Analysis of Dual Combination Therapies Used in Treatment of Hypertension in a Multinational Cohort

Lu, Yuan; Zandt, Mui Van; Liu, Yun; Li, Jing; Wang, Xialin; Chen, Yong; Chen, Zhengfeng; Cho, Jaehyeong; Dorajoo, Sreemanee Raaj; Feng, Mengling; Hsu, Min‐Huei; Hsu, Jason C; Iqbal, Usman; Jonnagaddala, Jitendra; Li, Yu-Chuan; Liaw, Siaw‐Teng; Lim, Hong–Seok; Ngiam, Kee Yuan; Nguyen, Phung‐Anh; Park, Rae Woong; Pratt, Nicole; Reich, Christian; Rhee, Sang Youl; Sathappan, Selva Muthu Kumaran; Shin, Seo Jeong; Tan, Hui Xing; You, Seng Chan; Zhang, Xin; Krumholz, Harlan M.; Suchard, Marc A.; Xu, Hua

doi:10.1001/jamanetworkopen.2022.3877

Cited by 12 publications

(13 citation statements)

References 31 publications

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“…However, in real‐life practice, BB + CCB dual therapy is underused in China 16 . Among hypertensive patients receiving dual treatment, the percentage of those receiving BB + CCB in China was much lower than those in the US, European countries, Australia, South Korea, and Singapore 16 . By comparing CV outcome associated with BB + CCB initial dual therapy versus other optimal initial dual therapies recommended by the Chinese guideline, 11 our study could provide some guidance for clinical practice regarding the use of BB + CCB in newly‐diagnosed hypertensive patients.…”

Section: Discussionmentioning

confidence: 99%

Cardiovascular outcomes of β‐blocker—calcium channel blocker initial dual therapy vs. other initial dual therapies in Chinese patients with hypertension: A real‐world retrospective study

Lin

Guo

et al. 2023

J of Clinical Hypertension

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This retrospective study compared cardiovascular (CV) outcomes between initial β‐blocker (BB) + calcium channel blocker (CCB) dual therapy (“B + C”) and other initial dual therapies in Chinese newly diagnosed hypertensive patients. In this study, all patients in a regional electronic database with newly diagnosed hypertension from January 01, 2012 to December 31, 2016 who received any initial optimal dual therapy recommended by the Chinese hypertension guideline were included. 1:2 propensity score matching (PSM) was used to balance baseline characteristics between patients receiving B + C and patients receiving other initial dual therapies (“Others”). The primary outcome was major adverse cardiovascular events (MACE) that occurred from January 01, 2012 to December 31, 2017, consisting of non‐fatal stroke, non‐fatal myocardial infarction (MI), non‐fatal chronic heart failure (CHF), and all‐cause death. Cox proportional hazard models were used to compare these CV outcomes in the 2 matched cohorts. After the PSM, 6227 patients receiving B + C and 12 454 patients receiving Others were included. Compared to patients receiving Others, patients receiving B + C had a significantly lower risk of MACE (hazard ratio [HR] 0.85; 95% confidential interval [CI] 0.78–0.92; p < .001), non‐fatal stroke (HR 0.89; 95% CI 0.81–0.98; p = .018) and non‐fatal CHF (HR 0.74; 95% CI 0.63–0.86; p < .0001). Additionally, differences in risks of non‐fatal MI and all‐cause death between the 2 treatment cohorts were not statistically significant. In conclusion, BB + CCB initial dual therapy was associated with a lower risk of MACE, stroke, and CHF than other optimal initial dual therapies recommended by the Chinese hypertension guideline in Chinese newly diagnosed hypertensive patients.

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Section: Discussionmentioning

confidence: 99%

Cardiovascular outcomes of β‐blocker—calcium channel blocker initial dual therapy vs. other initial dual therapies in Chinese patients with hypertension: A real‐world retrospective study

Lin

Guo

et al. 2023

J of Clinical Hypertension

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“…Benefit-risk assessments facilitate understanding of the potential consequences of various measures undertaken. Large-scale comparative effectiveness analyses have been performed using OMOP-CDM converted data [ 8 – 10 ]. While these are useful, the primary focus and presentation of results in these analyses tend to focus on presenting risks on a relative scale.…”

Section: Discussionmentioning

confidence: 99%

“…Individual data elements from source are translated to the standardized vocabularies and columns from various source tables are split or merged to fit into target table columns of the CDM [ 5 , 7 ]. CDM-converted databases may then facilitate multi-centre analyses and pooling of results to obtain more robust inferences for various study questions of interest [ 6 , 8 – 10 ].…”

