Construction of conditional survival nomograms for metastatic early onset colon cancer patients

构建转移性早发性结肠癌患者的条件生存列线图

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Abstract

BACKGROUND: Conditional survival (CS), which factors in the postoperative survival duration of the patient, provides supplementary prognostic insights. The principal objectives of this study were to evaluate CS in metastatic early onset colon cancer (mEO-CC) patients and to construct innovative nomograms designed to predict the probability of CS, thus advancing the precision of prognostic modeling in this distinct clinical context. However, CS tools tailored to mEO-CC remain limited. METHODS: The data of patients diagnosed with mEO-CC between 2010 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database were included in our study. CS was defined as the probability of surviving for an additional number of years after already surviving for a specific number of years since diagnosis. Nomograms were constructed to predict the probability of conditional overall survival (OS) and cancer-specific survival (CSS) respectively. RESULTS: A total of 1,988 patients with mEO-CC were included in this study. The 5-year OS and CSS after surgery increased gradually with additional survival time. The univariate and multivariate Cox regression analyses identified a right-colon tumor, poorly differentiated tumor, mucinous/signet ring tumors, a late tumor stage, a high lymph node ratio (LNR), an elevated carcinoembryonic antigen (CEA) level, perineural invasion, and bone, liver or lung metastasis as independent risk factors for OS and CSS. Two nomograms with considerable predictive ability were successfully established for the prediction of conditional 5-year OS [area under the curve (AUC) =0.765] and CSS (AUC =0.761). CONCLUSIONS: The probability of achieving 5-year OS and 5-year CSS in mEO-CC patients increased based on the years already survived. Nomograms that consider survival time are more reliable and informative in terms of prognosis prediction in patients with mEO-CC. These time-adjusted estimates may facilitate risk communication and follow-up planning.

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