Predicting the risk of disease recurrence and death following curative-intent radiotherapy for non-small cell lung cancer: the development and validation of two scoring systems from a large multicentre UK cohort

Abstract

Aims: There is a paucity of evidence on which to produce recommendations on neither the clinical nor the imaging follow-up of lung cancer patients after curative-intent radiotherapy. In the 2019 National Institute for Health and Care Excellence lung cancer guidelines, further research into risk-stratification models to inform follow-up protocols was recommended. Materials and methods: A retrospective study of consecutive patients undergoing curative-intent radiotherapy for non-small cell lung cancer from 1 October 2014 to 1 October 2016 across nine UK trusts was carried out. Twenty-two demographic, clinical and treatment-related variables were collected and multivariable logistic regression was used to develop and validate two risk-stratification models to determine the risk of disease recurrence and death. Results: In total, 898 patients were included in the study. The mean age was 72 years, 63% (562/898) had a good performance status (0-1) and 43% (388/898), 15% (134/898) and 42% (376/898) were clinical stage I, II and III, respectively. Thirty-six per cent (322/898) suffered disease recurrence and 41% (369/898) died in the first 2 years after radiotherapy. The ASSENT score (age, performance status, smoking status, staging endobronchial ultrasound, N-stage, T-stage) was developed, which stratifies the risk for disease recurrence within 2 years, with an area under the receiver operating characteristic curve (AUROC) for the total score of 0.712 (0.671-0.753) and 0.72 (0.65-0.789) in the derivation and validation sets, respectively. The STEPS score (sex, performance status, staging endobronchial ultrasound, T-stage, N-stage) was developed, which stratifies the risk of death within 2 years, with an AUROC for the total score of 0.625 (0.581-0.669) and 0.607 (0.53-0.684) in the derivation and validation sets, respectively. Conclusions: These validated risk-stratification models could be used to inform follow-up protocols after curative-intent radiotherapy for lung cancer. The modest performance highlights the need for more advanced risk prediction tools.