Reduced rank proportional hazards model for competing risks: An application to a breast cancer trial |
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| Affiliation: | 1. Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands;2. Department of Surgery, Leiden University Medical Center, P.O. Box 9604, 2300 RC Leiden, The Netherlands;1. Department of Statistics, University of Pune, Pune 411 007, India;2. Department of Mathematics, Univeristy of Technology, 2628 CD Delft, The Netherlands;1. Department of Orthopaedics and Traumatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China;2. Department of Orthopaedic, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510665, Guangdong, China;3. Department of Orthopaedic, People’s Hospital of Inner Mongolia Autonomous Region, Inner Mongolia Autonomous Region, Hohhot 010050, China;4. Department of Dermatology and STD, Guangdong No.2 Provincial People’s Hospital, Guangzhou 510000, Guangdong, China;5. Department of Dermatology, People’s Hospital of Inner Mongolia Autonomous Region, Inner Mongolia Autonomous Region, Hohhot 010050, China;1. Department of Internal Medicine, Kidney Institute, University of Kansas Medical Center, Kansas City, Kansas;2. Division of Biostatistics, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas;3. Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas;4. Division of Nephrology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas;5. Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas;6. Division of Cardiology, Department of Internal Medicine, Veterans Affairs North Texas Health Care System, Dallas, Texas;7. Division of Nephrology, Department of Internal Medicine, Veterans Affairs North Texas Health Care System, Dallas, Texas;1. Center for Biomedical Informatics and Biostatistics, The University of Arizona, Tucson, AZ 85721, USA;2. Bio5 Institute, The University of Arizona, Tucson, AZ 85721, USA;3. Department of Medicine, The University of Arizona, Tucson, AZ 85721, USA;4. Graduate Interdisciplinary Program in Statistics, The University of Arizona, Tucson, AZ 85721, USA;5. Department of Mathematics, The University of Arizona, Tucson, AZ 85721, USA;6. University of Arizona Cancer Center, The University of Arizona, Tucson, AZ 85721, USA;7. Institute for Genomics and Systems Biology, The University of Chicago, IL 60637, USA |
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| Abstract: | In many cancer trials patients are at risk of recurrence and death after the appearance and the successful treatment of the first diagnosed tumour. In this situation competing risks models that model several competing causes of therapy or surgery failure are a natural framework to describe the evolution of the disease.Typically, regression models for competing risks outcomes are based on proportional hazards model for each of the cause-specific hazard rates. An immediate practical problem is then how to deal with the abundance of regression parameters. The aim of reduced rank proportional hazards models is to reduce the number of parameters that need to be estimated while at the same time keeping the distinction between different transitions. They have the advantage of describing the competing risks model in fewer parameters, cope with transitions where few events are present and facilitate the interpretation of these estimates.We shall illustrate the use of this technique on 2795 patients from a breast cancer trial (EORTC 10854). |
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