The prognostic value of machine learning techniques versus cox regression model for head and neck cancer

Peng, Jiajia; Lu, Yongmei; Chen, Li; Qiu, Ke; Chen, Fei; Liu, Jun; Xu, Wei; Zhang, Wei; Zhao, Yu; Yu, Zhonghua; Ren, Jianjun

doi:10.1016/j.ymeth.2022.07.001

Cited by 8 publications

(16 citation statements)

References 29 publications

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“…Each patient’s risk score was calculated as previously described ( Peng et al, 2022 ). Furthermore, the risk score of each ACC patient was directly computed using the above formula.…”

Section: Resultsmentioning

confidence: 99%

“…The results of Figures 2C, D determined that the model fit best when the penalty coefficient was 3, and the corresponding three immune genes, TNFAIP3, AURKA, and HELLS, were included in the model (Figure 2E). Each patient's risk score was calculated as previously described (Peng et al, 2022). Furthermore, the risk score of each ACC patient was directly computed using the above formula.…”

Section: Construction and Prognostic Value Of Irssmentioning

confidence: 99%

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Comprehensive pan-cancer analysis and the regulatory mechanism of AURKA, a gene associated with prognosis of ferroptosis of adrenal cortical carcinoma in the tumor micro-environment

Yuan

Zhao

et al. 2023

Front. Genet.

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Background: The only curative option for patients with locally or locally advanced adrenocortical carcinoma is primary tumor curative sexual resection (ACC). However, overall survival remains low, with most deaths occurring within the first 2 years following surgery. The 5-year survival rate after surgery is less than 30%. As a result, more accurate prognosis-related predictive biomarkers must be investigated urgently to detect patients’ disease status after surgery.Methods: Data from FerrDb were obtained to identify ferroptosis-related genes, and ACC gene expression profiles were collected from the GEO database to find differentially expressed ACC ferroptosis-related genes using differential expression analysis. The DEFGs were subjected to Gene Ontology gene enrichment analysis and KEGG signaling pathway enrichment analysis. PPI network building and predictive analysis were used to filter core genes. The expression of critical genes in ACC pathological stage and pan-cancer was then investigated. In recent years, immune-related factors, DNA repair genes, and methyltransferase genes have been employed in diagnosing and prognosis of different malignancies. Cancer cells are mutated due to DNA repair genes, and highly expressed DNA repair genes promote cancer. Dysregulation of methyltransferase genes and Immune-related factors, which are shown to be significantly expressed in numerous malignancies, also plays a crucial role in cancer. As a result, we investigated the relationship of AURKA with immunological checkpoints, DNA repair genes, and methyltransferases in pan-cancer.Result: The DEGs found in the GEO database were crossed with ferroptosis-related genes, yielding 42 differentially expressed ferroptosis-related genes. Six of these 42 genes, particularly AURKA, are linked to the prognosis of ACC. AURKA expression was significantly correlated with poor prognosis in patients with multiple cancers, and there was a significant positive correlation with Th2 cells. Furthermore, AURKA expression was positively associated with tumor immune infiltration in Lung adenocarcinoma (LUAD), Liver hepatocellular carcinoma (LIHC), Sarcoma (SARC), Esophageal carcinoma (ESCA), and Stomach adenocarcinoma (STAD), but negatively correlated with the immune score, matrix score, and calculated score in these tumors. Further investigation into the relationship between AURKA expression and immune examination gene expression revealed that AURKA could control the tumor-resistant pattern in most tumors by regulating the expression level of specific immune examination genes.Conclusion: AURKA may be an independent prognostic marker for predicting ACC patient prognosis. AURKA may play an essential role in the tumor microenvironment and tumor immunity, according to a pan-cancer analysis, and it has the potential to be a predictive biomarker for multiple cancers.

