ASCL1-mediated direct reprogramming: converting ventral midbrain astrocytes into dopaminergic neurons for Parkinson's disease therapy.

Parkinson's disease (PD), characterized by dopaminergic neuron degeneration in the substantia nigra, is caused by various genetic and environmental factors. Current treatment methods are medication and surgery; however, a primary therapy has not yet been proposed. In this study, we aimed to develop a new treatment for PD that induces direct reprogramming of dopaminergic neurons (iDAN). Achaete-scute family bHLH transcription factor 1 (ASCL1) is a primary factor that initiates and regulates central nervous system development and induces neurogenesis. In addition, it interacts with BRN2 and MYT1L, which are crucial transcription factors for the direct conversion of fibroblasts into neurons. Overexpression of ASCL1 along with the transcription factors NURR1 and LMX1A can directly reprogram iDANs. Using a retrovirus, GFP-tagged ASCL1 was overexpressed in astrocytes. One week of culture in iDAN convertsion medium reprogrammed the astrocytes into iDANs. After 7 days of differentiation, TH+/TUJ1+ cells emerged. After 2 weeks, the number of mature TH+/TUJ1+ dopaminergic neurons increased. Only ventral midbrain (VM) astrocytes exhibited these results, not cortical astrocytes. Thus, VM astrocytes can undergo direct iDAN reprogramming with ASCL1 alone, in the absence of transcription factors that stimulate dopaminergic neuron development.

Evaluating the HYDRASHIFT 2/4 Daratumumab assay: a powerful approach to assess treatment response in multiple myeloma.

OBJECTIVES: This study evaluates the HYDRASHIFT assay's effectiveness in mitigating daratumumab interference on serum protein tests during multiple myeloma (MM) treatment, aiming to ensure an accurate assessment of treatment response. METHODS: We analyzed 113 serum samples from 68 MM patients undergoing daratumumab treatment, employing both standard IF and the HYDRASHIFT assay. The assay's precision was determined through intra-day and inter-day variability assessments, while its specificity was verified using serum samples devoid of daratumumab. Comparative analysis of IF results, before and after the application of the HYDRASHIFT assay, facilitated the categorization of treatment responses in alignment with the International Myeloma Working Group's response criteria. RESULTS: The precision underscored the assay's consistent repeatability and reproducibility, successfully eliminating interference of daratumumab-induced Gκ bands. Specificity assessments demonstrated the assay's capability to distinguish daratumumab from both isatuximab and naturally occurring M-proteins. Of the analyzed cases, 91 exhibited successful migration of daratumumab-induced Gκ bands, thereby enhancing the accuracy of treatment response classification. The remaining 22 cases did not show a visible migration complex, likely due to the low concentration of daratumumab in the serum. These findings underscore the assay's critical role in distinguishing daratumumab from endogenous M-protein, particularly in samples with a single Gκ band on standard IF, where daratumumab and endogenous M-protein had co-migrated. CONCLUSIONS: The HYDRASHIFT assay demonstrates high precision, specificity, and utility in the accurate monitoring of treatment responses in MM patients receiving daratumumab. This assay represents a significant advancement in overcoming the diagnostic challenges posed by daratumumab interference.

Therapeutic Drug Monitoring of 6 New-Generation Antiseizure Medications Using a Mass Spectrometry Method: Analysis of 2-Year Experience in a Large Cohort of Korean Epilepsy Patients.

