OBJECTIVE Previous studies have demonstrated that among patients with adult spinal deformity (ASD), sagittal plane malalignment is poorly tolerated and correlates with suboptimal patient-reported health-related quality of life (HRQOL). These studies included a broad range of radiographic abnormalities and various types of ASD. However, the clinical and radiographic characteristics of de novo degenerative lumbar scoliosis (DNDLS), a subtype of ASD, may influence previously reported correlation strengths. The aim of this study was to correlate sagittal radiographic parameters with pretreatment HRQOL in patients with symptomatic DNDLS. METHODS In this multicenter retrospective study of prospectively collected data, 74 patients with symptomatic DNDLS were enrolled based on anteroposterior and lateral 36-inch standing radiographs. Measurements included Cobb angle, coronal imbalance, pelvic incidence (PI), pelvic tilt (PT), lumbar lordosis (LL), sagittal vertical axis (SVA), thoracic kyphosis, pelvic incidence minus lumbar lordosis (PI-LL), T1-pelvic angle, and global tilt. HRQOL questionnaires included the Oswestry Disability Index (ODI), Scoliosis Research Society (SRS-22r), 36-item Short-Form Health Survey, and numeric rating scale (NRS) for back and leg pain. Correlations between radiographic parameters and HRQOL were assessed. Finally, HRQOL and increasing severity of sagittal modifiers (SVA, PI-LL, and PT) were evaluated. RESULTS Weak correlations were found between SVA and ODI (r = 0.296, p < 0.05) and PT with NRS back pain and the SRS pain domain (r = -0.260, p < 0.05, and r = 0.282, p < 0.05, respectively). Other sagittal radiographic parameters did not show any significant correlation with HRQOL. No significant differences in HRQOL were found concerning the increasing severity of PT, PI-LL, and SVA. CONCLUSIONS While DNDLS is a severe disabling condition, no noteworthy association between clinical and sagittal radiographic parameters was found through this study, demonstrating that sagittal radiographic parameters should not be considered the unique predictor of pretreatment suboptimal health status in this specific group of patients. Future studies addressing classification and treatment algorithms will have to take into account the existing subgroups of ASD.