Purpose: Limited treatment options exist for patients with metastatic castration-resistant prostate cancer (mCRPC) after the failure of taxane-based chemotherapy and novel hormonal therapy. Here, we report the safety and efficacy of ifosfamide and mesna in patients with mCRPC after the failure of taxane-based chemotherapy and novel hormonal therapy (NCT06236789). Materials and Methods: Patients with histologically confirmed prostate cancer who had failed taxane-based chemotherapy and novel hormonal therapy received ifosfamide 2,500 mg/m2 and mesna 1,500 mg/m2 on days 1–3, repeated every 21 days. Safety, objective response rate, disease control rate, reduction in serum prostate-specific antigen (PSA) concentration by >50% (PSA50) or >90% (PSA90), radiographic progression-free survival (rPFS), and overall survival (OS) were analyzed. Results: A total of 47 patients with mCRPC were included in the study. The median number of lines of treatment was 5 (range, 3 to 7). All patients were previously administered docetaxel and novel hormonal therapies including abiraterone (51.1%) and/or enzalutamide (61.7%). Thirty-eight patients (80.9%) were administered cabazitaxel. The objective response and disease control rates were 21.3% and 80.9%, respectively. PSA50 and PSA90 were achieved in 31.9% and 10.6%, respectively. During a median follow-up duration of 54.3 months, rPFS and OS were 5.0 and 9.0 months, respectively. All the patients experienced treatment-related adverse events of any grades; however, no new safety signs were detected. Genomic biomarker analysis revealed that alterations in the TP53 pathway were associated with inferior rPFS and OS. Conclusion Ifosfamide and mesna showed appreciable efficacy and manageable safety profiles in heavily treated patients with mCRPC.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Environmental damage affects many aspects of healthcare, from extreme weather events to evolving population disease. Singapore's healthcare sector has the world's second highest healthcare emissions per capita, hampering the nation's pledge to reduce emissions by 2030 and achieve net zero emissions by 2050. In this review, we provide an overview of the impact environmental damage has on healthcare, including facilities, supply chain and human health, and examine measures to address healthcare's impact on the environment. Utilising the 'R's of sustainability - rethinking, reducing/refusing, reusing/repurposing/reprocessing, repairing, recycling and research - we have summarised the opportunities and challenges across medical disciplines. Awareness and advocacy to adopt strategies at institutional and individual levels is needed to revolutionise our environmental footprint and improve healthcare sustainability. By leveraging evidence from ongoing trials and integrating sustainable practices, our healthcare system can remain resilient against environment-driven challenges and evolving healthcare demands while minimising further impacts of environmental destruction.
Humans ; Climate Change ; Delivery of Health Care ; Singapore ; Conservation of Natural Resources ; Sustainable Development ; Environment

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.