Follicular lymphoma (FL), caused due to the abnormal growth of B-cells, is the most common form of indolent Non-Hodgkin\u27s Lymphoma (NHL) in the United States. Majority of the patients diagnosed with FL are subjected to a series of treatment during their clinical course, thereby providing researchers an opportunity to evaluate sequential effect of different treatment regimens and identify significant risk factors affecting the survival of patients.
National Lymphocare Study (NLCS) is the largest (n = 2,740) prospective study conducted in the United States that collected information about different prognostic factors and outcomes required to conduct a comprehensive multi-state survival analysis. Using the data set, we analyzed the effect of 11 stationary and 5 dynamic variables on the death-specific transition and compared the results obtained from two multi-state models. We identified significant clinical factors impacting all-cause and FL-specific death using Cox proportional hazard model and predicted the course of disease using Aalen-Johansen estimator.
The risk of all-cause death was 16.37\% following 5-years from diagnosis. At the same time point, patients initially kept under watchful waiting (WW) were at a lower risk of FL-specific death, 4.52\%, compared to death due to other-causes, 8.25\%. Similarly, patients receiving an induction treatment without WW had an reduced risk of FL-specific death compared to death due to other cause at the 5-years time point. We further identified that the risk of FL-specific death increase after first-, second-, and third-line treatment with an increase in age of diagnosed patients. Dynamic variables, such as low albumin and elevated lactate dehydrogenase, were associated with poor outcomes after first-, second-, and third-line treatment. The presence of B-symptoms at diagnosis was not associated with an increased risk of FL death. On the other hand, being female reduced the risk (hazard ratio: 0.46 [0.3 - 0.8]) of FL death following treatment 2.
Using a multi-state survival analysis framework allowed to quantify the effect of prognostic factors on cause-specific death. We identified that the risk of death due to other-cause is higher compared to the risk of death due to FL
