Evaluation of COVID-19 impact on DELAYing diagnostic-therapeutic pathways of lung cancer patients in Italy (COVID-DELAY study): fewer cases and higher stages from a real-world scenario

Introduction

COVID-19 has disrupted the global health care system since March 2020. Lung cancer (LC) patients (pts) represent a vulnerable population highly affected by the pandemic. This multicenter Italian study aimed to evaluate whether the COVID-19 outbreak had an impact on access to cancer diagnosis and treatment of LC pts compared with pre-pandemic time.

Methods

Consecutive newly diagnosed LC pts referred to 25 Italian Oncology Departments between March and December 2020 were included. Access rate and temporal intervals between date of symptoms onset and diagnostic and therapeutic services were compared with the same period in 2019. Differences between the 2 years were analyzed using the chi-square test for categorical variables and the Mann–Whitney U test for continuous variables.

Results

A slight reduction (−6.9%) in newly diagnosed LC cases was observed in 2020 compared with 2019 (1523 versus 1637, P = 0.09). Newly diagnosed LC pts in 2020 were more likely to be diagnosed with stage IV disease (P < 0.01) and to be current smokers (someone who has smoked more than 100 cigarettes, including hand-rolled cigarettes, cigars, cigarillos, in their lifetime and has smoked in the last 28 days) (P < 0.01). The drop in terms of new diagnoses was greater in the lockdown period (percentage drop −12% versus −3.2%) compared with the other months included. More LC pts were referred to a low/medium volume hospital in 2020 compared with 2019 (P = 0.01). No differences emerged in terms of interval between symptoms onset and radiological diagnosis (P = 0.94), symptoms onset and cytohistological diagnosis (P = 0.92), symptoms onset and treatment start (P = 0.40), and treatment start and first radiological revaluation (P = 0.36).

Conclusions

Our study pointed out a reduction of new diagnoses with a shift towards higher stage at diagnosis for LC pts in 2020. Despite this, the measures adopted by Italian Oncology Departments ensured the maintenance of the diagnostic-therapeutic pathways of LC pts.

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The COVID-19 outbreak had an impact on access to lung cancer (LC) diagnosis and treatment.

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A slight reduction (−6.9%) in newly diagnosed LC cases was observed in 2020 compared with 2019.

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Newly diagnosed LC pts in 2020 were more likely to be diagnosed with stage IV disease.

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The Italian Oncology Departments ensured the maintenance of the diagnostic-therapeutic pathways of LC pts.

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A reverse migration from high-volume to low-volume cancer centers was noted during the pandemic.

The lung immuno-oncology prognostic score (LIPS-3): a prognostic classification of patients receiving first-line pembrolizumab for PD-L1 ≥ 50% advanced non-small-cell lung cancer

Background

To stratify the prognosis of patients with programmed cell death-ligand 1 (PD-L1) ≥ 50% advanced non-small-cell lung cancer (aNSCLC) treated with first-line immunotherapy.

Methods

Baseline clinical prognostic factors, the neutrophil-to-lymphocyte ratio (NLR), PD-L1 tumour cell expression level, lactate dehydrogenase (LDH) and their combination were investigated by a retrospective analysis of 784 patients divided between statistically powered training (n = 201) and validation (n = 583) cohorts. Cut-offs were explored by receiver operating characteristic (ROC) curves and a risk model built with validated independent factors by multivariate analysis.

Results

NLR < 4 was a significant prognostic factor in both cohorts (P < 0.001). It represented 53% of patients in the validation cohort, with 1-year overall survival (OS) of 76.6% versus 44.8% with NLR > 4, in the validation series. The addition of PD-L1 ≥ 80% (21% of patients) or LDH < 252 U/l (25%) to NLR < 4 did not result in better 1-year OS (of 72.6% and 74.1%, respectively, in the validation cohort). Eastern Cooperative Oncology Group (ECOG) performance status (PS) of 2 [P < 0.001, hazard ratio (HR) 2.04], pretreatment steroids (P < 0.001, HR 1.67) and NLR < 4 (P < 0.001, HR 2.29) resulted in independent prognostic factors. A risk model with these three factors, namely, the lung immuno-oncology prognostic score (LIPS)-3, accurately stratified three OS risk-validated categories of patients: favourable (0 risk factors, 40%, 1-year OS of 78.2% in the whole series), intermediate (1 or 2 risk factors, 54%, 1-year OS 53.8%) and poor (>2 risk factors, 5%, 1-year OS 10.7%) prognosis.

