Breast cancer epigenetics: current and evolving treatment.

BACKGROUND: Breast cancer (BC) presents persistent challenges due to subtype-specific limited efficacy and potential resistance to standard therapy, influenced by the dynamic reversible nature of epigenetic plasticity. This study aims to comprehensively explore the evolving BC epigenetic landscape, analyzing trends and evaluating the therapeutic potential of epigenetic drugs (epi-drugs) for BC treatment. METHODS: We conducted a cross-sectional study of BC epigenetic trials using ClinicalTrials.gov until July 18, 2023. Additionally, results from randomized controlled trials were retrieved from the registry or PubMed using trial registration numbers. RESULTS: In total, 22 epi-drugs were investigated in 100 trials, with 11 currently being studied in 38 ongoing trials for BC. Over the years, epigenetic clinical trials for BC have notably increased, with histone deacetylase inhibitors constituting 45.45% of the candidate agents in the development pipeline. All ongoing trials are enrolling human epidermal growth factor receptor2 (HER2)-negative BC patients. Epi-drugs are commonly explored in combination with multiple anti-cancer therapies, such as aromatase or microtubule inhibitors, using an intermittent sequential administration approach. Emerging strategies include new-generation epi-drugs and combination involving immunotherapy or targeted therapy. Among candidate drugs, tucidinostat and entinostat, in combination with exemestane, demonstrated significant improvements in progression-free survival in phase III trials for hormone receptor-positive, HER2-negative BC patients. CONCLUSION: This study highlights the growing interest in BC epigenetics, suggesting a potential shift from a one-size-fits-all approach to precision medicine, and emphasizes the necessity for robust evidence on their efficacy and safety to support continuous development and approval, addressing the unmet needs in BC treatment.

Biomarkers as Endpoints in Clinical Trials for Alzheimer's Disease.

Background: Alzheimer's disease (AD) is a neurodegenerative disease that imposes economic and societal burden. Biomarkers have played a crucial role in the recent approval of aducanumab and lecanemab as disease-modifying therapies which marked a significant milestone for the treatment of AD. The inclusion of biomarkers in AD trials facilitates precise diagnosis, monitors safety, demonstrates target engagement, and supports disease modification. Objective: This study analyzed the utilization state and trends of biomarkers as endpoints in AD trials. Methods: In this retrospective study, trials were collected by searching clinicaltrials.gov using the term "Alzheimer". Primary and secondary outcomes were analyzed separately for each phase. Results: Among the 1,048 analyzed trials, 313 (29.87%) adopted biomarkers as primary endpoints and 364 (34.73%) as secondary endpoints, mainly in phases 1 and 2. The top three biomarkers adopted as primary endpoints in phases 1, 2, and 3 were amyloid-PET, tau-PET, and MRI. The top three biomarkers adopted as secondary endpoints, in phase 1, were cerebrospinal fluid (CSF) amyloid-ß (Aß), blood Aß and amyloid-PET; in phase 2, they were MRI, CSF Aß, and CSF phospho-tau; and in phase 3, they were amyloid PET, MRI, and blood Aß. There was a statistically significant increase in the adoption of biomarkers as primary endpoints in phase 2 trials (p = 0.001) and secondary endpoints in phase 3 trials (p = 0.001). Conclusions: The growing recognition of the importance of biomarkers in AD trial' design and drug development is evident by the significant steady increase in biomarkers' utilization in phases 2 and 3.

Analysis and comparative evaluation of expedited programs for gene therapy products: insights from the United States, the European Union, Japan, and South Korea.

Gene therapy products (GTPs) used for incurable diseases can be expedited for early commercialization to fulfill unmet needs. This study analyzed the expedited programs available for GTPs in the US, EU, Japan, and South Korea using their regulatory authorities' websites, related regulations, and documents. In total, there were five expedited programs available for GTPs in the US, four in the EU, and three in both Japan and South Korea, of which four are tailored for GTPs. These programs, sharing similar objectives, can be categorized as those expediting drug development, review, and approval. However, variations are observed in eligibility criteria, specific benefits, and post-marketing study conditions across regulatory authorities. Additionally, the criteria for orphan drug designation for a rare disease differs in prevalence thresholds, incentive offered, and marketing exclusivity period. Overall, 19 GTPs were approved-13 in the US, 14 in the EU, eight in Japan, and three in South Korea-with majority obtaining regulatory approval through at least one expedited program. Therefore, future studies can analyze whether acquiring multiple expedited programs accelerates the drug development and commercialization of GTPs compared with when only one expedited program is processed. Additionally, inter-authority scientific discussion is encouraged for harmonization of expedited program requirements.

The Adverse Effects and Nonmedical Use of Methylphenidate Before and After the Outbreak of COVID-19: Machine Learning Analysis.

