Nitin Ohri1, Fenghai Duan2, Mitchell Machtay2, Jeremy J Gorelick2, Bradley S Snyder2, Abass Alavi2, Barry A Siegel2, Douglas W Johnson2, Jeffrey D Bradley2, Albert DeNittis2, Maria Werner-Wasik2. 1. Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY (NO); Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (FD, JJG, BSS); Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Comprehensive Cancer Center and Case Western Reserve University, Cleveland, OH (MM); Department of Radiology, University of Pennsylvania, Philadelphia, PA (AA); Mallinckrodt Institute of Radiology and the Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO (BAS); Baptist Cancer Institute, Jacksonville, FL (DWJ); Department of Radiation Oncology and the Alvin J Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO (JDB); Lankenau Medical Center and Lankenau Institute for Medical Research, Lower Merion, PA (AD); Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA (MWW). ohri.nitin@gmail.com. 2. Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY (NO); Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (FD, JJG, BSS); Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Comprehensive Cancer Center and Case Western Reserve University, Cleveland, OH (MM); Department of Radiology, University of Pennsylvania, Philadelphia, PA (AA); Mallinckrodt Institute of Radiology and the Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO (BAS); Baptist Cancer Institute, Jacksonville, FL (DWJ); Department of Radiation Oncology and the Alvin J Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO (JDB); Lankenau Medical Center and Lankenau Institute for Medical Research, Lower Merion, PA (AD); Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA (MWW).
Abstract
BACKGROUND: ACRIN 6668/RTOG 0235 evaluated the prognostic value of positron emission tomography with (18)F-fluorodeoxyglucose (FDG-PET) uptake before and after definitive, concurrent, platinum-based chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). In this secondary analysis, we evaluate volumetric pretreatment PET measures as predictors of clinical outcomes. METHODS: Patients with stage III NSCLC underwent FDG-PET prior to treatment. A commercially available gradient-based segmentation tool was used to contour all visible hypermetabolic lesions on each scan. For each patient, the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total glycolytic activity (TGA) for all contoured lesions were recorded. Cox proportional hazards regression models were used to evaluate clinical variables and PET metrics as predictors of overall survival (OS) and locoregional control (LRC). Time-dependent covariables were added to the models when necessary to address nonproportional hazards. All statistical tests were two-sided. RESULTS: Complete data were available for 214 patients in the OS analysis and 189 subjects in the LRC analysis. In multivariable analysis incorporating clinical and imaging data available prior to treatment, MTV was an independent predictor of OS (HR = 1.04 per 10 cm(3) increase, 95% CI = 1.03 to 1.06, P < .001). High MTV was also associated with increased risk of locoregional failure at baseline (HR = 1.16 per 10 cm(3) increase, 95% CI = 1.08 to 1.23, P < .001) and at six months (HR = 1.05 per 10 cm(3) increase, 95% CI = 1.02 to 1.07, P < .001) but not at 12 months or later time points. CONCLUSION: Pretreatment MTV is a predictor of clinical outcomes for NSCLC patients treated with chemoradiotherapy. Quantitative PET measures may serve as stratification factors in clinical trials for this patient population and may help guide novel trial designs.
BACKGROUND: ACRIN 6668/RTOG 0235 evaluated the prognostic value of positron emission tomography with (18)F-fluorodeoxyglucose (FDG-PET) uptake before and after definitive, concurrent, platinum-based chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). In this secondary analysis, we evaluate volumetric pretreatment PET measures as predictors of clinical outcomes. METHODS:Patients with stage III NSCLC underwent FDG-PET prior to treatment. A commercially available gradient-based segmentation tool was used to contour all visible hypermetabolic lesions on each scan. For each patient, the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total glycolytic activity (TGA) for all contoured lesions were recorded. Cox proportional hazards regression models were used to evaluate clinical variables and PET metrics as predictors of overall survival (OS) and locoregional control (LRC). Time-dependent covariables were added to the models when necessary to address nonproportional hazards. All statistical tests were two-sided. RESULTS: Complete data were available for 214 patients in the OS analysis and 189 subjects in the LRC analysis. In multivariable analysis incorporating clinical and imaging data available prior to treatment, MTV was an independent predictor of OS (HR = 1.04 per 10 cm(3) increase, 95% CI = 1.03 to 1.06, P < .001). High MTV was also associated with increased risk of locoregional failure at baseline (HR = 1.16 per 10 cm(3) increase, 95% CI = 1.08 to 1.23, P < .001) and at six months (HR = 1.05 per 10 cm(3) increase, 95% CI = 1.02 to 1.07, P < .001) but not at 12 months or later time points. CONCLUSION: Pretreatment MTV is a predictor of clinical outcomes for NSCLCpatients treated with chemoradiotherapy. Quantitative PET measures may serve as stratification factors in clinical trials for this patient population and may help guide novel trial designs.
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