Chemoradiotherapy of locally advanced nonsmall cell lung cancer

Antoni, D.; Mornex, F.

doi:10.1097/cco.0000000000000265

Cited by 16 publications

(14 citation statements)

References 37 publications

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“…Approximately 20–25% patients with NSCLC are diagnosed with locally advanced disease (stage III) and have poor survival [ 3 ]. For these patients, two standard treatment options are offered: the concurrent chemoradiotherapy (CRT) or induction chemotherapy followed by surgery [ 4 , 5 ]. However, even after complete resection and postoperative consolidation chemotherapy, 20–40% patients still have a risk of local recurrence [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Systemic immune-inflammation index predicting chemoradiation resistance and poor outcome in patients with stage III non-small cell lung cancer

et al. 2017

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BackgroundThere is increasing evidence that the existence of systemic inflammation response is correlated with poor prognosis in several solid tumors. The aim of this retrospective study was to investigate the association between systemic immune-inflammation index (SII) and therapy response and overall survival in patients with stage III non-small cell lung cancer (NSCLC). The prognostic values of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and prognostic nutritional index (PNI) were also evaluated.MethodsIn total, 332 patients with new diagnosis of stage III NSCLC were included in this retrospective analysis. SII was defined as platelet counts × neutrophil counts/lymphocyte counts. Receiver operating characteristic (ROC) curve was used to evaluate the optimal cut-off value for SII, NLR, PLR and PNI. Univariate and multivariate survival analysis were performed to identify the factors correlated with overall survival.ResultsApplying cut-offs of ≥ 660 (SII), ≥ 3.57 (NLR), ≥ 147 (PLR), ≤ 52.95 (PNI), SII ≥ 660 was significantly correlated with worse ECOG PS (< 0.001), higher T stage (< 0.001), advanced clinical stage (p = 0.019), and lower response rate (p = 0.018). In univariate analysis, SII ≥ 660, NLR ≥ 3.57, PLR ≥ 147, and PNI ≤ 52.95 were significantly associated with worse overall survival (p all < 0.001). Patients with SII ≥ 660 had a median overall survival of 10 months, and patients with SII < 660 showed a median overall survival of 30 months. In multivariate analysis only ECOG PS (HR, 1.744; 95% CI 1.158–2.626; p = 0.008), T stage (HR, 1.332; 95% CI 1.032–1.718; p = 0.028), N stage (HR, 1.848; 95% CI 1.113–3.068; p = 0.018), SII (HR, 2.105; 95% CI 1.481–2.741; p < 0.001) and NLR ≥ 3.57 (HR, 1.934; 95% CI 1.448–2.585; p < 0.001) were independently correlated with overall survival.ConclusionsThis study demonstrates that the SII is an independent prognostic indicator of poor outcomes for patients with stage III NSCLC and is superior to other inflammation-based factors in terms of prognostic ability.

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Section: Introductionmentioning

confidence: 99%

Systemic immune-inflammation index predicting chemoradiation resistance and poor outcome in patients with stage III non-small cell lung cancer

et al. 2017

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“…The majority of non-small cell lung cancer (NSCLC) patients present with locally advanced or metastatic disease, leading to limited therapeutic options and the overall 5-year survival rates of those patients was approximately 17%. 2,3 Therefore, understanding of tumour biology and pathogenesis of NSCLC is conducive to clarifying favourable response to targeted therapy.…”

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confidence: 99%

miR‐193b availability is antagonized by LncRNA‐SNHG7 for FAIM2‐induced tumour progression in non‐small cell lung cancer

et al. 2017

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Objectives: Long non-coding RNAs have identified to involve into the tumour cell proliferation, apoptosis and metastasis. We previously found that up-regulated LncRNA-SNHG7 (SNHG7) positively correlated to the Fas apoptosis inhibitory molecule 2 (FAIM2) in lung cancer cells with unclear mechanism.Methods: Non-small cell lung cancer (NSCLC) and relative normal tissues (n = 25) were collected. The SNHG7 expression and function in NSCLC was determined. The SNHG7-miR 193b-FAIM2 network was analysed in vitro and vivo.Results: We reported that oncogene SNHG7 predicted a poor clinical outcome and functioned as competitive endogenous RNA (ceRNA) antagonized microRNA-193b Conclusion:The results indicated that miR-193b is indispensible for the ceRNA role of SNHG7 in FAIM2-supported tumourigenesis of lung cancer.

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“…2 Concomitant chemoradiotherapy (CCRT) is the established standard of care for unresectable stage III disease with evidence of better results compared with either modality used alone or sequentially. 3 Despite the Asian J Oncol 2019;5:56-63 dismal 5-year overall survival (OS) rate of 15 to 35% for stage IIIA and 5 to 10% for stage IIIB, 4 a subset of patients in these stages show significantly better OS. Conventional patient, tumor, and treatment related parameters often do no correlate with the survival outcome, largely due to complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables.…”

Section: Introductionmentioning

confidence: 99%

Identifying Prognostic Groups Using Machine Learning Tools in Patients Undergoing Chemoradiation for Inoperable Locally Advanced Nonsmall Cell Lung Carcinoma

Pahuja

Chufal

Ahmad

et al. 2019

ASJO

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Introduction Unresectable stage III nonsmall cell lung cancer (NSCLC) continues to have dismal 5-year overall survival (OS) rate. However, a subset of the patients treated with chemoradiation show significantly better outcome. Prediction of treatment outcome can be improved by utilizing machine learning tools, such as cluster analysis (CA), and is capable of identifying complex interactions among many variables. We have utilized CA to identify a cluster with good prognosis within stage III NSCLC. Materials and Methods Retrospective analysis of treatment outcomes was done for 92 patients who underwent chemoradiation for inoperable locally advanced NSCLC from 2012 to 2018. Using various patient- and treatment-related variables, an exploratory factor analysis was performed to extract factors with eigenvalue > 1. An appropriate number of homogeneous groups were identified using agglomerative hierarchical cluster analysis. Further K-mean cluster analysis was applied to classify each patient into their homogeneous clusters. The newly formed cluster variable was used as an independent variable to estimate survival over time using Kaplan–Meier method. Results With a median follow-up of 18 months, median OS was 14 months. Using CA, three prognostic clusters were obtained. Cluster 2 with 36 patients had a median OS of 36 months, whereas Cluster 1 with 34 patients had a median OS of 20 months (p = 0.004). Conclusion A cluster could thus be identified with a relatively good prognosis within stage III NSCLC. Using CA, we have attempted to create a model which may provide more specific prognostic information in addition to that provided by tumor node metastasis-based models.

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Chemoradiotherapy of locally advanced nonsmall cell lung cancer

Cited by 16 publications

References 37 publications

Systemic immune-inflammation index predicting chemoradiation resistance and poor outcome in patients with stage III non-small cell lung cancer

Systemic immune-inflammation index predicting chemoradiation resistance and poor outcome in patients with stage III non-small cell lung cancer

miR‐193b availability is antagonized by LncRNA‐SNHG7 for FAIM2‐induced tumour progression in non‐small cell lung cancer

Identifying Prognostic Groups Using Machine Learning Tools in Patients Undergoing Chemoradiation for Inoperable Locally Advanced Nonsmall Cell Lung Carcinoma

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