Introduction: There exist a wide range of clinical treatments for NSCLC, each with a corresponding range of outcomes. Risk calculators predicting overall survival would aid in treatment planning and prognosis counseling. Traditional risk calculators use clinical and histopathologic data to predict survival. We propose incorporating the PHOM score, the radiomic quantification of solid tumor topology, to predict overall survival. Methods: Patients diagnosed with stage I or II NSCLC and status post SBRT were selected (n = 554). The PHOM score was calculated on each patient's pre-treatment CT scan. PHOM score, age, sex, stage, KPS, CCI, and post-SBRT chemotherapy were predictors in the generated Cox proportional hazards models for overall and cancer-specific survival. Patients were split into high and low PHOM score groups by median value and compared using KM curves for overall survival and cumulative incidence curves for cause specific death. Optimized tertile PHOM risk groups were calculated and similarly compared for overall survival and cause-specific death. Internal validation was conducted with bootstrap resampling and calibration curves were checked. Finally, a nomogram to predict overall survival was generated and is publicly available at https://eashwarsoma.shinyapps.io/LungCancerTDATest/. Results: PHOM score was a significant predictor for overall survival (HR: 1.17, 95% CI: 1.07-1.28) and was the only significant predictor for cancer-specific survival (1.31, 95% CI: 1.11-1.56) in the multivariable Cox model. The median survival for the above median PHOM group was 888 days (95% CI: 719-1043), which was significantly worse compared to the below median PHOM group (1,382 days, 95% CI: 1220-1576, p < 0.001). The above median PHOM group had a significantly greater chance of cancer-specific death at post treatment day 2,000 (0.244, 95% CI: 0.192-0.296) compared to lower scorers (0.171, 95% CI: 0.123-0.218, p = 0.029). Nomograms for 1, 2, 5, and 8-year overall survival were successfully calibrated using the Cox model. Conclusions: The PHOM score is associated with cancer-specific survival and predictive of overall survival. Our developed nomogram can be used to inform clinical prognosis and assist in making post-SBRT treatment considerations.

The authors have declared no competing interest.

Jacob Scott was supported by NIH grant R37 CA244613. Eashwar Somasundaram and Raoul Wadhwa were supported by the Case Comprehensive Cancer Center Summer Training Grant for medical students.

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