A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions

被引:364
作者
Latouche, Aurelien [1 ,2 ]
Allignol, Arthur [3 ]
Beyersmann, Jan [3 ]
Labopin, Myriam [4 ]
Fine, Jason P. [5 ]
机构
[1] Conservatoire Natl Arts & Metiers, IMATH, EA4629, Paris, France
[2] INSERM, Ctr Res Epidemiol & Populat Hlth, Biostat Team, F-94807 Villejuif, France
[3] Univ Freiburg, Freiburg Ctr Data Anal & Modelling, D-79104 Freiburg, Germany
[4] Univ Paris 06, Dept Hematol, EBMT ALWP Off, Fac Med St Antoine, F-75571 Paris, France
[5] Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
关键词
Competing risks; Cumulative incidence; Endpoints; Bone marrow transplant; Proportional hazards; Survival analysis; HEMATOPOIETIC-CELL TRANSPLANTATION; BONE-MARROW TRANSPLANTS; REDUCED-INTENSITY; STATISTICAL-METHODS; REGRESSION-MODELS; MULTISTATE MODELS; SUBDISTRIBUTION; CLINICIAN; LYMPHOMA; LEUKEMIA;
D O I
10.1016/j.jclinepi.2012.09.017
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Competing risks endpoints are frequently encountered in hematopoietic stem cell transplantation where patients are exposed to relapse and treatment-related mortality. Both cause-specific hazards and direct models for the cumulative incidence functions have been used for analyzing such competing risks endpoints. For both approaches, the popular models are of a proportional hazards type. Such models have been used for studying prognostic factors in acute and chronic leukemias. We argue that a complete understanding of the event dynamics requires that both hazards and cumulative incidence be analyzed side by side, and that this is generally the most rigorous scientific approach to analyzing competing risks data. That is, understanding the effects of covariates on cause-specific hazards and cumulative incidence functions go hand in hand. A case study illustrates our proposal. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:648 / 653
页数:6
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