Immune checkpoint inhibitors as first line in advanced melanoma: Evaluating progression‐free survival based on reconstructed individual patient data

Abstract

Background In patients with advanced melanoma, immune‐checkpoint inhibitors (ICIs) represent the mainstay for first line treatment. Recently, relatlimab+nivolumab was proposed as a new combination therapy. This review was aimed at summarizing the current data of effectiveness for ICIs. Progression‐free survival (PFS) was the endpoint of our analysis. Methods After a standard literature search, Phase II/III studies comparing different ICI regimens in previously untreated advanced melanoma patients were analyzed. Patient‐level data were reconstructed from Kaplan–Meier curves by application of the IPDfromKM method. These reconstructed datasets were used to perform indirect comparisons between treatments. Standard statistical testing was used, including hazard ratio and medians. A secondary analysis employed the restricted mean survival time. Results Six trials were included in our analysis. Information on PFS from these trials was pooled according to the following treatments: nivolumab or pembrolizumab as monotherapy, or in combination with ipilimumab, and relatlimab + nivolumab. Pembrolizumab+ipilimumab showed significantly better PFS compared with the other treatments; nivolumab+ipilimumab ranked second; the other treatments showed a similar survival pattern. Conclusions The picture of comparative effectiveness resulting from our analysis is complex. The IPDfromKM method is advantageous because it accounts for the length of follow‐up but loses the balance between treatment group and controls determined by randomization. Based on indirect comparisons, the combination of pembrolizumab+ipilimumab showed a particularly high efficacy, and so deserves further investigation. While the effect of between‐trial differences in inclusion criteria plays an important role, our results do not support the proposal of relatlimab+nivolumab as a new standard of care.

Epigenetic Suppression of the IL-7 Pathway in Progressive Glioblastoma

“…In contrast to other solid tumors, treating GBM with immunotherapies is more challenging because of the blood–brain barrier, the high degree of intra- and inter-tumor heterogeneity, and the complexity of the tumor’s microenvironment (TME) that significantly contributes to immune evasion. Mechanisms of immune evasion in GBM include the tumor’s and TME’s expression of inhibitor proteins targeting CD4 + and CD8 + T cells, B and NK cells, the recruitment of immunosuppressive regulatory T cells and myeloid-derived suppressor cells, as well as the production of immunosuppressive cytokines that induce rapid T cell exhaustion and reduced T cell survival [ 8 , 10 , 11 , 17 ]. Epigenetic regulation in the tumor and the TME, but also in the infiltrative immune cells during the initial and progressive stages of gliomagenesis contribute to mechanisms of immune evasion.…”

“…Several research groups have sought to develop an effective immune strategy to circumvent the GBM cells’ immune escape mechanisms. After the disappointing outcome of early growth factor receptor inhibition strategies, the newer approaches include immune checkpoint inhibitors, modulation of tumor infiltrating lymphocytes (TILs), and most recently, the engineered chimeric antigen receptors (CAR) carried by thymocytes (T) and natural killer (NK) cells [ 10 , 11 ]. Significant efforts have been made to equip tumor-infiltrating CAR-T cells with various interleukins to prolong their persistence and to enhance therapeutic efficacy against solid tumors [ 16 ].…”

“…Mechanisms of immune evasion have been well understood in various tumors, including GBM [ 8 ]. However, while immune checkpoint inhibitors or other means of immune therapies have been quite successful in many cancers [ 9 , 10 ], such approaches have largely failed and the reason for that is only partially understood in GBM [ 11 ]. Molecular engineering, however, may improve treatment efficacy by incorporating and combining well-selected immune pathway elements that are suppressed by the tumor.…”

The “One-to-Many” Survival Analysis to Evaluate a New Treatment in Comparison With Therapeutic Alternatives Based on Reconstructed Patient Data: Enfortumab Vedotin Versus Standard of Care in Advanced or Metastatic Urothelial Carcinoma

“…The characteristics of the Shiny method have previously been described in detail [1,2]. It should be stressed that the reconstruction of patient-level data can have two different purposes: first, reconstructed individual patient data are estimated to determine the restricted mean survival time (RMST) [15]; second, reconstructed individual patient data are estimated to perform indirect comparisons between treatments and to generate a multi-treatment KM graph [3][4][5][6][7][8][9][10][11][12][13][14]. This second application of the Shiny method is increasingly considered the most important one.…”

“…The main prerequisite for performing the Shiny analysis is that the same time-to-event endpoint (e.g., OS or PFS) has been employed in all the trials included in the comparison. Numerous experiences with the Shiny method have already been reported [3][4][5][6][7][8][9][10][11][12][13][14]; anti-cancer treatments are the most suitable area for this analysis [3][4][5][6][7][8][9][10][11][12][13].…”