A validated nomogram integrating baseline peripheral T-lymphocyte subsets and NK cells for predicting survival in stage I–IIIA non-small cell lung cancer after resection

Xu, Lili; Luo, Yingbin; Tian, Jing; Fang, Zhihong; Zhu, Wei; Zhang, Bo; Wu, Jianchun; Li, Yan

doi:10.21037/atm-21-6347

Cited by 4 publications

(4 citation statements)

References 48 publications

(40 reference statements)

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“…Similar to neoadjuvant therapy, neoadjuvant immunotherapy aims to shrink the primary tumor and enable downstaging, thereby facilitating or simplifying surgery ( 32 ). Despite the variety of clinical prognostic prediction models for neoadjuvant therapy, T staging is commonly included and recognized as a critical predictor of patient outcomes ( 33 , 34 ), aligning with the findings of our model.…”

Section: Discussionsupporting

confidence: 73%

Pulmonary function test-related prognostic models in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy

Zhang,

Zhu,

Liang

et al. 2024

Front. Oncol.

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BackgroundThis study aimed to establish a comprehensive clinical prognostic risk model based on pulmonary function tests. This model was intended to guide the evaluation and predictive management of patients with resectable stage I-III non-small cell lung cancer (NSCLC) receiving neoadjuvant chemoimmunotherapy.MethodsClinical pathological characteristics and prognostic survival data for 175 patients were collected. Univariate and multivariate Cox regression analyses, and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to identify variables and construct corresponding models. These variables were integrated to develop a ridge regression model. The models’ discrimination and calibration were evaluated, and the optimal model was chosen following internal validation. Comparative analyses between the risk scores or groups of the optimal model and clinical factors were conducted to explore the potential clinical application value.ResultsUnivariate regression analysis identified smoking, complete pathologic response (CPR), and major pathologic response (MPR) as protective factors. Conversely, T staging, D-dimer/white blood cell ratio (DWBCR), D-dimer/fibrinogen ratio (DFR), and D-dimer/minute ventilation volume actual ratio (DMVAR) emerged as risk factors. Evaluation of the models confirmed their capability to accurately predict patient prognosis, exhibiting ideal discrimination and calibration, with the ridge regression model being optimal. Survival analysis demonstrated that the disease-free survival (DFS) in the high-risk group (HRG) was significantly shorter than in the low-risk group (LRG) (P=2.57×10-13). The time-dependent receiver operating characteristic (ROC) curve indicated that the area under the curve (AUC) values at 1 year, 2 years, and 3 years were 0.74, 0.81, and 0.79, respectively. Clinical correlation analysis revealed that men with lung squamous cell carcinoma or comorbid chronic obstructive pulmonary disease (COPD) were predominantly in the LRG, suggesting a better prognosis and potentially identifying a beneficiary population for this treatment combination.ConclusionThe prognostic model developed in this study effectively predicts the prognosis of patients with NSCLC receiving neoadjuvant chemoimmunotherapy. It offers valuable predictive insights for clinicians, aiding in developing treatment plans and monitoring disease progression.

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Section: Discussionsupporting

confidence: 73%

Pulmonary function test-related prognostic models in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy

Zhang,

Zhu,

Liang

et al. 2024

Front. Oncol.

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“…Nomograms, a statistic-based tool, can assess the risk of clinicopathological features by quantifying the biological and clinical variables of patients with cancer (6). To date, nomograms have been widely applied in the personalized prediction of cancer, such lung, cervical, prostate, and hepatocellular carcinomas (7)(8)(9)(10)(11). To the best of our knowledge, several studies have reported risk factors associated with breast cancer (12)(13)(14)(15)(16)(17).…”

