Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Objective: To demonstrate the noninferiority of the novel hemostatic agent, Hemofence (BMI Korea Co., Ltd., thrombin cross-linked sodium hyaluronate gel matrix) compared to the established agent, Floseal Hemostatic Matrix (Baxter, thrombin-gelatin matrix) in achieving hemostasis for spinal surgeries, with secondary objectives to assess additional efficacy and safety. Methods: This clinical trial was a multicenter, randomized, subject-blinded, active-controlled, parallel-group, phase 3 study. Investigational drugs were administered to the first and second bleeding sites of each participant (or only to the first site if a second site was absent), evaluating hemostasis success rate within 10 minutes and the time to achieve hemostasis. Subsequent visits were conducted for safety assessments. For noninferiority test, a 97.5% one-sided confidence interval (CI) was used; the test group was deemed noninferior if the lower limit exceeded -10%. Results: This trial showed a 97.10% success rate in the test group and 96.05% in the control group for primary efficacy. The 95% CI (-4.90% to 7.44%) confirmed the test drug’s noninferiority. Time to hemostasis showed no significant difference between groups. All adverse events, adverse drug reactions, and serious adverse events were statistically similar between groups (p=1.000, p=0.243, and p=0.966, respectively). Conclusion A novel hemostatic agent, Hemofence, demonstrated an efficacy and safety profile comparable to that of Floseal.

Objective: To demonstrate the noninferiority of the novel hemostatic agent, Hemofence (BMI Korea Co., Ltd., thrombin cross-linked sodium hyaluronate gel matrix) compared to the established agent, Floseal Hemostatic Matrix (Baxter, thrombin-gelatin matrix) in achieving hemostasis for spinal surgeries, with secondary objectives to assess additional efficacy and safety. Methods: This clinical trial was a multicenter, randomized, subject-blinded, active-controlled, parallel-group, phase 3 study. Investigational drugs were administered to the first and second bleeding sites of each participant (or only to the first site if a second site was absent), evaluating hemostasis success rate within 10 minutes and the time to achieve hemostasis. Subsequent visits were conducted for safety assessments. For noninferiority test, a 97.5% one-sided confidence interval (CI) was used; the test group was deemed noninferior if the lower limit exceeded -10%. Results: This trial showed a 97.10% success rate in the test group and 96.05% in the control group for primary efficacy. The 95% CI (-4.90% to 7.44%) confirmed the test drug’s noninferiority. Time to hemostasis showed no significant difference between groups. All adverse events, adverse drug reactions, and serious adverse events were statistically similar between groups (p=1.000, p=0.243, and p=0.966, respectively). Conclusion A novel hemostatic agent, Hemofence, demonstrated an efficacy and safety profile comparable to that of Floseal.

Objective: To demonstrate the noninferiority of the novel hemostatic agent, Hemofence (BMI Korea Co., Ltd., thrombin cross-linked sodium hyaluronate gel matrix) compared to the established agent, Floseal Hemostatic Matrix (Baxter, thrombin-gelatin matrix) in achieving hemostasis for spinal surgeries, with secondary objectives to assess additional efficacy and safety. Methods: This clinical trial was a multicenter, randomized, subject-blinded, active-controlled, parallel-group, phase 3 study. Investigational drugs were administered to the first and second bleeding sites of each participant (or only to the first site if a second site was absent), evaluating hemostasis success rate within 10 minutes and the time to achieve hemostasis. Subsequent visits were conducted for safety assessments. For noninferiority test, a 97.5% one-sided confidence interval (CI) was used; the test group was deemed noninferior if the lower limit exceeded -10%. Results: This trial showed a 97.10% success rate in the test group and 96.05% in the control group for primary efficacy. The 95% CI (-4.90% to 7.44%) confirmed the test drug’s noninferiority. Time to hemostasis showed no significant difference between groups. All adverse events, adverse drug reactions, and serious adverse events were statistically similar between groups (p=1.000, p=0.243, and p=0.966, respectively). Conclusion A novel hemostatic agent, Hemofence, demonstrated an efficacy and safety profile comparable to that of Floseal.

Objective: To demonstrate the noninferiority of the novel hemostatic agent, Hemofence (BMI Korea Co., Ltd., thrombin cross-linked sodium hyaluronate gel matrix) compared to the established agent, Floseal Hemostatic Matrix (Baxter, thrombin-gelatin matrix) in achieving hemostasis for spinal surgeries, with secondary objectives to assess additional efficacy and safety. Methods: This clinical trial was a multicenter, randomized, subject-blinded, active-controlled, parallel-group, phase 3 study. Investigational drugs were administered to the first and second bleeding sites of each participant (or only to the first site if a second site was absent), evaluating hemostasis success rate within 10 minutes and the time to achieve hemostasis. Subsequent visits were conducted for safety assessments. For noninferiority test, a 97.5% one-sided confidence interval (CI) was used; the test group was deemed noninferior if the lower limit exceeded -10%. Results: This trial showed a 97.10% success rate in the test group and 96.05% in the control group for primary efficacy. The 95% CI (-4.90% to 7.44%) confirmed the test drug’s noninferiority. Time to hemostasis showed no significant difference between groups. All adverse events, adverse drug reactions, and serious adverse events were statistically similar between groups (p=1.000, p=0.243, and p=0.966, respectively). Conclusion A novel hemostatic agent, Hemofence, demonstrated an efficacy and safety profile comparable to that of Floseal.

Objective: To demonstrate the noninferiority of the novel hemostatic agent, Hemofence (BMI Korea Co., Ltd., thrombin cross-linked sodium hyaluronate gel matrix) compared to the established agent, Floseal Hemostatic Matrix (Baxter, thrombin-gelatin matrix) in achieving hemostasis for spinal surgeries, with secondary objectives to assess additional efficacy and safety. Methods: This clinical trial was a multicenter, randomized, subject-blinded, active-controlled, parallel-group, phase 3 study. Investigational drugs were administered to the first and second bleeding sites of each participant (or only to the first site if a second site was absent), evaluating hemostasis success rate within 10 minutes and the time to achieve hemostasis. Subsequent visits were conducted for safety assessments. For noninferiority test, a 97.5% one-sided confidence interval (CI) was used; the test group was deemed noninferior if the lower limit exceeded -10%. Results: This trial showed a 97.10% success rate in the test group and 96.05% in the control group for primary efficacy. The 95% CI (-4.90% to 7.44%) confirmed the test drug’s noninferiority. Time to hemostasis showed no significant difference between groups. All adverse events, adverse drug reactions, and serious adverse events were statistically similar between groups (p=1.000, p=0.243, and p=0.966, respectively). Conclusion A novel hemostatic agent, Hemofence, demonstrated an efficacy and safety profile comparable to that of Floseal.