Survival Of Non-small Cell Lung Cancer Patients Research Articles

The Glasgow Prognostic Score Predicts Survival in Patients with Advanced Non-Small Cell Lung Cancer Harboring Sensitive Epidermal Growth Factor Receptor Mutations Who Are Treated with Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitors

Introduction: Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) with sensitive EGFR mutations. The Glasgow prognostic score (GPS) is an inflammation-assessing score based on C-reactive protein and albumin concentrations. Information regarding the association between the GPS and EGFR-TKI treatment effectiveness is limited; hence, we investigated whether the GPS can predict the response of NSCLC to EGFR-TKIs. Methods: We evaluated 340 patients with NSCLC harboring sensitive EGFR mutations who received EGFR-TKI monotherapy between March 2009 and July 2021. The Kaplan-Meier method and Cox proportional hazards models were used to assess progression-free survival (PFS) and overall survival (OS). Results: After a median follow-up of 26.6 months, patients with a GPS of 0, 1, and 2 had PFS of 15.7, 10.0, and 6.3 months, respectively, and OS of 40.1, 25.8, and 14.4 months, respectively; patients with a GPS of 0 had significantly better PFS and OS than those with a GPS of 1 (p = 0.03, p = 0.001, respectively) or 2 (p < 0.001, p < 0.001, respectively). Multivariate analysis identified poor performance status, stage 4 at diagnosis, type of EGFR-TKI (gefitinib/erlotinib vs. afatinib), and GPS = 2 as predictors of a short PFS. Meanwhile, poor performance status, gefitinib/erlotinib administration, and GPS = 2 were predictors of a short OS. Conclusion: The GPS predicted the survival of NSCLC patients harboring sensitive EGFR mutations who were undergoing EGFR-TKI treatment. The GPS might be ideal for routine use in clinical practice, given that it is an easily calculated parameter.

Using genomic scars to select immunotherapy beneficiaries in advanced non-small cell lung cancer

In advanced non-small cell lung cancer (NSCLC), response to immunotherapy is difficult to predict from pre-treatment information. Given the toxicity of immunotherapy and its financial burden on the healthcare system, we set out to identify patients for whom treatment is effective. To this end, we used mutational signatures from DNA mutations in pre-treatment tissue. Single base substitutions, doublet base substitutions, indels, and copy number alteration signatures were analysed in m=101 patients (the discovery set). We found that tobacco smoking signature (SBS4) and thiopurine chemotherapy exposure-associated signature (SBS87) were linked to durable benefit. Combining both signatures in a machine learning model separated patients with a progression-free survival hazard ratio of 0.40_{-0.17}^{+0.28} on the cross-validated discovery set and 0.24_{-0.14}^{+0.31} on an independent external validation set (m=56). This paper demonstrates that the fingerprints of mutagenesis, codified through mutational signatures, select advanced NSCLC patients who may benefit from immunotherapy, thus potentially reducing unnecessary patient burden.

Bayesian network enables interpretable and state-of-the-art prediction of immunotherapy responses in cancer patients.

Immune checkpoint inhibitors, especially PD-1/PD-L1 blockade, have revolutionized cancer treatment and brought tremendous benefits to patients who otherwise would have had a limited prognosis. Nonetheless, only a small fraction of patients respond to immunotherapy, and the costs and side effects of immune checkpoint inhibitors cannot be ignored. With the advent of machine and deep learning, clinical and genetic data have been used to stratify patient responses to immunotherapy. Unfortunately, these approaches have typically been "black-box" methods that are unable to explain their predictions, thereby hindering their responsible clinical application. Herein, we developed a "white-box" Bayesian network model that achieves accurate and interpretable predictions of immunotherapy responses against nonsmall cell lung cancer (NSCLC). This tree-augmented naïve Bayes (TAN) model accurately predicted durable clinical benefits and distinguished two clinically significant subgroups with distinct prognoses. Furthermore, our state-of-the-art white-box TAN approach achieved greater accuracy than previous methods. We hope that our model will guide clinicians in selecting NSCLC patients who truly require immunotherapy and expect our approach to be easily applied to other types of cancer.

Association of heartbeat complexity with survival in advanced non-small cell lung cancer patients.

