A New Model to Predict Benign Histology in Residual Retroperitoneal Masses After Chemotherapy in Nonseminoma

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

Research output: Contribution to journalArticle

6 Citations (Scopus)

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. The Princess Margaret model (PMM) has higher accuracy and sensitivity in the prediction of residual benign histology when compared with other models. The PMM identifies a higher number of patients for whom retroperitoneal lymph node dissection can be avoided, and gives confidence to be used as an extensive and prospective clinical application.

Original languageEnglish (US)
JournalEuropean Urology Focus
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Lymph Node Excision
Histology
Drug Therapy
Testicular Neoplasms
Fetal Proteins
Unnecessary Procedures
Aptitude
Orchiectomy
Teratoma
Tumor Biomarkers
Counseling
Biomarkers
Logistic Models
Prospective Studies
Therapeutics

Keywords

  • Nonseminoma germ cell testicular cancer
  • Postchemotherapy
  • Predictive model
  • Retroperitoneal lymph node dissection
  • Viable disease

ASJC Scopus subject areas

  • Urology

Cite this

Leão, R., Nayan, M., Punjani, N., Jewett, M. A. S., Fadaak, K., Garisto, J., ... Hamilton, R. J. (Accepted/In press). A New Model to Predict Benign Histology in Residual Retroperitoneal Masses After Chemotherapy in Nonseminoma. European Urology Focus. https://doi.org/10.1016/j.euf.2018.01.015

A New Model to Predict Benign Histology in Residual Retroperitoneal Masses After Chemotherapy in Nonseminoma. / Leão, Ricardo; Nayan, Madhur; Punjani, Nahid; Jewett, Michael A.S.; Fadaak, Kamel; Garisto, Juan; Lewin, Jeremy; Atenafu, Eshetu G.; Sweet, Joan; Anson-Cartwright, Lynn; Boström, Peter; Chung, Peter; Warde, Padraig; Bedard, Philippe L.; Bagrodia, Aditya; Freifeld, Yuval; Power, Nicholas; Winquist, Eric; Hamilton, Robert J.

In: European Urology Focus, 01.01.2018.

Research output: Contribution to journalArticle

Leão, R, Nayan, M, Punjani, N, Jewett, MAS, Fadaak, K, Garisto, J, Lewin, J, Atenafu, EG, Sweet, J, Anson-Cartwright, L, Boström, P, Chung, P, Warde, P, Bedard, PL, Bagrodia, A, Freifeld, Y, Power, N, Winquist, E & Hamilton, RJ 2018, 'A New Model to Predict Benign Histology in Residual Retroperitoneal Masses After Chemotherapy in Nonseminoma', European Urology Focus. https://doi.org/10.1016/j.euf.2018.01.015
Leão, Ricardo ; Nayan, Madhur ; Punjani, Nahid ; Jewett, Michael A.S. ; Fadaak, Kamel ; Garisto, Juan ; Lewin, Jeremy ; Atenafu, Eshetu G. ; Sweet, Joan ; Anson-Cartwright, Lynn ; Boström, Peter ; Chung, Peter ; Warde, Padraig ; Bedard, Philippe L. ; Bagrodia, Aditya ; Freifeld, Yuval ; Power, Nicholas ; Winquist, Eric ; Hamilton, Robert J. / A New Model to Predict Benign Histology in Residual Retroperitoneal Masses After Chemotherapy in Nonseminoma. In: European Urology Focus. 2018.
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title = "A New Model to Predict Benign Histology in Residual Retroperitoneal Masses After Chemotherapy in Nonseminoma",
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. The Princess Margaret model (PMM) has higher accuracy and sensitivity in the prediction of residual benign histology when compared with other models. The PMM identifies a higher number of patients for whom retroperitoneal lymph node dissection can be avoided, and gives confidence to be used as an extensive and prospective clinical application.",
keywords = "Nonseminoma germ cell testicular cancer, Postchemotherapy, Predictive model, Retroperitoneal lymph node dissection, Viable disease",
author = "Ricardo Le{\~a}o and Madhur Nayan and Nahid Punjani and Jewett, {Michael A.S.} and Kamel Fadaak and Juan Garisto and Jeremy Lewin and Atenafu, {Eshetu G.} and Joan Sweet and Lynn Anson-Cartwright and Peter Bostr{\"o}m and Peter Chung and Padraig Warde and Bedard, {Philippe L.} and Aditya Bagrodia and Yuval Freifeld and Nicholas Power and Eric Winquist and Hamilton, {Robert J.}",
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T1 - A New Model to Predict Benign Histology in Residual Retroperitoneal Masses After Chemotherapy in Nonseminoma

AU - Leão, Ricardo

AU - Nayan, Madhur

AU - Punjani, Nahid

AU - Jewett, Michael A.S.

AU - Fadaak, Kamel

AU - Garisto, Juan

AU - Lewin, Jeremy

AU - Atenafu, Eshetu G.

AU - Sweet, Joan

AU - Anson-Cartwright, Lynn

AU - Boström, Peter

AU - Chung, Peter

AU - Warde, Padraig

AU - Bedard, Philippe L.

AU - Bagrodia, Aditya

AU - Freifeld, Yuval

AU - Power, Nicholas

AU - Winquist, Eric

AU - Hamilton, Robert J.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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. The Princess Margaret model (PMM) has higher accuracy and sensitivity in the prediction of residual benign histology when compared with other models. The PMM identifies a higher number of patients for whom retroperitoneal lymph node dissection can be avoided, and gives confidence to be used as an extensive and prospective clinical application.

AB - 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. The Princess Margaret model (PMM) has higher accuracy and sensitivity in the prediction of residual benign histology when compared with other models. The PMM identifies a higher number of patients for whom retroperitoneal lymph node dissection can be avoided, and gives confidence to be used as an extensive and prospective clinical application.

KW - Nonseminoma germ cell testicular cancer

KW - Postchemotherapy

KW - Predictive model

KW - Retroperitoneal lymph node dissection

KW - Viable disease

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