Demographic and other characteristics of nodal non-Hodgkin's lymphoma managed in academic versus non-academic centers

Disparity in Utilization of Multiagent Therapy for Acute Promyelocytic Leukemia in the United States

BACKGROUND

Despite high rate of cure in acute promyelocytic leukemia (APL) in clinical trials, outcomes in real-world practice are dismal. We utilized National Cancer Database (NCDB) to explore utilization of multiagent therapy in APL and identify any disparities in treatment in real-world practices.

PATIENTS AND METHODS

NCDB categorizes use of systemic chemotherapy into single agent versus multiagent therapy. Some patients received hormonal therapy, immunotherapy, and unknown therapy; details of these treatments could not be ascertained. We therefore used multiple logistic regression analysis to evaluate effects of covariates on the probability of multiagent therapy use in 6678 patients.

RESULTS

Compared to patients >60 years, patients aged 0 to 18 years (hazard ratio[HR] 3.2, 95% confidence interval [CI] 1.8-5.5, P< .0001), 19 to 40 years (HR 1.6, 95% CI 1.03-2.54, P= .03), and 41 to 60 years (HR 1.6, 95% CI 1.3-1.9, P< .0001) were more likely to receive multiagent therapy. Patients with Charlson comorbidity index (CCI) of 0 (HR 1.6, 95% CI 1.2-2.3, P= .001) and CCI of 1 (HR 1.4, 95% CI 1.0-1.9, P= .04) had a higher likelihood of receiving multiagent therapy than patients with CCI ≥ 3. Patients treated at academic cancer centers, compared to those treated at community cancer center (HR 0.5, 95% CI 0.3-0.7, P= .001), comprehensive community cancer center (HR 0.7, 95% CI 0.6-0.8, P< .0001), and integrated network cancer center (HR 0.8, 95% CI 0.6-0.9, P= .02) were more likely to be treated with multiagent therapy. Compared to the patients with private insurance, those with Medicaid had increased likelihood (HR 1.2, 95% CI 1.0-1.4, P= .04) whereas uninsured patients had a lower likelihood of receiving multiagent therapy (HR 0.6, 95% CI 0.5-0.8, P= .0005).

CONCLUSION

To our knowledge, this study is the first and the largest scale analysis of treatment practices in APL in real-world practices. Our findings highlight significant disparities in treatment of APL based on age, insurance, and health-system factors.

Effects of Distance From Academic Cancer Center on Overall Survival of Acute Myeloid Leukemia: Retrospective Analysis of Treated Patients

INTRODUCTION

Patients living farther away from academic centers may not have easy access to resources for management of acute myeloid leukemia (AML). We aimed to analyze the effect of distance traveled on overall survival (OS) of AML patients treated at an academic center.

PATIENTS AND METHODS

AML patients diagnosed at the University of Nebraska Medical Center were divided into 4 groups according to the shortest distance between the cancer center and patients' residence (<25, 25-50, 50-100, and > 100 miles). Chi-square test and ANOVA were used to examine the association of distance with patient characteristics. OS, defined as the time from diagnosis of AML to death from any cause, was determined by the Kaplan-Meier method. Comparison of survival curves was done by the log-rank test. Multivariable analysis using Cox regression was performed to detect the survival effect of distance from the cancer center.

RESULTS

The total number of patients was 449. Median distance was 85 miles (interquartile range, 20-180). OS at 1 year for < 25, 25-50, 50-100, and > 100 miles was 45%, 55%, 38%, and 40% respectively (P = .6). In a Cox regression analysis, distance from treatment center, as a continuous variable, was not a significant factor for death (hazard ratio, 1.001; 95% confidence interval, 1.000-1.001). Multivariable analysis showed nonsignificant trend of increased mortality for patients traveling > 100 miles to a cancer center.

CONCLUSION

This study did not demonstrate an association between distance from an academic cancer center and OS in AML. This finding should provide some assurance to patients who live farther away from academic centers.

Improving survival of 3760 patients with lymphoma: Experience of an academic center over two decades

Background

The treatment outcomes and prognosis of lymphoma are affected by various factors such as hospital types. This study was to describe the temporal trend in the survival of lymphoma in an academic center in China.

