Predicting Retroperitoneal Histology in Postchemotherapy Testicular Germ Cell Cancer: A Model Update and Multicentre Validation with More Than 1000 Patients

Yvonne Vergouwe, Ewout W. Steyerberg, Richard Foster, Dirk T. Sleijfer, Sophie D. Fosså, Arthur Gerl, Ronald de Wit, J. Trevor Roberts, J. Dik F Habbema

Research output: Contribution to journalArticle

50 Citations (Scopus)

Abstract

Objectives: Surgical resection of postchemotherapy retroperitoneal lymph nodes is often performed in patients with advanced nonseminomatous testicular germ cell cancer. We previously developed a model to predict the probability that the lymph nodes contain only necrotic or fibrotic (benign) tissue versus mature teratoma and viable cancer (tumour) to identify patients who actually need resection. The present study used an updated model with new patient data and studied the validity of the updated model across various settings. Methods: We combined data of 544 patients from the original model with data of 550 new patients and performed a new logistic regression analysis, which included the same six predictors: histology of the primary tumour, prechemotherapy serum levels of α-fetoprotein, human chorionic gonadotropin, lactate dehydrogenase, residual mass size measured on computed tomography, and change in mass size. The validity of the updated model was studied in individual centres. Calibration of the predicted probabilities was assessed graphically and with the Hosmer-Lemeshow test. Discrimination was studied with the concordance (c)-statistic. Results: The updated model had slightly different, although more precise, regression coefficients. Statistically nonsignificant Hosmer-Lemeshow tests confirmed good calibration in most centres. The c-statistic for all centres except one exceeded 0.80. The updated model was valid over the complete range of predicted probabilities across a broad spectrum of centres. Conclusions: This finding gives confidence in the applicability of the model to select patients for resection, particularly patients with small residual masses and low predicted probabilities of benign tissue (i.e., substantial predicted risks of residual tumour).

Original languageEnglish
Pages (from-to)424-432
Number of pages9
JournalEuropean Urology
Volume51
Issue number2
DOIs
StatePublished - Feb 2007

Fingerprint

Germ Cell and Embryonal Neoplasms
Testicular Neoplasms
Histology
Calibration
Lymph Nodes
Fetal Proteins
Neoplasms
Teratoma
Residual Neoplasm
Chorionic Gonadotropin
L-Lactate Dehydrogenase
Logistic Models
Tomography
Regression Analysis
Serum

Keywords

  • Histology
  • Lymphatic metastasis
  • Model update
  • Prediction model
  • Testicular neoplasms

ASJC Scopus subject areas

  • Urology

Cite this

Predicting Retroperitoneal Histology in Postchemotherapy Testicular Germ Cell Cancer : A Model Update and Multicentre Validation with More Than 1000 Patients. / Vergouwe, Yvonne; Steyerberg, Ewout W.; Foster, Richard; Sleijfer, Dirk T.; Fosså, Sophie D.; Gerl, Arthur; de Wit, Ronald; Roberts, J. Trevor; Habbema, J. Dik F.

In: European Urology, Vol. 51, No. 2, 02.2007, p. 424-432.

Research output: Contribution to journalArticle

Vergouwe, Yvonne ; Steyerberg, Ewout W. ; Foster, Richard ; Sleijfer, Dirk T. ; Fosså, Sophie D. ; Gerl, Arthur ; de Wit, Ronald ; Roberts, J. Trevor ; Habbema, J. Dik F. / Predicting Retroperitoneal Histology in Postchemotherapy Testicular Germ Cell Cancer : A Model Update and Multicentre Validation with More Than 1000 Patients. In: European Urology. 2007 ; Vol. 51, No. 2. pp. 424-432.
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AU - Fosså, Sophie D.

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AB - Objectives: Surgical resection of postchemotherapy retroperitoneal lymph nodes is often performed in patients with advanced nonseminomatous testicular germ cell cancer. We previously developed a model to predict the probability that the lymph nodes contain only necrotic or fibrotic (benign) tissue versus mature teratoma and viable cancer (tumour) to identify patients who actually need resection. The present study used an updated model with new patient data and studied the validity of the updated model across various settings. Methods: We combined data of 544 patients from the original model with data of 550 new patients and performed a new logistic regression analysis, which included the same six predictors: histology of the primary tumour, prechemotherapy serum levels of α-fetoprotein, human chorionic gonadotropin, lactate dehydrogenase, residual mass size measured on computed tomography, and change in mass size. The validity of the updated model was studied in individual centres. Calibration of the predicted probabilities was assessed graphically and with the Hosmer-Lemeshow test. Discrimination was studied with the concordance (c)-statistic. Results: The updated model had slightly different, although more precise, regression coefficients. Statistically nonsignificant Hosmer-Lemeshow tests confirmed good calibration in most centres. The c-statistic for all centres except one exceeded 0.80. The updated model was valid over the complete range of predicted probabilities across a broad spectrum of centres. Conclusions: This finding gives confidence in the applicability of the model to select patients for resection, particularly patients with small residual masses and low predicted probabilities of benign tissue (i.e., substantial predicted risks of residual tumour).

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