Previous studies have shown that the predictive value of traditional linear (time domain and frequency domain) heart rate variability (HRV) for the survival of patients with advanced non-small cell lung cancer (NSCLC) is controversial. Nonlinear methods, based on the concept of complexity, have been used to evaluate HRV, providing a new means to reveal the physiological and pathological changes in HRV. This study aimed to assess the association between heartbeat complexity and overall survival in patients with advanced NSCLC. This study included 78 patients with advanced NSCLC (mean age: 62.0 ± 9.3 years). A 5-min resting electrocardiogram of advanced NSCLC patients was collected to analyze the following HRV parameters: time domain indicators, i.e., standard deviation of the normal-normal intervals (SDNN) and root mean square of successive interval differences (RMSSD); frequency domain indicators, i.e., total power (TP), low frequency power (LF), high frequency power (HF), and the ratio of LF to HF (LF/HF); nonlinear HRV indicators characterizing heartbeat complexity, i.e., approximate entropy (ApEn), sample entropy (SampEn), and recurrence quantification analysis (RQA) indexes: mean diagonal line length (Lmean), maximal diagonal line length (Lmax), recurrence rate (REC), determinism (DET), and shannon entropy (ShanEn). Univariate analysis revealed that the linear frequency domain parameter HF and nonlinear RQA parameters Lmax, REC, and DET were significantly correlated with the survival of advanced NSCLC patients (all p < 0.05). After adjusting for confounders in the multivariate analysis, HF, REC, and DET were found to be independent prognostic factors for the survival of patients with advanced NSCLC (all p < 0.05). There was an independent association between heartbeat complexity and survival in advanced NSCLC patients. The nonlinear analysis method based on RQA may provide valuable additional information for the prognostic stratification of patients with advanced NSCLC and may supplement the traditional time domain and frequency domain analysis methods.

Intrathecal chemotherapy combined with systemic therapy in patients with refractory leptomeningeal metastasis of non-small cell lung cancer: a retrospective study

BackgroundLeptomeningeal metastasis (LM) is the most devastating complication of non-small cell lung cancer (NSCLC), and its incidence is increasing. There is currently no standard treatment for LM, and the efficacy of traditional intravenous drug treatment is low, making refractory LM a difficult problem. In this study, we evaluated the efficacy and safety of intrathecal chemotherapy (IC)-based regimens in patients with refractory LM.MethodsWe retrospectively enrolled NSCLC patients with confirmed LM who received IC and systemic therapy at the Second Affiliated Hospital of Nanchang University from December 2017 to July 2022. We analysed overall survival (OS), intracranial progression-free survival (iPFS), clinical response, and safety in these patients.ResultsA total of 41 patients were enrolled. The median number of IC treatments was seven (range: 2–22). Seven patients received intrathecal methotrexate, and 34 patients received intrathecal pemetrexed. Clinical manifestations related to LM improved after IC and systemic therapy in 28 (68.3%) patients. The median iPFS in the whole cohort was 8 months (95% confidence interval [CI]: 6.4–9.7 months), and the median OS was 10.1 months (95% CI: 6.8–13.4 months). Multivariate analysis of the 41 patients with LM using a Cox proportional risk model showed that bevacizumab was an independent prognostic factor in patients treated with combination therapy (p = 0.002; hazard ratio [HR] 0.240; 95% CI: 0.097–0.595). Poor ECOG performance status remained a significant predictor of poor prognosis for survival (p = 0.048; HR 2.560; 95% CI: 1.010–6.484). Myelosuppression was the major adverse event over all IC dose levels. There were 18 cases of myelosuppression, 15 cases of leukopenia, and nine cases of thrombocytopenia. Eleven patients had myelosuppression above grade 3, including four with thrombocytopenia and seven with leukopenia.ConclusionsCombination therapy based on IC had good curative effects, was safe to use, and was associated with prolonged survival in NSCLC patients with LM. The use of bevacizumab is a good prognostic factor for NSCLC LM patients with combination therapy.

Efficacy of immunotherapy as second-line or later-line therapy and prognostic significance of KRAS or TP53 mutations in advanced non-small cell lung cancer patients.

