Introduction

Chronic lymphocytic leukemia (CLL) is a low-grade malignancy that is generally indolent and often asymptomatic at presentation. While it can present with anemia, thrombocytopenia, progressive splenomegaly and adenopathy, it is usually diagnosed on routine laboratory studies with confirmatory flow cytometry. Complications of CLL include lack of appropriate immune response and surveillance, which may lead to more frequent infections and the development of second primary neoplasms, most commonly cutaneous malignancies. Prior studies have investigated the time to diagnose CLL from the onset of clinical signs and symptoms. One study looking at the Surveillance, Epidemiology, and End-Results (SEER) database found that the median time to diagnosis from the onset of signs or symptoms was approximately 63 days (1). While early diagnosis may not change the natural history of the disease, it may lead to earlier initiation of preventive strategies such as vaccinations and skin cancer screening. The purpose of this study is to investigate the time to diagnosis of patients with CLL from the onset of lymphocytosis meeting criteria for CLL to confirmatory flow cytometry and its correlation with patient characteristics within a rural health system. Methods A retrospective cohort analysis of patients with CLL who had an absolute lymphocyte count (ALC) greater than 5,000/microL and a flow cytometry was performed within the Geisinger Health System from 1997 to 2018. Patient age, sex, date of first lymphocytosis meeting diagnostic criteria, and date of flow cytometry was electronically extracted from the EMR. This data was then cross-referenced with the cancer registry database for accuracy of the diagnosis. To determine any difference between groups and the time from first ALC meeting criteria to confirmatory flow cytometry performed, the Wilcoxon Two-Sample Test was utilized. Associations between two continuous variables (age and time from first ALC meeting criteria to confirmatory flow cytometry performed, initial lymphocyte count and time from first ALC meeting criteria to confirmatory flow cytometry performed) were measured using the Pearson Correlation Coefficients. Results A total of 268 patients were identified. Univariate statistics are reported in Table 1. The median time from lymphocytosis to flow for our study was 7.5 days (IQR: 0 - 335) with a mean of 347 days (range: 0 - 5335 days). Just over half (53.8%) had a diagnosis within the first two weeks; however, greater than 20% were diagnosed after one year and just over 5% after five years (table 2). There was a positive correlation between age and time from lymphocytosis to flow (r=0.178, p=0.0034). Therefore, an increase in age at diagnosis was associated with an increase in time from initial lymphocytosis to flow. A weak negative correlation was seen between the degree of initial lymphocytosis and time from lymphocytosis to flow (r=-0.105, p=0.0867). Therefore, a lower lymphocyte count was associated with a slightly longer time to diagnosis. There was no significant difference between median time from lymphocytosis to flow in females (7 days IQR: 0 - 510) and males (8 days IQR: 0 - 271) with a p-value 0.4570. Conclusion This study demonstrates that there can be a broad range of time to diagnosis of CLL (figure 1). While gender did not play a significant role, increased age and lower initial lymphocyte value were associated with a delay in diagnosis. Larger studies are needed to include a more diverse population to confirm these predictive associations. Further data analyses are required to assess for co-morbidities and other characteristics in the identified at risk patient groups to help facilitate earlier diagnosis and appropriate preventative measures. References 1. Friese CR, Earle CC, Magazu LS, et al. Timeliness and quality of diagnostic care for medicare recipients with chronic lymphocytic leukemia. Cancer. 2011;117(7):1470-1477. doi:10.1002/cncr.25655

Disclosures

No relevant conflicts of interest to declare.

Author notes

*

Asterisk with author names denotes non-ASH members.

Sign in via your Institution