Closing the knowledge gap in Malaysian pharmacists: A virtual Allergic Rhinitis Boot Camp initiative

Background: In primary care, general practitioners (GPs) and pharmacists are at the frontline to identify, classify and manage patients suffering from allergic rhinitis (AR). The Allergic Rhinitis and its impact on Asthma (ARIA) guidelines aid clinicians in disease management by providing evidence-based recommendations. A recently published ASEAN primary care survey demonstrated that the awareness of ARIA guidelines was high among GPs but notably lower in pharmacists. Hence, this study seeks to evaluate the effectiveness of a Boot Camp education initiative in bridging the unmet needs in pharmacist awareness and education.Methods: The boot camp was organised as a virtual event. The participants answered the same questionnaire before (pre-assessment) and immediately after (post-assessment) the boot camp session. Statistical analysis was performed on the data paired between the pre- and post- assessments using SPSS v. 25.0 software.Results: The boot camp survey results showed that second-generation oral antihistamines and allergen avoidance are the most preferred options for AR treatment in pharmacy practice, irrespective of the disease severity. In both pre- and post-assessments, efficacy was ranked as the most important factor considered for choosing an antihistamine and which affects patient adherence. With the boot camp initiative, there was a statistically significant increase in awareness about the patient profiling tool (from 31.6% to 88.2%) and ARIA guidelines (from 40.4% to 91.2%) among the pharmacists (p<0.05). The proportion of pharmacists who were able to identify, classify and refer AR patients was significantly increased in post-assessment (p<0.05). Post the boot camp, among the proportion of pharmacists (91.2%) who were already aware of ARIA, a high percentage of them further agreed that ARIA guidelines were useful in identifying and treating patients with AR, as well as classifying AR, respectively (97.6%, 95.2%, and 93.5%).Conclusions: Based on improvements in knowledge and understanding of disease management post assessment, the Allergic Rhinitis Boot Camp initiative is effective and relevant to pharmacy practice. Outreach programs like this reiterate the emphasis on patient compliance and importance of utilizing ARIA guidelines in pharmacy practice that facilitates better management of AR in primary care.

Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome for patients with hepatocellular carcinoma

Aims: Individualized patient profiling is instrumental for personalized management in hepatocellular carcinoma (HCC). This study built a model based on bidirectional deep neural networks (BiDNNs), an unsupervised machine-learning approach, to integrate multi-omics data and predict survival in HCC. Methods: DNA methylation and mRNA expression data for HCC samples from the TCGA database were integrated using BiDNNs. With optimal clusters as labels, a support vector machine model was developed to predict survival. Results: Using the BiDNN-based model, samples were clustered into two survival subgroups. The survival subgroup classification was an independent prognostic factor. BiDNNs were superior to multimodal autoencoders. Conclusion: This study constructed and validated a BiDNN-based model for predicting prognosis in HCC, with implications for individualized therapies in HCC.

Profiling Colorectal Cancer in the Landscape Personalized Testing—Advantages of Liquid Biopsy

Drug-specific therapeutic approaches for colorectal cancer (CRC) have contributed to significant improvements in patient health. Nevertheless, there is still a great need to improve the personalization of treatments based on genetic and epigenetic tumor profiles to maximize the quality and efficacy while limiting cytotoxicity. Currently, CEA and CA 19-9 are the only validated blood biomarkers in clinical practice. For this reason, laboratories are trying to identify new specific prognostics and, more importantly, predictive biomarkers for CRC patient profiling. Thus, the unique landscape of personalized biomarker data should have a clinical impact on CRC treatment strategies and molecular genetic screening tests should become the standard method for diagnosing CRC. This review concentrates on recent molecular testing in CRC and discusses the potential modifications in CRC assay methodology with the upcoming clinical application of novel genomic approaches. While mechanisms for analyzing circulating tumor DNA have been proven too inaccurate, detecting and analyzing circulating tumor cells and protein analysis of exosomes represent more promising options. Blood liquid biopsy offers good prospects for the future if the results align with pathologists’ tissue analyses. Overall, early detection, accurate diagnosis and treatment monitoring for CRC with specific markers and targeted molecular testing may benefit many patients.

Social profile of tuberculosis in urban area

Background. Tuberculosis is an infectious socially significant disease. Apart from individual traits of the disease pathology, drug sensitivity and the availability of effective medicine and prevention, an important factor of its control is the patient’s social status. Social patient profiling in various locations across the country is vital for developing and deploying a high-quality and feasible tuberculosis care programme.Objectives. Social profiling of tuberculosis in St. Petersburg as an example of large urban area. Methods. We developed a questionnaire to assess 40 social parameters of a patient with tuberculosis. The study sample was representative and surveyed 666 (63.4%) and 704 (65.7%) patients with primary diagnosis in 2017 and 2018, respectively.Results. The survey showed almost no impact of external migration on tuberculosis epidemiology in St. Petersburg. Internal migrants counted 76 (11.4%) in 2017 and 96 (13.4%) in 2018, thus suggesting the majority of primary tuberculosis patients being permanent residents of St. Petersburg. The contribution of individuals with no fixed abode to the incidence rate was also insignificant, 2.4% and 1.9%. Most patients were unemployed people of working age, 236 (35.4%) in 2017, 261 (37.1%) in 2018. Incidence among students as a younger population was lowest, 2.1% and 2.8%. Smokers accounted for half of total patients, 370 (55.6%) and 368 (52.3%). One in five patients carried HIV infection, with half of them not receiving antiretroviral therapy. Patients with unfinished secondary education and residing in collective dwellings were significantly more frequent, whilst the proportion of persons with high income decreased. Over half of the patients had no family at primary diagnosis, and over a third had never been married.Conclusion. The social profile of primary tuberculosis in an urban area is as follows: single man, near 40 years old, permanent resident, unemployed, working-age, smoker, resides in private abode, has secondary or secondary vocational education, low to average income.

Patient Similarity Network of Newly Diagnosed Multiple Myeloma Identifies Patient Sub-groups with Distinct Genetic Features and Clinical Implications

The remarkable genetic heterogeneity of Multiple Myeloma poses a significant challenge for proper prognostication and clinical management of patients. Here, we introduce MM-PSN, the first multi-omics Patient Similarity Network of Myeloma. MM-PSN enabled accurate dissection of the genetic and molecular landscape of the disease and determined twelve distinct sub-groups defined by five data types generated from genomic and transcriptomic patient profiling of 655 patients. MM-PSN revealed that 1q gain is the most important single lesion conferring high risk of relapse and that it can improve on the current International Staging Systems (ISS and R-ISS). Several sub-groups uncovered novel associations between the gain of 1q and other adverse secondary lesions, thereby identifying the chromosomal hallmarks of sub-clonal heterogeneity and tumor progression in MM. We also determined gene vulnerabilities and potential therapeutic options for each sub-group and validated our prognostic model in an independent dataset.