Soft Tissue Sarcoma Metastasis Research Articles

Radiomics model for predicting distant metastasis in soft tissue sarcoma of the extremities and trunk treated with surgery.

The aim of this study was to develop a radiomics model based on magnetic resonance imaging (MRI) for predicting metastasis in soft tissue sarcomas (STSs) treated with surgery. MRI and clinical data of 73 patients with STSs of the extremities and trunk were obtained from TCIA database and Jiangsu Cancer Hospital as the training set, data of other 40 patients were retrospectively collected at our institution as the external validation set. Radiomics features were extracted from both intratumoral and peritumoral regions of fat-suppressed T2-weighted images (FS-T2WIs) of patients, and 3D ResNet10 was used to extract deep learning features. Recursive feature elimination (RFE) and least absolute shrinkage and selection operator (LASSO) algorithms were used for the selection of features. Based on 4 different sets of features, 5 machine learning algorithms were used to construct intratumor, peritumor, combined intratumor and peritumor radiomics models and deep learning radiomics (DLR) model. The area under the ROC curve (AUC) and Decision curve analysis (DCA) were used to evaluate the ability of models to predict metastasis. Based on 20 selected features from the deep-learning and radiomics features set, the DLR model was able to predict metastasis in the validation dataset, with an AUC of 0.9770. The DCA and Hosmer-Lemeshow test revealed that the DLR model had good clinical benefit and consistency. By getting richer information from MRI, The DLR model is a noninvasive, low-cost method for predicting the risk of metastasis in STSs, and can help develop appropriate treatment programs.

Immune evasion in lung metastasis of leiomyosarcoma: upregulation of EPCAM inhibits CD8+ T cell infiltration

BackgroundLeiomyosarcomas are among the most common histological types of soft tissue sarcoma (STS), with no effective treatment available for advanced patients. Lung metastasis, the most common site of distant metastasis, is the primary prognostic factor. We analysed the immune environment targeting lung metastasis of STS to explore new targets for immunotherapy.MethodsWe analysed the immune environment of primary and lung metastases in 38 patients with STS using immunohistochemistry. Next, we performed gene expression analyses on primary and lung metastatic tissues from six patients with leiomyosarcoma. Using human leiomyosarcoma cell lines, the effects of the identified genes on immune cells were assessed in vitro.ResultsImmunohistochemistry showed a significant decrease in CD8+ cells in the lung metastases of leiomyosarcoma. Among the genes upregulated in lung metastases, epithelial cellular adhesion molecule (EPCAM) showed the strongest negative correlation with the number of CD8+ cells. Transwell assay results showed that the migration of CD8+ T cells was significantly increased in the conditioned media obtained after inhibition or knock down of EPCAM.ConclusionsEPCAM was upregulated in lung metastases of leiomyosarcoma, suggesting inhibition of CD8+ T cell migration. Our findings suggest that EPCAM could serve as a potential novel therapeutic target for leiomyosarcoma.

The Impact of Edema on MRI Radiomics for the Prediction of Lung Metastasis in Soft Tissue Sarcoma.

This study aimed to evaluate whether radiomic features extracted solely from the edema of soft tissue sarcomas (STS) could predict the occurrence of lung metastasis in comparison with features extracted solely from the tumoral mass. We retrospectively analyzed magnetic resonance imaging (MRI) scans of 32 STSs, including 14 with lung metastasis and 18 without. A segmentation of the tumor mass and edema was assessed for each MRI examination. A total of 107 radiomic features were extracted for each mass segmentation and 107 radiomic features for each edema segmentation. A two-step feature selection process was applied. Two predictive features for the development of lung metastasis were selected from the mass-related features, as well as two predictive features from the edema-related features. Two Random Forest models were created based on these selected features; 100 random subsampling runs were performed. Key performance metrics, including accuracy and area under the ROC curve (AUC), were calculated, and the resulting accuracies were compared. The model based on mass-related features achieved a median accuracy of 0.83 and a median AUC of 0.88, while the model based on edema-related features achieved a median accuracy of 0.75 and a median AUC of 0.79. A statistical analysis comparing the accuracies of the two models revealed no significant difference. Both models showed promise in predicting the occurrence of lung metastasis in soft tissue sarcomas. These findings suggest that radiomic analysis of edema features can provide valuable insights into the prediction of lung metastasis in soft tissue sarcomas.

