Early-stage Hodgkin lymphoma in the modern era: simulation modelling to delineate long-term patient outcomes

Abstract

We developed a novel simulation model integrating multiple data sets to project long-term outcomes with contemporary therapy for early-stage Hodgkin lymphoma (ESHL), namely combined modality therapy (CMT) versus chemotherapy alone (CA) via ¹⁸ F-fluorodeoxyglucose positron emission tomography response-adaption. The model incorporated 3-year progression-free survival (PFS), probability of cure with/without relapse, frequency of severe late effects (LEs), and 35-year probability of LEs. Furthermore, we generated estimates for quality-adjusted life years (QALYs) and unadjusted survival (life years, LY) and used model projections to compare outcomes for CMTversusCA for two index patients. Patient 1: a 25-year-old male with favourable ESHL (stage IA); Patient 2: a 25-year-old female with unfavourable ESHL (stage IIB). Sensitivity analyses assessed the impact of alternative assumptions for LE probabilities. For Patient 1, CMT was superior to CA (CMT incremental gain = 0·11 QALYs, 0·21 LYs). For Patient 2, CA was superior to CMT (CA incremental gain = 0·37 QALYs, 0·92 LYs). For Patient 1, the advantage of CMT changed minimally when the proportion of severe LEs was reduced from 20% to 5% (0·15 QALYs, 0·43 LYs), whereas increasing the severity proportion for Patient 2's LEs from 20% to 80% enhanced the advantage of CA (1·1 QALYs, 6·5 LYs). Collectively, this detailed simulation model quantified the long-term impact that varied host factors and alternative contemporary treatments have in ESHL.

Keywords: Hodgkin lymphoma; decision making; health-related quality of life; late effects of therapy; simulation modelling.

Figure 1

The health state transition diagram. The bubbles represent individual health states. The value within each bubble is the utility weight (or health‐related quality of life impact) of that health state. The arrows represent transition pathways between states. Scaling each year of survival by that year's utility weight (specified for each health state in the figure) and then summing the quality‐adjusted years yields quality‐adjusted survival. Please see Table 1 for values used for each transition pathway and the associated health state. *Represents range of utility weight values categorised on the presence of severe (0·67) or non‐severe (0·73) late effects.