Since the statistical prediction model can be simplified into a continuous numerical estimate tailored to individual patient conditions, the role of the nomogram prediction model has gradually become prominent in the era of precision medicine. In order to improve the estimation of the prognosis for patients with subtype pathology, some nomogram prediction models have been incorporated into the AJCC staging system. In the eighth edition of the AJCC manual, the nomogram by Trans-Atlantic Retroperitoneal Sarcoma Working Group for retroperitoneal soft tissue sarcoma (RPS)  was included as a model that met all AJCC quality criteria.
There have been many reports on nomogram prediction models for leiomyosarcoma. For example, MingFeng Xue et al. used the SEER database to establish a nomogram prediction model based on 1528 patients with extremity leiomyosarcoma, which can predict 5- and 10-year OS and cancer specific survival, and The C-index values for internal validation of OS and cancer specific survival prediction were 0.776 (95% CI 0.752–0.801) and 0.835 (95% CI 0.810–0.860), respectively. Oliver Zivanovic et al. used a cohort of 185 cases of uterine leiomyosarcoma to establish a nomogram prediction model that can predict 5-year OS, with a c-index of 0.67 (95% confidence interval, 0.63–0.72). However, not only specific STS histology but also the site of origin maters in determining outcomes in patients with soft tissue sarcoma. But there is currently no nomogram prediction model focused on retroperitoneal leiomyosarcoma only. Therefor, we developed and internally validated a novel, RLMS-specific nomogram for predicting 1-, 2- and 5-year OS, and the c-index of our nomogram was 0.779 (95% CI, 0.659–0.898), the calibration plots shows that the predicted OS rate was perfectly match with the actual OS rate.
RLMS is a very rare mesenchymal malignant that originates in the retroperitoneal space. Its incidence rate is less than 1 per million population. For this usually fatal but rare disease, the question of how to obtain long-term survival is very important. Because of metastasis, multifocal disease, and multiple organ resection are usually contraindications to surgery, the potential beneficial effects of surgery are not always obvious, which lead decision-making very complicated. Because of metastasis, multifocal tumor, and multiple organ resection are usually contraindications to surgery. And it is extremely difficult for clinical decision-making whether or not patients with recurrence should undergo surgery. However, we can get some hints in the nomogram established in this research. For example, for those diseases where the preoperative assessment does not require combined organ resection, tumor burden is less than 5 cm, FNCLCC grade 1 and single center disease, even if it is a multiple recurrence disease, the 5-year OS rate after may exceed 90%, and the operation is obvious profitable. On the contrary, those who need combined resection of multiple organs, tumor burden is greater than 5cm, FNCLCC grade 3, multifocal disease, the nomogram score is greater than 200 points, and the OS is less than 30% at 2 years after surgery. For such people, the choice of surgery needs to be more cautious.
In the survival analysis, we found that FNCLCC grade and multifocal disease are independent risk factors for postoperative OS. The FNCLCC system is a commonly used histological grading system for soft tissue sarcomas, and it is one of the best indicators for predicting metastasis-free survival and OS. This study is similar to the previous study reported by Qian Li et al., for RLMS patients with recurrent or metastatic disease who had a higher FNCLCC grade experienced worse prognosis. Consistent with previous reports on RPS, patients with multifocal disease accounted for 23% of patients in this study, and compared with single-center disease, the risk of death in patients with multifocal disease increased by two times. Although there have been reports about the role of multifocal disease in the prognosis of RPS, as far as we know, this research is the first to report its a independent prognostic factors in RLMS.
This study had certain limitations. First, this study was based on a retrospective cohort. The selection and inclusion of retrospective patients may cause research bias. Second, the median follow-up time for surviving patients in this study was 31 months, and further extension of the follow-up time will increase the reliability of the data. Third, although internal verification shows that this nomogram was a good predictive model, it still needs to further incorporate data from other centers for external verification.