Lung Metastases of Soft Tissue Sarcoma Revealed by Bilateral Spontaneous Pneumothorax

Spontaneous pneumothorax is a relatively rare complication of metastatic lung tumors. In most of the previously reported cases, pulmonary metastases associated with spontaneous pneumothorax tended to originate from osteosarcoma or soft-tissue sarcomas. We hereby report a case of a bilateral spontaneous pneumothorax, in a 45 years-old female revealing lung metastasis of a soft tissue sarcoma.

Abstract 6007: Identification of drivers of soft tissue sarcoma metastasis

Abstract Soft tissue sarcomas are a rare and heterogeneous group of tumors with a 65% five-year survival rate despite aggressive treatment with surgery, radiation, and chemotherapy. Even with intensive multimodality treatment, many patients will develop incurable metastatic disease, providing evidence that our current therapies are ineffective and new treatments are desperately needed. Pre-clinical models to study metastasis of human soft tissue sarcomas are limited. We have developed a system that allows for the formation of distinct soft tissue sarcoma subtypes from mesenchymal stem cells that have been depleted of p53 and Rb1 using CRISPR. Injection of these cells intramuscularly results in metastasis to the lung. Using this novel model system, we have performed a genetic screen to identify pathways and specific drivers of sarcoma metastasis. This pre-clinical in vivo model system will allow for the identification of putative therapeutic targets to prevent the development of lethal metastatic growth. Citation Format: Janai R. Carr-Ascher, Maria Munoz. Identification of drivers of soft tissue sarcoma metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6007.

Epidemiological Trend Analysis and Survival Data of Balinese with Soft-Tissue Sarcoma in 2015–2021

BACKGROUND: Soft tissue sarcoma (STS) has a very heterogen features of its nature, subtypes, and clincial behaviour among population. Regardless, the epidemiology data of soft tissue sarcoma is very limited in developing countries, including Indonesia.
 AIM: To decribe the incidence and mortality trend analysis, as long as the survival data in Bali from 2015 to 2020.
 METHODS: This is a case control study including all subjects with STS in Denpasar, Bali, Indonesia from January 2015 to September 2021. Data about demographics, clinical, and survival timing data were collected from Cancer Registry. Soft tissue sarcoma diagnosis was confirmed after histopathological examination. Joinpoint regression was used for crude rate trend analysis. Data was analyzed by SPSS 22.0, using Kaplan-Meier for survival analysis.
 RESULTS: Ninety three subjects with STS were included in this study. Most patients died at the end of the study (65.6%) with median survival of only 30 months. The trend of STS age-standardized incidence and mortality rate was increasing from 2015 to 2018, then declining until 2020. The survival rate varies among the soft tissue sarcoma subtypes and location. It was better in the group without metastases, underwent therapy, but not statistically significant.
 CONCLUSION: Soft tissue sarcoma showed a diversity of demographic and clinical parameters. The incidence and mortality rate has plateued in 2018, but then declining. The survival rate diversed regarding of the STS subtype, location, metastasis, and treatment given.

