PUK2 The Impact of Clinical Heterogeneity on Conducting Network Meta-Analyses for Overall Survival in Previously Untreated Intermediate- or Poor-Risk Advanced/Metastatic Renal Cell Therapies

Abstract

The optimal treatment for patients with previously untreated advanced/metastatic renal cell carcinoma (aRCC) is based on the severity of disease. Recently approved novel treatments for patients with intermediate-/poor-risk disease requires indirect treatments comparisons in this patient population. This study evaluated the impact of clinical heterogeneity on the validity of a network meta-analysis (NMA) for overall survival in intermediate-/poor-risk by following the feasibility assessment framework of Cope et al. (2014) based on the ISPOR Good Practices Task Force Report. A systematic literature review was performed, after which a network of evidence, including 10 randomized clinical trials and 8 treatments of interest, was formed for the intermediate-/poor-risk population. First, heterogeneity was evaluated in terms of treatment and outcome characteristics, as well as study and patient characteristics using a pre-defined set of potential treatment effect modifiers (i.e. ECOG performance status, gender, IMDC/MSKCC risk factor, liver metastasis, number of metastatic sites, prior nephrectomy, PD-L1 status, race and region). Second, comparisons of baseline risk and observed treatment effects were evaluated for the presence of unmeasured effect modifiers. Imbalances were found in prognostic risk score (intermediate vs. poor), nephrectomy, and radiation. Furthermore, there was a lack of reporting on most of the 9 pre-specified potential treatment effect modifiers, hampering the ability to make conclusions on the presence of heterogeneity. Only one treatment comparison in the network diagram considered evidence from multiple studies, for which no significant differences were found. Due to the small number of studies included in the evidence network, using meta-regression or subgroup analyses to eliminate heterogeneity in the evidence base, caused by potential effect modifiers, was deemed infeasible. Furthermore, the presence of potential sources of heterogeneity could not be assessed for most potential treatment effect modifiers. Results of an NMA in this network should therefore be interpreted with caution.