A population-based propensity-matched study of regional dissections in patients with metastatic osteosarcoma

Clinical Features, Risk Factors, and Prediction Nomogram for Primary Spinal Osteosarcoma: A Large-Cohort Retrospective Study

STUDY DESIGN

Retrospective cohort study.

OBJECTIVES

The goal of this study was to determine the clinical characteristics of patients with primary spinal osteosarcoma and to construct a practical clinical prediction model for patients to achieve an accurate prediction of overall survival.

METHODS

This study included 230 patients diagnosed between 2004-2015 from the Surveillance, Epidemiology, and End Results database. Independent risk factors were screened in the training set using Cox regression algorithms, and a prognostic model was developed. Internal and external validation sets were used to test the nomogram model's calibration, discrimination, and clinical utility. A risk classification system based on the nomogram was developed and validated.

RESULTS

Four independent prognostic factors were identified, and based on this a nomogram model was developed for predicting patient prognosis. The C-index of the training set was .737, while that of the validation set was .693. The time-varying area under the curve values was greater than .720 in both cohorts. The calibration curves proved that the prediction model has high prediction accuracy. The decision curve analysis showed that the nomogram is clinically useful. A risk classification system was established, which allows all patients to be divided into two different risk groups.

CONCLUSIONS

A nomogram and risk classification system was developed for patients with primary spinal osteosarcoma to accurately predict overall patient survival and achieve risk stratification of patient mortality. These tools are expected to play an important role in clinical practice, informing clinicians in making decisions.

Clinical characteristic-assisted surgical benefit stratification for resection of primary tumor in patients with advanced primary malignant bone neoplasms: a population-based propensity score-matched analysis

Background

Primary tumor resection (PTR) is the standard treatment for patients with primary malignant bone neoplasms (PMBNs). However, it remains unclear whether patients with advanced PMBNs still benefit from PTR. This study aimed to develop a prediction model to estimate the beneficial probability of PTR for this population.

Methods

This study extracted data from patients diagnosed with advanced PMBNs, as recorded in the Surveillance, Epidemiology, and End Results (SEER) database, with the period from 2004 to 2015. The patient cohort was then bifurcated into two groups: those who underwent surgical procedures and the non-surgery group. Propensity score matching (PSM) was utilized to mitigate any confounding factors in the study. The survival rates of patients from both the surgical and non-surgery groups were evaluated using Kaplan-Meier (K-M) curves analysis. Moreover, the study used this method to assess the capacity of the nomogram to distinguish patients likely to derive benefits from surgical intervention. The study was grounded in the hypothesis that patients who underwent PTR and survived beyond the median overall survival (OS) time would potentially benefit from the surgery. Subsequently, logistic regression analysis was performed to ascertain significant predictors, facilitating the development of a nomogram. This nomogram was subjected to both internal and external validation using receiver operating characteristic curves, area under the curve analysis, calibration plots, and decision curve analysis.

Results

The SEER database provided a total of 839 eligible patients for the study, among which 536 (63.9%) underwent PTR. Following a 2:1 PSM analysis, patients were classified into two groups: 364 patients in the surgery group and 182 patients in the non-surgery group. Both K-M curves and multivariate Cox regression analysis revealed that patients who received PTR had a longer survival duration, observed both before and after PSM. Crucial factors such as age, M stage, and tumor size were identified to be significantly correlated with surgical benefits in patients with advanced PMBNs. Subsequently, a nomogram was developed that uses these independent predictors. The validation of this predictive model confirmed its high accuracy and excellent discrimination ability of the nomogram to distinguish patients who would most likely benefit from surgical intervention.

Conclusion

In this study, we devised a user-friendly nomogram to forecast the likehood of surgical benefits for patients diagnosed with advanced PMBNs. This tool facilitates the identification of the most suitable candidates for PTR, thus promoting more discerning and effective use of surgical intervention in this patient population.

Immunotherapeutic Strategies in the Management of Osteosarcoma

Osteosarcoma (OS) is the most common primary malignant bone cancer with a high tendency for metastasis. Although treatment strategies involving surgery and chemotherapy have improved outcomes for patients with OS, the prognosis of recurrent OS is quite unsatisfactory. Primary reasons leading to mortality in OS patients are resistance to currently used therapies and the subsequent lung metastasis. Immunotherapy, however, has been shown to be a promising therapeutic strategy against OS. As research progresses, immunotherapy is gradually becoming irreplaceable. This article provides a critical evaluation of several therapeutic strategies for OS including immunomodulation, vaccine therapy, and immunologic checkpoint blockade.

Osteosarcoma immune prognostic index can indicate the nature of indeterminate pulmonary nodules and predict the metachronous metastasis in osteosarcoma patients

Purpose

The relationship between indeterminate pulmonary nodules (IPNs) and metastasis is difficult to determine. We expect to explore a predictive model that can assist in indicating the nature of IPNs, as well as predicting the probability of metachronous metastasis in osteosarcoma patients.

Patients and methods

We conducted a retrospective study including 184 osteosarcoma patients at West China Hospital from January 2016 to January 2021. Hematological markers and clinical features of osteosarcoma patients were collected and analyzed.

