Dataset Information

Development and validation of a prognostic prediction model including the minor lymphatic pathway for distant metastases in cervical cancer patients.

ABSTRACT: To develop and validate a prognostic model, including the minor lymphatic pathway (internal iliac and presacral nodes).

Study design

Retrospective cohort.

Participants

Locally advanced cervical cancer underwent concurrent chemoradiotherapy.

Sample size

397 and 384 patients in the development and validation data set.

Predictors

Our new nodal staging system with the minor lymphatic pathway.

Outcome

Distant metastases.

Statistical analysis

Cox regression; net reclassification improvement (NRI) and decision curve analysis (DCA). Our new nodal system was the strongest predictor. The predictors in the final model were new nodal system, tumor stage, adenocarcinoma, initial hemoglobin, tumor size and age. The nodal system and the pretreatment model had concordance indices of 0.661 and 0.708, respectively, with good calibration curves. Compared to the OUTBACK eligibility criteria, the nodal system showed NRI for both cases (22%) and controls (16%). The pretreatment model showed NRI for cases (31%) and controls (18%). DCA in both models showed threshold probability of 15% and 12%, respectively, when compared with 24% in OUTBACK eligibility criteria. Our new nodal staging system and the pretreatment model could differentiate between high-risk and low-risk patients, thus facilitating decisions to provide more aggressive treatment to prevent distant metastases.

SUBMITTER: Thephamongkhol K

PROVIDER: S-EPMC9197836 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Development and validation of a prognostic prediction model including the minor lymphatic pathway for distant metastases in cervical cancer patients.

Thephamongkhol Kullathorn K Korpraphong Pornpim P Muangsomboon Kobkun K Sitathanee Chomporn C Lertkhachonsuk Arb-Aroon AA Phongkitkarun Sith S Srirattanapong Saowanee S Prapruttam Duangkamon D Bridhikitti Jidapa J Dendumrongsup Thaworn T Alisanant Petch P Amornwichet Napapat N Khorprasert Chonlakiet C Sasiwimonphan Kewalee K Tanprasertkul Chamnan C Dhanachai Mantana M Patumanond Jayanton J Setakornnukul Jiraporn J

Scientific reports 20220614 1

To develop and validate a prognostic model, including the minor lymphatic pathway (internal iliac and presacral nodes).<h4>Study design</h4>Retrospective cohort.<h4>Participants</h4>Locally advanced cervical cancer underwent concurrent chemoradiotherapy.<h4>Sample size</h4>397 and 384 patients in the development and validation data set.<h4>Predictors</h4>Our new nodal staging system with the minor lymphatic pathway.<h4>Outcome</h4>Distant metastases.<h4>Statistical analysis</h4>Cox regression; n ...[more]

PMID: 35701437

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Project description:Cervical cancer (CESC) is the second most common cancer death in middle-aged women. The N6-methyladenosine (m6A) plays an essential role in the epitranscriptomics of cancer and affects immune cell infiltration. Our study used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data to construct and validate prognostic prediction established on m6A-related genes in CESC. We gained gene expression and clinical characteristics from TCGA and GEO. After differentially expression analysis of the m6A-related genes, we identified eight genes of CESC development. Next, we executed consensus clustering to analyze CESC types established on the differential expression of the m6A-related genes and found different subtypes significantly correlate with survival prognosis, immune microenvironment, and PD-L1 expression. Then, based on Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, a five-gene (IGF2BP1, IGF2BP2, HNRNPA2B1, YTHDF1, RBM15) predictive model was built in the TCGA training cohort. Finally, we checked the predictive model with survival analysis and receiver operating characteristic (ROC) curve both in the training cohort (TCGA) and in the validation cohort (GSE44001). We found the expression and variation of the five genes significantly correlate with immune cell infiltration. The CESC could be divided into subtypes according to eight expression m6A-related genes. Different subtypes are related to various immune cells, immune scores, and the expression of the PD-L1. We develop a risk prediction model: risk score = (0.023558929) * Exp IGF2BP1 + (0.021148829) * Exp IGF2BP2 + (0.045035491) * Exp HNRNPA2B1 + (-0.106566550) * Exp YTHDF1 + (-0.001037932) * Exp RBM15. Moreover, different m6A-related genes significantly correlated with immune cells. The m6A-related genes risk prediction model plays an essential role in predicting CESC patients. The m6A-related genes affected the immune cell infiltration in CESC. These results suggest that the expression of m6A-related genes may influence the immune therapy of CESC and be the potential therapeutic target.

Dataset Information

Development and validation of a prognostic prediction model including the minor lymphatic pathway for distant metastases in cervical cancer patients.

Study design

Participants

Sample size

Predictors

Outcome

Statistical analysis

Publications

Development and validation of a prognostic prediction model including the minor lymphatic pathway for distant metastases in cervical cancer patients.

Similar Datasets

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