title: Baseline metabolic tumour volume is an independent prognostic factor in Hodgkin lymphoma.
abstract: OBJECTIVE
  The presence of a bulky tumour at staging in Hodgkin lymphoma (HL) is a predictor of a poor outcome. The total metabolic tumour volume at baseline (TMTV0) computed on PET may improve the evaluation of tumour burden. To explore the clinical usefulness of TMTV0, we compared the prognostic value of TMTV0, tumour bulk and interim PET response in a retrospective single-centre study.
  
  
  METHODS
  From 2007 to 2010, 59 consecutive patients with a first diagnosis of HL were treated in our institution. PET was done at baseline (PET0) and after two cycles of chemotherapy (PET2), and treatment was not modified according to the PET2 result. TMTV0 was measured with a semiautomatic method using a 41 % SUVmax threshold. SUVmax reduction between PET0 and PET2 (ΔSUVmaxPET0-2) was also computed. Based on ROC analysis, patients with a ΔSUVmaxPET0-2 >71 % were considered good responders and a TMTV0 >225 ml was considered to represent hypermetabolic bulky disease.
  
  
  RESULTS
  Median TMTV0 was 117 ml and 17 patients (29 %) had a TMTV0 >225 ml. TMTV0 (>225 ml vs. ≤225 ml) and tumour bulk (<10 cm vs. ≥10 cm) were predictive of 4-year PFS: 42 % vs. 85 % (p = 0.001) and 44 % vs. 79 % (p < 0.03), respectively. In multivariate analysis, using ΔSUVmaxPET0-2, TMTV0 and bulky tumour as covariates, only ΔSUVmaxPET0-2 (p = 0.0005, RR 6.3) and TMTV0 (p < 0.006, RR 4.4) remained independent predictors of PFS. Three prognosis groups were thus identified: ΔSUVmaxPET0-2 >71 % and TMTV0 ≤225 ml (n = 37, 63 %), ΔSUVmaxPET0-2 = <71 % or TMTV0 >225 ml (n = 17, 29 %), and ΔSUVmaxPET0-2 = <71 % and TMTV0 >225 ml (n = 5, 8 %). In these three groups the 4-year PFS rates were 92 %, 49 %, and 20 % (p < 0.0001), respectively.
  
  
  CONCLUSIONS
  TMTV0 is more relevant than tumour bulk for predicting the outcome in patients with HL, and adds a significant prognostic insight to interim PET response assessment. The combination of TMTV0 and ΔSUVmaxPET0-2 made it possible to identify three subsets of HL patients with different outcomes. This may guide clinicians in their choice of therapeutic strategy.
authors.affiliation: Médecine nucléaire, Centre G.F. Leclerc, Dijon, France.
authors.forename: Salim
authors.initials: S
authors.lastname: Kanoun
authors.forename: Cédric
authors.initials: C
authors.lastname: Rossi
authors.forename: Alina
authors.initials: A
authors.lastname: Berriolo-Riedinger
authors.forename: Inna
authors.initials: I
authors.lastname: Dygai-Cochet
authors.forename: Alexandre
authors.initials: A
authors.lastname: Cochet
authors.forename: Olivier
authors.initials: O
authors.lastname: Humbert
authors.forename: Michel
authors.initials: M
authors.lastname: Toubeau
authors.forename: Emmanuelle
authors.initials: E
authors.lastname: Ferrant
authors.forename: François
authors.initials: F
authors.lastname: Brunotte
authors.forename: René-Olivier
authors.initials: RO
authors.lastname: Casasnovas
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D005260:Female; D006689:Hodgkin Disease / Q000175:diagnosis* / Q000378:metabolism / Q000473:pathology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D011379:Prognosis; D012189:Retrospective Studies; D047368:Tumor Burden; D055815:Young Adult