Article Abstract

Clinical significance of pretreatment tumor growth rate for locally advanced non-small cell lung cancer

Authors: Benedict Osorio, Nikhil Yegya-Raman, Sinae Kim, Charles B. Simone II, Christina Theodorou Ross, Matthew P. Deek, Dakim Gaines, Wei Zou, Liyong Lin, Jyoti Malhotra, Ke Nie, Joseph Aisner, Salma K. Jabbour


Background: Locally advanced non-small cell lung cancer (NSCLC) may exhibit significant tumor growth before the initiation of definitive chemoradiation therapy (CRT). We thus investigated the prognostic value of pretreatment tumor growth rate as measured by specific growth rate (SGR).
Methods: We conducted a retrospective review of 42 patients with locally advanced NSCLC treated with definitive concurrent CRT. For each patient, we contoured the primary gross tumor volume (GTV) on the pretreatment diagnostic chest computed tomography (CT) scan and the radiation therapy (RT) planning CT scan. We then calculated SGR based on the primary GTV from each scan and the time interval between scans. We used log-rank tests and univariate Cox regression models to quantify differences in progression-free survival (PFS), overall survival (OS) and recurrence based on SGR.
Results: We divided patients into two groups for analysis: those with an SGR greater than or equal to the upper tercile value of 0.94%/day (high SGR) and those with SGR less than 0.94%/day (low SGR). Patients with high SGRs versus low SGRs experienced inferior PFS (median, 5.6 vs. 13.6 months, P=0.016), without a significant difference in OS. The inferior PFS in the high SGR group persisted on multivariate analysis [adjusted hazard ratio (HR) 2.37, 95% confidence interval (CI): 1.07–5.25, P=0.034]. The risk of distant recurrence was higher in the high SGR group (HR 2.62, 95% CI: 1.08–6.38, P=0.033), but there was no difference in the risk of locoregional recurrence between groups.
Conclusions: Pretreatment SGR was associated with inferior PFS and distant control among patients with locally advanced NSCLC treated with concurrent CRT. Further studies in larger populations may aid in elucidating optimal SGR cut-off points for risk stratification.