SAKK38/07 study: integration of baseline metabolic heterogeneity and metabolic tumor volume in DLBCL prognostic model

Abstract

Several functional parameters from baseline (18)F-fluorodeoxyglucose positron emission tomography (PET)/computed tomography have been proposed as promising biomarkers of treatment efficacy in diffuse large B-cell lymphoma (DLBCL). We tested their ability to predict outcome in 2 cohorts of DLBCL patients receiving conventional immunochemotherapy (rituximab, cyclophosphamide, doxorubicin hydrochloride, vincristine sulfate, and prednisone [R-CHOP] regimen), either every 14 (R-CHOP14) or 21 days (R-CHOP21). Baseline PET analysis was performed in 141 patients with DLBCL treated with R-CHOP14 in the prospective SAKK38/07 study (NCT00544219) of the Swiss Group for Clinical Cancer Research (testing set). Reproducibility was examined in a validation set of 113 patients treated with R-CHOP21. In the SAKK38/07 cohort, progression-free survival (PFS) at 5 years was 83% for patients with low metabolic tumor volume (MTV) and 59% for those with high MTV (hazard ratio [HR], 3.4; 95% confidence interval [CI], 1.6-7.0; P = .0005), whereas overall survival (OS) was 91% and 64%, respectively (HR, 4.4; 95% CI, 1.9-10; P = .0001). MTV was the most powerful predictor of outcome also in the validation set. Elevated metabolic heterogeneity (MH) significantly predicted poorer outcomes in the subgroups of patients with elevated MTV. A model integrating MTV and MH identified high-risk patients with shorter PFS (testing set: HR, 5.6; 95% CI, 1.8-17; P < .0001; validation set: HR, 5.6; 95% CI, 1.7-18; P = .0002) and shorter OS (testing set: HR, 9.5; 95% CI, 1.7-52; P < .0001; validation set: HR, 7.6; 95% CI, 2.0-28; P = .0003). This finding was confirmed by an unsupervised regression tree analysis indicating that prognostic models based on MTV and MH may allow early identification of refractory patients who might benefit from treatment intensification. This trial was registered at www.clinicaltrials.gov as #NCT00544219.

Graphical abstract

Figure 1.

OS and PFS according to the MTV in the testing and in the validation cohorts.

Figure 2.

OS and PFS according to the model built integrating the MTV and MH either in the testing or in the validation cohort.

Figure 3.

The classification trees showing the prognostic signature consisting of 2 variables, MTV and MH, whose dichotomization was significantly correlated with survival. MTV alone, when its value is low, identifies the prognostic category node 2 with best survival probability. To separate the prognostic categories node 4, with intermediate survival rates, from node 5, with poorer survival, the value of MTV must be high (node 3), and that of MH must be low or high, respectively. The Kaplan-Meier curves show statistically different overall and progression-free survival, either in both the testing and the validation patient sets. For each inner node, the Bonferroni-adjusted P values are given, which take into account the multiple testing and may differ from the P values of the log-rank test in the univariable analysis (Table 3).