Risk factors for lymph node metastasis of soft tissue sarcomas of the head, neck, and extremities, and the clinical significance of negative lymph node dissection

BackgroundThis study sought to define the risk factors for lymph node metastasis (LNM) of soft tissue sarcomas (STS) of the head, neck, and extremities, and the clinical significance of negative lymph node dissection (NLND).MethodsSTS patient data in the Surveillance, Epidemiology, and End Results (SEER) database from 1988 to 2015 were extracted and pooled. Logistics regression analysis was used to identify risk factors for LNM, Cox proportional hazards and Fine–Grey’s models were used for survival analysis, and Propensity score matching analysis (PSM) was used to assess the impact of NLND on patient prognosis.ResultsA total of 3276 patients were enrolled in the study, of whom 283 (8.6%) developed LNM. Rhabdomyosarcoma had the highest rate of LNM (25.3%), followed by clear cell sarcoma (16.8%) and epithelioid sarcoma (12.4%), while leiomyosarcoma had the lowest rate of LNM (1.3%). Sex, tumor size, grade, histology, and site were significantly associated with LNM. For specific histologic subtypes of STS, NLND significantly improves overall survival (HR: 0.718, 95%CI 0.535–0.962; P = 0.026) and cancer-specific survival (HR: 0.699, 95%CI 0.506–0.967; P = 0.031) and reduces cancer-specific mortality (Gray’s test, P = 0.017). However, NLND did not improve overall survival (P = 0.46) or reduce cancer-specific mortality (Gray’s test, P = 0.772) of patients with leiomyosarcoma.ConclusionsHistology is an independent risk factor for LNM in STS of the head, neck, and extremities. Prophylactic NLND treatment was necessary and had a clinical benefit for patients with STS who were at high risk for LNM but had no significant impact on the prognosis of patients with leiomyosarcoma.

Descriptive epidemiology of soft tissue and bone sarcomas in Lebanon.

ObjectivesMost epidemiologic studies on soft tissue sarcomas (STS) and bone sarcomas (BS) are performed in western countries, with few in the Middle East and North Africa region. We describe the epidemiology of sarcomas in Lebanon using the medical records database at the American University of Beirut Medical Center (AUBMC).MethodsThis single-center retrospective cohort study included patients with sarcomas registered in the database between 2015 and 2019. Their charts were reviewed for baseline characteristics, tumor biology and location, treatment modalities, recurrence, metastasis, and death.ResultsThe cohort included 234 patients with STS and 99 patients with BS. Most tumors were <10 cm in size. The most common subtypes were liposarcoma for STS and osteosarcoma for BS. The most common location of STS was the thigh. The most frequent sites of STS metastasis were the lungs. Histological subtype, smoking status, and tumor size and grade were significant for progression-free survival (PFS) in patients with STS. By multivariable analysis, smoking was significantly associated with poorer PFS in STS. For BS, only tumor grade was significant for PFS.ConclusionThe epidemiology of sarcomas at AUBMC is similar to that previously reported. Smoking history was associated with poorer survival in patients with STS.

The Role of Trabectedin in Soft Tissue Sarcoma.

Background: Systemic chemotherapy for advanced disease is another therapeutic option in the management of metastases in soft tissue sarcoma (STS). Doxorubicin either alone or in combination with ifosfamide has been used as first-line chemotherapy. Furthermore, in the past decade, new drugs have been shown to be effective in the treatment of advanced STS after the failure of first-line anthracycline-based chemotherapy: trabectedin, pazopanib and eribulin. However, the appropriate usage of these agents has not been established. Methods: We summarized clinical trials of trabectedin focusing on the efficacy and toxicity of trabectedin in the treatment of STS. Results: Trabectedin can be administered safely and effectively to the patients with advanced STS at second line setting or later. Although trabectedin may be effective as first-line treatment in selected patients, anthracycline-based chemotherapy should be recommended because no regimen in addition to trabectedin has proved to be unequivocally superior to doxorubicin as the first-line treatment for locally advanced or metastatic STS. Nucleotide excision repair (NER) and homologous recombination (HRe) repair may be of particular importance as efficacy of trabectedin. Conclusion: Trabectedin has shown a favorable toxicity profile and is an alternative therapeutic option in patients with advanced STS.

Surgical resection of regional lymph node metastases in soft tissue sarcoma may not result in improved long-term survival

Surgical resection of regional lymph node metastases in soft tissue sarcoma may not result in improved long-term survival

A Highly Reliable Convolutional Neural Network Based Soft Tissue Sarcoma Metastasis Detection from Chest X-ray Images: A Retrospective Cohort Study.