In this retrospective study, we aimed to assess the relationship between mutations in the Kirsten rats sarcoma viral oncogene (KRAS )/ tumor protein p53 (TP53 ) genes and the efficacy of immune checkpoint inhibitors (ICIs) therapy as a second-line or later-line treatment for patients with stage IIIB/IV non-small cell lung cancer (NSCLC). We retrospectively analyzed the clinical data of 143 patients with stage IIIB/IV NSCLC who were admitted to the Cancer Hospital of Harbin Medical University between January 2019 and September 2022. Kaplan-Meier survival curve analysis was performed to analyze the survival outcomes. Univariate and multivariate Cox proportional risk models were used to analyze the factors associated with the progression-free survival (PFS) and overall survival (OS) of advanced-stage NSCLC patients who received ICIs as second-line or later-line therapy. NSCLC patients with KRAS or TP53 mutations treated with ICIs showed significantly higher objective response rate, disease control rate, PFS, and OS compared to NSCLC patients with wild-type KRAS / TP53 (P < 0.05). Multivariate Cox regression analysis showed that a combined treatment regimen of ICIs plus chemotherapy was significantly associated with prolonged PFS [hazard ratio = 0.192; 95% confidence interval (CI), 0.094-0.392; P < 0.001] and OS (hazard ratio = 0.414; 95% CI, 0.281-0.612; P < 0.001). KRAS or TP53 mutations were associated with improved PFS of advanced NSCLC patients treated with ICIs as second-line or later-line therapy. KRAS or TP53 mutations show great potential as clinical biomarkers to predict the efficacy of ICIs therapy.

Abstract 5506: Circulating immature neutrophils early detect hyperprogressive disease upon first-line PD-1/PD-L1 inhibitors in non-small cell lung cancer patients selecting best candidates for platinum-based chemotherapy and PD-1/PD-L1 inhibitors combinations

Abstract Background: Hyperprogressive disease (HPD) has been described in ≃14-25% of pretreated non-small cell lung cancer (NSCLC) patients upon single-agent (SA) PD-1/PD-L1 inhibitors (ICI) and has not been reported upon platinum-based chemotherapy (PCT) and ICI combinations. So far, no predictive biomarkers are available for HPD early detection. Methods: NSCLC patients treated with 1st line SA-ICI or PCT-ICI were assessed for HPD and circulating neutrophils. HPD was defined as delta tumor growth rate (TGR) &amp;gt;50% and/or TGR ratio ≥2. Circulating low density neutrophils (LDNs) were assessed by flow cytometry on peripheral blood mononuclear cells (PMBCs). LDNs were defined as CD66b+CD15+ cells among CD11b+ PBMCs and immature subtypes as CD10− LDNs. The LDNs predictive role was assessed by penalized model-based tests. Results: 144 NSCLC patients were included: 75 treated with SA-ICI, 69 with PCT-ICI. In the SA-ICI cohort, HPD occurred in 8 (11%) patients, while progressive disease (PD) and response or stable disease (PR/SD) occurred in 33 (44%) and 34 (45%) of patients respectively. Immature circulating CD10− LDNs were significantly higher in baseline blood samples of HPD patients [median (ME): 39.3, interquartile range (IQR): 28.7] compared to PD [ME: 7.4, IQR: 14.9, p&amp;lt;0.01] or PR/SD patients [ME: 3.7, IQR: 12.6, p&amp;lt;0.01]. Circulating CD10− LDNs were associated with HPD [odds ratio (OR): 1.17, 95% CI: 1.06; 1.29], with a good prediction capability [cross-validated AUC 0.97 (95%CI: 0.94;1.00)]. A 30.5% cut-off value for CD10− LDNs circulating neutrophils was identified by Younden index to discriminate HPD from others. In the PCT-ICI cohort, 14 patients had circulating CD10− LDNs ≥30.5%, being at high risk of HPD. However, no HPD was observed in PCT-ICI cohort and dynamic LDNs evaluation in high HPD risk patients showed 52.3% (IQR: 28.4) median reduction in CD10− LDNs upon PCT-ICI, versus only 8.9% (IQR: 34.6) reduction in HPD patients upon SA-ICI, suggesting that PCT prevents HPD by reducing selectively immature LDNs. Conclusions: Baseline circulating immature neutrophils characterize HPD upon 1st line SA-ICI and a 30.5% cut-off of immature neutrophils could select NSCLC patients to be addressed to PCT-ICI combinations. Citation Format: Roberto Ferrara, Giuseppe Lo Russo, Chiara Maura Ciniselli, Annamaria Piva, Barbara Bassani, Elena Jachetti, Giuseppina Calareso, Valeria Duroni, Settimio Di Gregorio, Claudia Proto, Arsela Prelaj, Alessandro De Toma, Mario Occhipinti, Marta Brambilla, Sara Manglaviti, Laura Mazzeo, Arturo Rinaldi, Teresa Beninato, Monica Ganzinelli, Filippo De Braud, Marina Chiara Garassino, Paolo Verderio, Mario Paolo Colombo, Sabina Sangaletti. Circulating immature neutrophils early detect hyperprogressive disease upon first-line PD-1/PD-L1 inhibitors in non-small cell lung cancer patients selecting best candidates for platinum-based chemotherapy and PD-1/PD-L1 inhibitors combinations. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5506.