CONTEXT.­: New-generation antiseizure medications (ASMs) are increasingly prescribed, and therapeutic drug monitoring (TDM) has been proposed to improve clinical outcome. However, clinical TDM data on new-generation ASMs are scarce. OBJECTIVE.­: To develop and validate a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for therapeutic drug monitoring (TDM) of 6 new-generation ASMs in serum and analyze the clinical TDM data from a large cohort of Korean patients with epilepsy. DESIGN.­: Stable isotope-labeled internal standards were added to protein precipitations of serum. One microliter of sample was separated on Agilent Poroshell EC-C18 column, and lacosamide, perampanel, gabapentin, pregabalin, vigabatrin, and rufinamide were simultaneously quantified by Agilent 6460 triple-quad mass spectrometer in multiple-reaction monitoring mode. Linearity, sensitivity, precision, accuracy, specificity, carryover, extraction recovery, and matrix effect were evaluated. TDM data of 458 samples from 363 Korean epilepsy patients were analyzed. RESULTS.­: The method was linear with limit of detection less than 0.05 µg/mL in all analytes. Intraassay and interassay imprecisions were less than 5% coefficient of variation. Accuracy was within ±15% bias. Extraction recovery ranged from 85.9% to 98.8%. A total of 88% (403 of 458) were on polypharmacy, with 29% (118 of 403) using concomitant enzyme inducers. Only 38% (175 of 458) of the concentrations were therapeutic, with 53% (244 of 458) being subtherapeutic. Drug concentration and concentration-to-dose ratio were highly variable among individuals in all 6 ASMs. CONCLUSIONS.­: A simple and rapid LC-MS/MS method for TDM of 6 ASMs was developed and successfully applied to clinical practice. This large-scale TDM data could help establish an effective monitoring strategy for these drugs.

Clinical feature, GALC variant spectrum, and genotype-phenotype correlation in Korean Krabbe disease patients: Multicenter experience over 13 years.

Krabbe disease (KD) is an autosomal recessive neurodegenerative disorder caused by deficiency of the galactocerebrosidase (GALC) due to variants in the GALC gene. Here, we provide the first and the largest comprehensive analysis of clinical and genetic characteristics, and genotype-phenotype correlations of KD in Korean in comparison with other ethnic groups. From June 2010 to June 2023, 10 patients were diagnosed with KD through sequencing of GALC. Clinical features, and results of GALC sequencing, biochemical test, neuroimaging, and neurophysiologic test were obtained from medical records. An additional nine previously reported Korean KD patients were included for review. In Korean KD patients, the median age of onset was 2 years (3 months-34 years) and the most common phenotype was adult-onset (33%, 6/18) KD, followed by infantile KD (28%, 5/18). The most frequent variants were c.683_694delinsCTC (23%) and c.1901T>C (23%), while the 30-kb deletion was absent. Having two heterozygous pathogenic missense variants was associated with later-onset phenotype. Clinical features were similar to those of other ethnic groups. In Korean KD patients, the most common phenotype was the adult-onset type and the GALC variant spectrum was different from that of the Caucasian population. This study would further our understanding of KD.

Analysis of MicroRNA Signature Differentially Expressed in Pancreatic Islet Cells Treated with Pancreatic Cancer-Derived Exosomes.

Since the majority of patients with pancreatic cancer (PC) develop insulin resistance and/or diabetes mellitus (DM) prior to PC diagnosis, PC-induced diabetes mellitus (PC-DM) has been a focus for a potential platform for PC detection. In previous studies, the PC-derived exosomes were shown to contain the mediators of PC-DM. In the present study, the response of normal pancreatic islet cells to the PC-derived exosomes was investigated to determine the potential biomarkers for PC-DM, and consequently, for PC. Specifically, changes in microRNA (miRNA) expression were evaluated. The miRNA specimens were prepared from the untreated islet cells as well as the islet cells treated with the PC-derived exosomes (from 50 patients) and the healthy-derived exosomes (from 50 individuals). The specimens were subjected to next-generation sequencing and bioinformatic analysis to determine the differentially expressed miRNAs (DEmiRNAs) only in the specimens treated with the PC-derived exosomes. Consequently, 24 candidate miRNA markers, including IRS1-modulating miRNAs such as hsa-miR-144-5p, hsa-miR-3148, and hsa-miR-3133, were proposed. The proposed miRNAs showed relevance to DM and/or insulin resistance in a literature review and pathway analysis, indicating a potential association with PC-DM. Due to the novel approach used in this study, additional evidence from future studies could corroborate the value of the miRNA markers discovered.

