Affluence and Private Health Insurance Influence Treatment and Survival in Non-Hodgkin's Lymphoma

Outcomes of Lymphoma Among American Adolescent and Young Adult Patients Varied by Health Insurance-A SEER-based Study

INTRODUCTION

Impacts of health insurance status on survival outcomes among adolescent and young adult (AYA, 15 to 39 years of age) patients with lymphoma in the United States are insufficiently known. This study aimed to clarify associations between health insurance status and overall survival (OS) estimates in this population.

MATERIALS AND METHODS

We examined 18 Surveillance, Epidemiology, and End Results registries in the United States and analyzed American AYA patients with lymphoma diagnosed during January 2007 and December 2016. Health insurance status was categorized, and Kaplan-Meier and multifactor Cox regressions were adopted using hazard ratio and 95% confidence interval. Probable baseline confounding was modulated by multiple propensity score.

RESULTS

A total of 21,149 patients were considered; ~28% were 18 to 25 years old, and 63.5% and 7.5% had private and no insurance, respectively. Private insurance rates increased in the 18 to 25 age group (60.1% to 6.1%, P<0.001) following the 2010 Patient Protection and Affordable Care Act (ACA), and lymphoma survival rates improved slightly 1 to 5 years postdiagnosis. Five-year OS rates decreased with age (93.9%, 90.4%, and 87.0% at 15 to 17, 18 to 25, and 26 to 39, respectively) and differed among insurance conditions (81.7%, 79.2%, 89.2%, and 92.0% for uninsured, Medicaid, insured, and insured/no specifics, respectively). Risk of death was significantly higher for those with Medicaid or no insurance than for those with private insurance in multiple propensity score-adjusted models (hazard ratio [95% confidence interval]=1.07 [1.03-1.12]), independent of stage at diagnosis.

CONCLUSIONS

No or insufficient insurance was linked to poor OS in our sample in exposure-outcome association analysis. Insurance coverage and health care availability may enhance disparate outcomes of AYAs with cancer. The ACA has improved insurance coverage and survival rates for out sample. Nevertheless, strategies are needed to identify causality and eliminate disparities.

Excess Mortality by Multimorbidity, Socioeconomic, and Healthcare Factors, amongst Patients Diagnosed with Diffuse Large B-Cell or Follicular Lymphoma in England

(1) Background: Socioeconomic inequalities of survival in patients with lymphoma persist, which may be explained by patients' comorbidities. We aimed to assess the association between comorbidities and the survival of patients diagnosed with diffuse large B-cell (DLBCL) or follicular lymphoma (FL) in England accounting for other socio-demographic characteristics. (2) Methods: Population-based cancer registry data were linked to Hospital Episode Statistics. We used a flexible multilevel excess hazard model to estimate excess mortality and net survival by patient's comorbidity status, adjusted for sociodemographic, economic, and healthcare factors, and accounting for the patient's area of residence. We used the latent normal joint modelling multiple imputation approach for missing data. (3) Results: Overall, 15,516 and 29,898 patients were diagnosed with FL and DLBCL in England between 2005 and 2013, respectively. Amongst DLBCL and FL patients, respectively, those in the most deprived areas showed 1.22 (95% confidence interval (CI): 1.18-1.27) and 1.45 (95% CI: 1.30-1.62) times higher excess mortality hazard compared to those in the least deprived areas, adjusted for comorbidity status, age at diagnosis, sex, ethnicity, and route to diagnosis. (4) Conclusions: Deprivation is consistently associated with poorer survival among patients diagnosed with DLBCL or FL, after adjusting for co/multimorbidities. Comorbidities and multimorbidities need to be considered when planning public health interventions targeting haematological malignancies in England.

Factors Explaining Socio-Economic Inequalities in Cancer Survival: A Systematic Review

BACKGROUND

There is strong and well-documented evidence that socio-economic inequality in cancer survival exists within and between countries, but the underlying causes of these differences are not well understood.

METHODS

We systematically searched the Ovid Medline, EMBASE, and CINAHL databases up to 31 May 2020. Observational studies exploring pathways by which socio-economic position (SEP) might causally influence cancer survival were included.

RESULTS

We found 74 eligible articles published between 2005 and 2020. Cancer stage, other tumor characteristics, health-related lifestyle behaviors, co-morbidities and treatment were reported as key contributing factors, although the potential mediating effect of these factors varied across cancer sites. For common cancers such as breast and prostate cancer, stage of disease was generally cited as the primary explanatory factor, while co-morbid conditions and treatment were also reported to contribute to lower survival for more disadvantaged cases. In contrast, for colorectal cancer, most studies found that stage did not explain the observed differences in survival by SEP. For lung cancer, inequalities in survival appear to be partly explained by receipt of treatment and co-morbidities.

CONCLUSIONS

Most studies compared regression models with and without adjusting for potential mediators; this method has several limitations in the presence of multiple mediators that could result in biased estimates of mediating effects and invalid conclusions. It is therefore essential that future studies apply modern methods of causal mediation analysis to accurately estimate the contribution of potential explanatory factors for these inequalities, which may translate into effective interventions to improve survival for disadvantaged cancer patients.

Immunotherapeutic options for management of relapsed or refractory B-cell acute lymphoblastic leukemia: how to select newly approved agents?

Recently, immunotherapeutic agents such as inotuzumab ozogamicin (INO), blinatumomab (BLIN), and tisagenlecleucel (TISA) have been approved for treatment of relapsed or refractory (R/R) acute lymphoblastic leukemia (ALL). No head to head trials have compared these agents. Thus, various factors influence the decision to choose an appropriate treatment for R/R ALL. INO may be preferred in patients with high tumor burden; BLIN is preferred in patients with low tumor burden or to eradicate minimal residual disease (MRD). Both INO and BLIN, compared to standard chemotherapy, increase the probability of receiving subsequent hematopoietic stem cell transplant (HSCT). TISA, approved for patients ≤25 years of age, is effective regardless of tumor burden or prior receipt of HSCT and can be used as a definite treatment in some patients. Further studies comparing the efficacy, safety, and other outcomes related to different immunotherapeutic options in combination with other treatment modalities and among themselves are needed.

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.