Comparing the accuracy of quantitative versus qualitative analyses of interim PET to prognosticate Hodgkin lymphoma: a systematic review protocol of diagnostic test accuracy.

Abstract

Hodgkin lymphoma is an effectively treated malignancy, yet 20% of patients relapse or are refractory to front-line treatments with potentially fatal outcomes. Early detection of poor treatment responders is crucial for appropriate application of tailored treatment strategies. Tumour metabolic imaging of Hodgkin lymphoma using visual (qualitative) 18-fluorodeoxyglucose positron emission tomography (FDG-PET) is a gold standard for staging and final outcome assessment, but results gathered during the interim period are less accurate. Analysis of continuous metabolic-morphological data (quantitative) FDG-PET may enhance the robustness of interim disease monitoring, and help to improve treatment decision-making processes. The objective of this review is to compare diagnostic test accuracy of quantitative versus qualitative interim FDG-PET in the prognostication of patients with Hodgkin lymphoma. The literature on this topic will be reviewed in a 3-step strategy that follows methods described by the Joanna Briggs Institute (JBI). First, MEDLINE and EMBASE databases will be searched. Second, listed databases for published literature (MEDLINE, Tripdatabase, Pedro, EMBASE, the Cochrane Central Register of Controlled Trials and WoS) and unpublished literature (Open Grey, Current Controlled Trials, MedNar, ClinicalTrials.gov, Cos Conference Papers Index and International Clinical Trials Registry Platform of the WHO) will be queried. Third, 2 independent reviewers will analyse titles, abstracts and full texts, and perform hand search of relevant studies, and then perform critical appraisal and data extraction from selected studies using the DATARI tool (JBI). If possible, a statistical meta-analysis will be performed on pooled sensitivity and specificity data gathered from the selected studies. Statistical heterogeneity will be assessed. Funnel plots, Begg's rank correlations and Egger's regression tests will be used to detect and/or correct publication bias. The results will be disseminated by publishing in a peer-reviewed journal. Ethical assessment will not be needed; only existing sources of literature will be searched. CRD42016027953.