Simple SummarySoft tissue sarcomas are relatively rare malignant diseases. Part of the diagnosis and follow-up includes medical imaging of the thorax for detection of lung metastases. A Python script was created and trained using a set of lung X-rays and concordant CT scans from a high-volume German-speaking sarcoma center. It is capable of detecting malignant metastasis in the lung with a precision of 71.2%, specificity of 90.5%, sensitivity of 94% and accuracy of 91.2%. Furthermore, the program was able to detect even small nodules with a size <1 cm in conventional X-rays of the thorax. This algorithm was implemented into our daily clinical practice alongside with the radiologists’ findings. With this tool we aim to improve the quality of our service and reduce the expenditure of time.Introduction: soft tissue sarcomas are a subset of malignant tumors that are relatively rare and make up 1% of all malignant tumors in adulthood. Due to the rarity of these tumors, there are significant differences in quality in the diagnosis and treatment of these tumors. One paramount aspect is the diagnosis of hematogenous metastases in the lungs. Guidelines recommend routine lung imaging by means of X-rays. With the ever advancing AI-based diagnostic support, there has so far been no implementation for sarcomas. The aim of the study was to utilize AI to obtain analyzes regarding metastasis on lung X-rays in the most possible sensitive and specific manner in sarcoma patients. Methods: a Python script was created and trained using a set of lung X-rays with sarcoma metastases from a high-volume German-speaking sarcoma center. 26 patients with lung metastasis were included. For all patients chest X-ray with corresponding lung CT scans, and histological biopsies were available. The number of trainable images were expanded to 600. In order to evaluate the biological sensitivity and specificity, the script was tested on lung X-rays with a lung CT as control. Results: in this study we present a new type of convolutional neural network-based system with a precision of 71.2%, specificity of 90.5%, sensitivity of 94%, recall of 94% and accuracy of 91.2%. A good detection of even small findings was determined. Discussion: the created script establishes the option to check lung X-rays for metastases at a safe level, especially given this rare tumor entity.

Targeting Lymphotoxin Beta and Paired Box 5: a potential therapeutic strategy for soft tissue sarcoma metastasis

BackgroundSoft tissue sarcomas (STS) has a high rate of early metastasis. In this study, we aimed to uncover the potential metastasis mechanisms and related signaling pathways in STS with differentially expressed genes and tumor-infiltrating cells.MethodsRNA-sequencing (RNA-seq) of 261 STS samples downloaded from the Cancer Genome Atlas (TCGA) database were used to identify metastasis-related differentially expressed immune genes and transcription factors (TFs), whose relationship was constructed by Pearson correlation analysis. Metastasis-related prediction model was established based on the most significant immune genes. CIBERSORT algorithm was performed to identify significant immune cells co-expressed with key immune genes. The GSVA and GSEA were performed to identify prognosis-related KEGG pathways. Ultimately, we used the Pearson correlation analysis to explore the relationship among immune genes, immune cells, and KEGG pathways. Additionally, key genes and regulatory mechanisms were validated by single-cell RNA sequencing and ChIP sequencing data.ResultsA total of 204 immune genes and 12 TFs, were identified. The prediction model achieved a satisfactory effectiveness in distant metastasis with the Area Under Curve (AUC) of 0.808. LTB was significantly correlated with PAX5 (P < 0.001, R = 0.829) and hematopoietic cell lineage pathway (P < 0.001, R = 0.375). The transcriptional regulatory pattern between PAX5 and LTB was validated by ChIP sequencing data.ConclusionsWe hypothesized that down-regulated LTB (immune gene) modulated by PAX5 (TF) in STSs may have the capability of inducing cancer cell metastasis in patients with STS.

Should metastatic lymph nodes be considered at the same clinical stage as distant metastasis in soft tissue sarcomas?