Validation of the initial brain metastasis velocity in non-small cell lung cancer at a single cancer center

The initial brain metastasis velocity (iBMV) was recently reported as a survival predictor after brain metastases (BM) in patients treated by stereotactic radiosurgery. In this study, we validated whether iBMV is a prognostic tool, regardless of treatment modality, in patients with non-small cell lung cancer (NSCLC) with metachronous BM. We retrospectively reviewed consecutive 3,792 new lung cancer cases in which no BM was found on magnetic resonance (MR) screening between February 2014 and December 2019, and enrolled 176 NSCLC patients with subsequent BM. Overall survival (OS) was calculated from the date of MR to identify the time from BM to death. The median iBMV score was 1.9. We used an iBMV score of 2.0 as the cutoff level, as previously reported. An iBMV score ≥ 2.0 was significantly associated with older age, high neutrophil-to-lymphocyte ratio, and Stage IV (P = 0.04, 0.02, and 0.02, respectively). The median OS was 0.92 years. The median OS for patients with iBMV score ≥ 2.0 and < 2.0 were 0.59 years and 1.33 years, respectively (P < 0.001). Multivariate analysis showed that an iBMV score ≥ 2.0, ECOG performance status score of 1-3, Stage IV, and non-adenocarcinoma histology were independent poor prognostic factors (hazard ratio (HR), 1.94; P = 0.0001; HR, 1.53; P = 0.04; HR, 1.45; P = 0.04; and HR, 1.14; P = 0.03, respectively). Patients with iBMV scores of < 2.0 were more likely to undergo craniotomy or stereotactic irradiation. An iBMV score ≥ 2.0 is an independent predictor of survival in NSCLC patients with metachronous BM, regardless of the treatment modality.

Association of neutrophil–lymphocyte ratio with survival in peripheral early-stage non-small cell lung cancer after stereotactic body radiation therapy

BackgroundThe role of neutrophil–lymphocyte ratio (NLR) as a predictor for survival in single fraction SBRT-treated non-small cell lung cancer (NSCLC) patients remains unclear. We performed an observational cohort study to determine the role of pretreatment NLR in predicting survival of early-stage NSCLC patients after single fraction SBRT.MethodsA single-institution database of peripheral early-stage NSCLC patients treated with SBRT from February 2007 to May 2022 was queried. Optimal threshold of neutrophil–lymphocyte ratio (NLR) was defined based on maximally selected rank statistics. Cox multivariable analysis (MVA), Kaplan–Meier, and propensity score matching were performed to evaluate outcomes.ResultsA total of 286 patients were included for analysis with median follow up of 19.7 months. On Cox multivariate analysis, as a continuous variable, NLR was shown to be an independent predictor of OS (adjusted hazards ratio [aHR] 1.06, 95% CI 1.02–1.10, p = 0.005) and PFS (aHR 1.05, 95% CI 1.01–1.09, p = 0.013). In addition, NLR was associated with DF (aHR 1.11, 95% CI 1.05–1.18, p < 0.001). Maximally selected rank statistics determined 3.28 as the cutoff point of high NLR versus low NLR. These findings were confirmed upon propensity matching.ConclusionsPretreatment NLR is an independent predictor for survival outcomes of peripheral early-stage NSCLC patients after single fraction SBRT.

Identification and validation of novel prognostic biomarkers and therapeutic targets for non-small cell lung cancer.

