Comparison of Joint and Landmark Modeling for Predicting Cancer Progression in Men With Castration-Resistant Prostate Cancer-Reference-Cited by-同舟云学术

Comparison of Joint and Landmark Modeling for Predicting Cancer Progression in Men With Castration-Resistant Prostate Cancer

Published:2021-06-15 Issue:6 Volume:4 Page:e2112426
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Finelli Antonio¹,Beer Tomasz M.²,Chowdhury Simon³,Evans Christopher P.⁴,Fizazi Karim⁵,Higano Celestia S.⁶⁷,Kim Janet⁸,Martin Lisa¹,Saad Fred⁹,Saarela Olli¹⁰

Affiliation:

1. Princess Margaret Cancer Centre, University Health Network, Toronto, Canada

2. Knight Cancer Institute, Oregon Health & Science University, Portland

3. St Thomas’ Hospitals and Sarah Cannon Research Institute, London, United Kingdom

4. Department of Urologic Surgery, UC Davis Comprehensive Cancer Center, University of California, Davis

5. Institut Gustave Roussy, Université Paris-Saclay, Villejuif, France

6. University of Washington, Seattle

7. Fred Hutchinson Cancer Research Center, Seattle, Washington

8. Astellas Pharma Global Development, Northbrook, Illinois

9. Centre Hospitalier de l’Université de Montréal/CRCHUM, Montréal, Canada

10. Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2780960/finelli_2021_oi_210369_1622770099.60793.pdf

Reference31 articles.

1. Developing and validating risk assessment models of clinical outcomes in modern oncology.;Halabi;JCO Precis Oncol,2019

2. Identification of subgroups of metastatic castrate-resistant prostate cancer (mCRPC) patients treated with abiraterone plus prednisone at low- vs. high-risk of radiographic progression: an analysis of COU-AA-302.;Martin;Can Urol Assoc J,2019

3. Doc, shouldn’t we be getting some tests?;Loprinzi;J Clin Oncol,2003

4. Joint modelling of longitudinal and multi-state processes: application to clinical progressions in prostate cancer.;Ferrer;Stat Med,2016

5. From static to dynamic risk prediction: time is everything.;Greene;Am J Kidney Dis,2017

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