IntroductionLymph node metastasis (LNM) in soft tissue sarcomas (STS) are uncommon, occurring in only 3% – 5% of all sarcomas, and are classified as Stage IV, along with distant metastasis (DM). This paper compares the prognosis of patients with lymphatic and DM, in extremity STS (eSTS). MethodsA retrospective study was carried out in a high-volume sarcoma center; 853 patients with eSTS sarcomas were identified and classified from January 1, 1997 to December 31, 2017. Cases with pathological confirmation of LNM were included. Five-year survival rates were analyzed using the Kaplan-Meier method and the Cox proportional hazards model. ResultsLNM was present in 46 of the cases (5.4%), with an overall survival of 21 months (95% confidence interval [CI], 16.7 – 25.2), compared to 18 months (95% confidence interval [CI], 14.2 – 21.7) in those with only DM. Median recurrence-free survival was 21 months (95% confidence interval [CI], 19.7 – 22.4), vs. 20 months (95% confidence interval [CI], 16.2– 23.7), respectively. LNM only and DM only had also a similar OS of 21 months (95% CI 16.7–25.2) vs 18 months (95% CI 14.2–21.7. N1M1 cases had the worse median OS with 15 months (95% confidence interval [CI], 10.9–19.7) ConclusionsOverall survival and recurrence free survival in patients with lymph node disease and metastatic disease are similar. However prognosis is worse in N1M1. Use of systemic treatment in patients with LNM is not as common as in metastatic cases, this difference in treatment and the fact that prognosis is similar suggests that both biological behavior and effect of treatment have been underestimated. A subclassification of clinical stage IV might be the next step.

Delayed Initiation of Treatment Is Associated With Metastasis of Soft-tissue Sarcoma

The delayed initiation of treatment is associated with poor clinical outcomes in patients with malignancies. However, few previous studies have investigated prognostic factors, including the delayed initiation of treatment, in soft-tissue sarcoma. One hundred and fifty-three patients with soft-tissue sarcoma were enrolled. Univariate and multivariate analyses were performed to identify factors predicting metastasis, including factors that delay the initiation of treatment. The multivariate analysis revealed that high histological grade (p<0.01), tumor located in the trunk (p=0.04), >5-month delay from symptom initiation to consultation of general practitioner (p=0.02), and >29-day delay in referral to a specialized hospital by general practitioners (p=0.03) were independently associated with metastasis of soft tissue sarcoma. Early consultation of a general practitioner and early referral to a specialized hospital might be essential for preventing metastasis of soft-tissue sarcoma.

Metastases of soft tissue sarcoma to the liver: A Historical Cohort Study from a Hospital-based Cancer Registry.

BackgroundHepatic metastasis of soft tissue sarcoma is rare compared to lung metastasis, and the literature is scarce. We examined the risk of hepatic metastasis according to the site of occurrence and histological type.MethodsFrom a Hospital‐based Cancer Registry, 658 patients registered between 2007 and 2017 with soft tissue sarcomas were evaluated. The exclusion criteria were gastrointestinal stromal tumors, tumors of unknown origin, and follow‐up periods of less than 1 month. SPSS 25 was used for statistical analysis.ResultsThe risk of hepatic metastasis was significantly higher in the retroperitoneum (HR, 5.981; 95% CI, 2.793‐12.808) and leiomyosarcoma (HR, 4.303; 95% CI, 1.782‐10.390). Multivariate analysis showed that the risk of hepatic metastasis as first distant metastasis was high in leiomyosarcoma (HR, 4.546; 95% CI, 2.275‐9.086) and retroperitoneal onset (HR, 4.588; 95% CI, 2.280‐9.231). The 2‐year survival rate after hepatic metastasis was 21.7%.ConclusionsThe onset of hepatic metastasis indicates a poor prognosis. However, hepatic metastasis from retroperitoneal sarcoma and leiomyosarcoma may be the first distant metastasis in some cases. For retroperitoneal sarcoma and leiomyosarcoma, additional screening for hepatic metastasis such as contrast CT should be considered during staging and follow‐up after treatment.

Bone metastasis in extremity soft tissue sarcomas: risk factors and survival analysis using the SEER registry.