Conclusions

We advocate the use of LIPS-3 as an easy-to-assess and inexpensive adjuvant prognostic tool for patients with PD-L1 ≥ 50% aNSCLC.

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Immunotherapy/chemoimmunotherapy combinations are currently not superior to immunotherapy alone for high PD-L1 aNSCLC.

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NLR with a cut-off of 4 was validated as an independent prognostic factor for immunotherapy in high PD-L1 aNSCLC.

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The addition of either PD-L1 ≥ 80% or LDH < 252 U/l to NLR < 4 did not result in better prognostic stratification.

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The LIPS-3 is a validated 3-class prognostic classification based on the NLR, ECOG PS and pretreatment steroids.

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The LIPS-3 is a routinely assessable adjuvant prognostic tool for high PD-L1 aNSCLC patients.

KEAP1-driven co-mutations in lung adenocarcinoma unresponsive to immunotherapy despite high tumor mutational burden

BACKGROUND

Immune checkpoint inhibitors (ICIs) have demonstrated significant overall survival (OS) benefit in lung adenocarcinoma (LUAD). Nevertheless, a remarkable interpatient heterogeneity characterizes immunotherapy efficacy, regardless of programmed death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB). KEAP1 mutations are associated with shorter survival in LUAD patients receiving chemotherapy. We hypothesized that the pattern of KEAP1 co-mutations and mutual exclusivity may identify LUAD patients unresponsive to immunotherapy.

PATIENTS AND METHODS

KEAP1 mutational co-occurrences and somatic interactions were studied in the whole MSKCC LUAD dataset. The impact of coexisting alterations on survival outcomes in ICI-treated LUAD patients was verified in the randomized phase II/III POPLAR/OAK trials (blood-based sequencing, bNGS cohort, N = 253). Three tissue-based sequencing studies (Rome, MSKCC and DFCI) were used for independent validation (tNGS cohort, N = 289). Immunogenomic features were analyzed using The Cancer Genome Atlas (TCGA) LUAD study.

RESULTS

On the basis of KEAP1 mutational co-occurrences, we identified four genes potentially associated with reduced efficacy of immunotherapy (KEAP1, PBRM1, SMARCA4 and STK11). Independent of the nature of co-occurring alterations, tumors with coexisting mutations (CoMut) had inferior survival as compared with single-mutant (SM) and wild-type (WT) tumors (bNGS cohort: CoMut versus SM log-rank P = 0.048, CoMut versus WT log-rank P < 0.001; tNGS cohort: CoMut versus SM log-rank P = 0.037, CoMut versus WT log-rank P = 0.006). The CoMut subset harbored higher TMB than the WT disease and the adverse significance of coexisting alterations was maintained in LUAD with high TMB. Significant immunogenomic differences were observed between the CoMut and WT groups in terms of core immune signatures, T-cell receptor repertoire, T helper cell signatures and immunomodulatory genes.

CONCLUSIONS

This study indicates that coexisting alterations in a limited set of genes characterize a subset of LUAD unresponsive to immunotherapy and with high TMB. An immune-cold microenvironment may account for the clinical course of the disease.

Latency as a region contrast: Measuring ERP latency differences with Dynamic Time Warping

Methods for measuring onset latency contrasts are evaluated against a new method utilizing the dynamic time warping (DTW) algorithm. This new method allows latency to be measured across a region instead of single point. We use computer simulations to compare the methods' power and Type I error rates under different scenarios. We perform per-participant analysis for different signal-to-noise ratios and two sizes of window (broad vs. narrow). In addition, the methods are tested in combination with single-participant and jackknife average waveforms for different effect sizes, at the group level. DTW performs better than the other methods, being less sensitive to noise as well as to placement and width of the window selected.