Abstract

Objective: In clinical trials of second-line therapies for chronic phase chronic myeloid leukemia (CP-CML), to date, only single-arm trials have been conducted for the available tyrosine kinase inhibitor treatments (bosutinib, dasatinib and nilotinib). These trials included heterogeneous patient populations in terms of disease and baseline characteristics. These hamper the use of standard network meta-analyses for indirect treatment comparison of relative efficacy. In this situation, a matching-adjusted indirect comparison (MAIC) in second-line CP-CML was performed. The aim was to compare the relative efficacies of bosutinib, dasatinib and nilotinib in second-line CP-CML patients.Methods: The MAIC was preceded by a systematic literature review that ensured inclusion of the underlying data for the analyses. The outcomes were measured in terms of overall survival (OS), progression-free survival (PFS) and major cytogenetic response (MCyR). The treatments were quantitatively compared based on Cox proportional hazard ratio (HR) regressions, on restricted mean survival (RMST, when the proportionality assumption showed evidence of violation) and on odds ratios (for response measures).Results: Comparing with dasatinib, bosutinib resulted in HRs for PFS and OS of 0.63 (0.44–0.90, p < .05) and 0.82 (0.54–1.26, p = .37) respectively, and resulted in an OR for MCyR of 0.78 (0.53–1.16). Although the proportionality of hazards assumption was violated for PFS, the RMST analyses confirmed the findings of the Cox regression. When compared with nilotinib, bosutinib showed a significant HR of 0.54 (0.38–0.76, p < .01) in favor of bosutinib for PFS, a non-significant HR of 0.72 (0.46–1.13, p = .16) for OS and a non-significant OR of 0.98 (0.71–1.35) for MCyR.Conclusions: Bosutinib had a significantly greater PFS than both dasatinib and nilotinib. For OS, the findings were numerically in favor of bosutinib, but not statistically significant. For MCyR, the findings were numerically in favor of dasatinib and nilotinib, but not statistically significant.

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