A1 Journal article – refereed
A New Model to Predict Benign Histology in Residual Retroperitoneal Masses After Chemotherapy in Nonseminoma




List of Authors: Ricardo Leão, Madhur Nayan, Nahid Punjani, Michael A.S. Jewett, Kamel Fadaak, Juan Garisto, Jeremy Lewin, Eshetu G. Atenafu, Joan Sweet, Lynn Anson-Cartwright, Peter Boström, Peter Chung, Padraig Warde, Philippe L. Bedard, Aditya Bagrodia, Yuval Freifeld, Nicholas Power, Eric Winquist, Robert J. Hamilton
Publisher: Elsevier B.V.
Publication year: 2018
Journal: European Urology Focus
Journal name in source: European Urology Focus
Volume number: 4
Issue number: 6
eISSN: 2405-4569

Abstract

Background: Postchemotherapy retroperitoneal lymph node dissection (pcRPLND) is indicated in testicular cancer patients with normalised or plateaued serum tumour markers and residual retroperitoneal lesions >1 cm. Challenges remain in predicting postchemotherapy residual mass (pcRM) histology, which may lead to unnecessary surgery.

Objective: To develop an accurate model to predict pcRM histology in patients with nonseminomatous germ cell tumours (NSGCTs).

Design, setting, and participants: A retrospective review of 335 patients undergoing pcRPLND for metastatic NSGCTs to develop a model to predict benign histology in retroperitoneal pcRM. Our model was compared with others and externally validated.

Intervention: Chemotherapy and pcRPLND.

Outcome measurements and statistical analysis: Multivariable logistic regression to evaluate the presence of benign histology, and fractional polynomials to allow for a nonlinear association between continuous variables and the outcome. The final Princess Margaret model (PMM) was selected based on the number of variables used, reliability, and discriminative capacity to predict benign pcRM.

Results and limitations: PMM included the presence of teratoma in the orchiectomy, prechemotherapy α-fetoprotein, prechemotherapy mass size, and change in mass size during chemotherapy. Model specificity was 99.3%. Compared with Vergouwe et al’s model, PMM had significantly better accuracy (C statistic 0.843 vs 0.783). PMM appropriately identified a larger number of patients for whom pcRPLND can safely be avoided (13.9% vs 0%). Validated in external cohorts, the model retained high discrimination (C statistic 0.88 and 0.80). Larger and prospective studies are needed to further validate this model.

Conclusions: Our clinical model, externally validated, showed improved discriminative ability in predicting pcRM histology when compared with other models. The higher accuracy and reduced number of variables make this a novel and appealing model to use for patient counselling and treatment strategies.

Patient summary: Princess Margaret model accurately predicted postchemotherapy benign histology. These results might have clinical impact by avoiding unnecessary retroperitoneal lymph node dissection and consequently changing the paradigm of advanced testicular cancer treatment.


Last updated on 2019-30-01 at 00:52