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Updated: Jun 24, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Risk stratification for recurrence in patients with esophageal and junctional carcinoma treated with neoadjuvant
S Dixit1, M Tilston, W M Peter
1Department of Clinical Oncology, Castle Hill Hospital, Hull & East Yorkshire NHS Trust, Castle Road, Cottingham, Hull HU16 JQ, UK. sanjay.dixit@hey.nhs.uk
Aim:
To stratify the risk for recurrence in patients with esophageal cancer treated with neoadjuvant chemotherapy and surgery.
Materials And Methods:
The prognostic and predictive factors were analyzed in 62 patients who underwent curative resection following chemotherapy. The factors found significant on multivariate analysis were stratified into good, intermediate and high risk groups for recurrence.
Results:
Kaplan-Meier survival at 3 and 5 years was 32% and 20%, respectively, with a median survival of 19 months. Pathological response and percent node positive were the significant factors on multivariate analysis. Three groups were formed and their recurrence free survivals were calculated using Kaplan-Meier method. The low risk composed of good responders and patients with less than 20% positive lymph node; the intermediate risk composed of non-responders and patients with less than 20% positive lymph node and the high risk group composed of non-responders and patients with more than 20% positive lymph node. The median recurrence time was 8 months for the high risk group, 39 months for the intermediate group, and it has not reached in the low risk group. Hazard ratio was 0.39(95% C.I. 0.09-0.98) for the risk group low to intermediate, 0.1(95% C.I. 0.04-0.25) for the low to high risk group and 0.26(95% C.I. 0.11-0.66) for the intermediate to high risk group.
Conclusions:
Pathological response rate and percent node positive were significant predictive factors on multivariate analysis. Stratification based on these two predictive factors may help in optimizing any adjuvant treatment.
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