PURPOSE: We validated a prediction model for histology of residual retroperitoneal masses, either benign or tumor, in patients treated with chemotherapy for metastatic nonseminomatous testicular cancer. MATERIALS AND METHODS: We studied 276 patients treated with chemotherapy before retroperitoneal lymph node dissection at Indiana University Medical Center between 1985 and 1999. A previously developed prediction model was modified to provide predictions for the Indiana population based on 5 predictors. For these predictors, including teratomatous elements in the primary tumor, pre-chemotherapy tumor markers (alpha-fetoprotein and human chorionic gonadotropin), size of the residual mass and reduction in mass size, univariate and multivariate odds ratios were determined. The modified model was evaluated by calculating the concordance statistic and studying model reliability. RESULTS: All odds ratios from univariate and multivariate analyses were in the expected directions. The modified model had good discriminative ability (concordance statistic 0.79). However, the predicted probabilities for benign tissue were generally too high due to the low prevalence of benign tissue (76 of 276 cases or 28%). CONCLUSIONS: This study confirms the predictive ability of formerly identified predictors for the histology of residual retroperitoneal masses in testicular cancer. However, the previously developed prognostic model must be adjusted for the local overall ratio of benign versus tumor histology to provide reliable predictions in the Indiana population.
PURPOSE: We validated a prediction model for histology of residual retroperitoneal masses, either benign or tumor, in patients treated with chemotherapy for metastatic nonseminomatous testicular cancer. MATERIALS AND METHODS: We studied 276 patients treated with chemotherapy before retroperitoneal lymph node dissection at Indiana University Medical Center between 1985 and 1999. A previously developed prediction model was modified to provide predictions for the Indiana population based on 5 predictors. For these predictors, including teratomatous elements in the primary tumor, pre-chemotherapy tumor markers (alpha-fetoprotein and human chorionic gonadotropin), size of the residual mass and reduction in mass size, univariate and multivariate odds ratios were determined. The modified model was evaluated by calculating the concordance statistic and studying model reliability. RESULTS: All odds ratios from univariate and multivariate analyses were in the expected directions. The modified model had good discriminative ability (concordance statistic 0.79). However, the predicted probabilities for benign tissue were generally too high due to the low prevalence of benign tissue (76 of 276 cases or 28%). CONCLUSIONS: This study confirms the predictive ability of formerly identified predictors for the histology of residual retroperitoneal masses in testicular cancer. However, the previously developed prognostic model must be adjusted for the local overall ratio of benign versus tumor histology to provide reliable predictions in the Indiana population.
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