While lung is the most common site of metastasis, bone metastasis of soft tissue sarcoma is a part of the natural history affecting the prognosis of these patients. To date, no studies have analyzed the histologic subtypes more likely to metastasize to bone, the risk factors for bone metastasis at initial presentation, or the effect that bone metastasis has on the survival of these patients. Patients were identified from the Surveillance, Epidemiology and End Results database with primary extremity STS between 2010 and 2015. Risk factors for early bone metastasis, survival based on different sites of metastasis, and prognostic factors of survival were analyzed. Among 8,234 STS, 2.2% (n = 180) presented with skeletal metastasis. Bone metastasis was more likely when regional lymph nodes were involved (OR = 4.48, p = 0.008). Deep and moderate or high-grade sarcomas had 5-12-fold tendency to present with bone and lung metastasis (p = 0.046, 0.006, 0.030, respectively). The 5-year survival rate was 41.2% (26.9-54.9%) for isolated bone metastasis and 32.9% (21.2-45.1%) for patients with bone and lung metastasis. Resection of the primary sarcoma was the only significant predictor of survival (HR = 0.44, p = 0.021) for patients with bone metastasis. High tumor grade, deep location to fascia and regional lymph node metastasis are significant risk factors for skeletal metastasis at diagnosis of an extremity STS. While neither systemic chemotherapy nor radiotherapy of the primary sarcoma has a significant influence on survival in the presence of bone metastasis, radical resection of the primary STS is associated with increased survival.

A nomogram to predict metastasis of soft tissue sarcoma of the extremities.

Soft tissue sarcoma (STS) of the extremities are a rare tumor. Metastases develop in about 40%-50% of patients, most of whom die from their disease. We sought to identify potential risk factors associated with metastatic diseases upon presentation for patients with STS and established a reliable nomogram model to predict distant metastasis of STS at presentation. The current study retrospectively analyzed 3884 STS of the extremities or trunk patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Based on patient registration, all patients were randomly allocated to training sets and validation sets (2:1). Then, univariate and binary logistic regression analysis was used to determine the significantly correlated predictors of metastasis. Finally, the nomogram model was established, using these predictors and validated it. 311 (8.21%) of the cases experienced distant metastatic disease was present at the time of presentation. The nomogram was developed from age, histology subtype, primary site, tumor size, grade and depth. Encouragingly, the nomogram showed favorable calibration with C-index 0.790 in the training set and 0.801 in validation set. The DCA showed that the novel model was clinically useful. This nomogram model had a high precision to predict the metastasis of soft tissue sarcoma of the extremities. We expect this model could be used in different clinical consultation and established risk assessment.

Fusion of FDG-PET Image and Clinical Features for Prediction of Lung Metastasis in Soft Tissue Sarcomas.

Extracting massive features from images to quantify tumors provides a new insight to solve the problem that tumor heterogeneity is difficult to assess quantitatively. However, quantification of tumors by single-mode methods often has defects such as difficulty in features extraction and high computational complexity. The multimodal approach has shown effective application prospects in solving these problems. In this paper, we propose a feature fusion method based on positron emission tomography (PET) images and clinical information, which is used to obtain features for lung metastasis prediction of soft tissue sarcomas (STSs). Random forest method was adopted to select effective features by eliminating irrelevant or redundant features, and then they were used for the prediction of the lung metastasis combined with back propagation (BP) neural network. The results show that the prediction ability of the proposed model using fusion features is better than that of the model using an image or clinical feature alone. Furthermore, a good performance can be obtained using 3 standard uptake value (SUV) features of PET image and 7 clinical features, and its average accuracy, sensitivity, and specificity on all the sets can reach 92%, 91%, and 92%, respectively. Therefore, the fusing features have the potential to predict lung metastasis for STSs.

