Purpose To investigate the prognosis value of a combined model based on F-18-fluoro-deoxyglucose positron emission tomography-computed tomography (F-18-FDG PET-CT) baseline and interim parameters in patients with diffuse large B-cell lymphoma (DLBCL). Methods We retrospectively analyzed the PET metabolic parameters and clinical data of 154 DLBCL patients between December 2015 and October 2020. All of these patients underwent F-18-FDG PET/CT scan before treatment and after three or four courses of chemotherapy. The optimal cut-off values for quantitative variables were determined by the receiver operating characteristic (ROC) curve. The baseline and interim PET/CT parameters, which respectively included maximum standardized uptake value (SUVmax0), total metabolic tumor volume (TMTV0), standardized total metabolic tumor volume (STMTV0), and the distance between the two furthest lesions (Dmax) and total tumor lesion glycolysis (TTLG1), SUVmax1, TMTV1, and the rate of change of SUVmax (%Delta SUVmax), and clinical characteristics were analyzed by chi-squared test, Kaplan-Meier survival curve, and Cox regression analysis. Results Of 154 patients, 35 exhibited disease progression or recurrence. ROC analysis revealed that baseline F-18-FDG PET/CT metabolic parameters, including maximum standardized uptake value (SUVmax0), total metabolic tumor volume (TMTV0), standardized total metabolic tumor volume (STMTV0), and the distance between the two furthest lesions (Dmax), along with interim F-18-FDG PET/CT metabolic parameters such as total tumor lesion glycolysis (TTLG1), SUVmax1, TMTV1, and the rate of change of SUVmax (%Delta SUVmax), were predictive of relapse or progression in DLBCL patients (P < 0.05). The chi-squared test showed that TMTV0, STMTV0, Dmax, SUVmax1, TMTV1, TTLG1, %Delta SUVmax, Deauville score, IPI, Ann Arbor stage, and LDH were associated with patient prognosis (P < 0.05). Multivariate Cox regression analysis showed that Dmax (P = 0.021) and %Delta SUVmax (P = 0.030) were independent predictors of prognosis in DLBCL patients. There were statistically significant differences in PFS among the three groups with high, intermediate, and low risk according to the combination model (P < 0.001). The combination model presented higher predictive efficacy than single indicators. Conclusion The combined model of baseline parameter Dmax and intermediate parameter %Delta SUVmax of F-18-FDG PET/CT improved the predictive efficacy of PFS and contributed to the risk stratification of patients, providing a reference for clinical individualization and precision treatment.