Immunotherapy in advanced melanoma: a network meta-analysis

Estimating the replicability of highly cited clinical research (2004-2018)

INTRODUCTION

Previous studies about the replicability of clinical research based on the published literature have suggested that highly cited articles are often contradicted or found to have inflated effects. Nevertheless, there are no recent updates of such efforts, and this situation may have changed over time.

METHODS

We searched the Web of Science database for articles studying medical interventions with more than 2000 citations, published between 2004 and 2018 in high-impact medical journals. We then searched for replications of these studies in PubMed using the PICO (Population, Intervention, Comparator and Outcome) framework. Replication success was evaluated by the presence of a statistically significant effect in the same direction and by overlap of the replication's effect size confidence interval (CIs) with that of the original study. Evidence of effect size inflation and potential predictors of replicability were also analyzed.

RESULTS

A total of 89 eligible studies, of which 24 had valid replications (17 meta-analyses and 7 primary studies) were found. Of these, 21 (88%) had effect sizes with overlapping CIs. Of 15 highly cited studies with a statistically significant difference in the primary outcome, 13 (87%) had a significant effect in the replication as well. When both criteria were considered together, the replicability rate in our sample was of 20 out of 24 (83%). There was no evidence of systematic inflation in these highly cited studies, with a mean effect size ratio of 1.03 [95% CI (0.88, 1.21)] between initial and subsequent effects. Due to the small number of contradicted results, our analysis had low statistical power to detect predictors of replicability.

CONCLUSION

Although most studies did not have eligible replications, the replicability rate of highly cited clinical studies in our sample was higher than in previous estimates, with little evidence of systematic effect size inflation. This estimate is based on a very select sample of studies and may not be generalizable to clinical research in general.

Updates in Glioblastoma Immunotherapy: An Overview of the Current Clinical and Translational Scenario

Glioblastoma (GBM) is the most common and aggressive central nervous system tumor, requiring multimodal management. Due to its malignant behavior and infiltrative growth pattern, GBM is one of the most difficult tumors to treat and gross total resection is still considered to be the first crucial step. The deep understanding of GBM microenvironment and the possibility of manipulating the patient's innate and adaptive immune system to fight the neoplasm represent the base of immunotherapeutic strategies that currently express the future for the fight against GBM. Despite the immunotherapeutic approach having been successfully adopted in several solid and haematologic neoplasms, immune resistance and the immunosuppressive environment make the use of these strategies challenging in GBM treatment. We describe the most recent updates regarding new therapeutic strategies that target the immune system, immune checkpoint inhibitors, chimeric antigen receptor T cell therapy, peptide and oncolytic vaccines, and the relevant mechanism of immune resistance. However, no significant results have yet been obtained in studies targeting single molecules/pathways. The future direction of GBM therapy will include a combined approach that, in contrast to the inescapable current treatment modality of maximal resection followed by chemo- and radiotherapy, may combine a multifaceted immunotherapy treatment with the dual goals of directly killing tumor cells and activating the innate and adaptive immune response.

Acceptability of Drugs in the Treatment of Unresectable/Metastatic BRAF V600-Mutant Melanoma: A Systematic Review and Network Meta-Analysis

Background

Although many novel regimens have entered the treatment paradigm for unresectable/metastatic BRAF V600-mutant melanoma, there is still a lack of head-to-head comparison in terms of security. We conducted a network meta-analysis to compare the risk of adverse events (AEs) across different treatments and to provide an acceptability ranking for patients.

Methods

A systematic literature review was conducted in Embase, PubMed, WHO International Clinical Trials Registry Platform, and Clinical Trials.gov with a time frame from database inception to December 24, 2021. We retrieved evidence on the cumulative incidence of any-grade AEs means grades 1-5 AEs (regardless of severity) and severe AEs based on the pooled risk ratios (RRs) and 95% credible intervals (95% CrI).

Results

Twelve publications and thirteen treatments enrolling 5,803 patients were included. For any-grade AEs, the acceptability of combined dabrafenib and trametinib is superior to the combination of vemurafenib and cobimetinib (RR: 0.94; Crl: 0.89, 0.98). Furthermore, nivolumab combined with ipilimumab increases any-grade AEs than single-agent ipilimumab (RR: 0.90; Crl: 0.83, 0.96) or nivolumab (RR: 0.90; Crl: 0.84, 0.97). For severe AEs, dabrafenib has the best acceptability than single-agent vemurafenib (RR: 0.66; Crl: 0.50, 0.87) or encorafenib (RR: 0.64; Crl: 0.43, 0.94). In addition, ipilimumab (SUCRA: 0.87) ranks first in the acceptability for any-grade AEs, and nivolumab (SUCRA: 0.95) ranks first in the acceptability for severe AEs. The ranking of the combination of vemurafenib and cobimetinib (SUCRA: 0.66) is superior to encorafenib in combination with binimetinib (SUCRA: 0.39) and combination of vemurafenib and cobimetinib (SUCRA: 0.18).

