Background Osteosarcoma is most common malignant bone tumors. OS patients with metastasis have a poor prognosis. There are few tools to assess metastasis; we want to establish a nomogram to evaluate metastasis of osteosarcoma. Methods Data from the Surveillance, Epidemiology, and End Results (SEER) database of patients with osteosarcoma were retrieved for retrospective analysis. We identify risk factors through univariate logistic regression and multivariate logistic regression analysis. Based on the results of multivariate analysis, we established a nomogram to predict metastasis of patients with osteosarcoma and used the concordance index (C-index) and calibration curves to test models. Results One thousand fifteen cases were obtained from the SEER database. In the univariate and multivariate logistic regression analysis, age, primary site, grade, T stage, and surgery are risk factors. The nomogram for metastasis was constructed based on these factors. The C-index of the training and validation cohort was 0.754 and 0.716. This means that the nomogram predictions of patients with metastasis are correct, and the calibration plots also show the good prediction performance of the nomogram. Conclusion We successfully develop the nomogram which can reliably predict metastasis in different patients with osteosarcoma and it only required basic information of patients. The nomogram that we developed can help clinicians better predict the metastasis with OS and determine postoperative treatment strategies.

Osteosarcoma serves as a prevalent bone cancer with a high metastasis and common drug resistance, resulting in poor prognosis and high mortality. Photodynamic therapy (PDT) is a patient-specific and non-invasive tumor therapy. Nanoparticles, like graphene oxide have been widely used in drug delivery and PDT. Ginsenoside Rg3 is a principal ginseng component and has presented significant anti-cancer activities. Here, we constructed the nanoparticles using GO linked with photosensitizer (PS) indocyanine green (ICG), folic acid, and polyethylene glycol (PEG), and loaded with Rg3 (PEG–GO–FA/ICG–Rg3). We aimed to explore the effect of PEG–GO–FA/ICG–Rg3 combined with PDT for the treatment of osteosarcoma. Significantly, we found that Rg3 repressed proliferation, invasion, and migration, and enhanced apoptosis and autophagy of osteosarcoma cells, while the PEG–GO–FA/ICG–Rg3 presented a higher activity, in which NIR laser co-treatment could remarkably increase the effect of PEG–GO–FA/ICG–Rg3. Meanwhile, stemness of osteosarcoma cell–derived cancer stem cells was inhibited by Rg3 and PEG–GO–FA/ICG–Rg3, and the combination of PEG–GO–FA/ICG–Rg3 with NIR laser further significantly attenuated this phenotype in the system. Moreover, NIR laser notably improved the inhibitor effect of PEG–GO–FA/ICG–Rg3 on the tumor growth of osteosarcoma cells in vivo. Consequently, we concluded that PEG–GO–FA/ICG–Rg3 improved PDT in inhibiting malignant progression and stemness of osteosarcoma cell. Our finding provides a promising and practical therapeutic strategy for the combined treatment of osteosarcoma.