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.
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.
Authors: Lori Wood; Christian Kollmannsberger; Michael Jewett; Peter Chung; Sebastian Hotte; Martin O'Malley; Joan Sweet; Lynn Anson-Cartwright; Eric Winquist; Scott North; Scott Tyldesley; Jeremy Sturgeon; Mary Gospodarowicz; Roanne Segal; Tina Cheng; Peter Venner; Malcolm Moore; Peter Albers; Robert Huddart; Craig Nichols; Padraig Warde Journal: Can Urol Assoc J Date: 2010-04 Impact factor: 1.862
Authors: Samuel A Funt; Sujata Patil; Darren R Feldman; Robert J Motzer; Dean F Bajorin; Joel Sheinfeld; Satish K Tickoo; Victor E Reuter; George J Bosl Journal: J Clin Oncol Date: 2019-06-24 Impact factor: 44.544
Authors: M Bamberg; H J Schmoll; L Weissbach; J Beyer; C Bokemeyer; A Harstrick; W Höltl; R Souchon; H Vogler Journal: Strahlenther Onkol Date: 1997-08 Impact factor: 3.621
Authors: Solomon L Woldu; Joseph A Moore; Bo Ci; Yuval Freifeld; Timothy N Clinton; Ahmet M Aydin; Nirmish Singla; Krabbe Laura-Maria; Ryan C Hutchinson; James F Amatruda; Arthur Sagalowsky; Yair Lotan; Yull Arriaga; Vitaly Margulis; Yang Xie; Aditya Bagrodia Journal: Eur Urol Oncol Date: 2018-06-06
Authors: Ewout W Steyerberg; Andrew J Vickers; Nancy R Cook; Thomas Gerds; Mithat Gonen; Nancy Obuchowski; Michael J Pencina; Michael W Kattan Journal: Epidemiology Date: 2010-01 Impact factor: 4.822