BACKGROUND: Methylphenidate is an effective first-line treatment for attention-deficit/hyperactivity disorder (ADHD). However, many adverse effects of methylphenidate have been recorded from randomized clinical trials and patient-reported outcomes, but it is difficult to determine abuse from them. In the context of COVID-19, it is important to determine how drug use evaluation, as well as misuse of drugs, have been affected by the pandemic. As people share their reasons for using medication, patient sentiments, and the effects of medicine on social networking services (SNSs), the application of machine learning and SNS data can be a method to overcome the limitations. Proper machine learning models could be evaluated to validate the effects of the COVID-19 pandemic on drug use. OBJECTIVE: To analyze the effect of the COVID-19 pandemic on the use of methylphenidate, this study analyzed the adverse effects and nonmedical use of methylphenidate and evaluated the change in frequency of nonmedical use based on SNS data before and after the outbreak of COVID-19. Moreover, the performance of 4 machine learning models for classifying methylphenidate use based on SNS data was compared. METHODS: In this cross-sectional study, SNS data on methylphenidate from Twitter, Facebook, and Instagram from January 2019 to December 2020 were collected. The frequency of adverse effects, nonmedical use, and drug use before and after the COVID-19 pandemic were compared and analyzed. Interrupted time series analysis about the frequency and trends of nonmedical use of methylphenidate was conducted for 24 months from January 2019 to December 2020. Using the labeled training data set and features, the following 4 machine learning models were built using the data, and their performance was evaluated using F-1 scores: naïve Bayes classifier, random forest, support vector machine, and long short-term memory. RESULTS: This study collected 146,352 data points and detected that 4.3% (6340/146,352) were firsthand experience data. Psychiatric problems (521/1683, 31%) had the highest frequency among the adverse effects. The highest frequency of nonmedical use was for studies or work (741/2016, 36.8%). While the frequency of nonmedical use before and after the outbreak of COVID-19 has been similar (odds ratio [OR] 1.02 95% CI 0.91-1.15), its trend has changed significantly due to the pandemic (95% CI 2.36-22.20). Among the machine learning models, RF had the highest performance of 0.75. CONCLUSIONS: The trend of nonmedical use of methylphenidate has changed significantly due to the COVID-19 pandemic. Among the machine learning models using SNS data to analyze the adverse effects and nonmedical use of methylphenidate, the random forest model had the highest performance.

Reporting quality was suboptimal in a systematic review of randomized controlled trials with adaptive designs.

OBJECTIVE: The study was conducted to evaluate the reporting quality of randomized controlled trials (RCTs) that use an adaptive design (AD) based on the 2020 AD Consolidated Standards for Reporting Trials 2010 extension (ACE) guidelines and identify factors associated with better reporting quality. STUDY DESIGN AND SETTING: PubMed, Embase, Cochrane, Web of Science, and Google Scholar were searched until November 1, 2022. Multivariable linear regression analysis was performed to investigate potential predictors. RESULTS: In total, 109 RCTs were included in our study. The mean compliance rate for the ACE checklist items was 69.75% ± 16.02. Key methodological items including allocation concealment and its implementations were poorly reported. There was also suboptimal reporting of checklist items related to the conduct of interim analyzes. Multivariable regression analysis showed better reporting quality with trial registration, nonindustry affiliation (first author), a sample size of >100, general medical journal type, publication date (≥2020), funding, and disclosure of the number of interim analyzes. CONCLUSION: Our study showed that RCTs with AD had suboptimal reporting of 2020 ACE checklist items, particularly AD-specific items. Following the development of ACE guidelines, stricter adherence to the ACE guideline is necessary to improve their reporting quality. Pre-ACE and post-ACE adherence comparisons can be conducted in the future.

Efficacy, Immunogenicity, and Safety of COVID-19 Vaccines in Randomized Control Trials in the Pre-Delta Era: A Systematic Review and Network Meta-Analysis.

The most effective method of limiting the coronavirus disease pandemic of 2019 (COVID-19) is vaccination. For the determination of the comparative efficacy and safety of COVID-19 vaccines and their platforms during the pre-Delta era, a systematic review and network meta-analysis was conducted. The MEDLINE, Embase, and MedRxiv databases were searched, and the gray literature was manually searched up to 8 July 2021. The review includes the phase II and III randomized controlled trials (RCTs) that assessed the efficacy, immunogenicity, and safety of the COVID-19 vaccines. The network meta-analysis used a Bayesian model and used the surface under the cumulative ranking to rank the comparisons between the vaccines. All included studies were quality appraised according to their design, and the heterogeneity of the analyses was assessed using I2. In terms of vaccine efficacy, the mRNA-1273 vaccine ranked the highest, and the CoronaVac vaccine ranked the lowest. The mRNA-1273 ranked the highest for neutralizing antibody responses to live SARS-CoV-2. The WIV04 vaccine was associated with the lowest incidence of both local and systemic adverse reactions. All studies except one had a low to moderate risk of bias. The mRNA platform vaccines showed higher efficacy and more adverse reactions than the other vaccines.

