of the intravitreal dexamethasone implant.

The analysis entailed the comparison between two scenarios: a first scenario based on the current use of therapeutic alternatives available in the Italian healthcare setting (as is) and an alternative scenario based on the assumption of an increased use of intravitreal dexamethasone implant (to be). The results of the analysis are expressed in terms of resource absorption associated with the two scenarios as well as in terms of the cost differential given by their comparison.

Despite an increase in expenditure in terms of acquisition costs of pharmacological alternatives (EUR 898,362) and interventions provided (EUR 22,093,160), the greater use of prolonged-release dexamethasone allows for significant savings in terms of healthcare professionals’ time, follow-up and productivity losses incurred by patient/caregiver. These reductions in healthcare costs resulted in a saving of EUR 1,987,678 over a 5-year period. Such a reduction would allow, considering a total annual management cost of EUR 6,115 for the intravitreal dexamethasone, to treat 325 more patients at the same cost of the as is scenario based on the current rate of use of dexamethasone.

In a context characterized by the need to increase the allocative efficiency of economic resources, the recourse to therapeutic alternatives, such as prolonged release dexamethasone, allowing the reduction of costs for the management of a given pathology is crucial to generate more value for patients and the entire society.

In many low- and middle-income countries scarcity of local data on health outcomes and health-related quality of life (HRQoL) is a hindrance to conducting cost-effectiveness analyses. The Tunisian National Authority for Accreditation and Assessment in Healthcare (INEAS) developed a set of methodological guidelines to support pharmaceutical companies in the submission of health technology assessment (HTA) dossiers. The guidelines include INEAS’ methodological choices for pharmacoeconomic analysis, which take into consideration the specificities and constraints of the Tunisian context. We aimed to present the principal recommendations of the Tunisian guidelines for pharmacoeconomic studies, with a focus on patient-reported outcome and HRQoL measurement.

The INEAS pharmacoeconomic analysis guidelines were reviewed and the recommendations regarding outcome measurement and HRQoL were retrieved and reported.

To populate the economic model, INEAS recommends using the best available evidence. Health outcomes should be measured in terms of life-years gained and quality-adjusted life-years (QALYs); disability-adjusted life-years can be used but are not the preferred method. To estimate QALYs, INEAS favors the indirect measure of patient preferences with a validated measurement instrument. Alternatively, other measures of utility may be used, including those identified through a systematic review of the scientific literature and the publications of other HTA agencies. Justification and details of the source of the data must be provided. The utility values selected should be recent and representative of the Tunisian population, as far as possible. The guidelines refer to a set of generic preference-based HRQoL instruments, including the EuroQol five-dimensions (EQ5D), the Health Utilities Index Mark 2 (HUI2) and Mark 3 (HUI3), and the Short-Form Six-Dimension (SF-6D), but do not provide any explicit recommendations on their use.

The INEAS pharmacoeconomic analysis guidelines adhere to international best practices but provide more flexibility for overcoming the lack of local data. The INEAS economic guidelines constitutes a further milestone in the process of implementing HTA in Tunisia and in the Middle Eastern and African regions.

Patients treated with immunotherapy are divided into two subgroups: (i) long-term survivors (LTS) and (ii) moderate survivors. Nevertheless, clinical trials (RCTs) report only average treatment effects such as hazard rate (HRs). Health economic-models often only input average treatment effects, even though it has been shown that accounting for the LTS subgroup is crucial for accurate projection of long-term survival under immunotherapy. We investigated the incorporation of a statistical mixture cure model (MCM) in a health-economic model for lung cancer as a way to account for LTS while incorporating reported average RCT-based treatment effects.

We developed a microsimulation model describing disease progression under three treatment lines in advanced lung cancer using Dutch real-world data of chemotherapies treated patients. Here we focus on first-line treatment, for which we used gompertz distribution to simulate time-to-progression. To simulate the impact of immunotherapy, we adjusted base-model assuming MCM for first-line treatment, where the LTS subgroup was not at risk to progress, but instead die from background mortality. The subgroup of moderate survivors on the other hand are at risk to progress with adjusted progression-free HR (PF-HR). We simulated the model with size of LTS (prop_LTS) ranging from 14-34 percent (keynote-001 five-year overall survival [OS], 95% confidence interval) while fixing average RCT PF-HR at 0.5. Model predictions under the different prop_LTS were compared to real-world Dutch OS as well as the long-term RCT five-year OS.

With respect to observed short-term survival outcomes, model predictions were insensitive to assumptions regarding the size of the LTS subgroup. However, to match the five-year RCT OS rate reported (32%), the prop_LTS had to be equal to 34 percent. Under this latter setting for the prop_LTS, the progression HR in the subgroup of moderate survivors was calibrated to be 1.1.

The use of a mixture cure model improves long-term model-based projections with the implicit assumption that moderate survivors have little or no treatment benefit.

