Nomogram for predicting the overall survival and cancer-specific survival of patients with extremity liposarcoma: a population-based study

Abstract

Background Extremity liposarcoma represents 25% of extremity soft tissue sarcoma and has a better prognosis than liposarcoma occurring in other anatomic sites. The purpose of this study was to develop two nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of patients with extremity liposarcoma. Methods A total of 2170 patients diagnosed with primary extremity liposarcoma between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were performed to explore the independent prognostic factors and establish two nomograms. The area under the curve (AUC), C-index, calibration curve, decision curve analysis (DCA), Kaplan-Meier analysis, and subgroup analyses were used to evaluate the nomograms. Results Six variables were identified as independent prognostic factors for both OS and CSS. In the training cohort, the AUCs of the OS nomogram were 0.842, 0.841, and 0.823 for predicting 3-, 5-, and 8-year OS, respectively, while the AUCs of the CSS nomogram were 0.889, 0.884, and 0.859 for predicting 3-, 5-, and 8-year CSS, respectively. Calibration plots and DCA revealed that the nomogram had a satisfactory ability to predict OS and CSS. The above results were also observed in the validation cohort. In addition, the C-indices of both nomograms were significantly higher than those of all independent prognostic factors in both the training and validation cohorts. Stratification of the patients into high- and low-risk groups highlighted the differences in prognosis between the two groups in the training and validation cohorts. Conclusion Age, sex, tumor size, grade, M stage, and surgery status were confirmed as independent prognostic variables for both OS and CSS in extremity liposarcoma patients. Two nomograms based on the above variables were established to provide more accurate individual survival predictions for extremity liposarcoma patients and to help physicians make appropriate clinical decisions.

Development and Validation of a Contrast-Enhanced CT-Based Radiomics Nomogram for Prediction of Therapeutic Efficacy of Anti-PD-1 Antibodies in Advanced HCC Patients

“…Moreover, radiomics has recently been recognized as a newly emerging form of imaging technology in oncology using a series of statistical analysis tools or data-mining algorithms on high-throughput imaging features to obtain predictive or prognostic information (25). Its application has achieved successful prediction abilities in various tumors by building appropriate models with refined features and clinical data (26)(27)(28)(29)(30). For instance, radiomic features extracted from contrast-enhanced CT (CECT) have been proved to be useful in predicting microvascular invasion (MVI) and the long-term clinical outcomes in patients with HCC (31).…”

A Novel Clinical Nomogram for Predicting Cancer-Specific Survival in Adult Patients After Primary Surgery for Epithelial Ovarian Cancer: A Real-World Analysis Based on the Surveillance, Epidemiology, and End Results Database and External Validation in a Tertiary Center

“…Reliable determinations of prognosis for adult EOC remain a difficult problem for clinicians. However, nomograms can be used to evaluate individual survival prognosis according to disease characteristics with high accuracy, which can aid in clinical decision-making for patients with various types of tumors (29)(30)(31). Moreover, nomograms have been significantly better at judging prognosis than traditional AJCC stage and clinician experience.…”

Development and Validation of Prognostic Survival Nomograms for Patients with Anal Canal Cancer: A SEER-Based Study

“…It is acknowledged that the AJCC system is considered the gold standard to predict the prognosis of patients with tumours. 12 In our study, the hazard ratio (HR) values of stage II relative to stage I were 1.317 ( P = 0.120) and 2.444 ( P = 0.002) for OS and CSS, respectively, while the HR values for stage IV relative to the stage I increased to 2.761 ( P < 0.001) and 4.998 ( P < 0.001), indicating that as the tumour progresses, the HR values of OS and CSS gradually increase. Yu et al demonstrated that the SEER stage was statistically associated with CSS in gastric cancer.…”

“…In addition, a nomogram can display prognosis prediction results and guide individualised treatment for patients with tumours based on their personal and disease characteristics. 11 , 12 Tsikitis et al 13 constructed nomograms of overall survival (OS) and salvage abdominoperineal resection for anal cancer patients based on data from 1778 anal cancer patients in the US National Cancer Database between 1998 and 2010. Although the potency of nomograms 14–17 has been verified in various cancers, sufficient studies have not been performed on its application in patients with anal canal cancer.…”