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Volumn 8, Issue 3, 2007, Pages 576-594

Estimating and modeling the cure fraction in population-based cancer survival analysis

Author keywords

Cure models; Relative survival; Survival analysis

Indexed keywords

AGED; ARTICLE; BIOMETRY; COLON TUMOR; FEMALE; HUMAN; MALE; MIDDLE AGED; MORTALITY; NEOPLASM; OVARY TUMOR; PROPORTIONAL HAZARDS MODEL; STATISTICAL MODEL; SURVIVAL; UNITED KINGDOM;

EID: 34648828972     PISSN: 14654644     EISSN: 14684357     Source Type: Journal    
DOI: 10.1093/biostatistics/kxl030     Document Type: Article
Times cited : (215)

References (35)
  • 4
    • 0030889042 scopus 로고    scopus 로고
    • Deriving more up-to-date estimates of long-term patient survival
    • BRENNER, H. AND GEFELLER, O. (1997). Deriving more up-to-date estimates of long-term patient survival. Journal of Clinical Epidemiology 50, 211-216.
    • (1997) Journal of Clinical Epidemiology , vol.50 , pp. 211-216
    • BRENNER, H.1    GEFELLER, O.2
  • 7
    • 0345597229 scopus 로고
    • Partitioning of a patient population with respect to different mortality patterns
    • CUTLER, S. J. AND AXTELL, L. M. (1963). Partitioning of a patient population with respect to different mortality patterns. Journal of the American Statistical Association 58, 701-712.
    • (1963) Journal of the American Statistical Association , vol.58 , pp. 701-712
    • CUTLER, S.J.1    AXTELL, L.M.2
  • 8
    • 0014643909 scopus 로고
    • Adjustments of long-term survival rates due to intercurrent disease
    • CUTLER, S. J. AND AZTELL, L. M. (1969). Adjustments of long-term survival rates due to intercurrent disease. Journal of Chronic Diseases 22, 485-495.
    • (1969) Journal of Chronic Diseases , vol.22 , pp. 485-495
    • CUTLER, S.J.1    AZTELL, L.M.2
  • 9
    • 0033611747 scopus 로고    scopus 로고
    • Mixture models for cancer survival analysis: Application to population-based data with covariates
    • DE ANGELIS, R., CAPOCACCIA, R., HAKULINEN, T., SODERMAN, B. AND VERDECCHIA, A. (1999). Mixture models for cancer survival analysis: application to population-based data with covariates. Statistics in Medicine 18, 441-454.
    • (1999) Statistics in Medicine , vol.18 , pp. 441-454
    • DE ANGELIS, R.1    CAPOCACCIA, R.2    HAKULINEN, T.3    SODERMAN, B.4    VERDECCHIA, A.5
  • 12
    • 0025285232 scopus 로고
    • Relative survival and the estimation of net survival: Elements for further discussion
    • ESTEVE, J., BENHAMOU, E., CROASDALE, M. AND RAYMOND, L. (1990). Relative survival and the estimation of net survival: elements for further discussion. Statistics in Medicine 9, 529-538.
    • (1990) Statistics in Medicine , vol.9 , pp. 529-538
    • ESTEVE, J.1    BENHAMOU, E.2    CROASDALE, M.3    RAYMOND, L.4
  • 16
    • 0020390843 scopus 로고
    • Cancer survival corrected for heterogeneity in patient withdrawal
    • HAKULINEN, T. (1982). Cancer survival corrected for heterogeneity in patient withdrawal. Biometrics 38, 933-942.
    • (1982) Biometrics , vol.38 , pp. 933-942
    • HAKULINEN, T.1
  • 17
    • 0000345820 scopus 로고
    • Regression analysis of relative survival rates
    • HAKULINEN, T. AND TENKANEN, L. (1987). Regression analysis of relative survival rates. Applied Statistics 36, 309-317.
    • (1987) Applied Statistics , vol.36 , pp. 309-317
    • HAKULINEN, T.1    TENKANEN, L.2
  • 18
    • 2642611572 scopus 로고
    • A two-parameter model for the survival curve of treated cancer patients
    • HAYBITTLE, J. L. (1965). A two-parameter model for the survival curve of treated cancer patients. Journal of the American Statistical Association 60, 16-26.
    • (1965) Journal of the American Statistical Association , vol.60 , pp. 16-26
    • HAYBITTLE, J.L.1
  • 19
    • 33747585552 scopus 로고    scopus 로고
    • Predicting the lung cancer burden: Accounting for selection of the patients with respect to general population mortality
    • HEINAVAARA, S. AND HAKULINEN, T. (2006). Predicting the lung cancer burden: accounting for selection of the patients with respect to general population mortality. Statistics in Medicine 25, 2967-2980.
    • (2006) Statistics in Medicine , vol.25 , pp. 2967-2980
    • HEINAVAARA, S.1    HAKULINEN, T.2
  • 21
    • 0035739153 scopus 로고    scopus 로고
    • Failure-time mixture models: Yet another way to establish efficacy
    • KOTI, K. M. (2001). Failure-time mixture models: yet another way to establish efficacy. Drug Information Journal 35, 1253-1260.
    • (2001) Drug Information Journal , vol.35 , pp. 1253-1260
    • KOTI, K.M.1
  • 22
    • 30944440022 scopus 로고    scopus 로고
