One-month daily and three-month weekly rifapentine plus isoniazid are comparable in completion rate and safety for latent tuberculosis infection in non-HIV Population: a randomized controlled trial.

OBJECTIVES: The weekly rifapentine plus isoniazid for 3 months (3HP) improves completion rate of latent tuberculosis infection treatment, but flu-like symptoms are common. The novel 1HP regimen, involving daily rifapentine plus isoniazid for 28 days, has demonstrated low toxicity in HIV-infected populations. We aimed to investigate whether 1HP has a lower incidence rate of systemic drug reaction (SDR) compared with 3HP during treatment in non-HIV populations. METHODS: This randomized, multicentre trial compared the completion rate and risks of SDRs of 1HP and 3HP in aged ≥13 years non-HIV subjects with latent tuberculosis infection between September 2019 and September 2023 (ClinicalTrials.gov: NCT04094012). We also investigated associations between SDRs and plasma levels of drugs and their metabolites. RESULTS: A total of 251 and 239 individuals were randomly assigned to 1HP and 3HP groups, respectively, with completion rates of 82.9% (208/251) and 84.5% (202/239), respectively. Among them, 12.7% (32/251) and 10.9% (26/239) of 1HP and 3HP groups experienced SDRs, respectively (p 0.522), predominantly urticaria in 1HP group (59.4% [19/32]) and flu-like syndrome in 3HP group (80.8% [21/26]). Among participants experiencing SDRs, 43.8% (14/32) and 34.6% (9/26) in 1HP and 3HP groups, respectively, completed treatment (p 0.470). Cutaneous reactions were more common in 1HP than 3HP group (32.7% [82/251] vs. 13.0% [31/239], p < 0.001). In 1HP group, urticaria was associated with a higher plasma desacetyl-rifapentine level (ug/mL) at both 2 (median [interquartile range]: 36.06 [17.46-50.79] vs. 22.94 [14.67-31.65], p 0.018) and 6 hours (26.13 [15.80-53.06] vs. 29.83 [18.13-34.01], p 0.047) after dosing. DISCUSSION: In non-HIV population, the incidence rate of SDR under 1HP is not lower than 3HP. Notably, urticaria, rather than flu-like syndrome, was the predominant SDR associated 1HP. The findings of this study underscore the feasibility of 1HP regimen in non-HIV populations with a high-completion rate exceeding 80%.

Integrating predictive coding and a user-centric interface for enhanced auditing and quality in cancer registry data.

Data curation for a hospital-based cancer registry heavily relies on the labor-intensive manual abstraction process by cancer registrars to identify cancer-related information from free-text electronic health records. To streamline this process, a natural language processing system incorporating a hybrid of deep learning-based and rule-based approaches for identifying lung cancer registry-related concepts, along with a symbolic expert system that generates registry coding based on weighted rules, was developed. The system is integrated with the hospital information system at a medical center to provide cancer registrars with a patient journey visualization platform. The embedded system offers a comprehensive view of patient reports annotated with significant registry concepts to facilitate the manual coding process and elevate overall quality. Extensive evaluations, including comparisons with state-of-the-art methods, were conducted using a lung cancer dataset comprising 1428 patients from the medical center. The experimental results illustrate the effectiveness of the developed system, consistently achieving F1-scores of 0.85 and 1.00 across 30 coding items. Registrar feedback highlights the system's reliability as a tool for assisting and auditing the abstraction. By presenting key registry items along the timeline of a patient's reports with accurate code predictions, the system improves the quality of registrar outcomes and reduces the labor resources and time required for data abstraction. Our study highlights advancements in cancer registry coding practices, demonstrating that the proposed hybrid weighted neural-symbolic cancer registry system is reliable and efficient for assisting cancer registrars in the coding workflow and contributing to clinical outcomes.

Sputum bacterial microbiota signature as a surrogate for predicting disease progression of nontuberculous mycobacterial lung disease.

OBJECTIVES: Predicting progression of nontuberculous mycobacterial lung disease (NTM-LD) remains challenging. This study evaluated whether sputum bacterial microbiome diversity can be the biomarker and provide novel insights into related phenotypes and treatment timing. METHODS: We analyzed 126 sputum microbiomes of 126 patients with newly diagnosed NTM-LD due to Mycobacterium avium complex, M. abscessus complex, and M. kansasii between May 2020 and December 2021. Patients were followed for 2 years to determine their disease progression status. We identified consistently representative genera that differentiated the progressor and nonprogressor by using six methodologies. These genera were used to construct a prediction model using random forest with 5-fold cross validation. RESULTS: Disease progression occurred in 49 (38.6%) patients. Compared with nonprogressors, α-diversity was lower in the progressors. Significant compositional differences existed in the ß-diversity between groups (p=0.001). The prediction model for NTM-LD progression constructed using seven genera (Burkholderia, Pseudomonas, Sphingomonas, Candidatus Saccharibacteria, Phocaeicola, Pelomonas, and Phascolarctobacterium) with significantly differential abundance achieved an area under curve of 0.871. CONCLUSIONS: Identification of the composition of sputum bacterial microbiome facilitates prediction of the course of NTM-LD, and maybe used to develop precision treatment involving modulating the respiratory microbiome composition to ameliorate NTM-LD.

Clinical outcome of bevacizumab or ramucirumab combined with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors as the first line therapy in susceptible EGFR-mutated advanced non-small-cell lung.

Combining epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) with an anti- vascular endothelial growth factor (VEGF) agent, bevacizumab or ramucirumab, is indicated for advanced lung adenocarcinoma harboring EGFR mutation. This study aimed to show the real-world data of combination therapy and compare the effectiveness between bevacizumab and ramucirumab in combination with an EGFR-TKI. This retrospective study enrolled 47 patients diagnosed of stage IV lung adenocarcinoma with exon 19 deletion or L858R point mutation, receiving a first-line EGFR-TKI with anti-VEGF agent, including 34 (72%) and 13 (28%) patients receiving bevacizumab and ramucirumab, respectively. The response rate was similar in both groups (p = 0.38). Patients receiving bevacizumab had similar progression free survival (PFS) as those receiving ramucirumab (median PFS: 21.9 vs. 24.2 months, p = 0.4871); similar finding was noted in overall survival (OS) (median OS: 33.5 months vs. not reached, p = 0.4618). Patients receiving ramucirumab experienced a significantly high-grade hypertension compared to those receiving bevacizumab (p = 0.0351). Multivariable Cox regression analysis found independent risk factors for worse PFS included poorer ECOG performance status, multiple (≥3) metastatic sites, brain metastasis, and pleural metastasis/effusion, while the type of anti-VEGF agent was not a risk factor. Pericardial metastasis/effusion was the only one independent risk factor for worse OS. In summary, ramucirumab may have similar effectiveness as bevacizumab in combination with an EGFR-TKI as first line therapy for advanced lung adenocarcinoma harboring susceptible EGFR mutation. Further large-scale registry-based cohort studies may be needed to validate our findings.