Background: Despite the significant survival benefits of anti-PD-1/PD-L1 immunotherapy, non-small cell lung cancer (NSCLC) remains one of the most common tumors and major causes of cancer-related deaths worldwide. Thus, there is an urgent need to identify new therapeutic targets for this refractory disease. Methods: In this study, microarray datasets GSE27262, GSE75037, GSE102287, and GSE21933 were integrated by Venn diagram. We performed functional clustering and pathway enrichment analyses using R. Through the STRING database and Cytoscape, we conducted protein-protein interaction (PPI) network analysis and identified the key genes, which were verified by the GEPIA2 and UALCAN portal. Validation of actin-binding protein anillin (ANLN) was performed by quantitative real-time polymerase chain reaction and Western blotting. Additionally, Kaplan-Meier methods were used to compute the survival analyses. Results: In total, 126 differentially expressed genes were identified, which were enriched in mitotic nuclear division, mitotic cell cycle G2/M transition, vasculogenesis, spindle, and peroxisome proliferator-activated receptor signaling pathway. 12 central node genes were identified in the PPI network complex. The survival analysis revealed that high transcriptional levels were associated with inferior survival in NSCLC patients. The clinical implication of ANLN was further explored; its protein expression showed a gradually increasing trend from grade I to III. Conclusion: These Key genes may be involved in the carcinogenesis and progression of NSCLC, which may serve as useful targets for NSCLC diagnosis and treatment.

Addition of metformin for non-small cell lung cancer patients receiving antineoplastic agents.

Background and purpose: Previous studies have found that metformin can inhibit tumor growth and improve outcomes for cancer patients. However, the association between the addition of metformin to the treatment regimen and survival in non-small cell lung cancer (NSCLC) patients receiving antineoplastic agents such as chemotherapy drugs, epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), and immune checkpoint inhibitors (ICIs) remains unclear. This study aimed to evaluate the effect of metformin in NSCLC patients who received the aforementioned antineoplastic therapies. Methods: Several electronic databases were searched for relevant studies published by 10 September 2022. The primary and secondary outcomes were overall survival (OS) and progression-free survival (PFS); eligible studies were those comparing patients with and without the addition of metformin. Hazard ratios (HRs) and 95% confidence intervals (CIs) were combined, with all statistical analyses performed using STATA 15.0. Results: A total of 19 studies involving 6,419 participants were included, of which six were randomized controlled trials. The overall pooled results indicate that the addition of metformin improved OS (HR = 0.84, 95% CI: 0.71-0.98, p = 0.029) and PFS (HR = 0.85, 95% CI: 0.74-0.99, p = 0.039). However, subgroup analysis based on treatment type and comorbidity of diabetes mellitus demonstrated that improvements in OS and PFS were observed only in diabetic and EGFR-TKI-treated patients (OS: HR = 0.64, 95% CI: 0.45-0.90, p = 0.011; PFS: HR = 0.59, 95% CI: 0.34-1.03, p = 0.061). Conclusion: Overall, this meta-analysis found that metformin use could improve outcomes for diabetic patients receiving EGFR-TKIs. However, no significant association between the addition of metformin and the survival of non-diabetic NSCLC patients receiving chemotherapy or ICI therapy was identified based on the current evidence.

Osimertinib Improves overall survival of EGFR-mutant NSCLC patients with leptomeningeal metastases

ObjectiveOsimertinib is a third-generation, irreversible, small-molecule epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) that can effectively penetrate the blood brain-barrier (BBB). This study mainly explored the factors affecting the prognosis of EGFR-mutant advanced non-small cell lung cancer (NSCLC) patients with leptomeningeal metastases (LM), and whether osimertinib could improve the survival benefit in these patients compared with those not treated with osimertinib. MethodsWe retrospectively analyzed patients who had been admitted with EGFR-mutant NSCLC and cytologically confirmed LM to the Peking Union Medical College Hospital between January 2013 and December 2019. Overall survival (OS) was defined as the primary outcome of interest. ResultsA total of 71 patients with LM were included in this analysis, with a median OS (mOS) of 10.7 months (95% CI [7.6, 13.8]). Among them, 39 patients were treated with osimertinib after LM while 32 patients were untreated. Patients treated with osimertinib had a mOS of 11.3 months (95%CI [0, 23.9]) compared with the untreated patients who had a mOS of 8.1 months (95%CI [2.9, 13.3]), with a significant difference between the groups (hazard ratio [HR]): 0.43, 95%CI:0.22–0.66, p = 0.0009). Multivariate analysis revealed the use of osimertinib were correlated with superior OS with a HR of 0.43 (95%CI [0.25, 0.75]), with a statistically significant difference (p = 0.003). ConclusionsOsimertinib can prolong the overall survival of EGFR-mutant NSCLC patients with LM and improve patient outcomes.