Circulating tumor DNA (ctDNA) is a promising new biomarker with multiple potential applications in cancer care. As part of the “ctDNA on the way to implementation in the Netherlands (COIN)” project, an early, comprehensive Health Technology Assessment (HTA) is ongoing. Information about the costs of ctDNA testing is essential for implementation. Estimating the total cost associated with ctDNA-testing is challenging due to variation in the workflow, wide range in purchase and operational costs of the platforms, and the highly dynamic field. As a first step in the HTA, the aim of this study was to develop a flexible micro-costing framework and open-access model for consistent cost calculation of ctDNA-testing.

First, the complete diagnostic workflow of ctDNA-testing was mapped based on expert discussions. This step-wise workflow was used as the foundation of the framework. Second, the activity-based costing method was used and included costs for personnel, materials, equipment, overhead, housing, and test failures. Third, the framework was validated by experts and by applying the cost calculation model to six case studies.

The diagnostic workflow was mapped from blood sample collection to reporting the diagnostic findings. The framework was developed from a Dutch perspective and takes into account the testing volume. The total cost per sample for the case studies with different workflows and testing volumes ranged from EUR 168 to EUR 7,638.

The developed micro-costing framework can be used to calculate the costs for ctDNA-testing for different workflows. The results from the case studies show the wide range of costs for ctDNA-testing and that the costs are determined by the choice of platform, setting, and testing volume. The open access model allows users to adapt and specify parameters in the diagnostic workflow matching their setting and can be used to support investment decisions and future cost-effectiveness studies.

It is estimated that prostate cancer will reach 66 thousand by the triennium 2020-2022 according to the National Cancer Institute (INCA). After initial diagnosis and staging the patient may undergo radical prostatectomy and/or curative radiotherapy. In patients with biochemical relapse (PSA >0.2 ng/ml) initially treated with radical prostatectomy, salvage external radiotherapy is indicated. The [68Ga] Prostate Specific Membrane Antigen Positron Emission Tomography-Computed Tomography (PSMA PET-CT) scan is mainly used for localization of prostate cancer in the setting of first biochemical recurrence and can significantly influence the clinical management of the patient.

The overall objective of this work is to perform a treatment cost analysis for patients in first biochemical recurrence of prostate cancer after curative radical prostatectomy and after performing [68Ga] PSMA PET-CT from the perspective of the Brazilian Health System (SUS). A decision tree was constructed through consultation with experts to outline the patient’s entire treatment. Values per modelled therapeutic procedure were surveyed in two different scenarios, with and without [68Ga] PSMA PET-CT. The average treatment in scenario 1 was stereotaxic radiation therapy (SBRT), and rescue radiotherapy and androgen deprivation therapy (ADT). In scenario 2, it was salvage radiotherapy and ADT. The reimbursement table was prepared from data collected by SUS system. Variations were analyzed using a sensitivity study. Total average values included: individual procedure, according to medical management (up to 3 years) and population percentage with and without [68Ga] PSMA PET-CT.

Values were calculated in Brazilian currency (BRL) for each procedure. The total amount calculated for scenario 1 was BRL 264,965,465.00 (USD 55,642,747.65) and for scenario 2 was BRL 123,585,612.72 (USD 26,162,978.67).

The reimbursement of line of care adopted after [68Ga] PSMA PET-CT is an important information to expand access to the Brazilian population. It shows an increased cost with [68Ga] PSMA PET-CT adoption. A prospective study should be considered with high follow up.

Migraine, the second leading cause of disability worldwide, remains underdiagnosed and undertreated. Considering the high burden of migraine, we analyzed the strengths and limitations of existing migraine management guidelines.

A targeted literature review was conducted using MEDLINE on 24 March 2021 to identify current migraine management guidelines (including policies and position statements) published in the English language from France, Germany, Italy, Spain, the United Kingdom, and the USA. This was supplemented by a gray literature search. Disease state or pharmacological management guidelines for adults with migraine comprising any of the following perspectives were included: health economics; payer; health technology assessment; treatment access; and impact of guideline implementation on economic or disease burden. Guidelines were analyzed using the Centers for Disease Control and Prevention (CDC) policy analytical framework, which comprises three domains: problem identification, policy analysis, and strategy or policy development, with ranking criteria for each.

Of 39 selected guidelines, 25 adequately identified problems related to migraine, 35 sufficiently reviewed the literature on migraine treatment, three failed to cite literature, and one lacked sufficient content. Twenty-three guidelines targeted healthcare professionals. Almost all guidelines lacked a stepwise migraine treatment approach; only the American Academy of Family Physicians guideline offered first- and second-line treatment options. Four guidelines mentioned current political forces, and coverage of economic or budgetary impact aspects was limited. Numerous guidelines described the substantial economic burden of migraine and were categorized as ‘high’ for benefits. Public health impact was categorized as ‘high’ for 28 guidelines and budgetary impact was rated as ‘more favorable’ for 27 guidelines. Thirteen guidelines defined a strategy for the intended purpose. Only the United States Department of Health and Human Services pain management guideline met all of the CDC criteria.

Future policies on migraine management may benefit from the inclusion of information on economic data, political feasibility, and public health impact. Furthermore, migraine management guidelines could potentially be improved by considering a comprehensive treatment approach and guideline implementation, as well as addressing knowledge gaps in disease state, public health, and economic aspects.

