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Predicting 2-year survival in stage I-III non-small cell lung cancer: the development and validation of a scoring system from an Australian cohort.

Authors :
Lee, Natalie Si-Yi
Shafiq, Jesmin
Field, Matthew
Fiddler, Caroline
Varadarajan, Suganthy
Gandhidasan, Senthilkumar
Hau, Eric
Vinod, Shalini Kavita
Source :
Radiation Oncology. 4/13/2022, Vol. 17 Issue 1, p1-12. 12p.
Publication Year :
2022

Abstract

<bold>Background: </bold>There are limited data on survival prediction models in contemporary inoperable non-small cell lung cancer (NSCLC) patients. The objective of this study was to develop and validate a survival prediction model in a cohort of inoperable stage I-III NSCLC patients treated with radiotherapy.<bold>Methods: </bold>Data from inoperable stage I-III NSCLC patients diagnosed from 1/1/2016 to 31/12/2017 were collected from three radiation oncology clinics. Patient, tumour and treatment-related variables were selected for model inclusion using univariate and multivariate analysis. Cox proportional hazards regression was used to develop a 2-year overall survival prediction model, the South West Sydney Model (SWSM) in one clinic (nā€‰=ā€‰117) and validated in the other clinics (nā€‰=ā€‰144). Model performance, assessed internally and on one independent dataset, was expressed as Harrell's concordance index (c-index).<bold>Results: </bold>The SWSM contained five variables: Eastern Cooperative Oncology Group performance status, diffusing capacity of the lung for carbon monoxide, histological diagnosis, tumour lobe and equivalent dose in 2 Gy fractions. The SWSM yielded a c-index of 0.70 on internal validation and 0.72 on external validation. Survival probability could be stratified into three groups using a risk score derived from the model.<bold>Conclusions: </bold>A 2-year survival model with good discrimination was developed. The model included tumour lobe as a novel variable and has the potential to guide treatment decisions. Further validation is needed in a larger patient cohort. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1748717X
Volume :
17
Issue :
1
Database :
Academic Search Index
Journal :
Radiation Oncology
Publication Type :
Academic Journal
Accession number :
156375419
Full Text :
https://doi.org/10.1186/s13014-022-02050-1