Osteoporosis is a major health problem in our aging society. As a silent disease, diagnosis and risk assessment of osteoporosis rely on diagnostic tests. In the past decade, a great number of diagnostic techniques have been developed and used to assess bone density and quality. The accuracy and cost of these tests vary greatly. With such a variety of diagnostic tests, the clinicians must determine the best diagnostic strategy for specific patient populations, both for screening and for selecting and monitoring treatment. Because of the lack of appropriate statistical tools to assess diagnostic utility of combining multiple tests in their accuracy in predicting osteoporotic fractures and cost-effectiveness, it is difficult to identify the optimum combination of tests.
The specific aims of our study are the following: 1. Development of receiver operating characteristics (ROC) region analysis for parallel tests. 2. Development of recursive partitioning trees for test series using cost criteria. 3. Development of cost-effectiveness models of optimal decision thresholds for sequential tests. We will study theoretical properties, develop computer software for above statistical tools and apply them to examine the combinations of DXA, SXA, QCT, QUS, biomarkers, and epidemiological risk factors such as age, weight, fall rate, family and fracture history, etc., based on data from the Study of Osteoporotic Fractures (SOF) and simulation models using cost-effectiveness and population distribution parameters published in literature.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Small Research Grants (R03)
Project #
5R03AR047104-03
Application #
6628110
Study Section
Special Emphasis Panel (ZAR1-RJB-C (J1))
Program Officer
Lester, Gayle E
Project Start
2001-04-01
Project End
2005-01-31
Budget Start
2003-02-01
Budget End
2005-01-31
Support Year
3
Fiscal Year
2003
Total Cost
$73,750
Indirect Cost
Name
University of California San Francisco
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Jin, Hua; Lu, Ying (2011) Cost-saving tree-structured survival analysis for hip fracture of study of osteoporotic fractures data. Med Decis Making 31:299-307
Jin, Hua; Lu, Ying (2009) Permutation test for non-inferiority of the linear to the optimal combination of multiple tests. Stat Probab Lett 79:664-669
Jin, Hua; Lu, Ying (2009) A non-inferiority test of areas under two parametric ROC curves. Contemp Clin Trials 30:375-9
Shepherd, John A; Morgan, Sarah L; Lu, Ying (2008) Comparing BMD results between two similar DXA systems using the generalized least significant change. J Clin Densitom 11:237-42
Jin, Hua; Lu, Ying (2008) A procedure for determining whether a simple combination of diagnostic tests may be noninferior to the theoretical optimum combination. Med Decis Making 28:909-16
Jin, Hua; Lu, Ying; Stone, Kaite et al. (2004) Alternative tree-structured survival analysis based on variance of survival time. Med Decis Making 24:670-80
Jin, Hua; Lu, Ying; Harris, Steven T et al. (2004) Classification algorithms for hip fracture prediction based on recursive partitioning methods. Med Decis Making 24:386-98
Lu, Ying; Jin, Hua; Genant, Harry K (2003) On the non-inferiority of a diagnostic test based on paired observations. Stat Med 22:3029-44
Lu, Ying; Heller, Daniel N; Zhao, Shoujun (2002) Receiver operating characteristic (ROC) analysis for diagnostic examinations with uninterpretable cases. Stat Med 21:1849-65