Haval Balata1, Philip Foden2, Tim Edwards3, Anshuman Chaturvedi4, Mohamed Elshafi3, Alexander Tempowski3, Benjamin Teng3, Paul Whittemore3, Kevin G Blyth5, Andrew Kidd6, Deborah Ellames7, Louise Ann Flint7, Jonathan Robson7, Elaine Teh8, Robin Jones8, Timothy Batchelor8, Philip Crosbie9, Richard Booton9, Matthew Evison9. 1. Manchester Thoracic Oncology Centre, North West Lung Centre, Manchester University NHS Foundation Trust, Wythenshawe Hospital, Southmoor Road, Manchester, UK; Institute of Infection, Immunity and Respiratory Medicine, University of Manchester, Oxford Road, Manchester, UK. Electronic address: haval.balata@mft.nhs.uk. 2. Department of Medical Statistics, Manchester University NHS Foundation Trust, Wythenshawe Hospital, Southmoor Road, Manchester, UK. 3. Manchester Thoracic Oncology Centre, North West Lung Centre, Manchester University NHS Foundation Trust, Wythenshawe Hospital, Southmoor Road, Manchester, UK. 4. Department of Histopathology, Manchester University NHS Foundation Trust, Wythenshawe Hospital, Southmoor Road, Manchester, UK. 5. Glasgow Pleural Disease Unit, Queen Elizabeth Hospital, Glasgow, UK; Institute of Infection, Immunity of Inflammation, University of Glasgow, UK. 6. Glasgow Pleural Disease Unit, Queen Elizabeth Hospital, Glasgow, UK. 7. Respiratory Department, St James's University Hospital, Leeds, UK. 8. Department of thoracic surgery, University Hospitals Bristol NHS Foundation Trust, Bristol, UK. 9. Manchester Thoracic Oncology Centre, North West Lung Centre, Manchester University NHS Foundation Trust, Wythenshawe Hospital, Southmoor Road, Manchester, UK; Institute of Infection, Immunity and Respiratory Medicine, University of Manchester, Oxford Road, Manchester, UK.
Abstract
INTRODUCTION: The aim of this study was to develop and validate a simple prognostic scoring system using readily available clinical and pathological variables that could stratify patients according to the risk of death following lung cancer resection. We hypothesized that by using additional pathological variables not accounted for by pathological stage alone coupled with markers of overall fitness a new prognostic tool could be developed. METHODS: Multivariable logistic regression analysis of pathological and other clinical variables from patients undergoing surgical resection of non-small cell lung cancer (NSCLC) were used to determine factors independently associated with 2-year overall survival and so derive the scoring system. The model was then validated in an external multi-centre dataset. RESULTS: Using multivariable logistic regression on a large dataset (n = 1,421) the 'LNC-PATH' (Lymphovascular invasion, N-stage, adjuvant Chemotherapy, Performance status, Age, T-stage, Histology) prognostic score was devised and then validated using an external dataset (n = 402). This can be used to risk stratify patients into low, moderate and high-risk groups with a statistically significant difference between the three groups in their survival distributions. 83.8% of patients in the low-risk group survived two years after surgery compared to 55.6% in the moderate-risk group and 26.2% in the high-risk group. The score was shown to perform moderately well with an Area Under the Receiver Operating Characteristic curve (AUROC) value of 0.76 (95% CI: 0.73-0.79) and 0.70 (95% CI: 0.64-0.76) in the derivation and validation cohorts respectively. DISCUSSION: The LNC-PATH score predicts 2-year overall survival after surgery for NSCLC. This may allow the development of risk stratified follow-up protocols in survivorship clinics which could be the subject of future prospective studies.
INTRODUCTION: The aim of this study was to develop and validate a simple prognostic scoring system using readily available clinical and pathological variables that could stratify patients according to the risk of death following lung cancer resection. We hypothesized that by using additional pathological variables not accounted for by pathological stage alone coupled with markers of overall fitness a new prognostic tool could be developed. METHODS: Multivariable logistic regression analysis of pathological and other clinical variables from patients undergoing surgical resection of non-small cell lung cancer (NSCLC) were used to determine factors independently associated with 2-year overall survival and so derive the scoring system. The model was then validated in an external multi-centre dataset. RESULTS: Using multivariable logistic regression on a large dataset (n = 1,421) the 'LNC-PATH' (Lymphovascular invasion, N-stage, adjuvant Chemotherapy, Performance status, Age, T-stage, Histology) prognostic score was devised and then validated using an external dataset (n = 402). This can be used to risk stratify patients into low, moderate and high-risk groups with a statistically significant difference between the three groups in their survival distributions. 83.8% of patients in the low-risk group survived two years after surgery compared to 55.6% in the moderate-risk group and 26.2% in the high-risk group. The score was shown to perform moderately well with an Area Under the Receiver Operating Characteristic curve (AUROC) value of 0.76 (95% CI: 0.73-0.79) and 0.70 (95% CI: 0.64-0.76) in the derivation and validation cohorts respectively. DISCUSSION: The LNC-PATH score predicts 2-year overall survival after surgery for NSCLC. This may allow the development of risk stratified follow-up protocols in survivorship clinics which could be the subject of future prospective studies.