Prognostic factors for overall survival of stage III non-small cell lung cancer patients on computed tomography: a systematic review and meta-analysis

Lung Cancer
26/07/2020

Radiother Oncol. 2020 Jul 22:S0167-8140(20)30674-5. doi: 10.1016/j.radonc.2020.07.030. Online ahead of print.

ABSTRACT

INTRODUCTION: Prognosis prediction is central in treatment decision making and quality of life for non-small cell lung cancer (NSCLC) patients. However, conventional computed tomography (CT) related prognostic factors may not apply to the challenging stage III NSCLC group. The aim of this systematic review was therefore to identify and evaluate CT-related prognostic factors for overall survival (OS) of stage III NSCLC.

METHODS: The Medline, Embase, and Cochrane electronic databases were searched.After study selection, risk of bias was estimated for the included studies. Meta-analysis of univariate results was performed when sufficient data were available.

RESULTS: 1,595 of the 11,996 retrieved records were selected for full text review, leading to inclusion of 65 studies that reported data of 144,513 stage III NSCLC patients andcompromising 26 unique CT-related prognostic factors. Relevance and validity varied substantially, few studies had low relevance and validity. Only four studies evaluated the added value of new prognostic factors compared with recognized clinical factors. Included studies suggested gross tumor volume (meta-analysis: HR=1.22, 95%CI: 1.05-1.42), tumor diameter, nodal volume, and pleural effusion, are prognostic in patients treated with chemoradiation. Clinical T-stage and location (right/left) were likely not prognostic within stage III NSCLC. Inconclusive are several radiomic features, tumor volume, atelectasis, location (pulmonary lobes, central/peripheral), interstitial lung abnormalities, great vessel invasion, pit-fall sign, and cavitation.

CONCLUSIONS: Tumor-size and nodal size-related factors are prognostic for OS in stage III NSCLC. Future studies should carefully report study characteristics and contrast factors with guideline recognized factors to improve evidence evaluation and validation.