Long-term cocaine use is associated with a wide range of cognitive deficits and neuropsychiatric pathologies. Repetitive transcranial magnetic stimulation (rTMS) is an emerging therapeutic strategy that stimulates the prefrontal cortex and may improve cognitive inhibitory control and decision-making. This systematic review aimed to evaluate and synthesize evidence on the safety, effectiveness, and cost effectiveness of rTMS for the treatment of cocaine addiction.

A systematic review of the literature was carried out. The following electronic databases were searched to identify relevant studies published from inception to October 2020: MEDLINE, Embase, CINAHL, PsycINFO, the Cochrane Central Register of Controlled Trials, and Web of Science. Randomized controlled trials (RCTs), non-randomized controlled trials (nRCTs), case series studies, and full economic evaluations were included.

A total of 12 relevant studies were identified, which included five RCTs, one nRCTs, and six case series studies. None of the studies reported data on cost effectiveness. The results indicated that rTMS reduces cocaine cravings and the number of doses consumed. No serious adverse effects were observed.

The ability to modulate the craving for cocaine in a specific way with non-invasive brain stimulation techniques, such as rTMS, could be a new adjunct to the behavioral treatment of addiction, especially for cocaine use where there is currently no approved pharmacological treatment. Despite the low quality of the included studies, preliminary results indicate that rTMS may reduce cocaine use and cravings. In any case, since this effect is considered moderate, future studies with larger sample sizes and longer follow up are required.

The assessment of current technologies needs a more holistic approach to obtain accurate recommendations for decision-making. The VALues In Doing Assessments of health TEchnologies (VALIDATE) methodology considers that facts and values from all stakeholders need to be included in the scoping of an assessment to gather the comprehensive information needed for unbiased decision-making. This report aimed to explore how to properly assess the integrated care of patients with aortic valve stenosis (AVS) using the VALIDATE approach.

A literature review was conducted, and 11 semi-structured interviews were performed with various hospital-based healthcare professionals (cardiac surgeon, clinical cardiologist, interventional cardiologist, anesthetist, process coordinator nurse, and others) and patients. Content analysis was used for data analysis and integration.

The literature review showed that the cardiology and cardiac surgery perspectives were dominant in 90 percent of the articles and present in the remaining ten percent. The perspectives of other specialties (anesthesiology, primary care, and psychology) were included in three percent of the articles and patient perspectives were included in nine percent. Interviewing and considering the perspectives of the different stakeholders involved in the care pathway identified the following indicators that should be included in the assessment care for patients with AVS: difficulties associated with late diagnosis of AVS; the need to incorporate a multidisciplinary approach in patient risk assessment; the importance of geriatric evaluations; considering patient (and family and caregiver) preferences for type of treatment; the importance of following up pharmaceutical treatment and palliative care; use of telemonitoring; and digital exclusion of patients with respect to the use of apps for prehabilitation and rehabilitation.

The stakeholders interviewed were involved in different steps of the care pathway and had differing needs, some of which were not found in the literature. The indicators suggested for inclusion in the assessment differed according to type of stakeholder and their involvement in the care pathway. Therefore, this case study exemplifies the VALIDATE method and endorses the need for multistakeholder involvement in eliciting values when scoping the assessment of a complex technology.

The reverse transcription polymerase chain reaction (RT-PCR) test is the gold standard for detecting coronavirus disease 2019 (COVID-19), but recent studies have reported false negative results for RT-PCR. Consequently, several countries are looking at chest computed tomography (CT) for the diagnostic workup of patients with suspected or probable COVID-19 to inform clinical management. Therefore, this rapid review provides the best available evidence on the use of chest CT for detecting COVID-19 pneumonia.

Literature searches were conducted in the PubMed, Cochrane Library, JBI Library, Epistemonikos, and Evidence Aid databases for relevant papers published from 1 December 2019 to 12 June 2020. The search strategy was based on the identified population, concept, and context with respect to the objective of the review. The methodological quality of the seven systematic reviews identified was appraised using the AMSTAR checklist.

The use of CT as a first-line screening tool for COVID-19 is not beneficial. Nevertheless, for patients with suspected COVID-19 pneumonia who had a false-negative RT-PCR results, cross-checking with CT and a repeated RT-PCR test is essential to avoid misdiagnosis. Chest CT offered high sensitivity for detecting COVID-19 pneumonia among symptomatic individuals, especially in those with severe disease. It was also useful for evaluating the potential complications, disease severity, and progression of COVID-19 pneumonia. The features of CT images differed at the early, intermediate, and late stages of COVID-19 pneumonia, but the most common imaging findings were patchy and ground glass opacities. It was also found that diagnosing COVID-19 in children using CT is challenging.

Even though chest CT is not useful for primary screening of COVID-19, it is useful for detecting later stage disease and for evaluating patients with COVID-19 pneumonia. For patients with suspected COVID-19 pneumonia and a false negative RT-PCR result, cross-checking with a chest CT and a repeat RT-PCR test is essential to avoid misdiagnosis.