The long term objective of this proposal is to develop statistical methodology for the analysis of nonlinear growth data. Growth data are repeated measurements over time of some characteristic of an individual. They are used in epidemiological treatment and prevention research to study individual's changing response over time, and the effects of treatment or exposures on this response. Specifically, we will (1) develop a parametric family of tumor growth curves which describes known behaviors of tumor response to therapeutic treatment, (2) develop efficient statistical techniques for estimating and analyzing characteristics of nonlinear growth curves, and relating them to other covariates, and (3) develop and implement computer software for analysis of growth curve characteristics. We propose a two-step approach which involves (1) separately fitting each individual's growth curve and estimating the growth curve characteristics and (2) analyzing these characteristics in a generalized linear model which reflects the uncertainty due to estimation error from both steps of the procedure. We will test the tumor growth curve model and the statistical methodology on tumor growth delay data from radiobiology and tumor biology data. Future directions include extending these results to multivariate analyses and pulmonary function data.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA052192-03
Application #
2094638
Study Section
Epidemiology and Disease Control Subcommittee 2 (EDC)
Project Start
1990-12-07
Project End
1994-11-30
Budget Start
1992-12-01
Budget End
1994-11-30
Support Year
3
Fiscal Year
1993
Total Cost
Indirect Cost
Name
Dartmouth College
Department
Family Medicine
Type
Schools of Medicine
DUNS #
041027822
City
Hanover
State
NH
Country
United States
Zip Code
03755
Robertson, Douglas J; Stukel, Therese A; Gottlieb, Daniel J et al. (2009) Survival after hepatic resection of colorectal cancer metastases: a national experience. Cancer 115:752-9
Demidenko, Eugene; Stukel, Therese A (2005) Influence analysis for linear mixed-effects models. Stat Med 24:893-909
Fisher, Elliott S; Wennberg, David E; Stukel, Therese A et al. (2003) The implications of regional variations in Medicare spending. Part 1: the content, quality, and accessibility of care. Ann Intern Med 138:273-87
Fisher, Elliott S; Wennberg, David E; Stukel, Therese A et al. (2003) The implications of regional variations in Medicare spending. Part 2: health outcomes and satisfaction with care. Ann Intern Med 138:288-98
Stukel, T A; Demidenko, E; Dykes, J et al. (2001) Two-stage methods for the analysis of pooled data. Stat Med 20:2115-30
O'Hara, J A; Goda, F; Demidenko, E et al. (1998) Effect on regrowth delay in a murine tumor of scheduling split-dose irradiation based on direct pO2 measurements by electron paramagnetic resonance oximetry. Radiat Res 150:549-56
Tosteson, T D; Buonaccorsi, J P; Demidenko, E (1998) Covariate measurement error and the estimation of random effect parameters in a mixed model for longitudinal data. Stat Med 17:1959-71
Stukel, T A; Demidenko, E (1997) Two-stage method of estimation for general linear growth curve models. Biometrics 53:720-8
Stukel, T A; Glynn, R J; Fisher, E S et al. (1994) Standardized rates of recurrent outcomes. Stat Med 13:1781-91
Stukel, T A (1993) Comparison of methods for the analysis of longitudinal interval count data. Stat Med 12:1339-51