OBJECTIVES: The treatment landscape is rapidly evolving for relapsed/refractory follicular lymphoma (r/r FL); however, prognostic factors and effect modifiers in later line settings in FL have not been assessed systematically. This systematic literature review (SLR) was conducted to identify prognostic factors and effect modifiers in adult patients with r/r FL who failed at least 2 prior lines of therapy (3L+).

METHODS: An SLR was performed following Cochrane and PRISMA guidelines. MEDLINE, Embase, and CENTRAL were searched for articles published from 2016 through 2021, supplemented by conference abstract review, forward-citation searches, and bibliography review of key publications. Clinical trials and observational studies evaluating prognostic factors or effect modifiers for clinical outcomes were included.

RESULTS: Among 856 records identified from the literature search, a total of 13 studies were included (2 trials and 11 observational studies). Twenty-eight prognostic factors had statistically significant associations (p <0.05) with 7 outcomes. Overall survival (OS) was the most frequently evaluated outcome (9 studies), followed by progression-free survival (PFS; 8 studies). Among identified prognostic factors, older age, having chemorefractory/chemoresistant disease, a greater number of prior lines of therapy, lower Karnofsky score, a high-risk follicular lymphoma international prognostic index composite score, not achieving complete response/partial response at transplant, use of myeloablative conditioning regimen, and a higher grade of graft-versus-host disease were associated with worse outcomes in ≥ 2 studies (PFS: 5; OS: 4; others: 6). None of the studies identified statistically significant effect modifiers for the population of interest.

CONCLUSIONS: To the best of our knowledge, this SLR is the first to provide a comprehensive assessment of prognostic factors for 3L+ r/r FL. No statistically significant effect modifiers were identified. Knowledge about important prognostic factors is critical for selecting and prespecifying variables for confounding adjustment and can support robust comparative analyses between real-world studies and clinical trials.