Prognostic role of pretreatment (18)F-FDG PET/CT and hematological parameters in relapsed/refractory Hodgkin lymphoma patients treated with immune checkpoint inhibitors and chemotherapy: a dual-center cohort study

BACKGROUND: The combination of anti-programmed death-1 antibodies and chemotherapy is effective; however, there are no reliable outcome prediction factors. We investigated the prognostic factors based on (18)Fluorine-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) quantitative and hematological parameters to predict progression-free survival (PFS) in relapsed/refractory classical Hodgkin lymphoma (R/R cHL) patients treated with immune checkpoint inhibitors (ICIs) and chemotherapy. METHODS: This retrospective study included 31 patients who underwent (18)F-FDG PET/CT before and during treatment. Pretreatment metabolic and hematological parameters were evaluated using Cox regression analysis to identify predictors of PFS. Based on the cut-off values calculated using the receiver operating characteristic (ROC) curve, patients were classified into low-, intermediate-, and high-risk groups. Kaplan–Meier curves and the log-rank test were used to compare survival differences between the groups. RESULTS: Cox multivariable analysis indicted that the treatment response based on Lactate dehydrogenase (LDH), Lugano classification and SUV(max) were independent predictors of PFS (P = 0.004, 0.007 and 0.039, respectively). The optimal cut-off values for SUV(max) and LDH were 11.62 and 258.5 U/L, respectively (P < 0.01). Survival curves showed that LDH ≥ 258.5U/L and SUV(max) ≥ 11.62 were correlated to shorter PFS (P < 0.001, P = 0.003, respectively). The differences in PFS between the low-, intermediate-, and high-risk groups were statistically significant (P = 0.0043). CONCLUSION: In R/R cHL patients treated with ICIs and chemotherapy, Lugano classification, SUV(max), and LDH were significantly correlated with PFS. The combination of metabolic and hematological parameters predicts PFS and may help to improve patient selection.