Clinical Nomogram Using Novel Computed Tomography–Based Radiomics Predicts Survival in Patients With Non–Small-Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy

Author:

Somasundaram Eashwar1ORCID,Wadhwa Raoul R.2ORCID,Litzler Adam3ORCID,Barker-Clarke Rowan4,Qi Peng5ORCID,Videtic Gregory5ORCID,Stephans Kevin5,Pennell Nathan A.67ORCID,Raymond Daniel8ORCID,Yang Kailin5ORCID,Kattan Michael W.79ORCID,Scott Jacob G.45710ORCID

Affiliation:

1. Case Western Reserve University School of Medicine, Cleveland, OH

2. Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH

3. Department of Applied Mathematics, University of Colorado Boulder, Boulder, CO

4. Department of Translational Hematology and Oncology Research, Lerner Research Institute, Cleveland Clinic, Cleveland, OH

5. Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH

6. Department of Hematology Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH

7. Case Comprehensive Cancer Center, Cleveland, OH

8. Department of Thoracic and Cardiovascular Surgery, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH

9. Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH

10. Department of Systems Biology and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, OH

Abstract

PURPOSE Improved survival prediction and risk stratification in non–small-cell lung cancer (NSCLC) would lead to better prognosis counseling, adjuvant therapy selection, and clinical trial design. We propose the persistent homology (PHOM) score, the radiomic quantification of solid tumor topology, as a solution. MATERIALS AND METHODS Patients diagnosed with stage I or II NSCLC primarily treated with stereotactic body radiation therapy (SBRT) were selected (N = 554). The PHOM score was calculated for each patient's pretreatment computed tomography scan (October 2008-November 2019). PHOM score, age, sex, stage, Karnofsky Performance Status, Charlson Comorbidity Index, and post-SBRT chemotherapy were predictors in the Cox proportional hazards models for OS and cancer-specific survival. Patients were split into high– and low–PHOM score groups and compared using Kaplan-Meier curves for overall survival (OS) and cumulative incidence curves for cause-specific death. Finally, we generated a validated nomogram to predict OS, which is publicly available at Eashwarsoma.Shinyapps. RESULTS PHOM score was a significant predictor for OS (hazard ratio [HR], 1.17; 95% CI, 1.07 to 1.28) and was the only significant predictor for cancer-specific survival (1.31; 95% CI, 1.11 to 1.56) in the multivariable Cox model. The median survival for the high-PHOM group was 29.2 months (95% CI, 23.6 to 34.3), which was significantly worse compared with the low-PHOM group (45.4 months; 95% CI, 40.1 to 51.8; P < .001). The high-PHOM group had a significantly greater chance of cancer-specific death at post-treatment month 65 (0.244; 95% CI, 0.192 to 0.296) compared with the low-PHOM group (0.171; 95% CI, 0.123 to 0.218; P = .029). CONCLUSION The PHOM score is associated with cancer-specific survival and predictive of OS. Our developed nomogram can be used to inform clinical prognosis and assist in making post-SBRT treatment considerations.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

General Medicine

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