The shape of the hazard function in breast carcinoma: Curability of the disease revisited

Cancer

Volumn 85, Issue 8, 1999, Pages 1789-1798

  Yakovlev, Andrej Y ^a   Tsodikov, Alexander D ^a   Boucher, Kenneth ^a   Kerber, Richard ^a  

^a UNIVERSITY OF UTAH   (United States)

Author keywords

Breast carcinoma; Cure rates; Hazard function; Survival analysis

Indexed keywords

ADULT; AGED; ARTICLE; BREAST CARCINOMA; CANCER SURVIVAL; CONVALESCENCE; FEMALE; HUMAN; MAJOR CLINICAL STUDY; PARAMETER; PRIORITY JOURNAL; PROBABILITY; PROGNOSIS; STATISTICAL ANALYSIS; TREATMENT OUTCOME;

ADULT; AGED; BREAST NEOPLASMS; CAUSE OF DEATH; FEMALE; FOLLOW-UP STUDIES; HUMANS; LIFE TABLES; MIDDLE AGED; MODELS, STATISTICAL; PROBABILITY; PROPORTIONAL HAZARDS MODELS; REGISTRIES; REGRESSION ANALYSIS; REMISSION INDUCTION; SURVIVAL ANALYSIS; SURVIVAL RATE; TREATMENT OUTCOME; UTAH;

EID: 0033561035     PISSN: 0008543X     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1097-0142(19990415)85:8<1789::AID-CNCR20>3.0.CO;2-Q     Document Type: Article

References (47)