Results

In this study, we constructed an osteosarcoma immune prognostic index (OIPI) based on the lung immune prognostic index (LIPI). Compared to other hematological markers and clinical features, OIPI had a better ability to predict metastasis. OIPI divided 184 patients into four groups, with the no-OIPI group (34 patients), the light-OIPI group (35 patients), the moderate-OIPI group (75 patients), and the severe-OIPI group (40 patients) (P < 0.0001). Subgroup analysis showed that the OIPI could have a stable predictive effect in both the no-nodule group and the IPN group. Spearman’s rank correlation test and Kruskal–Wallis test demonstrated that the OIPI was related to metastatic site and metastatic time, respectively. In addition, patients with IPNs in high-OIPI (moderate and severe) groups were more likely to develop metastasis than those in low-OIPI (none and light) groups. Furthermore, the combination of OIPI with IPNs can more accurately identify patients with metastasis, in which the high-OIPI group had a higher metastasis rate, and the severe-OIPI group tended to develop metastasis earlier than the no-OIPI group. Finally, we constructed an OIPI-based nomogram to predict 3- and 5-year metastasis rates. This nomogram could bring net benefits for more patients according to the decision curve analysis and clinical impact curve.

Conclusion

This study is the first to assist chest CT in diagnosing the nature of IPNs in osteosarcoma based on hematological markers. Our findings suggested that the OIPI was superior to other hematological markers and that OIPI can act as an auxiliary tool to determine the malignant transformation tendency of IPNs. The combination of OIPI with IPNs can further improve the metastatic predictive ability in osteosarcoma patients.

Does Primary Tumor Resection in Patients with Metastatic Primary Mobile Vertebral Column Sarcoma Improve Survival?

BACKGROUND

Primary mobile vertebral column sarcoma is an exceedingly rare malignancy. Although primary tumor resection has been reported to prolong survival in patients with metastatic bone sarcoma, whether primary tumor resection in patients with advanced primary mobile vertebral column sarcoma is associated with survival remains unclear owing to the rarity of this pathological entity.

METHODS

Using the Surveillance, Epidemiology, and End Results database, 182 patients with metastatic primary mobile vertebral column sarcoma were identified between 1983 and 2015. Of the 182 patients enrolled, 101 patients (55%) underwent primary tumor resection (Surgery group) and 81 patients (45%) did not undergo resection (No Surgery group). To account for imbalances in the basic characteristics of patients between groups, propensity score matching was performed. Survival analysis was performed by weighted Cox proportional hazards modeling to calculate hazard ratios.

RESULTS

After adjusting for patient background characteristics, 138 patients were included for the analysis (Surgery group: 69 patients; No Surgery group: 69 patients). The Surgery group did not show improved cancer-specific survival (hazard ratio = 0.73, 95% CI 0.49-1.10). Similarly, the Surgery group did not show improved overall survival compared with the No Surgery group (hazard ratio = 0.80, 95% CI 0.55-1.16).

CONCLUSIONS

To our knowledge, this is the first study to indicate that surgical resection for advanced primary mobile vertebral column sarcoma does not have a positive impact on survival.

Surgical resection of primary tumor in the extremities improves survival for metastatic soft-tissue sarcoma patients: a population-based study of the SEER database

PURPOSE

The objectives of this study were to clarify whether resection of primary tumor in the extremities for patients with metastatic soft-tissue sarcoma (STS) improves survival, and to clarify patient groups for whom primary tumor resection should be considered.

METHODS/PATIENTS

Using the surveillance, epidemiology, and end results database, we identified 1453 patients with metastatic STS of the extremities at initial presentation between 1983 and 2016. Of these 1453 patients, 898 patients underwent primary tumor resection (Surgery group), and 555 patients did not (No-surgery group).

RESULTS

After adjusting for patient background by propensity score matching, a total of 804 patients were included for analysis. Patients in the Surgery group showed improved survival (cancer-specific survival (CSS) hazard ratio (HR) = 0.59, 95% confidence interval (CI) 0.50-0.71 overall survival rate (OS) HR = 0.60, 95% CI 0.51-0.70). In subclass analysis, patients with high-grade STS, undifferentiated pleomorphic sarcoma, leiomyosarcoma, or synovial sarcoma showed improved survival in the Surgery group (high grade-CSS HR = 0.57, 95% CI 0.45-0.72, OS HR = 0.58, 95% CI 0.48-0.71; undifferentiated pleomorphic sarcoma-CSS HR = 0.60, 95% CI 0.42-0.84, OS HR = 0.61, 95% CI 0.46-0.82; leiomyosarcoma-CSS HR = 0.50, 95% CI 0.33-0.75, OS HR = 0.50, 95% CI 0.35-0.72; synovial sarcoma-CSS HR = 0.46, 95% CI 0.31-0.68, OS HR = 0.43, 95% CI 0.30-0.62).

CONCLUSIONS

Our results indicated that primary tumor resection in metastatic STS exerts positive impacts on survival. Further clinical research is needed to confirm these results.

Construction and validation of nomogram to predict distant metastasis in osteosarcoma: a retrospective study

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.

Thermogel Delivers Oxaliplatin and Alendronate in situ for Synergistic Osteosarcoma Therapy

The therapeutic effect of osteosarcoma (OS) has not made extraordinary progress in the past few decades. Oxaliplatin (OXA) is a widely used clinical anti-tumor drug. Recent studies have shown that OXA can trigger anti-tumor immunity by inducing immunogenic death (ICD). Alendronate (ALN) has been used to threaten the skeletal system tumors because of the unique bone affinity and the ability to inhibit bone destruction. In this study, we co-loaded OXA and ALN on mPEG45-PLV19 thermo-sensitive hydrogel to perform in situ treatment on the mouse OS model. Slowly released OXA can induce immunogenic death of tumor cells. At the same time, thermo-sensitive hydrogels can induce the accumulation of cytotoxic T lymphocytes. Besides, ALN could synergistically diminish tumors and prevent bone destruction. This system could synergistically inhibit the progression of OS and lung metastasis and has no toxicity to various organs throughout the body.