Maintenance rituximab in Veterans with follicular lymphoma

Predicting Survival in Veterans with Follicular Lymphoma Using Structured Electronic Health Record Information and Machine Learning

The most accurate prognostic approach for follicular lymphoma (FL), progression of disease at 24 months (POD24), requires two years’ observation after initiating first-line therapy (L1) to predict outcomes. We applied machine learning to structured electronic health record (EHR) data to predict individual survival at L1 initiation. We grouped 523 observations and 1933 variables from a nationwide cohort of FL patients diagnosed 2006–2014 in the Veterans Health Administration into traditionally used prognostic variables (“curated”), commonly measured labs (“labs”), and International Classification of Diseases diagnostic codes (“ICD”) sets. We compared performance of random survival forests (RSF) vs. traditional Cox model using four datasets: curated, curated + labs, curated + ICD, and curated + ICD + labs, also using Cox on curated + POD24. We evaluated variable importance and partial dependence plots with area under the receiver operating characteristic curve (AUC). RSF with curated + labs performed best, with mean AUC 0.73 (95% CI: 0.71–0.75). It approximated, but did not surpass, Cox with POD24 (mean AUC 0.74 [95% CI: 0.71–0.77]). RSF using EHR data achieved better performance than traditional prognostic variables, setting the foundation for the incorporation of our algorithm into the EHR. It also provides for possible future scenarios in which clinicians could be provided an EHR-based tool which approximates the predictive ability of the most accurate known indicator, using information available 24 months earlier.

Maintenance rituximab in Veterans with follicular lymphoma

Real-world practice patterns and clinical outcomes in patients with follicular lymphoma (FL), including the adoption of maintenance rituximab (MR) therapy in the United States (US), have been reported in few studies since the release of the National LymphoCare Study almost a decade ago. We analyzed data from the largest integrated healthcare system in the United States, the Veterans Health Administration (VHA), to identify rates of adoption and effectiveness of MR in FL patients after first-line (1L) treatment. We identified previously untreated patients with FL in the VHA between 2006 and 2014 who achieved at least stable disease after chemoimmunotherapy or immunotherapy. Among these patients, those who initiated MR within 238 days of 1L composed the MR group, whereas those who did not were classified as the non-MR group. We examined the effect of MR on progression-free survival (PFS) and overall survival (OS). A total of 676 patients met our inclusion criteria, of whom 300 received MR. MR was associated with significant PFS (hazard ratio [HR]=0.55, P < .001) and OS (HR = 0.53, P = .005) compared to the non-MR group, after adjusting by age, sex, ethnicity, geographic region, diagnosis period, stage, grade at diagnosis, hemoglobin, lactate dehydrogenase (LDH), Charlson comorbidity index (CCI), 1L treatment regimen, and response to 1L treatment. These results suggest that in FL patients who do not experience disease progression after 1L treatment in real-world settings, MR is associated with a significant improvement in both PFS and OS. Maintenance therapy should be considered in FL patients who successfully complete and respond to 1L therapy.