Validation of an Algorithm to Identify Venous Thromboembolism in Health Insurance Claims Data Among Patients with Rheumatoid Arthritis.

Purpose: Health insurance claims databases provide an opportunity to study uncommon events, such as venous thromboembolism (VTE), in large patient populations. This study evaluated case definitions for identifying VTE among patients treated for rheumatoid arthritis (RA) using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes in claims data. Patients and Methods: Study participants were insured adults who received treatment for and had a diagnosis of RA between 2016 and 2020. After a 6-month covariate assessment window, patients were observed for ≥1 month until health plan disenrollment, occurrence of a presumptive VTE, or end of the study (12/31/2020). Presumptive VTEs were identified using predefined algorithms based on ICD-10-CM diagnosis codes, anticoagulant use, and care setting. Medical charts were abstracted to confirm the VTE diagnosis. Performance of primary and secondary (less stringent) algorithms was assessed by calculating the positive predictive value (PPV; primary and secondary objectives). Additionally, a linked electronic health record (EHR) claims database and abstracted provider notes were used as a novel alternative source to validate claims-based outcome definitions (exploratory objective). Results: A total of 155 charts identified with the primary VTE algorithm were abstracted. The majority of patients were female (73.5%), with mean (standard deviation) age 66.4 (10.7) years and Medicare insurance (80.6%). Obesity (46.8%), ever smoking (55.8%), and prior evidence of VTE (28.4%) were commonly reported in medical charts. The PPV for the primary VTE algorithm was 75.5% (117/155; 95% confidence interval [CI], 68.7%, 82.3%). A less stringent secondary algorithm had a PPV of 52.6% (40/76; 95% CI, 41.4%, 63.9%). Using an alternative EHR-linked claims database, the primary VTE algorithm PPV was lower, potentially due to the unavailability of relevant records for validation. Conclusion: Administrative claims data can be used to identify VTE among patients with RA in observational studies.

Automatic Detection of Intimate Partner Violence Victims from Social Media for Proactive Delivery of Support.

Social media platforms are increasingly being used by intimate partner violence (IPV) victims to share experiences and seek support. If such information is automatically curated, it may be possible to conduct social media based surveillance and even design interventions over such platforms. In this paper, we describe the development of a supervised classification system that automatically characterizes IPV-related posts on the social network Reddit. We collected data from four IPV-related subreddits and manually annotated the data to indicate whether a post is a self-report of IPV or not. Using the annotated data (N=289), we trained, evaluated, and compared supervised machine learning systems. A transformer-based classifier, RoBERTa, obtained the best classification performance with overall accuracy of 78% and IPV-self-report class 𝐹1 -score of 0.67. Post-classification error analyses revealed that misclassifications often occur for posts that are very long or are non-first-person reports of IPV. Despite the relatively small annotated data, our classification methods obtained promising results, indicating that it may be possible to detect and, hence, provide support to IPV victims over Reddit.

Patient Characteristics, Testing and Treatment Patterns, and Outcomes in EGFR-Mutated Advanced Non-Small Cell Lung Cancer: A Multinational, Real-World Study.

