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

Author:

Thephamongkhol Kullathorn,Korpraphong Pornpim,Muangsomboon Kobkun,Sitathanee Chomporn,Lertkhachonsuk Arb-aroon,Phongkitkarun Sith,Srirattanapong Saowanee,Prapruttam Duangkamon,Bridhikitti Jidapa,Dendumrongsup Thaworn,Alisanant Petch,Amornwichet Napapat,Khorprasert Chonlakiet,Sasiwimonphan Kewalee,Tanprasertkul Chamnan,Dhanachai Mantana,Patumanond Jayanton,Setakornnukul JirapornORCID

Abstract

AbstractTo 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.

Funder

Faculty of Medicine Siriraj Hospital, Mahidol University

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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