Section: Introductionmentioning

confidence: 99%

Applying the OMOP Common Data Model to Facilitate Benefit-Risk Assessments of Medicinal Products Using Real-World Data from Singapore and South Korea

et al. 2022

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Objectives: The aim of this study was to characterize the benefits of converting Electronic Medical Records (EMRs) to a common data model (CDM) and to assess the potential of CDM-converted data to rapidly generate insights for benefit-risk assessments in post-market regulatory evaluation and decisions.Methods: EMRs from January 2013 to December 2016 were mapped onto the Observational Medical Outcomes Partnership-CDM (OMOP-CDM) schema. Vocabulary mappings were applied to convert source data values into OMOP-CDM-endorsed terminologies. Existing analytic codes used in a prior OMOP-CDM drug utilization study were modified to conduct an illustrative analysis of oral anticoagulants used for atrial fibrillation in Singapore and South Korea, resembling a typical benefit-risk assessment. A novel visualization is proposed to represent the comparative effectiveness, safety and utilization of the drugs.Results: Over 90% of records were mapped onto the OMOP-CDM. The CDM data structures and analytic code templates simplified the querying of data for the analysis. In total, 2,419 patients from Singapore and South Korea fulfilled the study criteria, the majority of whom were warfarin users. After 3 months of follow-up, differences in cumulative incidence of bleeding and thromboembolic events were observable via the proposed visualization, surfacing insights as to the agent of preference in a given clinical setting, which may meaningfully inform regulatory decision-making.Conclusions: While the structure of the OMOP-CDM and its accessory tools facilitate real-world data analysis, extending them to fulfil regulatory analytic purposes in the post-market setting, such as benefit-risk assessments, may require layering on additional analytic tools and visualization techniques.

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“…The TMUCRD retrieved data from various electronic medical records (EHR) of three hospitals, Taipei Medical University Hospital (TMUH), Wan-Fang Hospital (WFH), and Shuang-Ho Hospital (SHH). The database contains the electronic medical record data of 3.8 million people from 1998 to 2020, including structured data (e.g., basic information of patients, medical information, test reports, diagnosis results, treatment process, surgery, and medication history) and unstructured data (e.g., progress notes, pathology reports, and medical imaging reports) [ 17 ]. This study has been approved by the Joint Institute Review Board of Taipei Medical University (TMU-JIRB), Taipei, Taiwan (approval number N202101080).…”

Section: Methodsmentioning

confidence: 99%

Development and Validation of Novel Deep-Learning Models Using Multiple Data Types for Lung Cancer Survival

Hsu

Nguyen²,

Phuc³

et al. 2022

Cancers

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A well-established lung-cancer-survival-prediction model that relies on multiple data types, multiple novel machine-learning algorithms, and external testing is absent in the literature. This study aims to address this gap and determine the critical factors of lung cancer survival. We selected non-small-cell lung cancer patients from a retrospective dataset of the Taipei Medical University Clinical Research Database and Taiwan Cancer Registry between January 2008 and December 2018. All patients were monitored from the index date of cancer diagnosis until the event of death. Variables, including demographics, comorbidities, medications, laboratories, and patient gene tests, were used. Nine machine-learning algorithms with various modes were used. The performance of the algorithms was measured by the area under the receiver operating characteristic curve (AUC). In total, 3714 patients were included. The best performance of the artificial neural network (ANN) model was achieved when integrating all variables with the AUC, accuracy, precision, recall, and F1-score of 0.89, 0.82, 0.91, 0.75, and 0.65, respectively. The most important features were cancer stage, cancer size, age of diagnosis, smoking, drinking status, EGFR gene, and body mass index. Overall, the ANN model improved predictive performance when integrating different data types.

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Analysis of Dual Combination Therapies Used in Treatment of Hypertension in a Multinational Cohort

Abstract: This cohort study investigates differences in dual combination therapy use for hypertension in 8 countries and territories by country and patient demographic group.

Cited by 12 publications

References 31 publications

Cardiovascular outcomes of β‐blocker—calcium channel blocker initial dual therapy vs. other initial dual therapies in Chinese patients with hypertension: A real‐world retrospective study

Cardiovascular outcomes of β‐blocker—calcium channel blocker initial dual therapy vs. other initial dual therapies in Chinese patients with hypertension: A real‐world retrospective study

Applying the OMOP Common Data Model to Facilitate Benefit-Risk Assessments of Medicinal Products Using Real-World Data from Singapore and South Korea

Development and Validation of Novel Deep-Learning Models Using Multiple Data Types for Lung Cancer Survival

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