The prognosis for pathologically node-negative (pN0) esophageal squamous cell carcinoma
(ESCC) with surgery alone remains poor. We aimed to develop a model for a more precise
prediction of recurrence, which will allow personalized management for pN0 ESCC after
upfront complete resection. Clinical and pathological records of patients with completely
resected pT1-3N0M0 ESCC were retrospectively analyzed between January 2014 and December
2019. A nomogram for the prediction of recurrence was established based on the Cox
regression analysis and evaluated by C-index, AUC, and calibration curves. The model
was further validated using bootstrap resampling and k-fold cross-validation and compared
with the 8th edition of the AJCC TNM staging system using Td-ROC, NRI, IDI, and DCA.
Two-hundred-and seventy cases were included in this study. The median follow-up was
45 months. Distant and/or loco-regional recurrences were noted in 89 (33.0%) patients.
The predictive model revealed pT-category, differentiation, perineural invasion, examined
lymph nodes (ELN), and prognostic nutritional index (PNI) as independent risk factors
for recurrence, with a c-index of 0.725 in the bootstrapping cohort. Td-ROC, NRI,
and IDI showed a better predictive ability than the AJCC 8th TNM staging system. Based
on this model, patients in the low-risk group had a significantly lower recurrence
incidence than those in the high-risk group (p < .001). The predictive model developed in this study may facilitate the precise
prediction of recurrences for pN0 ESCC after upfront surgery. Stratifying management
of those patients might bring significantly better survival benefits.
Graphical abstract
Graphical Abstract
Keywords
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Article info
Publication history
Published online: September 08, 2022
Publication stage
In Press Journal Pre-ProofFootnotes
Funding: This research was supported by grants from the Affiliated Hospital of Qingdao University Youth Research Funds (No. QDFYQN202101013). The funding source has no role in the study design, in the collection, analysis and interpretation of data, in the writing of the report, and in the decision to submit the article for publication.
Disclosures: The authors have no potential conflicts of interest.
IRB Approval: Date of approval: October 07, 2021; IRB number: QYFY WZLL 26975
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