Section: Introductionmentioning

confidence: 99%

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

Wang¹,

Xing²,

X³

et al. 2022

Gland Surg

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Background: Nomograms can assess the risk of clinicopathological features by quantifying the biological and clinical variables of cancer patients. However, the nomogram based on significant factors that influence the survival of breast cancer in a large population has been rarely explored. This study was to investigate the predictive effectiveness of a nomogram for the survival of patients with breast cancer. Methods: Demographic and clinical data of 275,812 breast cancer patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. All patients aged ≥20 years in this retrospective cohort study were classified as two groups in a random manner, namely the training set (n=193,069) and validation set (n=82,743). The outcomes of our study were the 3-and 5-year survival of breast cancer. The potential predictors of cancer mortality were screened by univariate and multivariable Cox regression analyses. The nomogram was conducted based on the predictors. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curve was utilized to evaluate the performance of the nomogram.Results: The age at diagnosis, race, marital status, tumor size, first malignant primary indicator, American Joint Committee on Cancer (AJCC) T stage, M stage, tumor grade, and number of malignant tumors were independent predictors for the death of patients with breast cancer. The C-indexes of the training set and the validation set were 0.782 and 0.778, respectively. The area under the curve (AUC) values of the nomogram for predicting the 3-and 5-year survival of breast cancer were 0.770 and 0.756, respectively. Furthermore, the C-index values of our nomogram were 0.816, 0.775, 0.773, 0.734, and 0.750 for predicting survival in Asian, White, Hispanic, American Indian, and Black populations, respectively. Conclusions:The nomogram may have predictive performance for predicting the 3-and 5-year survival of breast cancer patients, and future studies need to validate our findings.

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“…11 In lung cancer patients, peripheral CD8+ T-cell counts were higher than in healthy controls, but CD3+, CD4+ T cells, and the CD4+/CD8+ were considerably lower. 12 Additionally, individuals with lung cancer who had higher percentages of peripheral CD3+ and CD4+ T cells, and higher CD4/CD8 ratios, had longer overall survival times. 13 Podoplanin (PDPN) is a mucin-type transmembrane glycoprotein that is known to be a hallmark of lymphatic endothelial cells.…”

Section: Introductionmentioning

confidence: 98%

Plasma Soluble Podoplanin as a Biomarker of Hypercoagulability and Cellular Immunity Status in Patients With Non-small Cell Lung Cancer

Zhang

Peng

Wang

et al. 2023

Clin Appl Thromb Hemost

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Podoplanin (PDPN) is known to play a role in thrombosis, metastasis of tumor cells, the epithelial–mesenchymal transition (EMT), and immune response. The present study aim to evaluate the clinical significance of soluble PDPN (sPDPN) in hypercoagulability and cellular immune status in patients with non-small cell lung cancer (NSCLC). Enzyme-linked immunosorbent assay (ELISA) was used to determine plasma sPDPN levels, and T-lymphocyte distribution was determined using flow cytometry. The levels of sPDPN were markedly higher in the NSCLC group than control group, and sPDPN was higher in patients with advanced-stage and with distant metastases. The high-sPDPN group had lower absolute numbers of CD3+, CD4+, and CD4+/CD8+ ratio than low-sPDPN group. Correlation analysis indicated that sPDPN was positively linked to platelet (r = 0.50, P < .001), D-dimer (r = 0.52, P < .001), and fibrinogen (r = 0.37, P < .001); and inversely correlated with CD3+ (r = −0.37, P < .001), CD4+ (r = −0.44, P < .001), and CD4+/CD8+ (r = −0.37, P < .001). Multivariate logistic regression analysis indicated that sPDPN (odds ratio [OR] = 2.293; 95% CI, 1.559−3.373) and tumor stage (OR = 15.857; 95% CI, 1.484−169.401) were separate risk indicators for hypercoagulability. The receiver operating characteristic curves (ROC) indicated that sPDPN had high diagnostic values for hypercoagulability in NSCLC patients. In conclusion, plasma sPDPN was not only linked to hypercoagulability, but it may also be an indicator of the body's cellular immune status in NSCLC patients.

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A validated nomogram integrating baseline peripheral T-lymphocyte subsets and NK cells for predicting survival in stage I–IIIA non-small cell lung cancer after resection

Cited by 4 publications

References 48 publications

Pulmonary function test-related prognostic models in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy

Pulmonary function test-related prognostic models in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

Plasma Soluble Podoplanin as a Biomarker of Hypercoagulability and Cellular Immunity Status in Patients With Non-small Cell Lung Cancer

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