Immuno-Oncological Treatment and Tumor Mass in Non-Small Cell Lung Cancer: Case-Control Analysis of Overall Survival in Routine Clinical Practice

Faehling, Martin; Копп, М. В.; Schwenk, B.; Fallscheer, Sabine; Kramberg, Sebastian; Eckert, R.

doi:10.1159/000500885

Cited by 14 publications

(8 citation statements)

References 20 publications

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“…7,19 A potential benefit from adding chemotherapy to ICI is that in mNSCLC, the benefit with ICI monotherapy tended to be greater in patients with lower tumor burden, although these data are limited and retrospective. 52 By contrast, a post hoc aanlysis from KEYNOTE-189 reported that the survival outcome with combination occurred regardless of the baseline tumor burden (defined as ≤ 3 or > 3 median number of organ systems involved). 53 This may suggest that patients with more indolent disease or less symptom burden may be optimal for single-agent immunotherapy (Fig 6).…”

Section: Clinical Decisionsmentioning

confidence: 98%

First-Line Immunotherapy for Non–Small-Cell Lung Cancer

Reck

Remón

Hellmann

2022

JCO

500

244

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For patients with metastatic non–small-cell lung cancer (mNSCLC), the last decade has been characterized by critical progress that has contributed to substantially improved survival. In particular, the development of specific antibodies against the programmed death (PD-1) receptor, programmed death-ligand 1 (PD-L1), and the cytotoxic T-lymphocyte–associated protein 4 receptor in the therapeutic strategy of mNSCLC either in first- or in second-line settings have led to unprecedented prolonged survival for a proportion of these patients. Although clinical development of immune checkpoint inhibitors with anti–PD-1 and PD-L1 therapies largely began as monotherapy in the second-line setting, the more recent progress has shifted toward combination approaches in first-line settings as well as the integration of immunotherapy into the clinical paradigm in earlier stages. Today, with the exception of mNSCLC harboring targetable oncogenes, nearly all patients with mNSCLC receive PD-1 or PD-L1 therapy in first-line settings. Here we report the current status of first-line immunotherapy in mNSCLC together with current challenges in selecting the best immunotherapeutic approach for the individual patient.

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Section: Clinical Decisionsmentioning

confidence: 98%

First-Line Immunotherapy for Non–Small-Cell Lung Cancer

Reck

Remón

Hellmann

2022

JCO

500

244

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“…ICIs have significant benefits in OS compared with traditional chemotherapy in the casecontrol analysis [13]. There was no considerable difference in OS and DFS between PD1 and PDL1 inhibitors, but odd ratios of pembrolizumab (PDL1 expression ≥ 50% ) and nivolumab (PDL1 expression ≥ 1%) were higher than that of atezolizumab [12].…”

Section: Overall Survival and Progression-free Survival Of Immune Chementioning

confidence: 88%

Immune Checkpoint Inhibitors in Lung Cancer: Role of Biomarkers and Combination Therapies

Maung

Ergin

Javed

et al. 2020

Cureus

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Lung cancer is the leading cause of cancer-related death worldwide, with a poor prognosis. Despite aggressive treatment, progression-free survival (PFS) and overall survival are limited. Recently, various kinds of immune checkpoint inhibitors (ICIs) have emerged for several cancers, targeting PD1, PDL1, and CTLA-4. ICIs have made a significant breakthrough in cancer and revolutionized the management of cancer including lung cancer. However, there are a lot of controversies regarding which group of patients is most suitable to be treated with ICIs in terms of monotherapy, combination, and predictive biomarkers. We reviewed various kinds of studies, such as meta-analysis, randomized control trials, multi-center cohort studies, and case-control studies from PubMed written in English from the last five years. ICIs have significant benefits in the overall survival compared with traditional chemotherapy. Patients with a higher level of PDL1 expression and high tumor mutational burden (TMB) have a higher response rate, and those with EGFR-/ALK-were better than those with EGFR+/ALK+. The patient who responded to immunotherapy completely can still maintain the efficacy after two years of treatment. Neoadjuvant immunotherapy in patients with resectable non-small cell lung cancer resulted in a 45% major pathology response (MPR) and 40% downstaging. Combined therapy (ICIs + chemotherapy) was better than chemotherapy alone, irrespective of PD-L1 expression. A combination of ICIs such as CTLA-4 and PD-1/PD-L1 improved PFS as well. Radiochemotherapy ahead of ICIs is promising as well. However, ICIs combined with EGFR/ALK-TKI (tyrosine kinase inhibitor) are not suggested for the time being. PDL1 expression, TMB, and EGFR/ALK mutations are promising predictive biomarkers. Gut microbiota, galectin-3, and intensity of CD8 cell infiltration are other potential predictive biomarkers. These are very important in the future management of lung cancers as they can prevent unnecessary toxicities and cost of treatment.

