{"title":"Predicting Liver Cancer Risk Using Comprehensive Medical History.","authors":"Tumen Sosorburam","doi":"10.1097/QMH.0000000000000521","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Liver cancer mortality is rising faster than any other cancer, significantly impacting life expectancy due to its relatively young median age at diagnosis and high mortality rate. There are currently no consistently recommended screening tests for liver cancer in individuals with a high-risk profile or abnormalities in body systems other than liver disease with cirrhosis. This study aims to screen various body system diseases that might be associated with liver cancer risk.</p><p><strong>Method: </strong>The study utilized the All of Us database, including 410 361 US-based adults aged 18 and above, of whom 2171 had liver cancer. Least Absolute Shrinkage and Selection Operator regression and logistic regression were used to identify significant predictors and calculate odds ratios (ORs). All statistical analyses were conducted using R software.</p><p><strong>Results: </strong>Out of the total participants, 0.5% had liver cancer diagnoses. Male gender and white race were associated with an increased risk of liver cancer (OR = 1.2). Certain diseases were strongly linked to a higher risk of liver cancer, such as liver cirrhosis, chronic steatorrhea, and neoplasms of unknown behavior in the genitourinary organs, each with an OR greater than 8. Digestive disorders, including pancreatic disorders and chronic hepatitis B and C, were also associated with an increased risk of liver cancer (OR > 4).</p><p><strong>Conclusion: </strong>The predictive model has the potential to enhance liver cancer outcomes by effectively targeting at-risk populations and by advocating for early screening among those with high-risk bodily diseases or specific diseases, which could impact survival rates.</p>","PeriodicalId":20986,"journal":{"name":"Quality Management in Health Care","volume":" ","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quality Management in Health Care","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/QMH.0000000000000521","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Liver cancer mortality is rising faster than any other cancer, significantly impacting life expectancy due to its relatively young median age at diagnosis and high mortality rate. There are currently no consistently recommended screening tests for liver cancer in individuals with a high-risk profile or abnormalities in body systems other than liver disease with cirrhosis. This study aims to screen various body system diseases that might be associated with liver cancer risk.
Method: The study utilized the All of Us database, including 410 361 US-based adults aged 18 and above, of whom 2171 had liver cancer. Least Absolute Shrinkage and Selection Operator regression and logistic regression were used to identify significant predictors and calculate odds ratios (ORs). All statistical analyses were conducted using R software.
Results: Out of the total participants, 0.5% had liver cancer diagnoses. Male gender and white race were associated with an increased risk of liver cancer (OR = 1.2). Certain diseases were strongly linked to a higher risk of liver cancer, such as liver cirrhosis, chronic steatorrhea, and neoplasms of unknown behavior in the genitourinary organs, each with an OR greater than 8. Digestive disorders, including pancreatic disorders and chronic hepatitis B and C, were also associated with an increased risk of liver cancer (OR > 4).
Conclusion: The predictive model has the potential to enhance liver cancer outcomes by effectively targeting at-risk populations and by advocating for early screening among those with high-risk bodily diseases or specific diseases, which could impact survival rates.
期刊介绍:
Quality Management in Health Care (QMHC) is a peer-reviewed journal that provides a forum for our readers to explore the theoretical, technical, and strategic elements of health care quality management. The journal''s primary focus is on organizational structure and processes as these affect the quality of care and patient outcomes. In particular, it:
-Builds knowledge about the application of statistical tools, control charts, benchmarking, and other devices used in the ongoing monitoring and evaluation of care and of patient outcomes;
-Encourages research in and evaluation of the results of various organizational strategies designed to bring about quantifiable improvements in patient outcomes;
-Fosters the application of quality management science to patient care processes and clinical decision-making;
-Fosters cooperation and communication among health care providers, payers and regulators in their efforts to improve the quality of patient outcomes;
-Explores links among the various clinical, technical, administrative, and managerial disciplines involved in patient care, as well as the role and responsibilities of organizational governance in ongoing quality management.