[Prognostic Value of Neutrophil-to-lymphocyte Ratio in Patients with Lung Adenocarcinoma Treated with Radical Dissection]

Analysis of prognostic factors and establishment of prediction model of lung adenocarcinoma based on SEER database

Background

Few models have been developed to predict survival outcomes for lung adenocarcinoma (LUAD). In this study, we aimed to establish a nomogram for the prediction of cancer-specific survival (CSS) in LUAD patients which can be further developed as a convenient web-based calculator.

Methods

We performed a retrospective analysis of 50,007 LUAD patients selected from the Surveillance, Epidemiology, and End Result (SEER) 18 registry database. To enhance the reliability of the analysis, the patients' data were further randomly divided into the training cohort (70%) and validation cohort (30%). The optimal age cut-off points were determined using X-tile software, and patients were divided into three age groups: 10-72, 73-79, and 80-99 years. We selected independent prognostic factors from 17 variables by Cox regression, and plotted a visual nomogram to predict the 1-, 3-, and 5-year CSS. The predictive performance of the nomogram was evaluated through the concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve. To facilitate CSS forecast, a web-based calculator has subsequently been developed.

Results

We selected sex, age, race, marital status, N stage, tumor size, surgery, radiotherapy, chemotherapy, and metastasis (bone, brain, liver, and lung) as independent prognostic factors. The C-index was 0.779 [95% confidence interval (CI): 0.775-0.783] in the training set prediction model, and 0.782 (95% CI: 0.778-0.786) in the validation set. ROC analysis showed that area under the curve (AUC) values were 0.700, 0.733 and 0.669 for the 1-, 3- and 5-year CSS in the training set and 0.700, 0.744 and 0.669 in the validation set, respectively. In the nomogram calibration curve, there was strong correlation between the observed and predictive values. A web-based calculator can be accessed at: https://hjhlovelfb.shinyapps.io/DynNomapp/.

Conclusions

This nomogram model has good predictive power and can help clinicians identify LUAD patients at high risk of cancer-related death. This nomogram is expected to be a precise and personalized tool for predicting the prognosis of patients with LUAD.

Association of PD-1 polymorphisms with the risk and prognosis of lung adenocarcinoma in the northeastern Chinese Han population

Background

Lung cancer is a leading cause of death from cancer worldwide, especially non-small cell lung cancer (NSCLC). The marker of progression in lung adenocarcinoma, the main type of NSCLC, has been rarely studied. Programmed death 1 (PD-1) is an effective drug target for the treatment of NSCLC. Our study aimed to examine the PD-1 role in the disease process. The study of the effect of polymorphisms on the progression of lung adenocarcinoma in the Han population of Northeast China may provide a valuable reference for the research and application of these drugs.

Methods

Chi-square test, Wilcoxon rank sum test, and classification efficiency assessment were used to test SNPs of PD-1 in 287 patients and combined with clinical information.

Results

We successfully identified biomarkers (rs2227981, rs2227982, and rs3608432) that could distinguish between lung adenocarcinoma patients of early stages and late stages. Multiple clinical indicators showed significant differences among different SNPs and cancer stages. Furthermore, this gene was confirmed to effectively distinguish the stages of lung adenocarcinoma with RNA-seq data in TCGA.

Conclusions

Out study indicated that the PD-1 gene and the SNPs on it could be used as markers for distinguishing lung adenocarcinoma staging in the Northeast Han population. Our investigation into the link between PD-1 polymorphisms and lung adenocarcinoma would help to provide guidance for the treatment and prognosis of lung adenocarcinoma.