Publications in 2022

Background: In older adults, the burden of respiratory syncytial virus (RSV) resembles that of influenza and may even be considered worse due to the lack of preventive interventions. This study was performed to identify the available literature on RSV infection in older adults, and to provide updated exploratory results of the cost-effectiveness of a hypothetical RSV vaccine in the Netherlands and the United Kingdom.

Methods: A literature search was performed in Medline and EMBASE on 11 November 2019, which served as input for a static decision-tree model that was used to estimate the EJP, for an RSV vaccine applying different willingness-to-pay (WTP) thresholds. WTP thresholds applied were €20 000 and €50 000 per quality-adjusted life-year for the Netherlands, and £20 000 and £30 000 per quality-adjusted life-year for the United Kingdom. Analyses were—in line with country-specific guidelines—conducted from a societal perspective for the Netherlands and a third-party payer perspective for the United Kingdom. The robustness of the cost-effectiveness results was tested in sensitivity analysis.

Results: After screening the literature, 3 studies for the Netherlands and 6 for the United Kingdom remained to populate the country-specific models. In the base case analysis for the Netherlands (mean RSV incidence, 3.32%), justifiable vaccine prices of €16.38 and €50.03 were found, based on applying the lower and higher WTP thresholds, respectively. Similarly, for the United Kingdom (mean incidence, 7.13%), vaccine prices of £72.29 and £109.74 were found, respectively.

Conclusion: RSV vaccination may well be cost-effective in both the Netherlands and the United Kingdom, depending on the exact RSV incidence, vaccine effectiveness and price. However, sensitivity analysis showed that the results were robust based on varying the different parameter estimates and assumptions. With RSV vaccines reaching the final stages of development, a strong need exists for cost-effectiveness studies to understand economically justifiable pricing of the vaccine.

Objectives: National health technology assessments (HTAs) across Europe show differences in evidentiary requirements from assessments by the European Medicines Agency (EMA), affecting time to patient access for drugs after marketing authorization. This article analyzes the differences between EMA and HTA bodies’ evidentiary requirements for oncology drugs and provides recommendations on potential further alignment to minimize and optimally manage the remaining differences.

Methods: Interviews were performed with representatives and drug assessment experts from EMA and HTA bodies to identify evidentiary requirements for several subdomains and collect recommendations for potentially more efficiently addressing differences. A comparative analysis of acceptability of the evidence by EMA and the HTA bodies and for potential further alignment between both authorities was conducted.

Results: Acceptability of available evidence was higher for EMA than HTA bodies. HTA bodies and EMA were aligned on evidentiary requirements in most cases. The subdomains showing notable differences concerned the acceptance of limitation of the target population and extrapolation of target populations, progression-free survival and (other) surrogate endpoints as outcomes, cross-over designs, short trial duration, and clinical relevance of the effect size. Recommendations for reducing or optimally managing differences included joint early dialogues, joint relative effectiveness assessments, and the use of managed entry agreements.

Conclusions: Differences between assessments of EMA and HTA bodies were identified in important areas of evidentiary requirements. Increased alignment between EMA and HTA bodies is suggested and recommendations for realization are discussed.

Background: Patients suffering from functional neurological disorder (FND) experience disabling neurological symptoms not caused by an underlying classical neurological disease (such as stroke or multiple sclerosis). The diagnosis is made based on reliable positive clinical signs, but clinicians often require additional time- and cost consuming medical tests and examinations. Resting-state functional connectivity (RS FC) showed its potential as an imaging-based adjunctive biomarker to help distinguish patients from healthy controls and could represent a “rule-in” procedure to assist in the diagnostic process. However, the use of RS FC depends on its applicability in a multi-centre setting, which is particularly susceptible to inter-scanner variability. The aim of this study was to test the robustness of a classification approach based on RS FC in a multi-centre setting.

