Risk factors for adverse events induced by immune checkpoint inhibitors in patients with non-small-cell lung cancer:a systematic review and meta-analysis

BACKGROUND: Immune checkpoint inhibitors (ICIs) can cause serious immune-related adverse events (irAEs). This study aimed to identify risk factors for all types of irAEs induced by ICIs in patients with non-small-cell lung cancer (NSCLC), by systematic review and meta-analyses. METHODS: A systematic search was performed in Pubmed, Embase and Web of Science by two independent reviewers. Studies were selected that included patients with NSCLC and evaluated characteristics of patients with and without irAEs induced by ICIs. Quality and risk of bias of the selected studies were assessed. Random effects meta-analyses were conducted to estimate pooled odds ratios (ORs) for risk factors of developing all type of irAEs, and separately for pneumonitis, interstitial lung disease and severe irAEs. With the objective of exploring sources of heterogeneity, stratified analyses were performed by quality and region. RESULTS: 25 studies met the inclusion criteria. In total, the data of 6696 patients were pooled. 33 different risk factors for irAEs were reported. irAEs of interest were reported for 1653 (25%) of the patients. Risk factors related to the development of irAEs were: C-reactive protein, neutrophil lymphocyte ratio (NLR), use of PD-1 inhibitor, high PD-L1 expression, an active or former smoking status, ground glass attenuation, and a better treatment response. CONCLUSION: The identified risk factors for the development of these irAEs are mostly related to the alteration of the immune system, proinflammatory states and loss of immunological self-tolerance. Patients identified as having a higher risk for irAEs should be monitored more closely

Quality of life after treatment with immune checkpoint inhibitors for lung cancer:the impact of age

Introduction: Immune checkpoint inhibitors (ICIs) have revolutionized lung cancer treatment. However, it remains unclear as to whether changes in Health-Related Quality-of-Life (HRQoL) are associated with the age of lung cancer patients treated using ICIs. This study aimed to evaluate this possible association and to compare ICI-treated patients’ HRQoL scores with normative data of an age-matched non-cancer general population.Methods: Lung cancer patients from the OncoLifeS data-biobank were included if they were treated with ICIs, irrespective of other treatments, at the University Medical Center Groningen between 2015 and 2021 and had completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTCQLQ-C30), both at the start of ICI treatment and after six months. Association of age as a continuous variable (per 10 years) and changes in HRQoL scores between baseline and 6 months was assessed using multivariable regression analyses. Clinical relevance of differences in HRQoL scores between OncoLifeS and the general population was classified into trivial, small, medium, and large, for three age groups (&lt;60, 60–69 and ≥ 70 years).Results: 151 patients were included with a mean age of 65.8 years. An increase in age per 10 years was associated with a larger decrease in the summary HRQoL score(β = -3.28,CI95%-6.42;-0.14), physical(β = -4.8, CI95% −8.71;-0.88), cognitive(β = −4.51,CI95%-8.24;−0.78), role functioning(β = −5.41,CI95%-10.78;−0.05), symptom burden(β = −3.66,CI95%-6.6;-0.73), and smaller negative changes in financial difficulties(β = 6.5 95 % CI 3.16; 9.85). OncoLifeS HRQoL scores were lower than those of the general population and differences were most often classified as large and medium.Conclusion: Older lung cancer patients experience larger deteriorations in most HRQoL domains after 6 months of ICI treatment. Also, these patients showed significantly lower HRQoL scores compared to the general population.</p