The Efficacy and Safety of Afatinib in Non-Small Cell Lung Cancer Patients with Brain Metastasis: A Meta-Analysis.

The aim of this study is to evaluate the efficacy and safety of afatinib in the treatment of non-small cell lung cancer (NSCLC) patients with brain metastasis based on meta-analysis. Related literatures were searched in the following databases: EMbase, PubMed, China Knowledge Network (CNKI), Wanfang, Weipu, Google Scholar, the China Biomedical Literature Service System, and other databases. Clinical trials and observational studies that met the requirements were selected for meta-analysis using Revman 5.3. The hazard ratio (HR) was used as an indicator of the impact of afatinib. A total of 142 related literatures were acquired, but after screening, five literatures were selected for data extraction. The following indices were compared: the progression-free survival (PFS), overall survival (OS), and common adverse reactions (ARs) of grade 3 and above. A total of 448 patients with brain metastases were included and were divided into two groups: the control group (no afatinib treatment, with chemotherapy alone and the first-generation EGFR-TKIs) and the afatinib group. The results showed that afatinib could improve PFS (HR: 0.58, 95% CI: 0.39-0.85, P < 0.05) and ORR (OR = 2.86, 95% CI: 1.45-2.57, P < 0.05), but had no benefit on OS (HR: 1.13, 95% CI: 0.15-8.75, P > 0.05) and DCR (OR = 2.87, 95% CI: 0.97-8.48, P > 0.05). For the safety of afatinib, the incidence of grade-3-and-above ARs was low (HR: 0.01, 95% CI: 0.00-0.02, P < 0.05). Afatinib improves the survival of NSCLC patients with brain metastases and shows satisfactory safety.

Interpretation of expert consensus on treatment for stage III non‐small cell lung cancer

Interpretation of expert consensus on treatment for stage III non‐small cell lung cancer

Integrative Nomogram of Computed Tomography Radiomics, Clinical, and Tumor Immune Features for Analysis of Disease-Free Survival of NSCLC Patients with Surgery.

To improve prognosis of cancer patients and determine the integrative value for analysis of disease-free survival prediction, a clinic investigation was performed involving with 146 non-small cell lung cancer (NSCLC) patients (83 men and 73 women; mean age: 60.24 years ± 8.637) with a history of surgery. Their computed tomography (CT) radiomics, clinical records, and tumor immune features were firstly obtained and analyzed in this study. Histology and immunohistochemistry were also performed to establish a multimodal nomogram through the fitting model and cross-validation. Finally, Z test and decision curve analysis (DCA) were performed to evaluate and compare the accuracy and difference of each model. In all, seven radiomics features were selected to construct the radiomics score model. The clinicopathological and immunological factors model, including T stage, N stage, microvascular invasion, smoking quantity, family history of cancer, and immunophenotyping. The C-index of the comprehensive nomogram model on the training set and test set was 0.8766 and 0.8426 respectively, which was better than that of the clinicopathological-radiomics model (Z test, P =0.041<0.05), radiomics model and clinicopathological model (Z test, P =0.013<0.05 and P =0.0097<0.05). Integrative nomogram based on computed tomography radiomics, clinical and immunophenotyping can be served as effective imaging biomarker to predict DFS of hepatocellular carcinoma after surgical resection.

