Development and external validation of a nomogram for individualized adjuvant imatinib duration for high-risk
Ruolin Liu1, Yingxin Wu2, Jin Gong3
1Department of Burn and Plastic Surgery, West China Hospital of Sichuan University, Chengdu, China.
Introduction:
The main emphasis of the research about adjuvant imatinib for high-risk gastrointestinal stromal tumors (GISTs) is prolonging the treatment duration and ignores the heterogeneous that 10-year recurrence rates ranged from about 20%-100%. Thus, this study evaluated the effect of different durations of adjuvant imatinib on outcomes in high-risk GISTs to explore the feasibility of individual treatment.
Methods:
We analyzed 855 high-risk GIST patients from three centers who underwent macroscopically complete resection between December 2007 and September 2020. The patients were divided into training (n =564) and two validation cohorts (n = 238 and53) based on their source. Recurrence-free survival (RFS) was the primary point. Cox multivariate analysis was used to develop the nomogram. C-index, time-dependent area under the curves, and calibration plots were used to assess the performance of the nomogram.
Results:
Univariate analysis showed that longer adjuvant imatinib was significantly associated with better 5-year RFS (p < 0.0001). Further investigation identified that the same high-risk patients with lower tumor-associated recurrence risk benefitted little from prolonged treatment and that the recommended adjuvant imatinib duration was insufficient for those with higher recurrence risk. A nomogram for predicting 2-, 3-, and 5-year RFS based on different treatment durations and four major risk factors, namely, tumor site, size, mitotic count, and rupture status, was built and validated, with a C-index of 0.82, 0.74, and 0.70 in training and two external validation cohorts, respectively. An online dynamic nomogram was further developed for clinical applications (https://ruolinliu666.shinyapps.io/GIST/), offering predictive recurrence rates based on different treatment durations and tumor features.
Conclusions:
We developed a nomogram to predict the recurrence risk for high-risk patients according to tumor features and treatment durations of imatinib to help physicians on decision-making for individualized treatment duration.