Methods: This study aimed to distinguish 86 FND patients from 86 healthy controls acquired in four different centres using a multivariate machine learning approach based on whole-brain resting-state functional connectivity. First, previously published results were replicated in each centre individually (intra-centre cross- validation) and its robustness across inter-scanner variability was assessed by pooling all the data (pooled cross-validation). Second, we evaluated the generalizability of the method by using data from each centre once as a test set, and the data from the remaining centres as a training set (inter-centre cross-validation).

Results: FND patients were successfully distinguished from healthy controls in the replication step (accuracy of 74%) as well as in each individual additional centre (accuracies of 73%, 71% and 70%). The pooled cross validation confirmed that the classifier was robust with an accuracy of 72%. The results survived post-hoc adjustment for anxiety, depression, psychotropic medication intake, and symptom severity. The most discriminant features involved the angular- and supramarginal gyri, sensorimotor cortex, cingular- and insular cortex, and hippocampal regions. The inter-centre validation step did not exceed chance level (accuracy below 50%).

Conclusions: The results demonstrate the applicability of RS FC to correctly distinguish FND patients from healthy controls in different centres and its robustness against inter-scanner variability. In order to generalize its use across different centres and aim for clinical application, future studies should work towards optimization of acquisition parameters and include neurological and psychiatric control groups presenting with similar symptoms.

The study aimed to determine the associations of Peak Inspiratory Flow (PIF), inhalation technique and adherence with health status and exacerbations in participants with COPD using DPI maintenance therapy. This cross-sectional multi-country observational real-world study included COPD participants aged ≥40 years using a DPI for maintenance therapy. PIF was measured three times with the In-Check DIAL G16: (1) typical PIF at resistance of participant’s inhaler, (2) maximal PIF at resistance of participant’s inhaler, (3) maximal PIF at low resistance. Suboptimal PIF (sPIF) was defined as PIF lower than required for the device. Participants completed questionnaires on health status (Clinical COPD Questionnaire (CCQ)), adherence (Test of Adherence to Inhalers (TAI)) and exacerbations. Inhalation technique was assessed by standardised evaluation of video recordings. Complete data were available from 1434 participants (50.1% female, mean age 69.2 years). GOLD stage was available for 801 participants: GOLD stage I (23.6%), II (54.9%), III (17.4%) and IV (4.1%)). Of all participants, 29% had a sPIF, and 16% were shown able to generate an optimal PIF but failed to do so. sPIF was significantly associated with worse health status (0.226 (95% CI 0.107–0.346), worse units on CCQ; p=0.001). The errors ‘teeth and lips sealed around mouthpiece’, ‘breathe in’, and ‘breathe out calmly after inhalation’ were related to health status. Adherence was not associated with health status. After correcting for multiple testing, no significant association was found with moderate or severe exacerbations in the last 12 months. To conclude, sPIF is associated with poorer health status. This study demonstrates the importance of PIF assessment in DPI inhalation therapy. Healthcare professionals should consider selecting appropriate inhalers in cases of sPIF.

Objectives: Spinal muscular atrophy (SMA) is a rare genetic disorder that causes progressive muscle weakness and paralysis. In its most common and severe form, the majority of untreated infants die before 2 years of age. Early detection and treatment, ideally before symptom onset, maximize survival and achievement of age-appropriate motor milestones, with potentially substantial impact on health-related quality of life. Therefore, SMA is an ideal candidate for inclusion in newborn screening (NBS) programs. We evaluated the cost-effectiveness of including SMA in the NBS program in The Netherlands.

Methods: We developed a cost-utility model to estimate lifetime health effects and costs of NBS for SMA and subsequent treatment versus a treatment pathway without NBS (ie, diagnosis and treatment after presentation with overt symptoms). Model inputs were based on literature, local data, and expert opinion. Sensitivity and scenario analyses were conducted to assess model robustness and validity of results.

Results: After detection of SMA by NBS in 17 patients, the number of quality-adjusted life-years gained per annual birth cohort was estimated at 320 with NBS followed by treatment compared with treatment after clinical SMA diagnosis. Total healthcare costs, including screening, diagnostics, treatment, and other healthcare resource use, were estimated to be V12014949 lower for patients identified by NBS.