INTRODUCTION: Treatment landscape for advanced/metastatic NSCLC (aNSCLC) has evolved considerably over the past few decades with the advent of targeted therapies for epidermal growth factor receptor-mutated (EGFRm+) aNSCLC treatment. This study described real-world patient and disease characteristics, treatment and practice patterns, and clinical, economic, and patient-reported outcomes (PROs) in patients with EGFRm+ aNSCLC. METHODS: Data were derived from the Adelphi NSCLC Disease Specific Programme™ (DSP™), a point-in-time survey conducted between July and December 2020. The survey included oncologists and pulmonologists, and their consulting patients (with physician-confirmed EGFRm+ aNSCLC) from nine countries: the US, Brazil, the UK, Italy, France, Spain, Germany, Japan, and Taiwan. All analyses were descriptive. RESULTS: Overall, 542 physicians reported data for 2857 patients (mean age 65.6 years), and most patients were female (56.0%), white (61.0%), and had stage IV disease at initial diagnosis (76.0%), and adenocarcinoma histology (89.0%). Most patients received EGFR-tyrosine kinase inhibitors (TKI) therapy in first- (91.0%), second- (74.0%), and third-line (67.0%). The most common tumor samples and methods for EGFR detection were EGFR-specific mutation detection tests (44.0%) and core needle biopsy (56.0%). Median time to next treatment was 14.0 (IQR 8.0-22.0) months and disease progression was the main physician-reported reason for early discontinuation. The most common physician-reported disease symptoms were cough (51.0%), fatigue (37.0%), and dyspnea (33.0%). In patients assessed for PROs, mean EQ-5D-5L index and FACT-L health utility scores were 0.71 and 83.5, respectively. On average, patients lost 10.6 h of work/week for approximately 29.2 weeks due to EGFRm+ aNSCLC. CONCLUSION: This real-world multinational data set showed that most patients with EGFRm+ aNSCLC were treated per the country relevant clinical guidelines, with progression as the main reason for early treatment discontinuation. For the included countries, these findings may offer a useful benchmark for decision makers to determine future allocation of healthcare resources for patients with EGFRm+ aNSCLC.

The HAVEN study-hydroxychloroquine in ANCA vasculitis evaluation-a multicentre, randomised, double-blind, placebo-controlled trial: study protocol and statistical analysis plan.

BACKGROUND: Patients with non-severe ANCA-associated vasculitis (AAV) are often prescribed immunosuppressive medications that are associated with severe side effects and a reduced quality of life. There is an unmet need for safer effective treatments for these patients. Hydroxychloroquine is being explored due to its effect in similar autoimmune conditions such as systemic lupus erythematosus. METHODS: Double-blind, placebo-controlled multicentre trial recruiting 76 patients across 20 sites. Participants will be randomised 1:1 to hydroxychloroquine or placebo in addition to standard of care immunosuppressive therapies over the course of 52 weeks. A phase II selection design will be used to determine hdroxychloroquine's efficacy, using prednisolone dosage and Birmingham Vasculitis Activity Score as a measure of disease activity. Secondary outcomes will explore other elements of AAV progression, including disease flares and time to remission. DISCUSSION: This trial aims to explore Hydroxychloroquine as a treatment for patients with AAV. If effective, the need for immunosuppressive treatments such as prednisolone could be reduced. Hydroxychloroquine is safer, cheaper and has fewer adverse effects than conventional immunosuppressive treatments. This could improve patient outcomes while saving money for the NHS. TRIAL REGISTRATION: ISRCTN: ISRCTN79334891. Registered 07 June 2021. EudraCT: 2018-001268-40. Registered 13 September 2019. CLINICALTRIALS: gov: NCT04316494. Registered 20 March 2020.

Characteristics of Intimate Partner Violence and Survivor's Needs During the COVID-19 Pandemic: Insights From Subreddits Related to Intimate Partner Violence.

Intimate partner violence (IPV) increased during the COVID-19 pandemic. Collecting actionable IPV-related data from conventional sources (e.g., medical records) was challenging during the pandemic, generating a need to obtain relevant data from non-conventional sources, such as social media. Social media, like Reddit, is a preferred medium of communication for IPV survivors to share their experiences and seek support with protected anonymity. Nevertheless, the scope of available IPV-related data on social media is rarely documented. Thus, we examined the availability of IPV-related information on Reddit and the characteristics of the reported IPV during the pandemic. Using natural language processing, we collected publicly available Reddit data from four IPV-related subreddits between January 1, 2020 and March 31, 2021. Of 4,000 collected posts, we randomly sampled 300 posts for analysis. Three individuals on the research team independently coded the data and resolved the coding discrepancies through discussions. We adopted quantitative content analysis and calculated the frequency of the identified codes. 36% of the posts (n = 108) constituted self-reported IPV by survivors, of which 40% regarded current/ongoing IPV, and 14% contained help-seeking messages. A majority of the survivors' posts reflected psychological aggression, followed by physical violence. Notably, 61.4% of the psychological aggression involved expressive aggression, followed by gaslighting (54.3%) and coercive control (44.3%). Survivors' top three needs during the pandemic were hearing similar experiences, legal advice, and validating their feelings/reactions/thoughts/actions. Albeit limited, data from bystanders (survivors' friends, family, or neighbors) were also available. Rich data reflecting IPV survivors' lived experiences were available on Reddit. Such information will be useful for IPV surveillance, prevention, and intervention.

