OBJECTIVES: To review existing cost-effectiveness analysis (CEA) models published in chronic lymphocytic leukaemia (CLL), follicular lymphoma (FL) and multiple myeloma (MM), with a view to critically appraise their methodological quality and highlight areas for improvement. METHODS: Peer-reviewed and grey literature identified in MEDLINE, EMBASE and Google Scholar (cut-off date March 2016), published in English. No restrictions on the treatment options included or the patients’ characteristics. When possible, studies were assessed against the ISPOR-SMDM modelling good research practice guideline recommendations. RESULTS: We identified 33 full-length CEAs reports (10 CLL, 8 FL, 15 MM). Most analyses used cohort models (27% CLL, 21% FL and 40% MM) - typically informed by aggregated data from the literature (67% CLL, 71% FL and 62% MM) - to represent disease prognoses and treatment pathways. Four CEAs (1 CLL, 1 FL and 2 MM) used discrete event simulation (DES) models, accounting for the effects of upstream/downstream decisions on the costs and outcomes of the primary object of the evaluation. Very few analyses (21%) used real-world data (alone or in combination with RCTs) to populate their models. The quality of these CEAs was heterogeneous when assessed against the ISPOR-SMDM modelling good research practice recommendations. Generally, the decision problem, target population, interventions/comparators and health outcomes were well defined, but some important features like the perspective of the analysis (12%), the time horizon (18%) and the conceptual representation of the decision problem (52%) were not systematically reported or provided. CONCLUSIONS: Treatment pathways in CLL, FL and MM are often individualised and difficult to model, given the heterogeneous events/outcomes profiles observed throughout the patients prognoses. CEA studies reporting quality needs to improve. Real-world long-term individual patient-level data is fundamental for modelling the nuanced sequential nature of treatment and therapy switch decisions in CLL, FL and MM and the outcomes that follow.