Estimation and prediction for cancer screening models using deconvolution and smoothing

Biometrics

Volumn 57, Issue 2, 2001, Pages 389-395

  Pinsky, Paul F ^a  

^a NATIONAL CANCER INSTITUTE   (United States)

Author keywords

Cancer screening; Competing mortality; Convolution model; Deconvolution; Lead time; Over diagnosis; Sojourn time

Indexed keywords

CONVOLUTION; DIAGNOSIS; EXPONENTIAL FUNCTIONS;

CANCER SCREENING; COMPETING MORTALITY; CONVOLUTION MODEL; DECONVOLUTIONS; ESTIMATION AND PREDICTIONS; INCIDENCE FUNCTION; LEADTIME; OVER-DIAGNOSE; SCREENING MODELS; SOJOURN TIME;

DISEASES;

ARTICLE; CANCER INCIDENCE; CANCER SCREENING; HUMAN; MEASUREMENT; MORTALITY; PREDICTION; STATISTICAL MODEL;

EID: 0035001547     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2001.00389.x     Document Type: Article

References (11)

1. Chen, H. H., Duffy, S. W., and Tabar, L. (1996). A Markov chain method to estimate the tumor progression rate from preclinical to clinical phase, sensitivity and positive predictive value for mammography in breast cancer screening. The Statistician 45, 307-317.
2. Day, N. E. and Walter, S. D. (1984). Simplified models of screening for chronic disease: Estimation procedures from mass screening programmes. Biometrics 40, 1-14.
3. Duffy, S. W., Chen, H. H., Tabar, L., and Day, N. E. (1995). Estimation of mean sojourn time in breast cancer screening using a Markov chain model of both entry to and exit from the preclinical detectable phase. Statistics in Medicine 14, 1531-1543.
4. Launoy, G., Smith, T. C., Duffy, S. W., and Bouvier, V. (1997). Colorectal cancer mass-screening: Estimation of faecal occult blood test sensitivity, taking into account cancer mean sojourn time. International Journal of Cancer 73, 220-224.
5. Liao, J. and Brookmeyer, R. (1995). An empirical Bayes approach to smoothing backcalculation of HIV infection rates. Biometrics 51, 579-588.
6. Linz, P. (1985). Analytical and Numerical Methods for Volterra Equations. Philadelphia: SIAM.
7. O'Sullivan, F. (1986). A statistical perspective on ill-posed inverse problems. Statistical Science 1, 502-527.
8. Prevost, T. C., Launoy, G., Duffy, S. W., and Chen, H. H. (1998). Estimating sensitivity and sojourn time in screening for colorectal cancer. American Journal of Epidemiology 148, 609-619.
9. Ries, L. A. G., Kosary, C. L., Hankey, B. F., Miller, B. A., Clegg, L., and Edwards, B. K. (1999). SEER Cancer Statistics Review, 1973-1996. Bethesda, Maryland: National Cancer Institute.
10. Shen, Y. and Zelen, M. (1999). Parametric estimation procedures for screening programmes: Stable and nonstable disease models for multimodality case finding. Biometrika 86, 503-515.
11. Simonoff, J. B. (1996). Smoothing Methods in Statistics. New York: Springer.