Oral Microbiome, Mental Health, and Sleep Outcomes During the COVID-19 Pandemic: An Observational Study in Chinese and Korean American Immigrants.

COVID-19 is a systemic disease whose effects are not limited to the respiratory system. The oral microbiome (OM)-brain axis is of growing interest in understanding the broader, neuropsychiatric, impacts of the COVID-19 pandemic through a systems biology lens. In this context, mental health and sleep disturbance are often reported by Asian Americans. In a cross-sectional observational study design, we examined the associations of the oral microbiome with mental health among Asian Americans during the COVID-19 pandemic (between November 2020 and April 2021). Participants (n = 20) were adult Chinese and Korean American immigrants in Atlanta, Georgia, and primarily born outside the United States (60%) with a mean age of 34.8 years ±14 (standard deviation). Participants reported depressive symptoms, anxiety, and sleep disturbance, as measured by standard questionnaires. The OM was characterized by 16S rRNA V3-V4 gene using saliva. Depressive symptoms and anxiety were reported by 60% (n = 12) of participants, whereas 35% (n = 7) reported sleep disturbance. The α-diversity was significantly associated with depressive symptoms, and marginally with anxiety. Participants with depressive symptoms and anxiety had enriched Rothia and Scardovia, respectively, whereas those without symptoms had enriched Fusobacterium. Individuals with sleep disturbance had enriched Kingella. In conclusion, this study suggests significant associations of the OM diversity with certain mental health dimensions such as depressive symptoms and anxiety. Specific taxa were associated with these symptoms. The present observations in a modest sample size suggest the possible relevance of the OM-brain axis in studies of mental health during COVID-19.

Factors Affecting Inpatients' Mortality through Intentional Self-Harm at In-Hospitals in South Korea.

This study aimed to identify the patient characteristics, comorbidities, risk factors, and means of the self-harm of patients who attempt self-harm in and outside of a hospital, and to determine the characteristics of death by suicide among survival and death patient groups in South Korea. This study used data from the Korean National Hospital Discharge In-depth Injury Survey conducted from 2007 to 2019. In total, 7192 outpatient participants and 43 inpatient participants performed self-harm. Frequency analysis, chi-square tests, Fisher's exact test, and logistic regression analysis were performed using STATA, version 15.0 (StataCorp), and statistical significance was set at 5%. Thirty-one inpatients who performed self-harm survived, and 12 died. Among male inpatients, the older they were, the higher the rates of self-harm and mortality rates due to falls and poisoning if they had comorbidities and financial problems. In addition, the rate of self-harm attempts within a short period after hospitalization was high. Our evidence of the characteristics of patients who performed self-harm in the hospital and the influencing factors of self-harm can be used as primary data for predicting patients at a high risk of self-harm and for creating preventative policies to reduce the risk of self-harm among inpatients in South Korea.

Risk thresholds for patients to switch between daily tablets and biweekly infusions in second-line treatment for advanced hepatocellular carcinoma: a patient preference study.

