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The Desmoid Tumor Research Foundation

February 2021

Development, Validation, and Visualization of A Web-Based Nomogram for Predicting the Recurrence-Free Survival Rate of Patients With Desmoid Tumors [Full Article]

Author Information

Liu H(1,2), Huang K(3,4,5), Li T(6), Yang T(1,2), Liao Z(1,2), Zhang C(1,2), Xiang L(1,2), Chen Y(3,4), Yang J(1,2).

(1)Dept of Bone & Soft Tissue Tumor, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China. (2)National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention & Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China. (3)Dept of Musculoskeletal Oncology, Fudan University Shanghai Cancer Center, Shanghai, China. (4)Dept of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. (5)Brandon Regional Hospital GME, HCA Healthcare/USF Morsani College of Medicine, Brandon, FL. (6)Dept of Bone & Soft-Tissue Tumor, Institute of Cancer & Basic Medicine, Chinese Academy of Sciences, Cancer Hospital of the Univ of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China.

Publication

Front Oncol

Summary

Surgery is an important treatment option for desmoid tumor (DT) patients, but how to decrease and predict the high recurrence rate remains a major challenge. Desmoid tumor patients diagnosed and treated at Tianjin Cancer Institute & Hospital were included, and a web-based nomogram was constructed by screening the recurrence-related risk factors using Cox regression analysis. External validation was conducted with data from the Fudan University Shanghai Cancer Center. A total of 385 patients were identified. Finally, after excluding patients without surgery, patients who were lost to follow-up, and patients without complete resection, a total of 267 patients were included in the nomogram construction. Among these patients, 53 experienced recurrence, with a recurrence rate of 20.15%. The 3-year and 5-year recurrence-free survival (RFS) rates were 82.5% and 78%, respectively. Age, tumor diameter, admission status, location, and tumor number were correlated with recurrence in univariate Cox analysis. In multivariate Cox analysis, only age, tumor diameter and tumor number were independent risk factors for recurrence and were then used to construct a web-based nomogram to predict recurrence. The concordance index (C-index) of the nomogram was 0.718, and the areas under the curves (AUCs) of the 3-year and 5-year receiver operating characteristic (ROC) curves were 0.751 and 0.761, respectively. In the external validation set, the C-index was 0.706, and the AUCs of the 3-year and 5-year ROC curves are 0.788 and 0.794, respectively. Age, tumor diameter, and tumor number were independent predictors of recurrence for DTs, and a web-based nomogram containing these three predictors could accurately predict RFS (https://stepforward.shinyapps.io/Desmoidtumor/).

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