# Head and Neck Sarcoma Assessor (HaNSA) for treatment decisions using real-world data

## TL;DR

The paper introduces HaNSA, a prognostic calculator for head and neck sarcomas in Asians, using real-world data to predict survival outcomes.

## Contribution

The study presents the largest Asian head and neck sarcoma cohort and a novel parametric model for predicting overall survival.

## Key findings

- Radiotherapy-associated sarcomas are linked to poorer survival outcomes.
- Microscopically negative surgical resection margins are significantly associated with improved survival.
- A parametric model predicts OS based on patient and treatment factors using real-world data.

## Abstract

Head and neck sarcomas (HNS) are rare and diverse cancers with distinct biology, unique treatment constraints and poor survival outcomes. Furthermore, HNS are understudied in Asians, and prospective clinical trials are untenable. To better understand HNS and improve treatment, real-world studies in Asians with accurate histological typing are thus needed.

A retrospective cohort study of patients with histologically confirmed sarcoma diagnosis in the head and neck region between 1985 and 2023 was carried out at the National Cancer Centre Singapore. Multivariate Cox regression was used to analyse risk factors for overall survival (OS), and parametric time-to-event modelling was used to develop a prognostic calculator.

A total of 275 patients were analysed. The 5-year OS was 43.2% (95% confidence interval 36.2% to 51.6%). Among demographic risk factors, a high incidence of radiotherapy-associated sarcomas in the population at 11.3% placed the population at higher risk for aggressive disease (decreased treatment response and poorer prognosis). With interventions, microscopically negative (R0) surgical resection margins were significantly associated with improved OS. Parametric time-to-event simulations suggested microscopically positive (R1) resections to also be beneficial for OS in locally advanced tumours and nonaggressive sarcoma histology, and improved greatly alongside high-dose radiotherapy.

We present the largest Asian HNS cohort, with diverse subtypes and disease extent. Our analysis highlights poor outcomes from a higher incidence of radiotherapy-associated disease, showing the challenging landscape of HNS in Asia. Through our prognostic calculator, we demonstrate how meaningfully curated real-world data in a rare disease entity can be used for the prediction of OS in individual patients with specific treatment approaches.

•Age, disease extent and radiotherapy-induced sarcomas predict OS.•Only surgical resection margins were significantly associated with improved OS.•Radiotherapy dose and chemotherapy use were not associated with OS.•Our parametric model predicts OS based on patient, disease and key treatment factors.•This prediction tool was developed using the largest published Asian cohort to date.

Age, disease extent and radiotherapy-induced sarcomas predict OS.

Only surgical resection margins were significantly associated with improved OS.

Radiotherapy dose and chemotherapy use were not associated with OS.

Our parametric model predicts OS based on patient, disease and key treatment factors.

This prediction tool was developed using the largest published Asian cohort to date.