BACKGROUND: Historically, high hepatocellular carcinoma (HCC)-related mortality has been, in part, due to lack of effective therapies; however, several systemic therapies have been recently approved for HCC treatment, including regorafenib and ramucirumab. These two treatments utilize different routes of administration (four daily tablets and biweekly intravenous infusions, respectively) and have different risks of adverse events (AEs). However, we lack data on patient preferences in balancing the route of administration and risk of AEs in patients with HCC. We aimed to determine patient preferences and trade-offs for second-line treatment in patients with HCC.  METHODS: Patients with advanced or metastatic HCC were recruited through their physicians for this study. Patient preferences were assessed by using a modified threshold technique (TT) design in which respondents were asked two direct-elicitation questions before (assuming same safety and efficacy and only varying mode of administration) and after (incorporating the safety profiles of ramucirumab and regorafenib) the TT series on seven risks of clinically relevant AEs. RESULTS: In total, of the 157 patients recruited by their physicians, 150 were eligible and consented to participate. In the first elicitation question (assuming risk and efficacy were equivalent), 61.3% of patients preferred daily tablets. However, 76.7% of patients preferred the biweekly infusion when the safety profiles of the two available second-line therapies were included. The TT analysis confirmed that preferences for oral administration were not strong enough to balance out the risk of AEs that differentiate the two therapies. DISCUSSION: We found that when patients were asked to choose between a daily, oral medication and a biweekly IV medication for HCC, they were more likely to choose a daily, oral medication if efficacy and safety profiles were the same. However, when risks of AEs representing the safety profiles of two currently available second-line treatments were introduced in a second direct-elicitation question, respondents often selected an IV administration with a safety profile similar to ramucirumab, rather than oral tablets with a safety profile similar to regorafenib. Our findings indicate that the risk profile of a second-line treatment for HCC may be more important than the mode of administration to patients.

Efficient Generation of Dopaminergic Neurons from Mouse Ventral Midbrain Astrocytes.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by tremors, bradykinesia, and rigidity. PD is caused by loss of dopaminergic (DA) neurons in the midbrain substantia nigra (SN) and therefore, replenishment of DA neurons via stem cell-based therapy is a potential treatment option. Astrocytes are the most abundant non-neuronal cells in the central nervous system and are promising candidates for reprogramming into neuronal cells because they share a common origin with neurons. The ability of neural progenitor cells (NPCs) to proliferate and differentiate may overcome the limitations of the reduced viability and function of transplanted cells after cell replacement therapy. Achaete-scute complex homolog-like 1 (Ascl1) is a wellknown neuronal-specific factor that induces various cell types such as human and mouse astrocytes and fibroblasts to differentiate into neurons. Nurr1 is involved in the differentiation and maintenance of DA neurons, and decreased Nurr1 expression is known to be a major risk factor for PD. Previous studies have shown that direct conversion of astrocytes into DA neurons and NPCs can be induced by overexpression of Ascl1 and Nurr1 and additional transcription factors genes such as superoxide dismutase 1 and SRY-box 2. Here, we demonstrate that astrocytes isolated from the ventral midbrain, the origin of SN DA neurons, can be effectively converted into DA neurons and NPCs with enhanced viability. In addition, when these NPCs are inducted to differentiate, they exhibit key characteristics of DA neurons. Thus, direct conversion of midbrain astrocytes is a possible cell therapy strategy to treat neurodegenerative diseases.

Automatic Detection of Twitter Users Who Express Chronic Stress Experiences via Supervised Machine Learning and Natural Language Processing.

Americans bear a high chronic stress burden, particularly during the COVID-19 pandemic. Although social media have many strengths to complement the weaknesses of conventional stress measures, including surveys, they have been rarely utilized to detect individuals self-reporting chronic stress. Thus, this study aimed to develop and evaluate an automatic system on Twitter to identify users who have self-reported chronic stress experiences. Using the Twitter public streaming application programming interface, we collected tweets containing certain stress-related keywords (eg, "chronic," "constant," "stress") and then filtered the data using pre-defined text patterns. We manually annotated tweets with (without) self-report of chronic stress as positive (negative). We trained multiple classifiers and tested them via accuracy and F1 score. We annotated 4195 tweets (1560 positives, 2635 negatives), achieving an inter-annotator agreement of 0.83 (Cohen's kappa). The classifier based on Bidirectional Encoder Representation from Transformers performed the best (accuracy of 83.6% [81.0-86.1]), outperforming the second best-performing classifier (support vector machines: 76.4% [73.5-79.3]). The past tweets from the authors of positive tweets contained useful information, including sources and health impacts of chronic stress. Our study demonstrates that users' self-reported chronic stress experiences can be automatically identified on Twitter, which has a high potential for surveillance and large-scale intervention.

