PURPOSE: This study evaluated whether males without partners were disadvantaged for survival in Radiation Therapy Oncology Group (RTOG) head and neck cancer clinical trials. METHODS: Patients treated on three RTOG trials were studied. The Cox proportional hazards model was used to determine if sex and the interaction between sex and marital/partner status were independent prognostic variables for overall survival controlling for Karnofsky performance status, tumor stage, nodal stage, primary site, and protocol treatment. RESULTS: A total of 1,901 patients (1,509 men) were entered onto the three RTOG trials, with 1,822 (1,438 men) analyzable patients. Prognostic variables independent of disease-related variables for survival in multivariate analyses restricted to men were age, marital/partner status, and income. CONCLUSION: The apparent disadvantage of unpartnered men is striking, even after controlling for disease and other demographic variables. Possible explanations could easily be tested in observational studies, leading to evaluation of simple interventions to improve their outcome.
PURPOSE: This study evaluated whether males without partners were disadvantaged for survival in Radiation Therapy Oncology Group (RTOG) head and neck cancer clinical trials. METHODS:Patients treated on three RTOG trials were studied. The Cox proportional hazards model was used to determine if sex and the interaction between sex and marital/partner status were independent prognostic variables for overall survival controlling for Karnofsky performance status, tumor stage, nodal stage, primary site, and protocol treatment. RESULTS: A total of 1,901 patients (1,509 men) were entered onto the three RTOG trials, with 1,822 (1,438 men) analyzable patients. Prognostic variables independent of disease-related variables for survival in multivariate analyses restricted to men were age, marital/partner status, and income. CONCLUSION: The apparent disadvantage of unpartnered men is striking, even after controlling for disease and other demographic variables. Possible explanations could easily be tested in observational studies, leading to evaluation of simple interventions to improve their outcome.
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