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Parametric relative survival regression using generalized linear models with application to Hodgkin's lymphoma
Author(s) -
Weller E. A.,
Feuer E. J.,
Frey C. M.,
Wesley M. N.
Publication year - 1999
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/1467-9876.00141
Subject(s) - procarbazine , relative survival , survival analysis , statistics , population , weibull distribution , medicine , proportional hazards model , oncology , mathematics , vincristine , chemotherapy , cancer registry , cyclophosphamide , environmental health
Changes in survival rates during 1940–1992 for patients with Hodgkin's disease are studied by using population‐based data. The aim of the analysis is to identify when the breakthrough in clinical trials of chemotherapy treatments started to increase population survival rates, and to find how long it took for the increase to level off, indicating that the full population effect of the breakthrough had been realized. A Weibull relative survival model is used because the model parameters are easily interpretable when assessing the effect of advances in clinical trials. However, the methods apply to any relative survival model that falls within the generalized linear models framework. The model is fitted by using modifications of existing software (SAS, GLIM) and profile likelihood methods. The results are similar to those from a cause‐specific analysis of the data by Feuer and co‐workers. Survival started to improve around the time that a major chemotherapy breakthrough (nitrogen mustard, Oncovin, prednisone and procarbazine) was publicized in the mid 1960s but did not level off for 11 years. For the analysis of data where the cause of death is obtained from death certificates, the relative survival approach has the advantage of providing the necessary adjustment for expected mortality from causes other than the disease without requiring information on the causes of death.