A Systematic Review on Neurological Aspects of COVID-19: Exploring the Relationship Between COVID-19-Related Olfactory Dysfunction and Neuroinvasion.

Objectives: To identify neurological aspects of Coronavirus disease 2019 (COVID-19) and to investigate COVID-19 infected patients with and without olfactory dysfunction in relation to polymerase chain reaction (PCR) assay results for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in the cerebrospinal fluid (CSF). Methods: PubMed and EMBASE databases were searched until March 26, 2021, for observational studies with COVID-19 patients that had performed CSF PCR assay due to the neurologic symptom and reported anosmia status. Results: Initially, 2,387 studies were identified;167 studies performed SARS-CoV-2 CSF PCR assay, of which our review comprised 45 observational studies that conducted CSF PCR assay for SARS-CoV-2 in 101 patients and reported anosmia status in 55 of 101 patients. Central and peripheral neurological manifestations observed in COVID-19 patients were diverse. The most common neurological diagnoses were Guillain-Barré syndrome (GBS) and its variants (24%), followed by encephalopathy (21%). The SARS-CoV-2 PCR assay was positive in only four CSF samples, of which two patients had olfactory dysfunction while the others did not. Conclusions: The neurological spectrum of COVID-19 is diverse, and direct neuroinvasion of SARS-CoV-2 is rare. The neuroprotection against SARS-CoV-2 in COVID-19 patients with anosmia is controversial, as an equal number of patients with and without olfactory dysfunction had positive CSF PCR results for SARS-CoV-2 in our study, and further studies are required to provide more insight into this topic.

Hypoglycemic agents and glycemic variability in individuals with type 2 diabetes: A systematic review and network meta-analysis.

While hemoglobin A1c (HbA1c) is commonly used to monitor therapy response in type 2 diabetes (T2D), GV is emerging as an essential additional metric for optimizing glycemic control. Our goal was to learn more about the impact of hypoglycemic agents on HbA1c levels and GV in patients with T2D. A systematic review and network meta-analysis (NMA) of randomized controlled trials were performed to assess the effects of glucagon-like peptide 1 receptor agonists (GLP-1 RAs), sodium-glucose cotransporter (SGLT)-2 inhibitors, dipeptidyl peptidase (DPP)-4 inhibitors, sulfonylurea and thiazolidinediones on Mean Amplitude of Glycemic Excursions (MAGE) and HbA1c. Searches were performed using PubMed and EMBASE. A random-effect model was used in the NMA, and the surface under the cumulative ranking was used to rank comparisons. All studies were checked for quality according to their design and also for heterogeneity before inclusion in this NMA. The highest reduction in MAGE was achieved by GLP-1 RAs (SUCRA 0.83), followed by DPP-4 inhibitors (SUCRA: 0.72), and thiazolidinediones (SUCRA: 0.69). In terms of HbA1c reduction, GLP-1 RAs were the most effective (SUCRA 0.81), followed by DPP-4 inhibitors (SUCRA 0.72) and sulfonylurea (SUCRA 0.65). Our findings indicated that GLP-1 RAs have relatively high efficacy in terms of HbA1c and MAGE reduction when compared with other hypoglycemic agents and can thus have clinical application. Future studies with a larger sample size and appropriate subgroup analyses are warranted to completely understand the glycemic effects of these agents in various patients with T2D. The protocol for this systematic review was registered with the International Prospective Register of Systematic Reviews (CRD42021256363).

Is loss of smell an early predictor of COVID-19 severity: a systematic review and meta-analysis.

Anecdotal evidence suggests that the severity of coronavirus disease of 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is likely to be distinguished by variations in loss of smell (LOS). Thus, we conducted a meta-analysis of 45 articles that include a total of 42,120 COVID-19 patients from 17 different countries to demonstrate that severely ill or hospitalized COVID-19 patients have a lesser chance of experiencing LOS than non-severely ill or non-hospitalized COVID-19 patients (odds ratio = 0.527 [95% CI 0.373-0.744; p < 0.001] and 0.283 [95% CI 0.173-0.462; p < 0.001], respectively). We also proposed a possible mechanism underlying the association of COVID-19 severity with anosmia, which may explain why patients without sense of smell develop severe COVID-19. Variations in LOS according to the severity of COVID-19 is a global phenomenon, with few exceptions. Since severely ill patients have a lower rate of anosmia, patients without anosmia should be monitored more closely in the early stages of COVID-19, for early diagnosis of severity of illness. An understanding of how the severity of COVID-19 infection and LOS are associated has profound implications for the clinical management and mitigation strategies for the disease.