Journal
BRITISH JOURNAL OF CANCER
Volume 127, Issue 10, Pages 1793-1798Publisher
SPRINGERNATURE
DOI: 10.1038/s41416-022-01959-4
Keywords
-
Categories
Funding
- Norwegian Cancer Society [1443852014]
- South-East Norway Regional Health Authority [2019064]
Ask authors/readers for more resources
This study validated the G-score model in a large international cohort with long-term follow-up and demonstrated its superior accuracy in predicting early and late recurrence risk in solitary fibrous tumours (SFTs) compared to other models. A less intensive follow-up schedule could be considered for low-risk patients according to the G-score.
Background Current risk models in solitary fibrous tumour (SFT) were developed using cohorts with short follow-up and cannot reliably identify low-risk patients. We recently developed a novel risk model (G-score) to account for both early and late recurrences. Here, we aimed to validate the G-score in a large international cohort with long-term follow-up. Methods Data were collected from nine sarcoma referral centres worldwide. Recurrence-free interval (RFi) was the primary endpoint. Results The cohort comprised 318 patients with localised extrameningeal SFTs. Disease recurrence occurred in 96 patients (33%). The estimated 5-year RFi rate was 72%, and the 10-year RFi rate was 52%. G-score precisely predicted recurrence risk with estimated 10-year RFi rate of 84% in low risk, 54% in intermediate risk and 36% in high risk (p < 0.001; C-index 0.691). The mDemicco (p < 0.001; C-index 0.749) and Salas(OS) (p < 0.001; C-index 0.674) models also predicted RFi but identified low-risk patients less accurate with 10-year RFi rates of 72% and 70%, respectively. Conclusions G-score is a highly significant predictor of early and late recurrence in SFT and is superior to other models to predict patients at low risk of relapse. A less intensive follow-up schedule could be considered for patients at low recurrence risk according to G-score.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available