Applicability of the Sarculator and MSKCC nomograms to retroperitoneal sarcoma prognostication in an Asian tertiary center

New Sarculator Prognostic Nomograms for Patients With Primary Retroperitoneal Sarcoma: Case Volume Does Matter

OBJECTIVE

To update the current Sarculator retroperitoneal sarcoma (RPS) prognostic nomograms considering the improvement in patient prognosis and the case volume effect.

BACKGROUND

Survival of patients with primary RPS has been increasing over time, and the volume-outcome relationship has been well recognized. Nevertheless, the specific impact on prognostic nomograms is unknown.

METHODS

All consecutive adult patients with primary localized RPS treated at 8 European and North American sarcoma reference centers between 2010 and 2017 were included. Patients were divided into 2 groups: high-volume centers (HVC, ≥13 cases/year) and low-volume centers (LVC, <13 cases/year). Primary end points were overall survival (OS) and disease-free survival (DFS). Multivariable analyses for OS and DFS were performed. The nomograms were updated by recalibration. Nomograms performance was assessed in terms of discrimination (Harrell C index) and calibration (calibration plot).

RESULTS

The HVC and LVC groups comprised 857 and 244 patients, respectively. The median annual primary RPS case volume (interquartile range) was 24.0 in HVC (15.0-41.3) and 9.0 in LVC (1.8-10.3). Five-year OS was 71.4% (95% CI: 68.3%-74.7%) in the HVC cohort and 63.3% (56.8%-70.5%) in the LVC cohort ( P =0.012). Case volume was associated with both OS (LVC vs. HVC hazard ratio 1.40, 95% CI: 1.08-1.82, P =0.011) and DFS (hazard ratio 1.93, 95% CI: 1.57-2.37, P <0.001) at multivariable analyses. When applied to the study cohorts, the Sarculator nomograms showed good discrimination (Harrell C index between 0.68 and 0.73). The recalibrated nomograms showed good calibration in the HVC group, whereas the original nomograms showed good calibration in the LVC group.

CONCLUSIONS

New nomograms for patients with primary RPS treated with surgery at high-volume versus low-volume sarcoma reference centers are available in the Sarculator app.

Risk Stratification with Sarculator and MSKCC in Patients with Primary and Secondary Angiosarcoma

BACKGROUND

Sarculator and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms are freely available risk prediction scores for surgically treated patients with primary sarcomas. Due to the rarity of angiosarcomas, these scores have only been tested on small cohorts of angiosarcoma patients. In neither the original patient cohort upon which the Sarculator is based nor in subsequent studies was a distinction made between primary and secondary angiosarcomas, as the app is intended to be applied to primary sarcomas. Therefore, the objective of our investigation was to assess whether the Sarculator reveals a difference in prognosis and whether such differentiation aligns with actual clinical data.

PATIENTS AND METHODS

Thirty-one patients with primary or secondary soft tissue angiosarcoma, treated at our Sarcoma Center from 2001 to 2023, were included in the study. Actual survival rates were compared with nomogram-derived data for predicted 5-year survival (Sarculator), as well as 4-, 8- and 12-year sarcoma-specific death probabilities (MSKCC). Harrell's c-index was utilized to assess predictive validity.

RESULTS

In total, 31 patients were analyzed. The actual overall 5-year survival was 22.57% with a predicted 5-year survival rate of 25.97%, and the concordance index was 0.726 for the entire cohort. The concordance index results from MSKCC for angiosarcoma patients were below 0.7 indicating limited predictive accuracy in this cohort, particularly when compared to Sarculator.

SUMMARY

Nomogram-based predictive models are valuable tools in clinical practice for rapidly assessing prognosis. They can streamline the decision-making process for adjuvant treatments and improve patient counselling especially in the treatment of rare and complicated tumor entities such as angiosarcomas.

Evaluation of AJCC staging system and proposal of a novel stage grouping system in retroperitoneal liposarcoma: the Fudan Zhongshan experience

Background

Overall survival (OS) varies significantly among individuals with heterogeneous retroperitoneal liposarcoma (RPLS), even among those with the same clinical stage. Improved staging of RPLS is a critical unmet need, given the disappointing results of external validations of the 8th American Joint Committee on Cancer (AJCC) TNM staging system.