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“…Each patient’s risk score was calculated as previously described ( Peng et al, 2022 ). Furthermore, the risk score of each ACC patient was directly computed using the above formula.…”

Section: Resultsmentioning

confidence: 99%

Section: Construction and Prognostic Value Of Irssmentioning

confidence: 99%

Comprehensive pan-cancer analysis and the regulatory mechanism of AURKA, a gene associated with prognosis of ferroptosis of adrenal cortical carcinoma in the tumor micro-environment

Yuan

Zhao

et al. 2023

Front. Genet.

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Section: Methodsmentioning

confidence: 99%

“…Patients with sinonasal NHL were identified from the Surveillance, Epidemiology, and End Results (SEER) Program (https://seer.cancer.gov/seerstat/), which comprises 18 population-based cancer registries from the United States, and cancer data were collected between 1975 and 2017 by professionals. 20,21 SEER is supported by the Surveillance Research Program (SRP) in NCI's Division of Cancer Control and Population Sciences (DCCPS). Institutional Review Board (IRB) approval was waived by the local ethics committee, as SEER data is publicly available and deidentified.…”

Section: Data Sourcementioning

confidence: 99%

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Comparison of Primary B/NKT Non‐Hodgkin Lymphomas in Nasopharynx, Nasal Cavity, and Paranasal Sinuses

Peng

Qiu

Cheng

et al. 2023

Otolaryngol.--head neck surg.

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Objective. We aimed to compare clinical and survival differences between B-cell (B-NHL) and NKT-cell non-Hodgkin lymphomas (NKT-NHL) located in the nasal cavity (NC), nasopharynx, and paranasal sinuses, which are always categorized as one sinonasal type.Study Design. Patients diagnosed with primary B-NHL and NKT-NHL in the nasal cavity, nasopharynx, and paranasal sinuses from Surveillance, Epidemiology, and End Results (SEER) database were included .Setting. Population-based cohort study.Methods. We conducted univariate and multivariate Cox regressions and Kaplan-Meier analysis to examine survival outcomes of B/NKT-NHL in the nasal cavity, nasopharynx, and paranasal sinuses, respectively.Results. Overall, most B-NHL cases originated from the nasopharynx, while the majority of NKT-NHL cases occurred in the nasal cavity. Notably, the cancer-special survival (CSS) outcomes improved significantly in all sinonasal B-NHL cases over time, whereas no such improvement trend was observed in each sinonasal NKT-NHL type. Additionally, increasing age was linked with an elevated risk of death in B-NHL, particularly in the nasal cavity (Hazard ratio [HR]: 3.37), rather than in NKT-NHL. Compared with B-NHL, the adverse effect of a higher stage on CSS was more evident in NKT-NHL, particularly in its nasopharynx site (HR: 5.12). Furthermore, radiotherapy was beneficial for survival in patients with sinonasal B-NHL and NKT-NHL, except in the nasopharynx NKT-NHL. However, chemotherapy has only been beneficial for CSS in patients with paranasal sinuses B-NHL (HR: 0.42) since 2010, rather than in other types of B/NKT-NHL. Conclusion.Although B-NHL and NKT-NHL in the nasal cavity, nasopharynx and paranasal sinuses have similar anatomical locations, their clinicodemographics and prognoses are largely different and should be treated and studied as distinct diseases.

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Predicting mortality and recurrence in colorectal cancer: Comparative assessment of predictive models

Alinia,

Asghari-Jafarabadi,

Mahmoudi

et al. 2024

Heliyon

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The prognostic value of machine learning techniques versus cox regression model for head and neck cancer

Cited by 8 publications

References 29 publications

Comprehensive pan-cancer analysis and the regulatory mechanism of AURKA, a gene associated with prognosis of ferroptosis of adrenal cortical carcinoma in the tumor micro-environment

Comprehensive pan-cancer analysis and the regulatory mechanism of AURKA, a gene associated with prognosis of ferroptosis of adrenal cortical carcinoma in the tumor micro-environment

Comparison of Primary B/NKT Non‐Hodgkin Lymphomas in Nasopharynx, Nasal Cavity, and Paranasal Sinuses

Predicting mortality and recurrence in colorectal cancer: Comparative assessment of predictive models

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