1. Harris JR, Hellman S. Natural history of breast cancer. In: Harris JR, Lippman ME, Morrow M, Hellman S, editors. Diseases of the breast. Philadelphia: Lippincott-Raven Publishers, 1996;375-91.
2. Rutqvist LE, Wallgren, A. Long-term survival of 458 young breast cancer patients. Cancer 1985;55:658-62.
3. Rutqvist LE, Wallgren A, Nilsson B. Is breast cancer a curable disease? A study of 14,731 women with breast cancer from the Cancer Registry of Norway. Cancer 1984;53:1793-800.
4. Asselain B, Fourquet A, Hoang T, Tsodikov A, Yakovlev AY. A parametric regression model of tumor recurrence: an application to the analysis of clinical data on breast cancer. Stat Prob Lett 1996;29:271-8.
5. Klawansky S, Fox MS. A joint hazard and time scaling model to compare survival curves. Proc Natl Acad Sci USA 1996;93: 8183-8.
6. Zahl PH, Tretli S. Long-term survival of breast cancer in Norway by age and clinical stage. Stat Med 1997;16:1435-49.
7. Pocock SJ, Gore SM, Kerr GR. Long-term survival analysis: the curability of breast cancer. Stat Med 1982;1:93-104.
8. Maller RA, Zhou S. Survival analysis with long-term survivors. Chichester: John Wiley & Sons, 1996.
9. Berkson J, Cage RP. Survival curves for cancer patients following treatment. J Am Stat Assoc 1952;47:501-15.
10. Farewell VT. The use of mixture models for the analysis of survival data with long-term survivors. Biometrics 1982;38: 1041-6.
11. Miller RG. Survival analysis. New York: John Wiley & Sons, 1981.
12. Gordon NH. Application of the theory of finite mixtures for the estimation of "cure" rates of treated cancer patients. Stat Med 1990;9:397-407.
13. Bentzen SM, Johansen LV, Overgaard J, Thames HD. Clinical radiobiology of squamous cell carcinoma of the oropharynx. Int J Radiat Oncol Biol Phys 1991;20:1197-206.
14. Laska EM, Meisner MJ. Nonparametric estimation and testing in a cure model. Biometrics 1992;48:1223-34.
15. Sposto R, Sather HN, Baker SA. A comparison of tests of the difference in the proportion of patients who are cured. Biometrics 1992;48:87-99.
16. Cantor AB, Shuster JJ. Parametric versus nonparametric methods for estimating cure rates based on censored survival data. Stat Med 1992;11:931-7.
17. Mailer RA, Zhou S. Estimating the proportion of immunes in a censored sample. Biometrika 1992;79:731-9.
18. Mailer RA, Zhou S. Testing for sufficient follow-up and outliers in survival data. J Am Stat Assoc 1994;89:1499-506.
19. Maller RA, Zhou S. Testing for the presence of immune or cured individuals in censored survival data. Biometrics 1995; 51:1197-205.
20. Gamel JW, McLean IW, Rosenberg SH. Proportion cured and mean log survival time as functions of tumour size. Stat Med 1990;9:999-1006.
21. Gamel JW, Vogel RL, McLean IW. Assessing the impact of adjuvant therapy on cure rate for stage 2 breast carcinoma. Br J Cancer 1993;68:115-8.
22. Gamel JW, Vogel RL, Valagussa P, Bonadonna G. Parametric survival analysis of adjuvant therapy for Stage II breast cancer. Cancer 1994;74:2483-90.
23. Gamel JW, Vogel RL. A model of long-term survival following adjuvant therapy for stage 2 breast cancer. Br J Cancer 1993;68:1167-70.
24. Gamel JW, Meyer JS, Feuer E, Miller BA. The impact of stage and histology on the long-term clinical course of 163,808 patients with breast carcinoma. Cancer 1996;77:1459-69.
25. Yakovlev AY. Letter to the editor. Stat Med 1994;13:983-6.
26. Taylor JMG. Semi-parametric estimation in failure time mixture models. Biometrics 1995;51:899-907.
27. Yakovlev AY, Tsodikov AD. Stochastic models of tumor latency and their biostatistical applications. Singapore: World Scientific Publications, 1996.
28. Myasnikova EM, Asselain B, Yakovlev AY. Spline-based estimation of cure rates: an application to the analysis of breast cancer data. Math Comput Modelling (in press).
29. Cantor AB. Cure rate estimation using the polynomial Gompertz model [abstract]. In: The communication of statistics: exchange and dissemination. The 1997 spring meeting of the International Biometric Society. Eastern North American Region. 1997:144.
30. Yakovlev AY, Asselain B, Bardou V-J, Fourquet A, Hoang T, Rochefodiere A, et al. A simple stochastic model of tumor recurrence and its application to data on premenopausal breast cancer. In: Asselain B, Boniface M, Duby C, Lopez C, Masson JP, Tranchefort J, editors. Biometrie et analyse de donnees spatio-temporelles, vol 12.Rennes, France: Societe Franccaise de Biometrie, ENSA, 1993:66-82.
31. Tsodikov AD. A proportional hazards model taking account of long-term survivors. Biometrics 1998;54:138-46.
32. Percy C, Muir C. The international comparability of cancer mortality data. Results of an international death certificate study. Am J Epidemiol 1989;129:934-46.
33. Percy C, Stanek E, Gloeckler L. Accuracy of cancer death certificates and its effect on cancer mortality statistics. Am J Public Health 1981;71:242-50.
34. Teicher H. Identifiability of finite mixtures. Ann Math Stat 1961;32:244-8.
35. Yakowitz SJ, Spragins JD. On the idetifiability of finite mixtures. Ann Math Stat 1968;39:209-14.
36. Klein JP, Moeschberger ML. Survival analysis: techniques for censored and truncated data. New York: Springer Series in Statistics for Biology and Health, 1997.
37. Simonoff JS. Smoothing methods in statistics. New York: Springer Series in Statistics, 1996.
38. Kalbfleisch JD, Prentice RL. The statistical analysis of failure time data. New York: John Wiley & Sons, 1980.
39. Zhigljavsky A. Theory of global random search. Dordrecht: Kluwer, 1992.
40. Himmelblau DM. Applied nonlinear programming. Austin, TX: McGraw-Hill Book Company, 1972.
41. Pepe MS, Mori M. Kaplan-Meier, marginal or conditional probability curves in summarizing competing risks failure time data? Stat Med 1993;12:737-51.
42. Tsodikov A. Asymptotic efficiency of a proportional hazards model with cure. Stat Prob Lett 1998;39:237-44.
43. Gore SM, Pocock SJ, Kerr GR. Regression models and nonproportional hazards in the analysis of breast cancer survival. Appl Stat 1984;33:176-95.
44. Cox DR. Regression models and life tables, with discussion. J R Stat Soc B 1972;34:187-220.
45. Aalen OO. A linear regression model for the analysis of lifetimes. Stat Med 1989;8:907-25.
46. Aalen OO. Further results on the non-parametric linear regression model in survival analysis. Stat Med 1993;12:1569-88.
47. Etezadi-Amoli L, Ciampi A. Extended hazard regression for censored survival data with covariates: a spline approximation for the baseline hazard function. Biometrics 1987; 43:181-92.