PURPOSE: 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. CONCLUSION: 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.
PURPOSE: 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. CONCLUSION: 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: C G Willett; R M Linggood; J C Leong; L M Miketic; M A Stracher; S J Skates; D C Kushner Journal: J Clin Oncol Date: 1988-05 Impact factor: 44.544
Authors: Bruce D Cheson; Beate Pfistner; Malik E Juweid; Randy D Gascoyne; Lena Specht; Sandra J Horning; Bertrand Coiffier; Richard I Fisher; Anton Hagenbeek; Emanuele Zucca; Steven T Rosen; Sigrid Stroobants; T Andrew Lister; Richard T Hoppe; Martin Dreyling; Kensei Tobinai; Julie M Vose; Joseph M Connors; Massimo Federico; Volker Diehl Journal: J Clin Oncol Date: 2007-01-22 Impact factor: 44.544