Treatment goals and changes over time in older patients with non-curable cancer

PURPOSE: To investigate the treatment goals of older patients with non-curable cancer, whether those goals changed over time, and if so, what triggered those changes. METHODS: We performed a descriptive and qualitative analysis using the Outcome Prioritization Tool (OPT) to assess patient goals across four conversations with general practitioners (GPs) over 6 months. Text entries from electronic patient records (hospital and general practice) were then analyzed qualitatively for this period. RESULTS: Of the 29 included patients, 10 (34%) rated extending life and 9 (31%) rated maintaining independence as their most important goals. Patients in the last year before death (late phase) prioritized extending life less often (3 patients; 21%) than those in the early phase (7 patients; 47%). Goals changed for 16 patients during follow-up (12 in the late phase). Qualitative analysis revealed three themes that explained the baseline OPT scores (prioritizing a specific goal, rating a goal as unimportant, and treatment choices related to goals). Another three themes related to changes in OPT scores (symptoms, disease course, and life events) and stability of OPT scores (stable situation, disease-unrelated motivation, and stability despite symptoms). CONCLUSION: Patients most often prioritized extending life as the most important goal. However, priorities differed in the late phase of the disease, leading to changed goals. Triggers for change related to both the disease (e.g., symptoms and course) and to other life events. We therefore recommend that goals should be discussed repeatedly, especially near the end of life. TRIAL REGISTRATION: OPTion study: NTR5419

Reliability of panel-based mutational signatures for immune-checkpoint-inhibition efficacy prediction in non-small cell lung cancer

OBJECTIVES: Mutational signatures (MS) are gaining traction for deriving therapeutic insights for immune checkpoint inhibition (ICI). We asked if MS attributions from comprehensive targeted sequencing assays are reliable enough for predicting ICI efficacy in non-small cell lung cancer (NSCLC).METHODS: Somatic mutations of m = 126 patients were assayed using panel-based sequencing of 523 cancer-related genes. In silico simulations of MS attributions for various panels were performed on a separate dataset of m = 101 whole genome sequenced patients. Non-synonymous mutations were deconvoluted using COSMIC v3.3 signatures and used to test a previously published machine learning classifier.RESULTS: The ICI efficacy predictor performed poorly with an accuracy of 0.51 -0.09 +0.09, average precision of 0.52 -0.11 +0.11, and an area under the receiver operating characteristic curve of 0.50 -0.09 +0.10. Theoretical arguments, experimental data, and in silico simulations pointed to false negative rates (FNR) related to panel size. A secondary effect was observed, where deconvolution of small ensembles of point mutations lead to reconstruction errors and misattributions. CONCLUSION: MS attributions from current targeted panel sequencing are not reliable enough to predict ICI efficacy. We suggest that, for downstream classification tasks in NSCLC, signature attributions be based on whole exome or genome sequencing instead.</p

Erratum to: Circulating tumor DNA as a biomarker for monitoring early treatment responses of patients with advanced lung adenocarcinoma receiving immune checkpoint inhibitors.

The following error appeared in Section 3.5 in Ref. [1]. Instead of ‘Progressive disease-L1 expression data were available for 87 patients’, the text should read ‘PD-L1 expression data were available for 87 patients’. We apologize for this error.</p

A comprehensive overview of the heterogeneity of EGFR exon 20 variants in NSCLC and (pre)clinical activity to currently available treatments

Activating EGFR mutations are commonly observed in non-small cell lung cancer (NSCLC). About 4-10 % of all activating epidermal growth factor receptor (EGFR) mutations are heterogenous in-frame deletion and/or insertion mutations clustering within exon 20 (EGFRex20+). NSCLC patients with EGFRex20+ mutations are treated as a single disease entity, irrespective of the type and location of the mutation. Here, we provide a comprehensive assessment of the literature reporting both in vitro and clinical drug sensitivity across different EGFRex20+ mutations. The activating A763_Y764insFQEA mutation has a better tumor response in comparison with mutations in the near- and far regions directly following the C-helix and should therefore be treated differently. For other EGFRex20+ mutations marked differences in treatment responses have been reported indicating the need for a classification beyond the exon-based classification. A further classification can be achieved using a structure-function modeling approach and experimental data using patient-derived cell lines. The detailed overview of TKI responses for each EGFRex20+ mutation can assist treating physicians to select the most optimal drug for individual NSCLC patients.</p