Methods

A total of 3840 consecutive patients with lymphoma diagnosed between 1996 and 2015 were reviewed. Eighty patients were excluded, and finally, 3760 patients were analyzed in this study. The cohort was divided into four groups according to calendar periods at diagnosis: 1996‐2000, 2001‐2005, 2006‐2010, and 2010‐2015. The overall survival (OS) rates among the four groups were compared.

Results

The 5‐ and 10‐year OS for the whole cohort were 62% and 52%, respectively. The 5‐year OS of patient with classic Hodgkin lymphoma (cHL), mature B‐cell lymphoma (BCL), and peripheral T‐cell lymphoma (PTCL) were 79%, 63%, and 50%, respectively. Among mature BCL, the 5‐year OS was highest in follicular lymphoma (77.8%), followed by Burkitt lymphoma (76.5%), marginal zone lymphoma (74.1%), diffuse large B‐cell lymphoma (61.5%), small lymphocytic lymphoma/chronic lymphocytic leukemia (55.1%), and mantle cell lymphoma (44.3%). Among PTCL, the 5‐year OS was highest in ALK+anaplastic large cell lymphoma (79.0%), followed by ALK−anaplastic large cell lymphoma (63.1%), natural killer/T‐cell lymphoma (57.7%), angioimmunoblastic T‐cell lymphoma (34.9%, and peripheral T‐cell lymphoma not otherwise specified (27.6%). Significant improvement in the survival of lymphoma was observed, with the 5‐year OS increasing from 48% in 1996‐2000 to 65% in 2011‐2015 (P < .001). The 5‐year OS of patients with cHL, mature BCL, and PTCL changed from 55%, 49%, and 41% in 1996‐2000 to 79%, 65%, and 51% in 2011‐2015, respectively (P values were .014, .002, and .592, respectively).

Conclusion

The survival of most types of lymphoma such as cHL and mature BCL, rather than PTCL, was improved significantly during the past two decades.

Effects of center type and socioeconomic factors on early mortality and overall survival of diffuse large B-cell lymphoma

Aim: To examine whether the center type and socioeconomic factors significantly impact 1-month mortality and overall survival (OS) of patients with diffuse large B-cell lymphoma (DLBCL). Methods: National Cancer Database (NCDB) was used to identify patients diagnosed with diffuse large B-cell lymphoma from 2006 to 2012 (postrituximab era). Results: Among 185,183 patients, 33% were treated at academic centers. The receipt of therapy at larger volume centers was associated with improved 1-month mortality. Academic centers had better OS than nonacademic centers in univariable analysis. Younger age, private insurance, lower Charlson comorbidity score and lower lymphoma stage were associated with improved 1-month mortality and OS. Conclusion: The receipt of therapy at larger volume centers and socioeconomic factors were associated with improved survival.

Early mortality and overall survival of acute myeloid leukemia based on facility type

Cancer health disparities may exist based on the facility type. We aimed to determine the association between the academic status of centers and outcomes of patients with acute myeloid leukemia (AML). Using the National Cancer Data Base, we compared 1-month mortality and long-term overall survival (OS) of 60 738 patients with AML, who received first course treatment between 2003 and 2011 at academic or nonacademic centers (community cancer program, comprehensive community cancer program, and others). Multivariate analysis was done using logistic regression for one-month mortality and Cox regression with backward elimination approach for OS. Patients treated at academic centers differed from those at nonacademic centers in that they were younger with a median age of 62 versus 70 years (P < .0001), more often an ethnic minority (P < .0001), had lower education level (P = .005), lower co-morbidity score (P < .0001), a different income (P < .0001), and insurance profile (P < .0001), and more often received chemotherapy (P < .0001) and transplant (P < .0001). Receipt of care at nonacademic centers was associated with worse 1-month mortality (29% vs. 16%, P < .0001) and 5-year OS (15% vs. 25%; P < .0001). After adjusting for prognostic covariates, the 1-month mortality (odds ratio, 1.52; 95% confidence interval, CI 1.46-1.59; P < .0001) and OS were significantly worse in nonacademic centers, compared to academic centers. Our large database study suggests that the receipt of initial therapy at academic centers is associated with lower 1-month mortality and higher long-term OS. Investigation of the underlying reasons may allow reducing this disparity.