Conclusions: NBS for early identification and treatment of SMA versus later symptomatic treatment after clinical diagnosis improves health outcomes and is less costly and, therefore, is a cost-effective use of resources. Results were robust in sensitivity and scenario analyses.

Objectives: Going beyond their initial use as antidiabetic agents, sodium-glucose cotransporter-2 (SGLT2) inhibitors have certified their roles in the treatment of other chronic diseases independent from diabetes. We aim to demonstrate how the positions of SGLT2 inhibitors have changed in the treatment algorithms of type 2 diabetes (T2DM), heart failure (HF), and chronic kidney disease (CKD), and which opportunities lie in the future.

Methods: A targeted review was performed. International guidelines for T2DM, HF, and CKD published from 2012 onward were included for the analysis of positioning. An advanced search on clinicaltrials.gov was conducted to identify recently published and ongoing trials of SGLT2 inhibitors in related diseases to analyse their possible positions in the future.

Results: Established evidence of cardiorenal protective benefits of these drugs has placed SGLT2 inhibitors as first-line monotherapy agents in T2DM patients with related comorbidities. Both dapagliflozin and empagliflozin are recommended in the combined therapy of chronic HF due to their clinical efficacy and cost-effectiveness. While dapagliflozin already has proven its place in the treatment algorithm of CKD, empagliflozin might share a similar position based on the early termination of the EMPA-KIDNEY trial due to clear positive results in patients with CKD. Furthermore, the cardiorenal benefits of SGLT2 inhibitors regardless of diabetic status are being investigated in ongoing trials looking at the efficacy and safety in patients with acute HF, myocardial infarction, and severe CKD, including dialysis and kidney transplantation.

Conclusions: Despite emerging evidence however, prescriptions of SGLT2 inhibitors are lagging. Their limited usage within T2DM at present and potentially slow adaptation in HF and CKD hinders treatment and protection in these patients, resulting in potential losses in health benefits, measured by quality adjusted life years. This suggests that policy makers should be attentive to their uptake among eligible patients since their protective evidence has already been established.

Background/Objectives: Smoking is the leading risk factor for many chronic diseases. The quantitative analysis of potential health gains from reduced smoking is important for establishing priorities in Mongolia’s health policy. This study quantifies the effect of tobacco-tax increases on future smoking prevalence and the associated smoking-related burden of disease in Mongolia.

Methods: The dynamic model for health impact assessment (DYNAMO-HIA) tool was used. The most recent data were used as input for evaluating tobacco-taxation scenarios. Demographic data were taken from the Mongolian Statistical Information Services. Smoking data came from a representative population-based STEPS survey, and smoking-related disease data were obtained from the health-information database of Mongolia’s National Health Center. Simulation was used to evaluate various levels of one-time price increases on tobacco products (25% and 75%) in Mongolia. Conservative interpretation suggests that the population will eventually adjust to the higher tobacco price and return to baseline smoking behaviors.

Results: Over a three-year period, smoking prevalence would be reduced by 1.2% points, corresponding to almost 40 thousand smokers at the population level for a price increase of 75%, compared to the baseline scenario. Projected health benefits of this scenario suggest that more than 137 thousand quality adjusted of life years would be gained by avoiding smoking-related diseases within a population of three million over a 30-year period.

Discussion: Prevention through effective tobacco-control policy could yield considerable gains in population health in Mongolia. Compared to current policy, tax increases must be higher to have a significant effect on population health.

Implications: Tobacco taxation is an effective policy for reducing the harm of tobacco smoking, while benefiting population health in countries where the tobacco epidemic is still in an early stage. Smoking prevalence and smoking behaviors in these countries differ from those in Western countries. Reducing the uptake of smoking among young people could be a particularly worthwhile benefit of tobacco-tax increases.

