Pretreatment nomogram for predicting the outcome of three-dimensional conformal radiotherapy in prostate cancer
- PMID: 11013275
- DOI: 10.1200/JCO.2000.18.19.3352
Pretreatment nomogram for predicting the outcome of three-dimensional conformal radiotherapy in prostate cancer
Abstract
Purpose: Several studies have defined risk groups for predicting the outcome after external-beam radiotherapy of localized prostate cancer. However, most models formed patient risk groups, and none of these models considers radiation dose as a predictor variable. The purpose of this study was to develop a nomogram to improve the accuracy of predicting outcome after three-dimensional conformal radiotherapy.
Materials and methods: This study was a retrospective, nonrandomized analysis of patients treated at the Memorial Sloan-Kettering Cancer Center between 1988 and 1998. Clinical parameters of the 1,042 patients included stage, biopsy Gleason score, pretreatment serum prostate-specific antigen (PSA) level, whether neoadjuvant androgen deprivation therapy was administered, and the radiation dose delivered. Biochemical (PSA) treatment failure was scored when three consecutive rises of serum PSA occurred. A nomogram, which predicts the probability of remaining free from biochemical recurrence for 5 years, was validated internally on this data set using a bootstrapping method and externally using a cohort of patients treated at the Cleveland Clinic, Cleveland, OH.
Results: When predicting outcomes for patients in the validation data set from the Cleveland Clinic, the nomogram had a Somers' D rank correlation between predicted and observed failure times of 0.52. Predictions from this nomogram were more accurate (P<.0001) than the best of seven published risk stratification systems, which achieved a Somers' D coefficient of 0.47.
Conclusion: The development process illustrated here produced a nomogram that seems to predict more accurately than other available systems and may be useful for treatment selection by both physicians and patients.
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