The Clinical Outcomes, Prognostic Factors and Nomogram Models for Primary Lung Cancer Patients Treated With Stereotactic Body Radiation Therapy

Abstract

Purpose: Stereotactic body radiation therapy (SBRT) is a standard treatment for early primary lung cancer patients. However, there are few simple models for predicting the clinical outcomes of these patients. Our study analyzed the clinical outcomes, identified the prognostic factors, and developed prediction nomogram models for these patients.

Materials and methods: We retrospectively analyzed 114 patients with primary lung cancer treated with SBRT from 2012 to 2020 at our institutions and assessed patient's clinical outcomes and levels of toxicity. Kaplan-Meier analysis with a log-rank test was used to generate the survival curve. The cut-off values of continuous factors were calculated with the X-tile tool. Potential independent prognostic factors for clinical outcomes were explored using cox regression analysis. Nomograms for clinical outcomes prediction were established with identified factors and assessed by calibration curves.

Results: The median overall survival (OS) was 40.6 months, with 3-year OS, local recurrence free survival (LRFS), distant disease-free survival (DDFS) and progression free survival (PFS) of 56.3%, 61.3%, 72.9% and 35.8%, respectively, with grade 3 or higher toxicity rate of 7%. The cox regression analysis revealed that the clinical stage, immobilization device, and the prescription dose covering 95% of the target area (D95) were independent prognostic factors associated with OS. Moreover, the clinical stage, and immobilization device were independent prognostic factors of LRFS and PFS. The smoking status, hemoglobin (Hb) and immobilization device were significant prognostic factors for DDFS. The nomograms and calibration curves incorporating the above factors indicated good predictive accuracy.

Conclusions: SBRT is effective and safe for primary lung cancer. The prognostic factors associated with OS, LRFS, DDFS and PFS are proposed, and the nomograms we proposed are suitable for clinical outcomes prediction.

Keywords: clinical outcomes; nomogram model; primary lung cancer; prognostic factors; stereotactic body radiation therapy.

Figure 1

Kaplan-Meier curves showing OS (A), LRFS (B), DDFS (C) and PFS (D) over time for the entire cohort. OS, overall survival; LRFS, local recurrence free survival; DDFS, distant disease-free survival; PFS, progression free survival.

Figure 2

Pearson’s correlation coefficients between pairs of dosimetric factors. D95, the prescription dose covers 95% of the target area; Dmax, the maximum dose in the whole plan; PTVmin, the minimum dose of PTV; PTVmean, mean dose of PTV; PTVmax, the maximum dose of PTV; GTVmin, the minimum dose of GTV; GTVmean, mean dose of GTV; GTVmax, the maximum dose of GTV.

Figure 3

The optimal cut-off values of NLR (A), PLR (B), equivalent diameter (C), GTV (D), PTV (E), PTVmin/PTVmax (F), GTVmin/GTVmax (G) in prognosis of OS, LRFS, DDFS and PFS by X-tile software. NLR, Neutrophil-to-Lymphocyte ratio; PLR, Platelet-to-Lymphocyte ratio; GTV, gross tumor volume; PTV, planning target volume; PTVmin/PTVmax, dose inhomogeneity of PTV; GTVmin/GTVmax, dose inhomogeneity of GTV; OS, overall survival; LRFS, local recurrence free survival; DDFS, distant disease-free survival; PFS, progression free survival.

Figure 4

The forest plot of the multivariate cox regression analyses of risk factors for OS (A), LRFS (B), DDFS (C) and PFS (D). *p-value < 0.05, ***p-value < 0.001. PTV, planning target volume; Hb, hemoglobin; NLR, Neutrophil-to-Lymphocyte ratio; PLR, Platelet-to-Lymphocyte ratio; 4DCT, four-dimensional computed tomography; D, the prescription dose covers 95% of the target area; OS, overall survival; LRFS, local recurrence free survival; DDFS, distant disease-free survival; PFS, progression free survival; HR, hazard ratio; CI, confidence interval.

Figure 5

Kaplan-Meier curves of OS, LRFS, DDFS and PFS stratified by independent risk factors. OS curves stratified by the clinical stage, immobilization device and D95 (A). LRFS curves (B) and PFS curves (D) stratified by the clinical stage and immobilization device. DDFS curves stratified by the smoking status, immobilization device and anemia or not (C). D95, the prescription dose covers 95% of the target area; OS, overall survival; LRFS, local recurrence free survival; DDFS, distant disease-free survival; PFS, progression free survival.

Figure 6

The nomogram containing identified factors for the 1-, 2-, and 3-year OS, LRFS, DDFS and PFS prediction of lung cancer patients. (A) Nomogram for OS, (B) nomogram for LRFS, (C) nomogram for DDFS and (D) nomogram for PFS. D95, the prescription dose covers 95% of the target area; OS, overall survival; LRFS, local recurrence free survival; DDFS, distant disease-free survival; PFS, progression free survival.

Figure 7

Calibration curves of each nomogram model. The calibration curves of the 1-, 2-, and 3-year OS prediction nomogram (A), LRFS prediction nomogram (B), DDFS prediction nomogram (C) and PFS prediction nomogram (D). OS, overall survival; LRFS, local recurrence free survival; DDFS, distant disease-free survival; PFS, progression free survival.