Methods

The cohort study included 220 consecutive patients who underwent surgical resection for primary RPLS at the largest sarcoma centre of Fudan University in China from September 2009 to August 2021, combined with 277 adult patients with RPLS in the SEER database from 1975 to 2020. Data analysis was performed from December 2021 to December 2022. Patients were retrospectively restaged according to the 8th and 7th editions of the TNM staging system as well as the new TNM (nTNM) staging system. The primary endpoint was overall survival (OS). Comparative analysis of postoperative survival was performed using the Kaplan-Meier method, and differences between subgroups were tested using the log-rank test. The OS prediction nomogram was generated based on baseline variables and tumour characteristics. Harrell's consistency index (C-index), area under the curve (AUC) of receiver operating characteristic curves (ROC), and calibration curves were used to evaluate the performance of the nomogram.

Results

A total of 497 patients were enrolled in the study, including 282 (56.7%) male patients. The median follow-up was 51 months (interquartile range, IQR, 23-83), and the OS rates at 1, 3, and 5 years were 87.9%, 75.3%, and 64.9%, respectively. According to the staging distribution of the AJCC 7th edition, 6 patients were stage IA (1.2%), 189 patients were stage IB (38%), 12 patients were stage IIA (2.4%), 150 patients were stage IIB (30.1%), 131 patients were stage III (26.3%), and 9 patients were stage IV (1.8%). With the 8th edition staging, this distribution changed: 6 patients (1.2%) were stage IA, 189 patients (38%) were stage IB, 12 patients (2.4%) were stage II, 24 patients (4.8%) were stage IIIA, 257 patients (51.7%) were stage IIIB, and 9 patients (1.8%) were stage IV. 182 patients (36.6%) were reclassified according to the nTNM staging system with the new T stage classification. The C-index and log-rank score improved after implementation of nTNM implementation. The nTNM system was associated with improved identification of high-risk patients compared with the AJCC 7th and 8th TNM. The FNCLCC stage proved to be highly prognostic with significant intergroup differences in OS. The calibration curve shows a high degree of agreement between the actual OS rate and the nomogram estimated OS rate.

Conclusion

Compared with 8th AJCC TNM, 7th AJCC TNM staging system showed a more homogeneous staging distribution and a slight improvement in the prognostic accuracy of RPLS. The revised T-stage and nTNM systems showed better risk stratification performance. The FNCLCC stage was found to have high prognostic value, further emphasising histological grade is the least negligible prognostic factor in predicting patient survival. The constructed nomogram model enables individualized prognostic analysis and helps to develop risk-adapted therapy for RPLS patients.

Staging Systems and Nomograms for Soft Tissue Sarcoma

Reliable tools for prognosis prediction are crucially needed by oncologists so they can tailor individual treatments. However, the wide spectrum of histologies and prognostic behaviors of sarcomas challenges their development. In this field, nomograms could definitely better account for their granularity compared to the more widely used AJCC/UICC TNM staging system. Nomograms are predictive tools that incorporate multiple risk factors and return a numerical probability of a clinical event. Since the development of the first nomogram in 2002, several other nomograms have been built, either general, site-specific, histology-specific, or both. Recently, some new “dynamic” nomograms and prognostic tools have been developed, allowing doctors to “recalculate” a patient’s prognosis by taking into account the time since primary surgery, the event history, and the potential time-dependent effect of covariates. Due to these new tools, prognosis prediction is no longer limited to the time of the first computation but can be adapted and recalculated based on the occurrence (or not) of any event as time passes from the first computation. In this review, we aimed to give an overview of the available nomograms for STS and to help clinicians in the process of selecting the best tool for each patient.

Development and Validation of a Nomogram for Predicting Recurrence-Free Survival of Surgical Resected Retroperitoneal Liposarcoma

Background and Objectives

Surgical treatment is still the mainstay of curative therapy for retroperitoneal liposarcoma (RLPS), but often recurs after surgical resection. We aimed to establish a nomogram for postoperative recurrence of RLPS based on the Asian population.

Methods

Patients after surgical resection at the South Hospital of Zhongshan Hospital/Shanghai Public Health Clinical Center between August 2011 and December 2020 were included. The enrolled patients are randomly divided into training set and test set according to the ratio of 7:3. Prognostic factors were chosen based on Akaike Information Criterion, and the nomogram was built based on Cox regression and then internally validated through calibration plots and concordance index (C-index).

