Robert J Glynn1,2,3, Graham A Colditz4, Rulla M Tamimi5,6, Wendy Y Chen5,7, Susan E Hankinson5,6,8, Walter W Willett5,9, Bernard Rosner5,10. 1. Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. rglynn@partners.org. 2. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. rglynn@partners.org. 3. Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. rglynn@partners.org. 4. Alvin J. Siteman Cancer Center and Department of Surgery, Division of Public Health Sciences, School of Medicine, Washington University of St. Louis, St. Louis, MO, USA. 5. Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. 6. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 7. Dana-Farber Cancer Institute, Boston, MA, USA. 8. Division of Biostatistics and Epidemiology, School of Public Health Sciences, University of Massachusetts, Amherst, MA, USA. 9. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 10. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Abstract
PURPOSE: A breast cancer risk prediction rule previously developed by Rosner and Colditz has reasonable predictive ability. We developed a re-fitted version of this model, based on more than twice as many cases now including women up to age 85, and further extended it to a model that distinguished risk factor prediction of tumors with different estrogen/progesterone receptor status. METHODS: We compared the calibration and discriminatory ability of the original, the re-fitted, and the type-specific models. Evaluation used data from the Nurses' Health Study during the period 1980-2008, when 4384 incident invasive breast cancers occurred over 1.5 million person-years. Model development used two-thirds of study subjects and validation used one-third. RESULTS: Predicted risks in the validation sample from the original and re-fitted models were highly correlated (ρ = 0.93), but several parameters, notably those related to use of menopausal hormone therapy and age, had different estimates. The re-fitted model was well-calibrated and had an overall C-statistic of 0.65. The extended, type-specific model identified several risk factors with varying associations with occurrence of tumors of different receptor status. However, this extended model relative to the prediction of any breast cancer did not meaningfully reclassify women who developed breast cancer to higher risk categories, nor women remaining cancer free to lower risk categories. CONCLUSIONS: The re-fitted Rosner-Colditz model has applicability to risk prediction in women up to age 85, and its discrimination is not improved by consideration of varying associations across tumor subtypes.
PURPOSE: A breast cancer risk prediction rule previously developed by Rosner and Colditz has reasonable predictive ability. We developed a re-fitted version of this model, based on more than twice as many cases now including women up to age 85, and further extended it to a model that distinguished risk factor prediction of tumors with different estrogen/progesterone receptor status. METHODS: We compared the calibration and discriminatory ability of the original, the re-fitted, and the type-specific models. Evaluation used data from the Nurses' Health Study during the period 1980-2008, when 4384 incident invasive breast cancers occurred over 1.5 million person-years. Model development used two-thirds of study subjects and validation used one-third. RESULTS: Predicted risks in the validation sample from the original and re-fitted models were highly correlated (ρ = 0.93), but several parameters, notably those related to use of menopausal hormone therapy and age, had different estimates. The re-fitted model was well-calibrated and had an overall C-statistic of 0.65. The extended, type-specific model identified several risk factors with varying associations with occurrence of tumors of different receptor status. However, this extended model relative to the prediction of any breast cancer did not meaningfully reclassify women who developed breast cancer to higher risk categories, nor women remaining cancer free to lower risk categories. CONCLUSIONS: The re-fitted Rosner-Colditz model has applicability to risk prediction in women up to age 85, and its discrimination is not improved by consideration of varying associations across tumor subtypes.
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