Is the Importance of Heart Dose Overstated in the Treatment of Non-Small Cell Lung Cancer? A Systematic Review of the Literature

Purpose Some recent studies have suggested a relationship between cardiac dose and mortality in non-small cell lung cancer (NSCLC), but others have reported conflicting data. The goal of this study was to conduct a systematic review and meta-analysis to provide an evidence-based estimate of the relationship between cardiac dose and mortality in these patients. Methods and Materials A systematic review of MEDLINE (PubMed) and Embase databases (inception to January 2018) was performed according to PRISMA guidelines. Studies that evaluated cardiac dosimetric factors in patients with NSCLC and included outcomes of cardiac events, cardiac mortality, and/or overall survival were identified. Results From 5614 patients across 22 studies, a total of 214 cardiac dosimetric parameters (94 unique) were assessed as possible predictors of cardiac toxicity or death. Assessed predictors included general (eg, mean heart dose [MHD]), threshold-based (eg, heart V5), and anatomic-based (eg, atria, ventricles) dosimetric factors. The most commonly analyzed parameters were MHD, heart V5, and V30. Most studies did not make corrections for multiplicity of testing. For overall survival, V5 was found to be significant on multivariable analysis (MVA) in 1 of 11 studies and V30 in 2 of 12 studies; MHD was not significant in any of 8 studies. For cardiac events, V5 was found to be significant on multivariable analysis in 1 of 2 studies, V30 in 1 of 3 studies, and MHD in 2 of 4 studies. A meta-analysis of the data could not be performed because most negative studies did not report effect estimates. Conclusions Consistent heart dose-volume parameters associated with overall survival of patients with NSCLC were not identified. Multiplicity of testing is a major issue and likely inflates the overall risk of type I errors in the literature. Future studies should specify predictors a priori, correct for multiplicity of testing, and report effect estimates for nonsignificant variables.