Rare Neurological Diseases: an Overreview of Pathophysiology, Epidemiology, Clinical Features and Pharmacoeconomic Considerations in the Treating

Rare diseases (RD) are serious chronic diseases affecting small number of people compared to the general population. There are between 6000 and 8000 RDs, which affect about 400 million people worldwide. Drugs used for causal treatment of RDs are called orphan drugs. RDs bear great clinical and economic burden for patients, their families, healthcare systems and society overall. There are at least two reasons for the high cost of treatment of RDs. First, there is no causal therapy for majority of RDs, so exacerbations, complications, and hospitalizations in those patients are common. The second reason is high price of available orphan drugs, which are not cost-effective when traditional pharmacoeconomic evaluation is employed. The pharmacoeconomic aspect of the treatment of RDs is especially important in the field of neurology, since at least one fifth of all RDs is composed of neurological conditions. The aim of this paper was to provide a concise overview of the pathophysiological, epidemiological and clinical characteristics of some of the most important and common rare neurological diseases, with special reference to their impact on society and economy.

Improving the causal treatment effect estimation with propensity scores by the bootstrap

When observational studies are used to establish the causal effects of treatments, the estimated effect is affected by treatment selection bias. The inverse propensity score weight (IPSW) is often used to deal with such bias. However, IPSW requires strong assumptions whose misspecifications and strategies to correct the misspecifications were rarely studied. We present a bootstrap bias correction of IPSW (BC-IPSW) to improve the performance of propensity score in dealing with treatment selection bias in the presence of failure to the ignorability and overlap assumptions. The approach was motivated by a real observational study to explore the potential of anticoagulant treatment for reducing mortality in patients with end-stage renal disease. The benefit of the treatment to enhance survival was demonstrated; the suggested BC-IPSW method indicated a statistically significant reduction in mortality for patients receiving the treatment. Using extensive simulations, we show that BC-IPSW substantially reduced the bias due to the misspecification of the ignorability and overlap assumptions. Further, we showed that IPSW is still useful to account for the lack of treatment randomization, but its advantages are stringently linked to the satisfaction of ignorability, indicating that the existence of relevant though unmeasured or unused covariates can worsen the selection bias.

Hepatitis A

Hepatitis A virus (HAV) is a single-stranded “nonenveloped” RNA virus in the picornaviridae family. HAV is most often transmitted by the fecal-oral route, but also by contaminated food, water, sexual contact, and intravenous drug use. HAV causes little if any symptoms in the very young. Disease symptoms from liver damage become more frequent in older ages and even fulminant liver failure with death is observed in the elderly. Unlike hepatitis B and C, hepatitis A does not cause chronic liver disease. With lack of sanitation and hygiene, HAV infection occurs early in life inducing life-long protection, whereas in countries with good sanitation and hygiene, infections are seen later in life and are more severe. There is no causal treatment, but available vaccines are well tolerated, have an excellent safety profile and are highly effective with long-lasting protection after 2 doses. Hepatitis A vaccines can be used for pre- as well as for post-exposure prophylaxis and for individual as well as for population protection. Vaccinating a small fraction of the population (3%) – i.e., children aged 1–4 years serving as the reservoir and source of HAV – resulted in herd protection with 96% disease reduction in the whole population of Israel.

Biological DMARDs and disease modification in axial spondyloarthritis: a review through the lens of causal inference

Axial spondyloarthritis (axSpA) is a chronic rheumatic disease characterised by inflammation predominantly involving the spine and the sacroiliac joints. In some patients, axial inflammation leads to irreversible structural damage that in the spine is usually quantified by the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS). Available therapeutic options include biological disease-modifying antirheumatic drugs (bDMARDs), which have been proven effective in suppressing inflammation in several randomised controlled trials (RCT), the gold standard for evaluating causal treatment effects. RCTs are, however, unfeasible for testing structural effects in axSpA mainly due to the low sensitivity to change of the mSASSS. The available literature therefore mainly includes observational research, which poses serious challenges to the determination of causality. Here, we review the studies testing the effect of bDMARDs on spinal radiographic progression, making use of the principles of causal inference. By exploring the assumptions of causality under counterfactual reasoning (exchangeability, positivity and consistency), we distinguish between studies that likely have reported confounded treatment effects and studies that, on the basis of their design, have more likely reported causal treatment effects. We conclude that bDMARDs might, indirectly, interfere with spinal radiographic progression in axSpA by their effect on inflammation. Innovations in imaging are expected, so that placebo-controlled trials can in the future become a reality. In the meantime, causal inference analysis using observational data may contribute to a better understanding of whether disease modification is possible in axSpA.

Impaired Myocardial Function Is Prognostic for Severe Respiratory Failure in the Course of COVID-19 Infection

COVID-19 may lead to severe acute respiratory distress syndrome (ARDS) resulting in increased morbidity and mortality. Heart failure and/or pre-existing cardiovascular disease may correlate with poor outcomes and thus require special attention from treating physicians. The present study sought to investigate a possible impact of impaired myocardial function as well as myocardial distress markers on mortality or ARDS with need for mechanical ventilation in 157 consecutive patients with confirmed SARS-CoV-2 infection. All patients were admitted and treated at the University Hospital of Tübingen, Germany, during the first wave of the pandemic. Electrocardiography, echocardiography, and routine blood sampling were performed at hospital admission. Impaired left-ventricular and right-ventricular function, tricuspid regurgitation > grade 1, and elevated RV-pressure as well as thrombotic and myocardial distress markers (D-dimers, NT-pro-BNP, and troponin-I) were associated with mechanical ventilation and/or all-cause mortality. Impaired cardiac function is more frequent amidst ARDS, leading to subsequent need for mechanical ventilation, and thus denotes a poor outcome in COVID-19. Since a causal treatment for SARS-CoV-2 infection is still lacking, guideline-compliant cardiovascular evaluation and treatment remains the best approach to improve outcomes in COVID-19 patients with cardiovascular comorbidities.