Prognostic factors in surgical treatment of the lungs metastases of soft tissue sarcoma

Objective. The aim of this study is to improve the results of surgical treatment of lung metastases of soft tissue sarcomas, to analyze the factors that may affect the effectiveness of surgical treatment.Materials and methods.The study included 80 patients with metastases of bone sarcomas in the lungs, who received treatment in the period from 2000 to 2013. Among the patients there were 42 (48,5 %) men and 38 (51,5 %) women.The median age at diagnosis was 33 years (range 17 to 75). The majority of soft tissue sarcomas were represented by malignant fibrous histiocytoma (27,5 %) and synovial sarcoma (28,5 %). Almost all patients (96 %) underwent chemotherapy before surgery for lung metastases. The indication for surgery in most cases (52,5 %) was metastases in the lungs as the only manifestation of the disease. Most often, operations were performed with unilateral lung lesions (67,5 %).Results. Atypical lung resections 58 (72 %) were the most frequently performed volume of surgical intervention, pneumonectomy, bilobectomy and lobectomy were used in 17 (22 %) cases. Combined resections were performed in six patients. Postoperative complications were observed in 6 (7,5 %) patients. The radicality of the operations performed in the study group was 93 % in the R0 volume, in the R1 volume, 4 % of the operations were performed, in the R2 volume, 1 patient was operated on. The most frequent postoperative complication was pneumonia, one patient died in the early postoperative period from complications of surgery. The median follow-up in the study group was 49,2 months (from 3,5 to 239 months). The overall 5-year survival rate in the study group was 41,5 %. Five-year overall survival was more than 30 % higher in the group of patients who had less than 3 metastatic lesions at baseline. Only the following factors have a direct impact on OS indicators: the number and size of metastatic foci, radical removal of metastatic foci, the effect of previous chemotherapy, and the timing of the development of metastatic lesions. In our study, there were also no differences in OS and PFS depending on the surgical approach used.Conclusion.Surgical treatment is currently fully justified and the only really effective treatment method that can lead to longer-term survival in patients with metastases of sarcomas in the lungs, despite the fact that some metastases have a clear resistance to all types of conservative therapy, while The best treatment results are achieved in the presence of a long disease-free interval (DFI), a small number of metastases and their removal in the R0 volume.

Efficacy and safety of anti-angiogenesis medicines for advanced soft tissue sarcoma: a meta-analysis.

BackgroundSurgery-based treatment is the standard method for the early-stage soft tissue sarcoma (STS) with relatively good clinical outcome. However, the recurrence and metastasis decrease the survival of STS, regardless of surgery, radiotherapy, and chemotherapy. On the other hand, anti-angiogenesis treatments for STS have been clinically applied in recent years. To evaluate the safety and efficacy of anti-angiogenesis medicines for the treatment of advanced STS, we conducted a meta-analysis.MethodsWe systematically searched PubMed, Web of Science, Cochrane Library, Excerpta Medica Database, and China National Knowledge Infrastructure from inception to September 5, 2019. And finally, nine studies with 1,230 patients were included after rigorous screening. The endpoints included objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and adverse reactions (AEs). And we analyzed them with the risk ratio (RR) or the hazard ratio (HR). Moreover, heterogeneity and sensitivity were also analyzed.ResultsThe pooled data showed that anti-angiogenesis medicines significantly benefited ORR [risk ratio (RR) =2.16, 95% CI: 1.47–3.17, P<0.001], and DCR (RR =1.68, 95% CI: 1.49–1.89, P<0.001), respectively, and improved the PFS (HR =0.50, 95% CI: 0.41–0.59, P<0.001), and OS (HR =0.77, 95% CI: 0.63–0.95, P<0.05), respectively. However, as for grade III or higher acute AEs, the antiangiogenic treatment increased morbidities of hypertension (RR =4.88, P<0.005), and diarrhea (RR =3.98, P=0.021) compared to the control group. And no significant difference was found in bone marrow inhibition, vomiting, anemia, and mucositis.ConclusionsAnti-angiogenesis treatments are beneficial in short-term efficacy and long-term survival for the recurrence and metastasis of STS, and the AEs are tolerable.