Purpose: Although intraocular anti-vascular endothelial growth factors (anti-VEGFs) are effective as treatment of neovascular age-related macular degeneration (nAMD), the (economic) burden on the healthcare system is considerable. A treat-andextend (T&E) regimen is associated with a lower number of injections without compromising the effectiveness and can therefore help optimise nAMD treatment. This study investigates the per-patient costs associated with nAMD treatment, when using aflibercept, bevacizumab, or ranibizumab with a T&E regimen.

Methods: In this cost-minimisation model, the per-patient costs in the Netherlands were modelled using a healthcare payers’ perspective over a 3-year time horizon with the assumption that efficacy of treatments is similar. Additionally, the break-even price of the different anti-VEGFs was calculated relative to the cheapest option and injection frequency.

Results: The injection frequency varied from 14.2 for aflibercept to 27.4 for bevacizumab in 3 years. Nonetheless, bevacizumab remains the cheapest treatment option (€14,215), followed by aflibercept (€18,202) and ranibizumab (€31,048). The medication covers the majority of the per-patient costs for aflibercept and ranibizumab, while administration covers the majority of the per-patient costs for bevacizumab. The break-even prices of aflibercept and ranibizumab are respectively €507 and €60.58 per injection. Brolucizumab was included in the scenario analysis and was more expensive than aflibercept (€20,446). Brolucizumab should reduce to 13.8 injections over 3 years to be as costly as aflibercept.

Conclusion: Bevacizumab is the cheapest anti-VEGF treatment. The list prices of all anti-VEGFs should reduce to be as costly as bevacizumab. Aflibercept is the second-choice treatment and so far brolucizumab is not.

Background: This study aimed to assess the association between multimorbidity and exit from paid employment, and which combinations of chronic health conditions (CHCs) have the strongest association with exit from paid employment.

Methods: Data from 111 208 workers aged 18–64years from Lifelines were enriched with monthly employment data from Statistics Netherlands. Exit from paid employment during follow-up was defined as a change from paid employment to unemployment, disability benefits, economic inactivity or early retirement. CHCs included cardiovascular diseases (CVD), chronic obstructive pulmonary disease (COPD), rheumatoid arthritis (RA), type 2 diabetes (T2DM) and depression. Cox-proportional hazards models were used to examine the impact of multimorbidity and combinations of CHCs on exit from paid employment.

Results: Multimorbidity increased the risk of exiting paid employment compared with workers without CHCs (hazard ratio (HR): 1.52; 95% confidence interval (CI): 1.35–1.71) or one CHC (HR: 1.14; 95% CI: 1.01–1.28). The risk for exit from paid employment increased among workers with COPD if they additionally had CVD(HR: 1.39; 95% CI: 1.03–1.88), depression (HR: 1.46; 95% CI: 1.10–1.93) or RA (HR: 1.44; 95% CI: 1.08–1.91), for workers with T2DM if they additionally had CVD (HR: 1.43; 95% CI: 1.07–1.91) or depression (HR: 2.09; 95% CI: 1.51–2.91) and for workers with depression who also had T2DM (HR: 1.68; 95% CI: 1.21–2.32).

Conclusion: This study showed that workers with multimorbidity, especially having a combination of COPD and depression or T2DM and depression, have a higher risk for early exit from paid employment and, therefore, may need tailored support at the workplace.

Aims: Valid health economic models are essential to inform the adoption and reimbursement of therapies for diabetes mellitus. Often existing health economic models are applied in other countries and settings than those where they were developed. This practice requires assessing the transferability of a model developed from one setting to another. We evaluate the transferability of the MICADO model, developed for the Dutch 2007 setting, in two different settings using a range of adjustment steps. MICADO predicts micro- and macrovascular events at the population level.

Methods: MICADO simulation results were compared to observed events in an Italian 2000–2015 cohort (Casale Monferrato Survey [CMS]) and in a Dutch 2008–2019 (Hoorn Diabetes Care Center [DCS]) cohort after adjusting the demographic characteristics. Additional adjustments were performed to: (1) risk factors prevalence at baseline, (2) prevalence of complications, and (3) all-cause mortality risks by age and sex. Model validity was assessed by mean average percentage error (MAPE) of cumulative incidences over 10 years of follow-up, where lower values mean better accuracy.

