Is the Memorial Sloan Kettering Cancer Centre (MSKCC) sarcoma nomogram useful in an Asian population?

Opportunities and Challenges in Soft Tissue Sarcoma Risk Stratification in the Era of Personalised Medicine

OPINION STATEMENT

Soft tissue sarcomas (STS) are a rare and heterogeneous group of cancers. Treatment options have changed little in the past thirty years, and the role of neoadjuvant chemotherapy is controversial. Accurate risk stratification is crucial in STS in order to facilitate clinical discussions around peri-operative treatment. Current risk stratification tools used in clinic, such as Sarculator, use clinicopathological characteristics and may be specific to anatomical site or to histology. More recently, risk stratification tools have been developed using molecular or immunological data. Combining Sarculator with other risk stratification tools may identify novel patient groups with differential clinical outcomes. There are several considerations when translating risk stratification tools into widespread clinical use, including establishing clinical utility, health economic value, being applicable to existing clinical pathways, having strong real-world performance, and being supported by investment into infrastructure. Future work may include incorporation of novel modalities and data integration techniques.

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.

Nomograms predicting local and distant recurrence and disease-specific mortality for R0/R1 soft tissue sarcomas of the extremities

Background

Prognostic models for patients with soft tissue sarcoma (STS) of the extremities have been developed from large multi-institutional datasets with mixed results. We aimed to develop predictive nomograms for sarcoma-specific survival (SSS) and, for the first time, long-term local recurrence (LR) and distant recurrence (DR) in patients with STS of the extremities treated at our institution.

Patients and methods

Data from patients treated at Humanitas Cancer Center from 1997 to 2015 were analyzed. Variable selection was based on the clinical knowledge and multivariable regression splines algorithm. Perioperative treatments were always included in the model. Prognostic models were developed using Cox proportional hazards model, and model estimates were plotted in nomograms predicting SSS at 5 and 10 years and LR and DR at 2, 5, and 10 years. Model performance was estimated internally via bootstrapping, in terms of optimism-corrected discrimination (Harrell C-index) and calibration (calibration plots).

Results

Data on 517 patients were analyzed. At 5 and 10 years, SSS was 68.1% [95% confidence interval (CI), 63.8-72.1] and 55.6% (50.5-60.3), respectively. LR was 79.1% (95% CI, 75.3-82.4), 71.1% (95% CI, 66.7-75.1), and 66.0% (95% CI, 60.7-70.7) at 2, 5, and 10 years, respectively, whereas DR was 65.9% (95% CI, 61.6-69.9), 57.5% (95% CI, 53.0-61.8), and 52.1% (95% CI, 47.1-56.8) at 2, 5, and 10 years, respectively. SSS nomogram included age, gender, margins, tumor size, grading, and histotype. LR and DR nomograms incorporated mostly the same variables, except for age for DR; LR nomogram did not include gender but included anatomic site. The optimism-corrected C-indexes were 0.73 and 0.72 for SSS at 5 and 10 years, respectively; 0.65, 0.64, and 0.64 for LR at 2, 5, and 10 years, respectively; and 0.68 for DR at 2, 5, and 10 years. Predicted probabilities were close to the observed ones for all outcomes.

Conclusions

We developed and validated three nomograms for STS of the extremities predicting the probability of SSS at 5 and 10 years and LR and DR at 2, 5, and 10 years. By accounting for the perioperative treatment, these models allow prediction for future patients who had no perioperative treatment, thus being useful in the clinical decision-making process.

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

AIM

To study the applicability of 2 common nomograms in retroperitoneal sarcoma patients treated in an Asian tertiary hospital, and to study relapse patterns.

METHODS

Patients from 1st January 2000 to 31st December 2017 were retrospectively analysed. R2 resection from an external institution were ineligible. Harrel's C concordance index and calibration plots were used to assess nomograms' accuracy.

RESULTS

109 patients were eligible, with a median age of 56, median tumour size of 16 cm and median follow up of 44.1 months. Most common subtypes were DDLPS (46.8%), LMS (19.3%) and WDLPS (13.8%). Overall, 81.1% had passed away from sarcoma. Recurrence patterns differed with subtypes; 6.7% of WDLPS and 66.7% of LMS had distant relapses. WDLPS patients had a median sarcoma specific survival of 139 months (122-NA), while the rest had a median SSS of 72.3 months (59.7-NA). The 5-years and 7-year OS were 63.0% (95% CI: 53.6%-74.0%) and 51.6% (41.1%-64.8%) respectively. The 5-years and 7-year DFS were 22.4% (15.5%-32.3%) and 17.5% (11%-27.8%) respectively. The 4-years, 8-years and 12-year SSS were 71.3% (62.7%-81.0%), 51.8% (40.8%-65.8%) and 32.2% (19.7%-52.6%) respectively. The concordance indices for 7-year DFS and OS (Sarculator) were 0.63 and 0.73. The concordance indices for 4-, 8- and 12-year SSS (MSKCC) were 0.64, 0.72 and 0.72.

CONCLUSION

Both nomograms were effective in our cohort. Both nomograms can be further improved by specifying the type of relapse and including a longer-term endpoint for the Sarculator.

Soft tissue sarcoma nomograms and their incorporation into practice

The accurate prediction of prognosis in patients with soft tissue sarcoma (STS) is a challenging issue. Extreme variability in the clinical and pathological characteristics of this family of tumors hinders the simple stratification of patients into meaningful prognostic cohorts. Precision medicine tools for the prediction of prognosis, such as nomograms, enable personalized computation of outcome based on clinical and pathological characteristics of both patient and tumor. The eighth edition of the American Joint Committee on Cancer staging manual moved from a "population-based" to a "personalized" approach endorsing high-quality nomograms to improve clinician prediction ability in definite patient subgroups. The first nomogram for STS was published in 2002, and this was followed by several prognostic predictors offered to clinicians. Focusing on a specific STS subgroup or site, nomograms can take into consideration highly specific factors relevant only in that particular scenario, thereby maximizing prognostic ability. The objective of this review was to critically evaluate available nomograms for patients with STS to provide clinicians and researchers with a choice of the most optimal tool for each specific patient. Cancer 2017;123:2802-20. © 2017 American Cancer Society.