Reduced Cytotoxicity by Repetitive mRNA Transfection in Differentiated Neurons.

Background and Objectives: mRNA-based protein expression technology has been used to express functional proteins. We have previously generated dopamine neurons from rat-embryo derived neural precursor cells (NPCs) through repeated transfection of synthetic transcription factor mRNA encoding dopamine-inducible genes. However, NPCs began to die approximately 10 d post-transfection. In this study, we examined a long-term transfection protocol that did not affect cell viability. Methods and Results: Experiments were performed in eight groups sorted according to the start date of mRNA transfection. mRNA was transfected into NPCs daily for 21 d and live cell images of each group were recorded. NPCs which were differentiated for more than five days showed sustained gene expression and appreciable viability despite daily mRNA transfection for 21 d. Conclusions: Repeated mRNA transfection requires cells with a sufficient differentiation period.

Treatment Patterns, Clinical Outcomes and Health Care Resource Utilisation in Patients with EGFR-mutated Metastatic Non-Small Cell Lung Cancer: A Real-World Study in South Korea.

BACKGROUND: Despite the dynamic treatment landscape for EGFR mutant-positive metastatic non-small cell lung cancer (EGFRm+ mNSCLC), most of the earlier studies have focused on US or Western populations. OBJECTIVE: The objective of this study was to explore real-world treatment patterns and outcomes of South Korean patients with EGFRm+ mNSCLC. METHODS: Retrospective chart review of adult patients with EGFRm+ mNSCLC who received systemic treatment between January-2019 and June-2019. RESULTS: A total of 162 patients were included from 21 hospitals, with a median follow-up of 15.6 months. Median age was 65.0 years, 22% had central nervous system metastasis, and 57% and 38% had exon 19 deletion and exon 21 L858R, respectively. Among 144 patients (89%) who received first-line EGFR-tyrosine kinase inhibitor, afatinib was most the common (44%), followed by gefitinib (28%) and erlotinib (13%). First-line chemotherapy was more common when an EGFR-mutation was detected after versus before first-line treatment initiation (31% vs 5%). Discontinuation of first-line treatment was mostly due to disease-progression (81%) and toxicity (7%). Among 58 (78%) patients who received second-line treatment, osimertinib was the most common (40%). Most (60%) patients reported ≥1 Grade ≥3 adverse event during first-line treatment. Following initiation of first-line treatment, physician visits and chest X-rays were the most frequent healthcare utilisation events. Rates of emergency-room visits and hospitalization were 12% and 16%, respectively, with a mean length-of-stay of 10.4 days. At 12 months, overall survival rate was 95%, and numerically worse for patients with exon 21 versus 19 mutations. CONCLUSIONS: Characteristics and clinical outcomes of Korean patients with EGFRm+ mNSCLC in real-world practice were comparable to those observed in clinical trials. As osimertinib was not reimbursed for first-line treatment before study completion, further investigation is warranted to explore evolving treatment practice.

Lessons from a Customer Discovery Study: a Technology-Based Cancer Support Program for Asian American Breast Cancer Survivors.

PURPOSE: A culturally tailored technology-based cancer support program was recently developed and tested among Asian American breast cancer survivors. To explore future opportunities to sustain the program, the research team participated in the SPeeding Research-tested INTervention (SPRINT) program sponsored by the National Cancer Institute. The purpose of this discussion paper is to share the lessons that the research team gained from a customer discovery study through the SPRINT program. METHODS: During the SPRINT program, a total of 73 stakeholders were recruited through a snowball sampling across the globe. Semi-structured interviews were conducted for customer discovery through WebEX, phone calls, and in-person visits (50 in-person interviews, 4 phone interviews, and 19 WebEx interviews). All the interviews were recorded using audio-taping or writing memos. Also, the research team wrote memos on the issues/concerns related to the project during the interview process. Then, the transcripts and memos were analyzed using a content analysis to provide evidence for the lessons. RESULTS: The themes reflecting the lessons from the customer discovery study included (a) "who are the stakeholders"; (b) "depending on stakeholders"; (c) "what works or not"; (d) "personal versus family responsibilities"; and (e) "depending on countries' situations." CONCLUSION: These lessons could provide directions for future development and implementation of technology-based cancer support programs for Asian American breast cancer survivors.