Results: For mortality, MAPE was lower for CMS compared to DCS (0.38 vs. 0.70 following demographic adjustment) and adjustment step 3 improved it to 0.20 in CMS, whereas step 2 showed best results in DCS (0.65). MAPE for heart failure and stroke in DCS were 0.11 and 0.22, respectively, while for CMS was 0.42 and 0.41.

Conclusions: The transferability of the MICADO model varied by event and per cohort. Additional adjustments improved prediction of events for MICADO. To ensure a valid model in a new setting it is imperative to assess the impact of adjustments in terms of model accuracy, even when this involves the same country, but a new time period.

Objectives: Chikungunya virus (CHIKV) is a re-emerging arbovirus with infection characterized by an acute phase commonly presenting with fever, severe polyarthralgia, and myalgia, which can progress to chronic sequelae resulting in productivity losses and a significant reduction in health-related quality-of-life (HRQoL). To investigate the available evidence on the disease burden associated with CHIKV, we conducted a systematic literature review (SLR) of the clinical evidence and a targeted literature review (TLR) on the burden of CHIKV.

Methods: The SLR of clinical evidence was conducted in Medline and Embase databases (no date restriction) and congress abstract repositories (2019–2021). The search adhered to Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A TLR of burden evidence was also performed.

Results: Of 13,285 records identified, 246 studies were included in the SLR of which 17 (6.91%) were interventional studies. The TLR included 101 studies. The acute and chronic polyarthralgia and myalgia associated with CHIKV infection was found to cause substantial physical incapacity impacting the daily functioning and HRQoL of patients. In addition, mental health is significantly affected, with patients experiencing pain, mental, mood, and sleep disorders. CHIKV infection may lead to long-term disability due to neurocognitive and psychological sequelae associated with a reduction in HRQoL. Population shifts, increased travel, and climate change are contributing to the increased spread of emerging and re-emerging CHIKV infections, yet effective preventive measures or treatments are lacking.

Conclusions: CHIKV is a serious threat to global public health and causes significant disease burden worldwide. The tools available to prevent and treat CHIKV infection are limited; vector control measures are suboptimal and challenging, and only symptomatic treatment currently exists for chikungunya. Due to the unpredictable nature of CHIKV spread and lack of treatment options for chikungunya, there is an immediate need for effective preventive measures such as vaccines.

Background: Sub-Saharan Africa (SSA) has the world's highest maternal and neonatal morbidity and mortality and has shown the slowest progress in reducing them. In addition, there is substantial inequality in terms of maternal and neonatal morbidity and mortality in the region. Geospatial studies can help prioritize scarce resources by pinpointing priority areas for implementation. This systematic review was conducted to explore the application of geospatial analysis to maternal and neonatal morbidity and mortality in SSA.

Methods: A systematic search of PubMed, SCOPUS, EMBASE, and Web of Science databases was performed. All observational and qualitative studies that reported on maternal or neonatal health outcomes were included if they used a spatial analysis technique and were conducted in a SSA country. After removing duplicates, two reviewers independently reviewed each study's abstract and full text for inclusion. Furthermore, the quality of the studies was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklists. Finally, due to the heterogeneity of studies, narrative synthesis was used to summarize the main findings, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was strictly followed to report the review results. A total of 56 studies were included in the review.

Results: We found that geospatial analysis was used to identify inequalities in maternal and neonatal morbidity, mortality, and health care utilization and to identify gaps in the availability and geographic accessibility of maternal health facilities. In addition, we identified a few studies that used geospatial analysis for modelling intervention areas. We also detected challenges and shortcomings, such as unrealistic assumptions used by geospatial models and a shortage of reliable, up-to-date, small-scale georeferenced data.

Conclusions: The use of geospatial analysis for maternal and neonatal health in SSA is still limited, and more detailed spatial data are required to exploit the potential of geospatial technologies fully.