Assessing Trends in Conditional Survival for Non–Hodgkin Lymphoma and Chronic Myeloid Leukemia via Novel Extensions to the Joinpoint Survival Model
Menée à l'aide de données des registres américains des cancers et d'une nouvelle méthode, cette étude estime la survie relative à 5 ans chez les patients atteints d'un lymphome non hodgkinien ou d'une leucémie myéloïde chronique
Background: Five-year relative survival for non–Hodgkin lymphoma (NHL) and chronic myeloid leukemia (CML) has improved, reflecting therapeutic advances, but prognosis beyond 5 years after diagnosis is less understood. We introduced a method to estimate trends in conditional survival, the probability of further survival given survival to a specific time.
Methods: We developed a landmarked joinpoint survival (JPSurv) model that uses data beginning at a prespecified follow-up interval. We apply this approach to NHL (overall and by major subtype) and CML survival data from the Surveillance, Epidemiology, and End Results program. We estimated calendar trends in both 5-year relative survival and 5-year conditional relative survival (given survival to 5 years) using annual absolute changes in survival represented by percentage points (pp) over a time frame.
Results: The largest annual increases in 5-year relative survival were observed for diffuse large B-cell lymphoma (+2.44 pp 1995–2002) and CML (+2.52 pp 1996–2011). Five-year conditional relative survival improved most for CML (+1.79 pp 1985–2016), chronic lymphocytic leukemia/small lymphocytic lymphoma (+0.80 pp 1988–2016), and follicular lymphoma (+80 pp 1990–2016). For patients diagnosed after 2010, 5-year conditional relative survival was approximately 90% for all cancers studied.
Conclusions: Both 5-year relative survival and 5-year conditional relative survival improved substantially, reflecting advances in therapy and long-term patient outcomes.
Impact:
The landmarked JPSurv model is a novel framework for conditional survival analysis that can be used to inform survivorship research, offering insight into lasting treatment effects and the likelihood of patients obtaining a sustained remission.
Cancer Epidemiology, Biomarkers & Prevention , résumé, 2026