title: Prediction of residual metabolic activity after treatment in NSCLC patients.
abstract: OBJECTIVE
  Metabolic response assessment is often used as a surrogate of local failure and survival. Early identification of patients with residual metabolic activity is essential as this enables selection of patients who could potentially benefit from additional therapy. We report on the development of a pre-treatment prediction model for metabolic response using patient, tumor and treatment factors.
  
  
  METHODS
  One hundred and one patients with inoperable NSCLC (stage I-IV), treated with 3D conformal radical (chemo)-radiotherapy were retrospectively included in this study. All patients received a pre and post-radiotherapy fluorodeoxyglucose positron emission tomography-computed tomography FDG-PET-CT scan. The electronic medical record system and the medical patient charts were reviewed to obtain demographic, clinical, tumor and treatment data. Primary outcome measure was examined using a metabolic response assessment on a post-radiotherapy FDG-PET-CT scan. Radiotherapy was delivered in fractions of 1.8 Gy, twice a day, with a median prescribed dose of 60 Gy.
  
  
  RESULTS
  Overall survival was worse in patients with residual metabolic active areas compared with the patients with a complete metabolic response (p=0.0001). In univariate analysis, three variables were significantly associated with residual disease: larger primary gross tumor volume (GTV(primary), p=0.002), higher pre-treatment maximum standardized uptake value (SUV(max), p=0.0005) in the primary tumor and shorter overall treatment time (OTT, p=0.046). A multivariate model including GTV(primary), SUV(max), equivalent radiation dose at 2 Gy corrected for time (EQD(2, T)) and OTT yielded an area under the curve assessed by the leave-one-out cross validation of 0.71 (95% CI, 0.65-0.76).
  
  
  CONCLUSIONS
  Our results confirmed the validity of metabolic response assessment as a surrogate of survival. We developed a multivariate model that is able to identify patients at risk of residual disease. These patients may benefit from an individualized and more adequate therapeutic approach, thereby improving local control and survival.
authors.affiliation: Department of Radiation Oncology (MAASTRO), GROW- School for Oncology and Developmental Biology, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands. emmanuel.rios@maastro.nl
authors.forename: Emmanuel Rios
authors.initials: ER
authors.lastname: Velazquez
authors.forename: Hugo J W L
authors.initials: HJ
authors.lastname: Aerts
authors.forename: Cary
authors.initials: C
authors.lastname: Oberije
authors.forename: Dirk
authors.initials: D
authors.lastname: De Ruysscher
authors.forename: Philippe
authors.initials: P
authors.lastname: Lambin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000032:analysis / Q000378:metabolism*; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging* / Q000378:metabolism / Q000473:pathology* / Q000532:radiotherapy; D002470:Cell Survival; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000378:metabolism / Q000473:pathology* / Q000532:radiotherapy; D008297:Male; D008875:Middle Aged; D018365:Neoplasm, Residual; D049268:Positron-Emission Tomography / Q000379:methods; D011379:Prognosis; D011838:Radiation-Sensitizing Agents / Q000627:therapeutic use; D020266:Radiotherapy, Conformal / Q000379:methods; D012189:Retrospective Studies; D017211:Treatment Failure
chemical_list: D014408:Biomarkers, Tumor; D011838:Radiation-Sensitizing Agents; D019788:Fluorodeoxyglucose F18