Beta Blockers with Statins May Decrease All-Cause Mortality in Patients with Cardiovascular Diseases and Locally Advanced Unresectable Non-Small-Cell Lung Cancer after Chemoradiotherapy

The study was conducted in the era when maintenance immunotherapy with durvalumab was not available in clinical practice after chemoradiotherapy (CRT) in unresectable non-small-cell lung cancer (NSCLC). The main aim of the study was to check whether the presence of cardiovascular diseases (CVD) and their pharmacotherapy affects the overall survival (OS) in such NSCLC patients undergoing sequential CRT. The group of 196 patients were analyzed: 101 patients with CVD (51.53%) and 95 patients with other reasons of qualification for sequential CRT (decreased performance status, older age, and other non-cardiovascular co-morbidities). Although patients with CVD were more often in older age, and they more often experienced cardiac and nephrological complications (p < 0.05 for all), there was a statistically nonsignificant trend for lower all-cause mortality in patients with CVD. The lowest all-cause mortality was observed in patients treated with beta-blockers and statins after two (HR = 0.31; 95%CI: 0.1-0.98; p = 0.047), three (HR = 0.33; 95%CI: 0.13-0.81; p = 0.015) and even four (HR = 0.45; 95%CI: 0.22-0.97; p = 0.027) years of follow-up. The benefit in OS remained significant in 101 patients with CVD treated with beta-blockers (HR = 0.65; 95%CI: 0.43-0.99; p = 0.045), and eventually statin, throughout the whole follow-up (log-rank p < 0.05). Further prospective studies are necessary to confirm the role of beta-blockers and statins in reduction of mortality in NSCLC patients undergoing radical CRT.

Integrated multi-dimensional deep neural network model improves prognosis prediction of advanced NSCLC patients receiving bevacizumab.

The addition of bevacizumab was found to be associated with prolonged survival whether in combination with chemotherapy, tyrosine kinase inhibitors or immune checkpoint inhibitors in the treatment landscape of advanced non-small cell lung cancer (NSCLC) patients. However, the biomarkers for efficacy of bevacizumab were still largely unknown. This study aimed to develop a deep learning model to provide individual assessment of survival in advanced NSCLC patients receiving bevacizumab. All data were retrospectively collected from a cohort of 272 radiological and pathological proven advanced non-squamous NSCLC patients. A novel multi-dimensional deep neural network (DNN) models were trained based on clinicopathological, inflammatory and radiomics features using DeepSurv and N-MTLR algorithm. And concordance index (C-index) and bier score was used to demonstrate the discriminatory and predictive capacity of the model. The integration of clinicopathologic, inflammatory and radiomics features representation was performed using DeepSurv and N-MTLR with the C-index of 0.712 and 0.701 in testing cohort. And Cox proportional hazard (CPH) and random survival forest (RSF) models were also developed after data pre-processing and feature selection with the C-index of 0.665 and 0.679 respectively. DeepSurv prognostic model, indicated with best performance, was used for individual prognosis prediction. And patients divided in high-risk group were significantly associated with inferior PFS (median PFS: 5.4 vs 13.1 months, P<0.0001) and OS (median OS: 16.4 vs 21.3 months, P<0.0001). The integration of clinicopathologic, inflammatory and radiomics features representation based on DeepSurv model exhibited superior predictive accuracy as non-invasive method to assist in patients counseling and guidance of optimal treatment strategies.

Predicting survival of NSCLC patients treated with immune checkpoint inhibitors: Impact and timing of immune-related adverse events and prior tyrosine kinase inhibitor therapy.

Immune checkpoint inhibitors (ICIs) produce a broad spectrum of immune-related adverse events (irAEs) affecting various organ systems. While ICIs are established as a therapeutic option in non-small cell lung cancer (NSCLC) treatment, most patients receiving ICI relapse. Additionally, the role of ICIs on survival in patients receiving prior targeted tyrosine kinase inhibitor (TKI) therapy has not been well-defined. To investigate the impact of irAEs, the relative time of occurrence, and prior TKI therapy to predict clinical outcomes in NSCLC patients treated with ICIs. A single center retrospective cohort study identified 354 adult patients with NSCLC receiving ICI therapy between 2014 and 2018. Survival analysis utilized overall survival (OS) and real-world progression free survival (rwPFS) outcomes. Model performance matrices for predicting 1-year OS and 6-month rwPFS using linear regression baseline, optimal, and machine learning modeling approaches. Patients experiencing an irAE were found to have a significantly longer OS and rwPFS compared to patients who did not (median OS 25.1 vs. 11.1 months; hazard ratio [HR] 0.51, confidence interval [CI] 0.39- 0.68, P-value <0.001, median rwPFS 5.7 months vs. 2.3; HR 0.52, CI 0.41- 0.66, P-value <0.001, respectively). Patients who received TKI therapy before initiation of ICI experienced significantly shorter OS than patients without prior TKI therapy (median OS 7.6 months vs. 18.5 months; P-value < 0.01). After adjusting for other variables, irAEs and prior TKI therapy significantly impacted OS and rwPFS. Lastly, the performances of models implementing logistic regression and machine learning approaches were comparable in predicting 1-year OS and 6-month rwPFS. The occurrence of irAEs, the timing of the events, and prior TKI therapy were significant predictors of survival in NSCLC patients on ICI therapy. Therefore, our study supports future prospective studies to investigate the impact of irAEs, and sequence of therapy on the survival of NSCLC patients taking ICIs.

