Comorbidity in limited disease small-cell lung cancer: Age-adjusted Charlson comorbidity index and its association with overall survival following chemoradiotherapy

Combined, platinum-based thoracic chemoradiotherapy (TCR) is the current state-of-the-art treatment for patients with limited disease (LD) small-cell lung cancer (SCLC). There is only limited data available regarding the effect of comorbidities on survival following TRC. The purpose of this study is to assess the age-adjusted Charlson comorbidity index (ACCI) as a predictor of overall survival in LD-SCLC patients undergoing TCR.We retrospectively analyzed 367 SCLC patients diagnosed with LD-SCLC who received TCR between 2003 and 2017. We evaluated the ACCI (n = 348) as a predictor of overall survival (OS). In this cohort, 322 patients (88%) received platinum-based TCR (either cisplatin or carboplatin), and 37 (10%) patients received vincristine based TCR. Median radiation dose was 60 Gy (range 24-66 Gy). Additionally, 83% of patients (n = 303) received prophylactic cranial irradiation (PCI, 30 Gy in 2 Gy fractions). Kaplan-Meier survival analysis was performed for OS. For comparison of survival curves, Log-rank (Mantel-Cox) test was used. Univariate and multivariate Cox proportional-hazards ratios (HRs) were used to assess the influence of cofactors on OS.Patients with an ACCI > 6 had a significantly shorter OS compared with patients with an ACCI ≤ 6 (median 11 vs. 20 months; p = 0.005). Univariate analysis for OS revealed a statistically significant effect for ACCI > 6 (HR 1.7; 95% CI 1.2-2.4; p = 0.003), PCI (HR 0.5; 95% CI 0.3-0.7; p < 0.001), and Karnofsky performance status ≤ 70% (KPS) (HR 1.4; 95% CI 1.1-1.90; p = 0.015). In multivariate analysis, OS was significantly associated with PCI (HR 0.6; 95% CI 0.4-0.9; p = 0.022) and ACCI > 6 (HR 1.5; 95% CI 1.0-2.1; p = 0.049).Comorbidity is significantly associated with survival in patients with LD-SCLC undergoing TCR. The ACCI may be a valuable tool to identify patients with a shorter survival and thus might be used for risk stratification and oncological decision making.