Development of a Multi-Institutional Prediction Model for Three-Year Survival Status in Patients with Uterine Leiomyosarcoma (AGOG11-022/QCGC1302 Study)

Abstract

Background: The existing staging systems of uterine leiomyosarcoma (uLMS) cannot classify the patients into four non-overlapping prognostic groups. This study aimed to develop a prediction model to predict the three-year survival status of uLMS. Methods: In total, 201 patients with uLMS who had been treated between June 1993 and January 2014, were analyzed. Potential prognostic indicators were identified by univariate models followed by multivariate analyses. Prediction models were constructed by binomial regression with 3-year survival status as a binary outcome, and the final model was validated by internal cross-validation. Results: Nine potential parameters, including age, log tumor diameter, log mitotic count, cervical involvement, parametrial involvement, lymph node metastasis, distant metastasis, tumor circumscription and lymphovascular space invasion were identified. 110 patients had complete data to build the prediction models. Age, log tumor diameter, log mitotic count, distant metastasis, and circumscription were significantly correlated with the 3-year survival status. The final model with the lowest Akaike’s Information Criterion (117.56) was chosen and the cross validation estimated prediction accuracy was 0.745. Conclusion: We developed a prediction model for uLMS based on five readily available clinicopathologic parameters. This might provide a personalized prediction of the 3-year survival status and guide the use of adjuvant therapy, a cancer surveillance program, and future studies.

Development and validation of tumor‐size‐stratified prognostic nomograms for patients with uterine sarcoma: A SEER database analysis

“… 16 Another study showed that 8 cm or 10 cm tumor size was a significant prognostic indicator, but not 5 cm. 15 In addition, the median tumor size of uterine sarcoma reported in the previous literature was mostly 7–9 cm, 17 , 18 , 19 which was consistent with our finding (7.8 cm). Therefore, factoring in the appropriate cut‐off value and median tumor size, this study stratified the patients according to the tumor size of 7.8 cm.…”

“…For instance, Garg et al demonstrated that the 5 cm was a better cut‐off 16 . Another study showed that 8 cm or 10 cm tumor size was a significant prognostic indicator, but not 5 cm 15 . In addition, the median tumor size of uterine sarcoma reported in the previous literature was mostly 7–9 cm, 17–19 which was consistent with our finding (7.8 cm).…”

“…In recent years, nomograms have become more popular than traditional staging systems in predicting the prognosis of tumor patients. This is because the nomogram incorporates multiple characteristic variables, such as age, race, marital status, and tumor grade, into a quantitative model and can calculate the survival rate based on the individual characteristics of the patient 15 . Nomogram has well promoted the development of personalized medicine.…”

“…This is because the nomogram incorporates multiple characteristic variables, such as age, race, marital status, and tumor grade, into a quantitative model and can calculate the survival rate based on the individual characteristics of the patient. 15 Nomogram has well promoted the development of personalized medicine. In a previous study, the researcher typically established one OS predicting nomogram for all tumor‐size groups of patients with uterine sarcoma.…”

Establishment of a staging system for visceral sarcoma

“…The FIGO staging system has been frequently applied to this disease 17,21 . However, the FIGO staging system cannot effectively and reliably stratify patients into four different prognostic groups, 13,14,25 which was also shown in this study (Figure 5A,C). This may be because STS is a very different disease entity that behaves differently from epithelial carcinoma.…”