Plaque Index and Gingival Index Evaluation in Subjects with Gingivitis after Two Months of Treatment with Two Different Probiotic Food Supply: A Retrospective Study

Objective: The purpose of this study is to investigate and compare the Gingival Index and the Plaque Index in a population treated with 2 probiotic food supplies (Reuterin Os® and Carioblis®) for two months. Material and Methods: The sample was composed of 92 patients suffering from gingivitis, divided into 4 groups: the first received only causal treatment (group A – control group), the second and the third (group B and C – test group) took respectively 1 and 2 tablet of probiotic food supplement Ruterin Os® every day for 60 days, the fourth (group D– test group) took 1 tablet of probiotic food supplement Carioblis® every day for 60 days. The patients were visited every 14 days. Statistical analysis was performed to compare the control group to test groups after 2 months and to compare each index from the beginning to the end of treatment. Result: The study showed that the use of the probiotics RuterinOs® or Carioblis® in combination with causal treatment in patients with gingivitis led to a statistically significant improvement in plaque indices (PI) and gingival inflammation indices (GI) compared to the control group subjected only to causal treatment. The analysis of the data also highlighted a better result for patients who took 1 tablet of RuterinOs® every day for 2 months. Conclusion: The Authors can deduce that the somministration of one daily tablet of ReuterinOs® can bring benefits to oral health.

Estimating Causal Treatment Effects of Femoral and Tibial Derotational Osteotomies on Foot Progression in Children with Cerebral Palsy

BackgroundFoot progression deviations are a common and important problem for children with CP. Tibial and femoral derotational osteotomies (TDO, FDO) are used to treat foot progression deviations, but outcomes are unpredictable. The available evidence for the causal effects of TDO and FDO is limited and weak, and thus modeling approaches are needed.MethodsWe queried our clinical database for individuals with a diagnosis of cerebral palsy (CP) who were less than 18 years old and had baseline and follow up gait data collected within a 3-year time span. We then used the Bayesian Causal Forest (BCF) algorithm to estimate the causal treatment effects of TDO and FDO on foot progression deviations (separate models). We examined average treatment effects and heterogeneous treatment effects (HTEs) with respect to clinically relevant covariates.ResultsThe TDO and FDO models were able to accurately predict follow-up foot progression (r2 ∼0.7, RMSE ∼8°). The estimated causal effect of TDO was bimodal and exhibited significant heterogeneity with respect to baseline levels of foot progression and tibial torsion as well as changes in tibial torsion at follow-up. The estimated causal effect of FDO was unimodal and largely homogeneous with respect to baseline or change characteristics.ConclusionsThis study demonstrated the potential for causal machine-learning algorithms to impact treatment in children with CP. The causal model is accurate and appears sensible – though no gold-standard exists for validating the causal estimates. The model results can provide guidance for planning surgical corrections, and partly explain unsatisfactory outcomes observed in prior observational clinical studies.

The Role of Mesh Implants in Surgical Treatment of Parastomal Hernia

A parastomal hernia is a common complication following stoma surgery. Due to the large number of hernial relapses and other complications, such as infections, adhesion to the intestines, or the formation of adhesions, the treatment of hernias is still a surgical challenge. The current standard for the preventive and causal treatment of parastomal hernias is to perform a procedure with the use of a mesh implant. Researchers are currently focusing on the analysis of many relevant options, including the type of mesh (synthetic, composite, or biological), the available surgical techniques (Sugarbaker’s, “keyhole”, or “sandwich”), the surgical approach used (open or laparoscopic), and the implant position (onlay, sublay, or intraperitoneal onlay mesh). Current surface modification methods and combinations of different materials are actively explored areas for the creation of biocompatible mesh implants with different properties on the visceral and parietal peritoneal side. It has been shown that placing the implant in the sublay and intraperitoneal onlay mesh positions and the use of a specially developed implant with a 3D structure are associated with a lower frequency of recurrences. It has been shown that the prophylactic use of a mesh during stoma formation significantly reduces the incidence of parastomal hernias and is becoming a standard method in medical practice.

Social Learning and Solar Photovoltaic Adoption

Growing literature points to the effectiveness of leveraging social interactions and nudges to spur adoption of prosocial behaviors. This study investigates a large-scale behavioral intervention designed to actively leverage social learning and peer interactions to encourage adoption of residential solar photovoltaic systems. Municipalities choose a solar installer offering group pricing and undertake an informational campaign driven by volunteer ambassadors. We find a causal treatment effect of 37 installations per municipality from the campaigns and no evidence of harvesting or persistence. The intervention also lowers installation prices. Randomized controlled trials based on the intervention show that selection into the program is important, whereas group pricing is not. Our results suggest that the program provided economies of scale and lowered consumer acquisition costs, leading to low-cost emission reductions. This paper was accepted by Matthew Shum, marketing.