Safety of extended interval dosing immune checkpoint inhibitors:a multicenter cohort study

BACKGROUND: Real-life spectrum and survival implications of immune-related adverse events (irAEs) in patients treated with extended interval dosing (ED) immune checkpoint inhibitors (ICIs) are unknown. METHODS: Characteristics of 812 consecutive solid cancer patients who received at least 1 cycle of ED monotherapy (pembrolizumab 400 mg Q6W or nivolumab 480 mg Q4W) after switching from canonical interval dosing (CD; pembrolizumab 200 mg Q3W or nivolumab 240 mg Q2W) or treated upfront with ED were retrieved. The primary objective was to compare irAEs patterns within the same population (before and after switch to ED). irAEs spectrum in patients treated upfront with ED and association between irAEs and overall survival were also described. RESULTS: A total of 550 (68%) patients started ICIs with CD and switched to ED. During CD, 225 (41%) patients developed any grade and 17 (3%) G3 or G4 irAEs; after switching to ED, any grade and G3 or G4 irAEs were experienced by 155 (36%) and 20 (5%) patients. Switching to ED was associated with a lower probability of any grade irAEs (adjusted odds ratio [aOR] = 0.83, 95% confidence interval [CI] = 0.64 to 0.99; P = .047), whereas no difference for G3 or G4 events was noted (aOR = 1.55, 95% CI = 0.81 to 2.94; P = .18). Among patients who started upfront with ED (n = 232, 32%), 107 (41%) developed any grade and 14 (5%) G3 or G4 irAEs during ED. Patients with irAEs during ED had improved overall survival (adjusted hazard ratio [aHR] = 0.53, 95% CI = 0.34 to 0.82; P = .004 after switching; aHR = 0.57, 95% CI = 0.35 to 0.93; P = .025 upfront). CONCLUSIONS: Switching ICI treatment from CD and ED did not increase the incidence of irAEs and represents a safe option also outside clinical trials.</p

Cessation of targeted therapy after a complete response in BRAF-mutant advanced melanoma : a case series

Background: It is unknown whether melanoma patients achieving complete response (CR) with targeted therapy can safely discontinue treatment. Methods: All patients treated with BRAF/MEK inhibitors achieving CR and ceasing treatment before progression were identified. Clinical data at treatment initiation, cessation and progression were examined. Results: A total of 12 eligible patients were identified, with median follow-up of 16 months, of whom 6 (50%) recurred at a median of 6.6 months after treatment cessation. One patient lost to follow-up until presentation with symptomatic recurrence was the only relapser to die. At relapse, the remaining five patients had an LDH <1.2 times ULN, four were ECOG 0 and one ECOG 1. Baseline characteristics and time to CR and to discontinuation did not influence the rate of relapse. Conclusions: A large proportion of patients achieving CR with BRAF/MEK inhibitors relapse after treatment cessation. The optimal treatment duration in such patients is unclear, particularly where alternative treatments are available.5 page(s

Sustainable responses in metastatic melanoma patients with and without brain metastases after elective discontinuation of anti-PD1-based immunotherapy due to complete response

BACKGROUND Anti-PD1-based immunotherapy is currently used in most patients with advanced melanoma. Despite the remarkable data regarding overall survival, the optimal treatment duration is still unknown. METHODS We evaluated the outcome of 125 patients with advanced melanoma with and without brain metastases (MBM), treated either with anti-PD1 monotherapy (N = 97) or combined with anti-CTLA4 (N = 28) after elective treatment discontinuation due to complete response (CR) (group A, N = 86), or treatment-limiting toxicity (N = 33) and investigator's decision (ID, N = 6) (group B) with subsequent CR. RESULTS For group A, median duration of treatment (mDoT) was 22 months (range 5-49) and median time to CR 9 months (range 2-47). Accordingly, mDoT for group B was 3 months (range 0-36) and median time to CR 7 months (range 1-32). Seven patients from group A and three from group B experienced disease recurrence. Off-treatment survival was not reached. Median off-treatment response time (mOTRt) was 19 months (range 0-42) and 25 months (range 0-66), respectively. For MBM, mOTRt was 17 months (range 7-41) and 28 months (range 9-39), respectively. After a median follow-up of 38 months (range 9-70), seven (5.6%) patients had deceased, one (0.8%) due to melanoma. CONCLUSIONS Treatment discontinuation is feasible also in patients with MBM. Efficacy outcomes seemed to be similar in both groups of patients who achieved CR, regardless of reason for discontinuation. In patients who experienced disease relapse, treatment re-challenge with anti-PD1 resulted in subsequent renewed response

Baseline neutrophil-to-lymphocyte ratio (NLR) and derived NLR could predict overall survival in patients with advanced melanoma treated with nivolumab