Sodium-glucose cotransporter 2 (SGLT2) inhibitors and non-small cell lung cancer survival.

Sodium-glucose cotransporter 2 (SGLT2) inhibitors are a relatively new class of antidiabetic drugs with demonstrated renal and cardiovascular disease benefit. This study evaluates the role of SGLT2 inhibitors on the survival of non-small cell lung cancer (NSCLC) patients. We used National Surveillance, Epidemiology and End Results (SEER)-Medicare linked data. Twenty four thousand nine hundred fifteen NSCLC patients newly diagnosed between 2014 and 2017 with pre-exiting diabetes and aged 66 years or older were included and followed to the end of 2019. Information on SGLT2 inhibitors use was extracted from the Medicare Part D file. SGLT2 inhibitor use was associated with significantly reduced mortality risk after adjusting for potential confounders (HR = 0.68, 95% CI = 0.60-0.77) with stronger association for longer duration of use (HR = 0.54, 85% CI = 0.44-0.68). Further, we found that SGLT2 inhibitor use was associated with a significant reduced risk of mortality regardless of patients' demographic, tumour characteristics and cancer treatments. Our large SEER-Medicare linked data study indicates that SGLT2 inhibitors use was associated with improved overall survival of NSCLC patients with pre-existing diabetes. Further studies are needed to confirm our findings and elucidate the possible mechanisms behind the association.

Gene mutation profiles and clinicopathological features of patients with non-small cell lung cancer harboring KRAS G12C mutation: a single-center retrospective study

Objective: To accurately screen non-small cell lung cancer (NSCLC) patients with KRAS G12C mutation and to evaluate their clinicopathological features, prognostic factors and current treatment status. Methods: A total of 19 410 NSCLC cases diagnosed at the Department of Pathology of Shanghai Chest Hospital, Shanghai, China from January 2018 to September 2021 were retrospectively reviewed, and the cases with KRAS gene mutation detected by next-generation sequencing were included. The clinicopathological and genetic mutation data of these cases were collected and analyzed. Results: A total of 1 633 (8.4%) NSCLC patients carried a KRAS gene mutation, among whom G12C was the most frequent (468 cases, 28.7%) mutant subtype. The mutation was more commonly found in males (414/468, 88.5%), patients with a history of smoking (308/468, 65.8%), and patients with a pathological type of invasive adenocarcinoma (231/468, 49.4%). The most common co-mutated genes in KRAS G12C mutant NSCLC were TP53 (52.4%, 245/468), STK11 (18.6%, 87/468) and ATM (13.2%, 62/468). The proportion of PD-L1 expression (≥1%) in KRAS G12C mutant NSCLC was significantly higher than that in patients without G12C mutation [64.3% (90/140) vs. 56.1% (193/344), P=0.014]. Immune checkpoint inhibitors (ICIs) treatment significantly prolonged progression-free survival (PFS) in NSCLC patients (10.0 months vs. 5.0 months, P=0.011). However, combination of chemotherapy and ICIs with anti-angiogenesis inhibitors or multi-target inhibitors did not significantly improve PFS in patients with KRAS G12C mutant NSCLC (P>0.05). Patients with KRAS G12C mutation NSCLC treated with ICIs and KRAS G12C patients with TP53 mutation had significantly longer median PFS than those with STK11 mutation (9.0 months vs. 4.3 months, P=0.012). Conclusions: Patients with KRAS G12C mutant NSCLC have relatively higher levels of PD-L1 expression and can benefit from ICIs treatment. The feasibility of chemotherapy, ICIs therapy and their combination needs further investigation.