Background: Small cell lung cancer (SCLC) is called ‘smoker’s disease’ because it is strongly associated with smoking and most cases occur in smokers. However, it can also occur in never smokers. We investigated the clinical features of never smokers with SCLC and compared their treatment outcomes with those of smokers with SCLC. Methods: We retrospectively reviewed the clinical data of patients who had proven SCLC and had received chemotherapy at a single cancer center between July 2002 and April 2021. Results: Of 1,643 patients, 1,416 (86.2%) were enrolled in this study. A total of 162 (11.4%) and 1,254 (88.6%) patients were never smokers and smokers, respectively. There were more female never smokers than smokers (n=130; 80.2% vs. 79, 6.3%, p=0.000), and the incidence of ischemic heart disease was lower among never smokers than among smokers (4/1,416, [2.5%] vs. 83/1,416 [6.6%], p=0.036). Never smokers showed less symptoms at diagnosis than smokers (80.9% vs. 87.2%, p=0.037); however, they showed more toxicity after first-line treatment (61.7% vs. 47.8%, p=0.001). The objective response rate (ORR) was significantly higher in never smokers (74.1% vs. 59.6%, p=0.000). In the multivariate analysis, never smoking and second-line treatment were associated with a better ORR. However, progression-free survival and overall survival were not significantly different between never smokers and smokers. Conclusion In conclusion, never smokers accounted for 11.4% of patients with SCLC. They had distinguishing clinical characteristics and showed better chemotherapeutic responses than smokers.

Background: Insulin resistance (IR) is central to metabolic disorders and significantly influenced by diet. Studies on meal frequency (MF) and metabolic indicators have shown mixed results. This study explores the link between MF and IR in middle-aged and older adults. Methods: This prospective cohort study included 4,570 adults aged 40 to 69 years from the Korean Genome and Epidemiologic Study. MF were divided into two groups based on whether they consumed three or more, or fewer than three, meals daily. IR was evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR); participants were classified as IR if their HOMA-IR value was ≥2.5. Multiple Cox proportional hazard regression analyses were conducted to examine the association between MF and the incidence of IR. Results: After adjusting for all variables, individuals in the MF ≥3 group showed a reduced incidence of IR compared to those in the MF <3 group (hazard ratio, 0.880; 95% confidence interval, 0.782 to 0.990). Additionally, subgroup analyses by sex, diabetes mellitus (DM), and body mass index (BMI) showed that this association persisted only in men, individuals without DM, and those with a BMI <25. Conclusion Our findings indicate that a higher MF among middle-aged and older adults is associated with a reduced incidence of IR. However, this association was maintained only in men, individuals without DM, and those without obesity.

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: Insulin resistance (IR) is central to metabolic disorders and significantly influenced by diet. Studies on meal frequency (MF) and metabolic indicators have shown mixed results. This study explores the link between MF and IR in middle-aged and older adults. Methods: This prospective cohort study included 4,570 adults aged 40 to 69 years from the Korean Genome and Epidemiologic Study. MF were divided into two groups based on whether they consumed three or more, or fewer than three, meals daily. IR was evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR); participants were classified as IR if their HOMA-IR value was ≥2.5. Multiple Cox proportional hazard regression analyses were conducted to examine the association between MF and the incidence of IR. Results: After adjusting for all variables, individuals in the MF ≥3 group showed a reduced incidence of IR compared to those in the MF <3 group (hazard ratio, 0.880; 95% confidence interval, 0.782 to 0.990). Additionally, subgroup analyses by sex, diabetes mellitus (DM), and body mass index (BMI) showed that this association persisted only in men, individuals without DM, and those with a BMI <25. Conclusion Our findings indicate that a higher MF among middle-aged and older adults is associated with a reduced incidence of IR. However, this association was maintained only in men, individuals without DM, and those without obesity.

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: Small cell lung cancer (SCLC) is called ‘smoker’s disease’ because it is strongly associated with smoking and most cases occur in smokers. However, it can also occur in never smokers. We investigated the clinical features of never smokers with SCLC and compared their treatment outcomes with those of smokers with SCLC. Methods: We retrospectively reviewed the clinical data of patients who had proven SCLC and had received chemotherapy at a single cancer center between July 2002 and April 2021. Results: Of 1,643 patients, 1,416 (86.2%) were enrolled in this study. A total of 162 (11.4%) and 1,254 (88.6%) patients were never smokers and smokers, respectively. There were more female never smokers than smokers (n=130; 80.2% vs. 79, 6.3%, p=0.000), and the incidence of ischemic heart disease was lower among never smokers than among smokers (4/1,416, [2.5%] vs. 83/1,416 [6.6%], p=0.036). Never smokers showed less symptoms at diagnosis than smokers (80.9% vs. 87.2%, p=0.037); however, they showed more toxicity after first-line treatment (61.7% vs. 47.8%, p=0.001). The objective response rate (ORR) was significantly higher in never smokers (74.1% vs. 59.6%, p=0.000). In the multivariate analysis, never smoking and second-line treatment were associated with a better ORR. However, progression-free survival and overall survival were not significantly different between never smokers and smokers. Conclusion In conclusion, never smokers accounted for 11.4% of patients with SCLC. They had distinguishing clinical characteristics and showed better chemotherapeutic responses than smokers.

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.