Abstract Background Previous studies have suggested that elevated neutrophil-to-lymphocyte ratio (NLR) is prognostic for worse outcomes in patients with a variety of solid cancers, including those treated with immune checkpoint inhibitors. Methods This was a retrospective analysis of 97 consecutive patients with stage IV melanoma who were treated with nivolumab. Baseline NLR and derived (d) NLR were calculated and, along with other characteristics, correlated with progression-free survival (PFS) and overall survival (OS) in univariate and multivariate analyses. The best cutoff values for NLR and dNLR were derived using Cutoff Finder software based on an R routine which optimized the significance of the split between Kaplan-Meier survival curves. Results In univariate analysis, increasing absolute neutrophil count (ANC), NLR, dNLR and lactate dehydrogenase (LDH) (continuous variables) were all significantly associated with OS. Only NLR (hazard ratio [HR] = 2.85; 95% CI 1.60–5.08; p < 0.0001) and LDH (HR = 2.51; 95% CI 1.36–4.64; p < 0.0001) maintained a significant association with OS in multivariate analysis. Patients with baseline NLR ≥5 had significantly worse OS and PFS than patients with NLR < 5, as did patients with baseline dNLR ≥3 versus < 3. Optimal cut-off values were ≥ 4.7 for NLR and ≥ 3.8 for dNLR. Using this ≥4.7 cut-off for NLR, the values for OS and PFS were overlapping to the canonical cut-off for values, and dNLR< 3.8 was also associated with better OS and PFS. Conclusion Both Neutrophil-to-lymphocyte ratio (NLR) and derived (d) NLR were associated with improved survival when baseline levels were lower than cut-off values. NLR and dNLR are simple, inexpensive and readily available biomarkers that could be used to help predict response to immunotherapy in patients with advanced melanoma

Immunotherapy Assessment: A New Paradigm for Radiologists

Immunotherapy denotes an exemplar change in an oncological setting. Despite the effective application of these treatments across a broad range of tumors, only a minority of patients have beneficial effects. The efficacy of immunotherapy is affected by several factors, including human immunity, which is strongly correlated to genetic features, such as intra-tumor heterogeneity. Classic imaging assessment, based on computed tomography (CT) or magnetic resonance imaging (MRI), which is useful for conventional treatments, has a limited role in immunotherapy. The reason is due to different patterns of response and/or progression during this kind of treatment which differs from those seen during other treatments, such as the possibility to assess the wide spectrum of immunotherapy-correlated toxic effects (ir-AEs) as soon as possible. In addition, considering the unusual response patterns, the limits of conventional response criteria and the necessity of using related immune-response criteria are clear. Radiomics analysis is a recent field of great interest in a radiological setting and recently it has grown the idea that we could identify patients who will be fit for this treatment or who will develop ir-AEs

PD-L1+ neutrophils as novel biomarkers for stage IV melanoma patients treated with nivolumab

Melanoma displays a rising incidence, and the mortality associated with metastatic form remains high. Monoclonal antibodies that block programmed death (PD-1) and PD Ligand 1 (PD-L1) network have revolutionized the history of metastatic disease. PD-L1 is expressed on several immune cells and can be also expressed on human neutrophils (PMNs). The role of peripheral blood PMNs as predictive biomarkers in anti-PD-1 therapy of melanoma is largely unknown. In this study, we aimed to determine activation status and PD-L1 expression on human neutrophils as possible novel biomarkers in stage IV melanoma patients (MPs). We found that PMNs from MPs displayed an activated phenotype and increased PD-L1 levels compared to healthy controls (HCs). Patients with lower PD-L1+ PMN frequencies displayed better progression-free survival (PFS) and overall survival (OS) compared to patients with high PD-L1+ PMN frequencies. Multivariate analysis showed that PD-L1+ PMNs predicted patient outcome in BRAF wild type MP subgroup but not in BRAF mutated MPs. PD-L1+ PMN frequency emerges as a novel biomarker in stage IV BRAF wild type MPs undergoing anti-PD-1 immunotherapy. Our findings suggest further evaluation of the role of neutrophil subsets and their mediators in melanoma patients undergoing immunotherapy

Clinical Categorization Algorithm (CLICAL) and Machine Learning Approach (SRF-CLICAL) to Predict Clinical Benefit to Immunotherapy in Metastatic Melanoma Patients: Real-World Evidence from the Istituto Nazionale Tumori IRCCS Fondazione Pascale, Napoli, Italy

The real-life application of immune checkpoint inhibitors (ICIs) may yield different outcomes compared to the benefit presented in clinical trials. For this reason, there is a need to define the group of patients that may benefit from treatment. We retrospectively investigated 578 metastatic melanoma patients treated with ICIs at the Istituto Nazionale Tumori IRCCS Fondazione “G. Pascale” of Napoli, Italy (INT-NA). To compare patients’ clinical variables (i.e., age, lactate dehydrogenase (LDH), neutrophil–lymphocyte ratio (NLR), eosinophil, BRAF status, previous treatment) and their predictive and prognostic power in a comprehensive, non-hierarchical manner, a clinical categorization algorithm (CLICAL) was defined and validated by the application of a machine learning algorithm—survival random forest (SRF-CLICAL). The comprehensive analysis of the clinical parameters by log risk-based algorithms resulted in predictive signatures that could identify groups of patients with great benefit or not, regardless of the ICI received. From a real-life retrospective analysis of metastatic melanoma patients, we generated and validated an algorithm based on machine learning that could assist with the clinical decision of whether or not to apply ICI therapy by defining five signatures of predictability with 95% accuracy