Follow up FDG PET/CT for Recurrence Detection and Survival Outcome Prediction in Patients with non-Hodgkin lymphoma

Objectives This study is designed to evaluate the value of follow up PET/CT in the detection of recurrence as well as determining its prognostic value in patients with non-Hodgkin lymphoma (NHL).

Methods All patients diagnosed with NHL who had at least one follow up PET/CT six months after the completion of their treatment were included. There were 204 eligible NHL patients and 560 eligible PET/CT scans. The accuracy of PET/CT scans was established with histopathology or six months clinical follow up as reference standard. The change in management was recorded after each follow up PET/CT scan in comparison to the management plan prior to the study. Cox regression model was established for clinical covariates and imaging results. Overall survival was evaluated using Kaplan-Meier plots with a Log-rank test.

Results The sensitivity, specificity, PPV, NPV, and accuracy of FDG-PET/CT in detecting recurrent lymphoma were 95.1%, 90.5%, 84.5%, 97.1%, 92.1% respectively. Among 560 scans, 388 (69.3%) scans were done routinely and 172 (30.7%) scans were done due to clinical suspicion. Follow up scan results suggested disease in 22.2% routine scan and ruled out suspected disease in 17.4% scans with prior clinical suspicion. The management of NHL patients was changed after 17% of follow up scans. New treatment modalities were started for 15.7% of patients, and the treatment modality was changed or stopped after 1.6% of scans. The management of NHL patients was not changed after 74.8% scans (53.6% no treatment to no treatment and 21.2% continue the same treatment). A total of 157 (77%) patients survived and 47 (23%) patients had died during the median follow up period of 16.5 months. On multivariate Cox regression analysis, age (p < 0.001) was the only significant factor predicting overall survival.

Conclusions Follow up PET/CT scans added value to clinical assessment and management of NHL patients and had excellent accuracy in recurrence detection.