PURPOSE: To develop a statistical model that predicts the histology (necrosis, mature teratoma, or cancer) after chemotherapy for metastatic nonseminomatous germ cell tumor (NSGCT). PATIENTS AND METHODS: An international data set was collected comprising individual patient data from six study groups. Logistic regression analysis was used to estimate the probability of necrosis and the ratio of cancer and mature teratoma. RESULTS: Of 556 patients, 250 (45%) had necrosis at resection, 236 (42%) had mature teratoma, and 70 (13%) had cancer. Predictors of necrosis were the absence of teratoma elements in the primary tumor, prechemotherapy normal alfa-fetoprotein (AFP), normal human chorionic gonadotropin (HCG), and elevated lactate dehydrogenase (LDH) levels, a small prechemotherapy or postchemotherapy mass, and a large shrinkage of the mass during chemotherapy. Multivariate combination of predictors yielded reliable models (goodness-of-fit tests, P > .20), which discriminated necrosis well from other histologies (area under the receiver operating characteristic (ROC) curve, .84), but which discriminated cancer only reasonably from mature teratoma (area, .66). Internal and external validation confirmed these findings. CONCLUSION: The validated models estimate with high accuracy the histology at resection, especially necrosis, based on well-known and readily available predictors. The predicted probabilities may help to choose between immediate resection of a residual mass or follow-up, taking into account the expected benefits and risks of resection, feasibility of frequent follow-up, the financial costs, and the patient's individual preferences.

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hdl.handle.net/1765/10632
Journal of Clinical Oncology
Erasmus MC: University Medical Center Rotterdam

Steyerberg, E., Keizer, H. J., Fossa, S., Sleijfer, D., Toner, G. C., Schraffordt Koops, H., … Donohue, J. P. (1995). Prediction of residual retroperitoneal mass histology after chemotherapy for metastatic nonseminomatous germ cell tumor: multivariate analysis of individual patient data from six study groups. Journal of Clinical Oncology, 13(5), 1177–1187. Retrieved from http://hdl.handle.net/1765/10632