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“…Although tumor load was available as a variable in this study, it was excluded due to missing information. Faehling, Schwenk, Kopp, Fallscheer, Kramberg, and Eckert [23] has shown that tumor load is an essential factor for overall survival, and patients with lower tumor load have a better outcome than patients with larger tumor load. PLNS, on the other hand, was unavailable in this study which makes the structural comparison somewhat unfair.…”

Section: Discussionmentioning

confidence: 99%

Bayesian network structure for predicting two-year survival in patients diagnosed with non small cell lung cancer

Osong

Dekker

Wee

et al. 2023

Preprint

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Purpose The aim of this study was to develop and internally validate a clinically plausible Bayesian network structure to predict two-year survival in patients diagnosed with non-small cell lung cancer (NSCLC) and primarily treated with (chemo) radiation therapy by combining expert knowledge and a learning algorithm. Summary of background The incidence of lung cancer has been increasing. Healthcare providers are trying to acquire more knowledge of the disease biology to treat their patients better. However, the information available is more than humans can efficiently process. Predictive models such as Bayesian networks, which can intricately represent causal relations between variables, are suitable structures to model this information. However, commonly known methods for developing Bayesian network structures are limited in healthcare. Patients and Methods 545 NSCLC patients treated primarily with (chemo) radiation therapy from Maastro clinic in The Netherlands between 2010 to 2013 were considered to develop this Bayesian network structure. All continuous variables were discretized before analysis. Patients with missing survival status and variables with more than 25% missing information were excluded. The causal relationships (arcs) between variables in the data were determined using the hill-climbing algorithm with domain experts restrictions. The learning algorithm was run on a number of bootstrapped samples (B=400) and for the final structure, we kept the arcs present in at least 70% of the learned structures. Performance was assessed by computing the area under the curve (AUC) values and producing calibration plots based on a 5-fold cross-validation. In addition, an adapted pre-specified expert structure was compared with a structure developed from the method in this study. Results Tumor load was included in the main structure due to its high percentage (37%) of missingness and lack of added value. The final cohort used to develop the structure was reduced to 499, excluding 46(8.4%) patients with missing survival status. The resulting structure mean AUC and confidence interval to predict two-year survival was 0.614 (0.499 - 0.730 ). The AUC of the compared structures was only slightly above the chance level, but the structure based on the method in this study was clinically more plausible. Conclusion The results of this study show that Bayesian network structures which combine expert knowledge with a rigorous structure learning algorithm produce a clinically plausible structure with optimal performance.

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Immuno-Oncological Treatment and Tumor Mass in Non-Small Cell Lung Cancer: Case-Control Analysis of Overall Survival in Routine Clinical Practice

Cited by 14 publications

References 20 publications

First-Line Immunotherapy for Non–Small-Cell Lung Cancer

First-Line Immunotherapy for Non–Small-Cell Lung Cancer

Immune Checkpoint Inhibitors in Lung Cancer: Role of Biomarkers and Combination Therapies

Bayesian network structure for predicting two-year survival in patients diagnosed with non small cell lung cancer

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