Cumulative incidence regression for dynamic treatment regimens

Chen L., YAVUZ İ., Cheng Y., Wahed A. S.

BIOSTATISTICS, vol.21, no.2, 2020 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 21 Issue: 2
  • Publication Date: 2020
  • Doi Number: 10.1093/biostatistics/kxy062
  • Journal Name: BIOSTATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Agricultural & Environmental Science Database, Applied Science & Technology Source, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, CINAHL, EMBASE, MEDLINE, zbMATH
  • Keywords: Competing risks, Fine and Gray, Inverse probability weighting, Scheike model, Sequential Multiple Assignment Randomized Trial, 2-STAGE RANDOMIZATION DESIGNS, SURVIVAL DISTRIBUTIONS
  • Dokuz Eylül University Affiliated: Yes


Recently dynamic treatment regimens (DTRs) have drawn considerable attention, as an effective tool for personalizing medicine. Sequential Multiple Assignment Randomized Trials (SMARTs) are often used to gather data for making inference on DTRs. In this article, we focus on regression analysis of DTRs from a two-stage SMART for competing risk outcomes based on cumulative incidence functions (CIFs). Even though there are extensive works on the regression problem for DTRs, no research has been done on modeling the CIF for SMART trials. We extend existing CIF regression models to handle covariate effects for DTRs. Asymptotic properties are established for our proposed estimators. The models can be implemented using existing software by an augmented-data approximation. We show the improvement provided by our proposed methods by simulation and illustrate its practical utility through an analysis of a SMART neuroblastoma study, where disease progression cannot be observed after death.