Results

A total of 447 patients were included. Gender, age, presentation status, organ invasion and FNCLCC grade were used to build nomogram. The calibration plots showed that RFS predicted probabilities are identical to the actual RFS rates. The C-index of the nomogram was 0.703 (95% CI 0.623–0.783) in the training set and 0.695 (95% CI 0.565–0.825) in test set.

Conclusion

The nomogram we established can accurately predict postoperative recurrence of RLPS patients for Asian population.

A multi-institutional validation study of prognostic nomograms for retroperitoneal sarcoma

BACKGROUND AND OBJECTIVES

Prognostic nomograms for patients undergoing resection of retroperitoneal sarcoma (RPS) include the Sarculator and Memorial Sloan Kettering (MSK) sarcoma nomograms. We sought to validate the Sarculator and MSK nomograms within a large, modern multi-institutional cohort of patients with primary RPS undergoing resection.

METHODS

Patients who underwent resection of primary RPS between 2000 and 2017 across nine high-volume US institutions were identified. Predicted 7-year disease-free (DFS) and overall survival (OS) and 4-, 8-, and 12-year disease-specific survival (DSS) were calculated from the Sarculator and MSK nomograms, respectively. Nomogram-predicted survival probabilities were stratified in quintiles and compared in calibration plots to observed survival outcomes assessed by Kaplan-Meier estimates. Discriminative ability of nomograms was quantified by Harrell's concordance index (C-index).

RESULTS

Five hundred and two patients underwent resection of primary RPS. Histologies included leiomyosarcoma (30%), dedifferentiated liposarcoma (23%), and well-differentiated liposarcoma (15%). Median tumor size was 14.0 cm (interquartile range [IQR], 8.5-21.0 cm). Tumor grade distribution was: Grade 1 (27%), Grade 2 (17%), and Grade 3 (56%). Median DFS was 31.5 months; 7-year DFS was 29%. Median OS was 93.8 months; 7-year OS was 51%. C-indices for 7-year DFS, and OS by the Sarculator nomogram were 0.65 (95% confidence interval [CI]: 0.62-0.69) and 0.69 (95%CI: 0.65-0.73); plots demonstrated good calibration for predicting 7-year outcomes. The C-index for 4-, 8-, and 12-year DSS by the MSK nomogram was 0.71 (95%CI: 0.67-0.75); plots demonstrated similarly good calibration ability.

CONCLUSIONS

In a diverse, modern validation cohort of patients with resected primary RPS, both Sarculator and MSK nomograms demonstrated good prognostic ability, supporting their ongoing adoption into clinical practice.

Gene Expression Changes Associated with Dedifferentiation in Liposarcoma Predict Overall Survival

Simple Summary

Previous studies have performed integrative analyses of genomic aberrations in soft tissue sarcomas. Utilising clinical information, groups have proposed nomograms for prediction of survival and recurrence in retroperitoneal sarcomas. Expanding on clinical nomogram prediction models with molecular classification of tumours may allow us to further identify clinical phenotypes within this heterogeneous group. We showed that a five-gene molecular prognostic panel can provide additional prognostic information in patients with retroperitoneal DDLS, independent of clinical features. A combined clinical and molecular prediction model may offer the best way to prognosticate patients for patient counselling and therapeutic decision making.

Abstract

Up to 10% of well-differentiated liposarcoma (WDLS) progress to dedifferentiated liposarcoma (DDLS). We aimed to identify gene expression changes associated with dedifferentiation and whether these were informative of tumour biology of DDLS. We analysed datasets from the Gene Expression Omnibus (GEO, ID = GSE30929) database to identify differentially expressed genes between WDLS (n = 52) and DDLS (n = 39). We validated the signature on whole and laser-capture microdissected samples from patients with tumours consisting of mixed WDLS and DDLS components. A subset of this signature was applied to an independent dataset from The Cancer Genome Atlas (TCGA, n = 58 DDLS) database to segregate samples based on gene expression and compared for recurrence and overall survival (OS). A 15-gene signature consisting of genes with increased expression in DDLS compared to WDLS was generated. This signature segregated WDLS and DDLS samples from patients with mixed component tumours and across multiple recurrences. A further subset of this signature, consisting of five genes (AQP7, ACACB, FZD4, GPD1, LEP), segregated DDLS in a TCGA cohort with a significant difference in OS (p = 0.019) and recurrence-free survival (RFS) (p = 0.061). The five-gene model stratified DDLS into prognostic groups and outperformed clinical factors in existing models in retroperitoneal DDLS.

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

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.