Combining information from cancer registry and medical records data to improve analyses of adjuvant cancer therapies

Biometrics

Volumn 65, Issue 3, 2009, Pages 946-952

  He, Yulei ^a   Zaslavsky, Alan M ^a  

^a HARVARD MEDICAL SCHOOL   (United States)

Author keywords

Cancer registry data; Hierarchical Bayesian model; Medical records data; Misclassification; Missing data; Multiple imputation

Indexed keywords

BAYESIAN NETWORKS; CHEMOTHERAPY; DISEASES; RANDOM PROCESSES;

CANCER PATIENTS; CANCER REGISTRIES; CANCER REGISTRY DATA; CANCER THERAPY; HIERARCHICAL BAYESIAN MODELING; MEDICAL RECORD; MEDICAL RECORD DATA; MISCLASSIFICATIONS; MISSING DATA; MULTIPLE IMPUTATION;

RADIOTHERAPY;

CANCER; CLASSIFICATION; DISEASE TREATMENT; MODELING; RECORD;

ALGORITHM; ARTICLE; BAYES THEOREM; CANCER ADJUVANT THERAPY; CANCER COMBINATION CHEMOTHERAPY; CANCER RADIOTHERAPY; CANCER REGISTRY; CANCER STAGING; COLORECTAL CANCER; DATA ANALYSIS; HEALTH CARE QUALITY; MEDICAL RECORD; METHODOLOGY; MULTIVARIATE ANALYSIS; PROBABILITY; STATISTICAL MODEL; VALIDATION PROCESS;

ADOLESCENT; ADULT; ANTINEOPLASTIC AGENTS; BAYES THEOREM; CALIFORNIA; CHEMOTHERAPY, ADJUVANT; COLORECTAL NEOPLASMS; DATA COLLECTION; FEMALE; GUIDELINE ADHERENCE; HOSPITALS; HUMANS; MALE; MEDICAL RECORDS; MIDDLE AGED; NEOPLASM STAGING; QUALITY OF HEALTH CARE; REGISTRIES;

EID: 70349254457     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2008.01164.x     Document Type: Article

References (23)

1. Ayanian, J. Z., Zaslavsky, A. M., Fuchs, C. S., Guadagnoli, E., Creech, C. M., Cress, R. D., O'Connor, L. C., West, D. W., Allen, M. E., Wolf, R. E., and Wright, W. E. (2003). Use of adjuvant chemotherapy and radiation therapy for colorectal cancer in a population-based cohort. Journal of Clinical Oncoloy 21, 1293 1300.
2. Ayanian, J. Z., Chrischilles, E. A., Wallace, R. B., Fletcher, R. H., Fouad, M. N., Kiefe, C. I., Harrington, D. P., Weeks, J. C., Kahn, K. L., Malin, J. L., Lipscomb, J., Potosky, A. L., Provenzale, D. T., Sandler, R. S., Ryn, M. V., and West, D. W. (2004). Understanding cancer treatment and outcomes: The Cancer Care Outcomes Research and Surveillance Consortium. Journal of Clinical Oncology 22, 2992 2996.
3. Bickell, N. A. and Chassin, M. R. (2000). Determining the quality of breast cancer care: Do tumor registries measure up Annals of Internal Medicine 132, 705 710.
4. Carroll, R. J., Ruppert, D., Stefanski, L. A., and Crainiceau, C. M. (2006). Measurement Error in Nonlinear Models: A Modern Perspective, 3rd edition, New York : CRC Press.
5. Chib, S. and Greenberg, E. (1998). Analysis of multivariate probit models. Biometrika 85, 347 361.
6. Clayton, D. G. (1992). Models for the analysis of cohort and case-control studies with inaccurately measured exposures. In Statistical Models for Longitudinal Studies of Health, J. H. Dwyer, M. Feinlab, P. Lippert, et al. (eds 301 311. New York : Oxford University Press.
7. Cress, R. D., Zaslavsky, A. M., West, D. W., Wolf, R. E., Felter, M. C., and Ayanian, J. Z. (2003). Completeness of information on adjuvant chemotherapies for colorectal cancer in population-based cancer registries. Medical Care 41, 1006 1012.
8. Deyo, R. A., Cherkin, D. C., and Ciol, M. A. (1992). Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. Journal of Clinical Epidemiology 45, 613 619.
9. Gelfand, A. E., Racine-Poon, A., and Smith, A. F. M. (1990). Illustration of Bayesian inference in normal data models using Gibbs sampling. Journal of the American Statistical Association 85, 972 985.
10. Gelman, A. (2004). Parameterization and Bayesian modeling. Journal of the American Statistical Association 99, 537 545.
11. Gelman, A., Meng, X. L., and Stern, H. S. (1996). Posterior predictive assessment of model fitness via realized discrepancies (with discussion). Statistica Sinica 6, 733 807. (Pubitemid 126706389)
12. Gelman, A., Carlin, J. B., Stern, H. S., and Rubin, D. B. (2004). Bayesian Data Analysis, 2nd edition. New York : CRC Press.
13. Gilks, W. R., Best, N. G., and Tan, K. K. C. (1995). Adaptive rejection Metropolis sampling within Gibbs sampling. Applied Statistics 44, 455 472.
14. Hewitt, M. and Simone, J. V. (1999). Ensuring Quality Cancer Care. Washington, DC : National Academy Press.
15. Keating, N. L., Landrum, M. B., Landon, B. E., Ayanian, J. Z., Borbas, C., and Guadagnoli (2003). Measuring the quality of diabetes care using administrative data: Is there bias Health Services Research 38, 1529 1545.
16. Klabunde, C. N., Harlan, L. C., and Warren, J. L. (2006). Data sources for measuring comorbidity. Medical Care 44, 921 928.
17. Little, R. J. A. and Rubin, D. B. (2002). Statistical Analysis with Missing Data, 2nd edition, New York : Wiley.
18. Malin, J. L., Kahn, K. L., Adams, J., Kwan, L., Laouri, M., and Ganz, P. A. (2002). Validity of cancer registry data for measuring the quality of breast cancer care. Journal of the National Cancer Institute 94, 835 844. (Pubitemid 34705055)
19. National Institute of Health 1990). NIH Consensus Conference: Adjuvant therapy for patients with colon and rectal cancer. Journal of the American Medical Association 264, 1444 1450.
20. Rubin, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. New York : Wiley.
21. Rubin, D. B. (1996). Multiple imputation after 18+ years. Journal of the American Statistical Association 91, 473 489.
22. Yucel, R. M. and Zaslavsky, A. M. (2005). Imputation of binary treatment variables with measurement error in administrative data. Journal of the American Statistical Association 100, 1123 1132.
23. Zheng, H., Yucel, R. M., Ayanian, J. Z., and Zaslavsky, A. M. (2006). Profiling providers on use of adjuvant chemotherapy by combining cancer registry and medical record data. Medical Care 44, 1 7.