    • Additive and multiplicative covariate regression models for relative survival incorporating fractional polynomials for time-dependent effects
    • LAMBERT, P. C., SMITH, L. K., JONES, D. R. AND BOTHA, J. L. (2005). Additive and multiplicative covariate regression models for relative survival incorporating fractional polynomials for time-dependent effects. Statistics in Medicine 24, 3871-3885.
    • (2005) Statistics in Medicine , vol.24 , pp. 3871-3885
    • LAMBERT, P.C.1    SMITH, L.K.2    JONES, D.R.3    BOTHA, J.L.4
  • 23
    • 0037093935 scopus 로고    scopus 로고
    • Estimating cancer prevalence using mixture models for cancer survival
    • PHILLIPS, N., COLDMAN, A. AND MCBRIDE, M. L. (2002). Estimating cancer prevalence using mixture models for cancer survival. Statistics in Medicine 21, 1257-1270.
    • (2002) Statistics in Medicine , vol.21 , pp. 1257-1270
    • PHILLIPS, N.1    COLDMAN, A.2    MCBRIDE, M.L.3
  • 24
    • 0016312195 scopus 로고
    • A log gamma model and its maximum likelihood estimation
    • PRENTICE, R. L. (1974). A log gamma model and its maximum likelihood estimation. Biometrika 61, 539-544.
    • (1974) Biometrika , vol.61 , pp. 539-544
    • PRENTICE, R.L.1
  • 25
    • 0009999141 scopus 로고
    • Lower confidence bounds for time to cure
    • RABINOWITZ, R. AND RYAN, L. (1993). Lower confidence bounds for time to cure. Biometrika 80, 681-687.
    • (1993) Biometrika , vol.80 , pp. 681-687
    • RABINOWITZ, R.1    RYAN, L.2
  • 26
    • 0000258857 scopus 로고    scopus 로고
    • Proportional excess hazards
    • SASIENI, P. D. (1996). Proportional excess hazards. Biometrika 83, 127-141.
    • (1996) Biometrika , vol.83 , pp. 127-141
    • SASIENI, P.D.1
  • 27
    • 1342281683 scopus 로고    scopus 로고
    • Providing more up-to-date estimates of patient survival: A comparison of standard survival analysis with period analysis using life-table methods and proportional hazards models
    • SMITH, L. K., LAMBERT, P. C., BOTHA, J. L. AND JONES, D. R. (2004). Providing more up-to-date estimates of patient survival: a comparison of standard survival analysis with period analysis using life-table methods and proportional hazards models. Journal of Clinical Epidemiology 57, 14-20.
    • (2004) Journal of Clinical Epidemiology , vol.57 , pp. 14-20
    • SMITH, L.K.1    LAMBERT, P.C.2    BOTHA, J.L.3    JONES, D.R.4
  • 28
    • 0037196195 scopus 로고    scopus 로고
    • Cure model analysis in cancer: An application to data from the Children's Cancer Group
    • SPOSTO, R. (2002). Cure model analysis in cancer: an application to data from the Children's Cancer Group. Statistics in Medicine 21, 293-312.
    • (2002) Statistics in Medicine , vol.21 , pp. 293-312
    • SPOSTO, R.1
  • 29
    • 0034021942 scopus 로고    scopus 로고
    • Estimation in a Cox proportional hazards cure model
    • SY, J. P. AND TAYLOR, J. M. (2000). Estimation in a Cox proportional hazards cure model. Biometrics 56, 227-236.
    • (2000) Biometrics , vol.56 , pp. 227-236
    • SY, J.P.1    TAYLOR, J.M.2
  • 30
    • 0029129572 scopus 로고
    • Semi-parametric estimation in failure time mixture models
    • TAYLOR, J. M. (1995). Semi-parametric estimation in failure time mixture models. Biometrics 51, 899-907.
    • (1995) Biometrics , vol.51 , pp. 899-907
    • TAYLOR, J.M.1
  • 31
    • 0037196899 scopus 로고    scopus 로고
    • Semi-parametric models of long- and short-term survival: An application to the analysis of breast cancer survival in Utah by age and stage
    • TSODIKOV, A. (2002). Semi-parametric models of long- and short-term survival: an application to the analysis of breast cancer survival in Utah by age and stage. Statistics in Medicine 21, 895-920.
    • (2002) Statistics in Medicine , vol.21 , pp. 895-920
    • TSODIKOV, A.1
  • 33
    • 0037202547 scopus 로고    scopus 로고
    • Estimation and projections of cancer prevalence from cancer registry data
    • VERDECCHIA, A., DE ANGELIS, G. AND CAPOCACCIA, R. (2002). Estimation and projections of cancer prevalence from cancer registry data. Statistics in Medicine 21, 3511-3526.
    • (2002) Statistics in Medicine , vol.21 , pp. 3511-3526
    • VERDECCHIA, A.1    DE ANGELIS, G.2    CAPOCACCIA, R.3
  • 34
    • 2942635215 scopus 로고    scopus 로고
    • Cure fraction estimation from the mixture cure models for grouped survival data
    • YU, B., TIWARI, R. C., CRONIN, K. A. AND FEUER, E. J. (2004). Cure fraction estimation from the mixture cure models for grouped survival data. Statistics in Medicine 23, 1733-1747.
    • (2004) Statistics in Medicine , vol.23 , pp. 1733-1747
    • YU, B.1    TIWARI, R.C.2    CRONIN, K.A.3    FEUER, E.J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.