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Network meta‐analysis of first‐line treatments in transplant‐ineligible multiple myeloma patients
Author(s) -
GilSierra Manuel David,
GimenoBallester Vicente,
FenixCaballero Silvia,
AlegreDel Rey Emilio Jesus
Publication year - 2020
Publication title -
european journal of haematology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.904
H-Index - 84
eISSN - 1600-0609
pISSN - 0902-4441
DOI - 10.1111/ejh.13407
Subject(s) - daratumumab , lenalidomide , medicine , multiple myeloma , bortezomib , oncology , thalidomide , dexamethasone , meta analysis , melphalan
Objectives Multiple myeloma (MM) is a complex disease. Lack of direct comparisons among treatments and incorporation of new alternatives make it necessary to perform studies that allow for clinical decision‐making. A network meta‐analysis (NMA) was developed to evaluate the comparative efficacy among different therapeutic alternatives in newly diagnosed transplant‐ineligible MM patients. Methods MEDLINE ® and EMBASE ® were systematically searched up for these drugs: lenalidomide, thalidomide, bortezomib, and daratumumab. Comparative phase II‐III randomized clinical trials (RCTs) were included. Progression‐free survival (PFS) was selected as efficacy outcome. The NMA was developed using Bayesian methods. Fixed‐ and random‐effects models were assessed using deviance information criteria. Results The systematic search yielded 593 results. Ten RCTs were included. No differences were observed between fixed‐ and random‐effects models. The combination of daratumumab, bortezomib, melphalan, and prednisone showed the best HR in PFS (reference treatment). Along with this scheme, the best PFS results were obtained by combination of daratumumab, lenalidomide, and dexamethasone (HR 1.2, 95% CrI 0.64‐2.4) and bortezomib with lenalidomide and dexamethasone (HR 1.6, 95% CrI 0.81‐3.0).Conclusions Schemes with the best PFS results were daratumumab treatments and combination of bortezomib, lenalidomide, and dexamethasone, although the latter scheme has been analyzed in heterogeneous populations.