A Pilot Study of the Gut Microbiota Associated With Depressive Symptoms and Sleep Disturbance Among Chinese and Korean Immigrants in the United States.

CONTEXT: Depression is prevalent among Asian Americans (AsA) during the COVID-19 pandemic, and depression often leads to sleep disturbance in this population. The gut microbiota (GM) plays a critical role in mental health and sleep quality, and the composition of the GM is largely unknown among AsA. OBJECTIVES: Examine associations of the GM with depressive symptoms and sleep disturbance among Chinese and Korean American immigrants. METHODS: Depressive symptoms (PROMIS Short Form-Depression) and sleep quality (Pittsburgh Sleep Quality Index [PSQI]) were collected via surveys. PROMIS measure T-score > 55 indicates positive depressive symptoms, and a total PSQI score > 5 indicates sleep disturbance. 16S rRNA V3-V4 gene regions were sequenced from fecal specimens to measure GM. Permutational multivariate analysis of variance and linear discriminant analysis effect size were applied to examine associations of the GM with symptoms. RESULTS: Among 20 participants, 55% (n = 11) reported depressive symptoms and 35% (n = 7) reported sleep disturbance. A higher α-diversity was marginally associated with lower depressive symptoms: Chao1 (r = -0.39, p = 0.09) and Shannon index (r = -0.41, p = 0.08); ß-diversity distinguished participants between categories of depressive symptoms (weighted UniFrac, p=0.04) or sleep disturbance (Jaccard, p=0.05). Those with depressive symptoms showed a higher abundance of Actinobacteria, while those without depressive symptoms had a higher abundance of Bacteroidetes. No significant taxa were identified for sleep disturbance. CONCLUSIONS: Gut microbial diversity showed promising associations with depressive symptoms and sleep disturbance among Chinese and Korean immigrants. Specific taxa were identified as associated with depressive symptoms. Future studies with a larger sample size are warranted to confirm our findings.

Can adverse childhood experiences predict chronic health conditions? Development of trauma-informed, explainable machine learning models.

Introduction: Decades of research have established the association between adverse childhood experiences (ACEs) and adult onset of chronic diseases, influenced by health behaviors and social determinants of health (SDoH). Machine Learning (ML) is a powerful tool for computing these complex associations and accurately predicting chronic health conditions. Methods: Using the 2021 Behavioral Risk Factor Surveillance Survey, we developed several ML models-random forest, logistic regression, support vector machine, Naïve Bayes, and K-Nearest Neighbor-over data from a sample of 52,268 respondents. We predicted 13 chronic health conditions based on ACE history, health behaviors, SDoH, and demographics. We further assessed each variable's importance in outcome prediction for model interpretability. We evaluated model performance via the Area Under the Curve (AUC) score. Results: With the inclusion of data on ACEs, our models outperformed or demonstrated similar accuracies to existing models in the literature that used SDoH to predict health outcomes. The most accurate models predicted diabetes, pulmonary diseases, and heart attacks. The random forest model was the most effective for diabetes (AUC = 0.784) and heart attacks (AUC = 0.732), and the logistic regression model most accurately predicted pulmonary diseases (AUC = 0.753). The strongest predictors across models were age, ever monitored blood sugar or blood pressure, count of the monitoring behaviors for blood sugar or blood pressure, BMI, time of last cholesterol check, employment status, income, count of vaccines received, health insurance status, and total ACEs. A cumulative measure of ACEs was a stronger predictor than individual ACEs. Discussion: Our models can provide an interpretable, trauma-informed framework to identify and intervene with at-risk individuals early to prevent chronic health conditions and address their inequalities in the U.S.