Conclusions

We identified the lowest AE risk treatment options for BRAF V600-mutant melanoma patients. In general, immunotherapy (ipilimumab or nivolumab) has better acceptability than most targeted therapies, and triplet therapies are related with the worst acceptability. Moreover, single-agent dabrafenib can be used as the first choice in monotherapy, and the combination of dabrafenib and trametinib is the preferred combination therapy. Overall, the combination of immunotherapy drugs increases any-grade and severe AEs than a single agent, whereas the condition of targeted therapy drugs cannot be simply generalized. Therefore, this information can facilitate evidence-based decision-making and support optimizing treatment and outcomes in clinical practice.

Prognostic value of lactate dehydrogenase for melanoma patients receiving anti-PD-1/PD-L1 therapy: A meta-analysis

BACKGROUND

Several studies indicate the level of pretreatment lactate dehydrogenase (LDH) may be associated with the prognosis of patients receiving immune checkpoint inhibitors targeting programmed death receptor-1 (PD-1)/programmed death ligand 1 (PD-L1) which had been reported to dramatically improve the survival of patients with advanced or metastatic melanoma; however, no consensus has been reached because the presence of controversial conclusions. This study was to perform a meta-analysis to comprehensively explore the prognostic values of LDH for melanoma patients receiving anti-PD1/PD-L1 monotherapy.

METHODS

A systematic electronic search in the databases of PubMed, EMBASE and the Cochrane library was performed to identify all related articles up to April, 2020. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were obtained to assess the prognostic values of pretreatment LDH in blood for overall survival (OS) and progression-free survival (PFS).

RESULTS

A total of 22 eligible studies involving 2745 patients were included. Of them, 19 studies with 20 results assessed the OS and the pooled analysis showed that an elevated pretreatment LDH level was significantly associated with a worse OS (HR = 2.44; 95% CI: 1.95-3.04, P < .001). Thirteen studies reported PFS and meta-analysis also revealed that a higher pretreatment LDH level predicted a significantly shorter PFS (HR, 1.61; 95% CI, 1.34-1.92; P < .001). Although heterogeneity existed among these studies, the same results were acquired in subgroup analyses based on sample size, country, study design, cut-off of LDH, type of PD-1/PD-L1 inhibitors and statistics for HRs (all HRs > 1 and P < .05).

CONCLUSION

This meta-analysis suggests LDH may serve as a potential biomarker to identify patients who can benefit from anti-PD-1/PD-L1 and then schedule treatments.

A twelve-gene signature for survival prediction in malignant melanoma patients

Background

Melanoma is defined as a highly mutational heterogeneous disease containing numerous alternations of the molecule. However, due to the phenotypically and genetically heterogeneity of malignant melanoma, conventional clinical characteristics remain restricted or limited in the ability to accurately predict individual outcomes and survival. This study aimed to establish an accurate gene expression signature to predict melanoma prognosis.

Methods

In this study, we established an RNA sequencing-based 12-gene signature data of melanoma patients obtained from 2 independent databases: the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. We evaluated the quality of each gene to predict survival conditions in each database by employing univariate and multivariate regression models. A prognostic risk score based on a prognostic signature was determined. This prognostic gene signature further classified patients into low-risk and high-risk groups.

Results

Based on a prognostic signature, a prognostic risk score was determined. This prognostic gene signature further divided the patients into low-risk and high-risk groups. In the chemotherapy and radiotherapy groups of the TCGA cohort and V-raf murine sarcoma viral oncogene homolog B1 (BRAF) expression group in the GEO cohort, patients in the low-risk group had a longer survival duration compared to patients in the high-risk group. Nevertheless, the immunotherapy group in the TCGA database and neuroblastoma RAS viral oncogene homolog (NRAS) expression group in the GEO database had no significant differences in statistics. Moreover, this gene signature was associated with patient prognosis regardless of whether the Breslow depth was greater than or less than 3.75 mm. Stratified gene set enrichment analysis (GSEA) revealed that certain immune-related pathways, such as the T-cell signaling pathway, chemokine signaling pathway, and primary immunodeficiency, were significantly enriched in the low-risk group of both TCGA and GEO cohorts. This information implied the immune-related properties of the 12-gene signature.

Conclusions

Our study emphasizes the significance of the gene expression signature in that it may be an indispensable prognostic predictor in melanoma and has great potential for application in personalized treatment.