BackgroundFactors associated with receiving initial care for thyroid cancer (TC) at academic centers (ACs) versus nonacademic centers (NACs) and their impact on patient outcomes have not been reported.MethodsThe National Cancer Database with TC cases from 2004 to 2013 was evaluated for association of type of center for initial care with socioeconomic factors and disease and treatment characteristics, as well as overall survival (OS; all‐cause mortality).ResultsThe patients with TC (n = 200,824) included were predominantly women (74%), non‐Hispanic Whites (85%), and from metro areas (84%). Sixty percent received initial care at a NAC. There were no significant differences between treatment groups by age or gender. Among those treated at an AC, a higher proportion belonged to racial/ethnic minorities (16.5%) versus at a NAC (11.6%). Hormone therapy was used more in an AC versus a NAC (60% vs 47%). Patients with all TC pathologies combined had a lower likelihood of death when they received initial care at an AC (hazard ratio [HR], 0.948; P = .0006). Among individual pathologic subtypes, a lower likelihood of death was noted when initial care was received at an AC for follicular (HR, 0.828, P = .0010) and Hurthle cell cancers (HR, 792; P = .0008), as well as stage II papillary thyroid cancer (HR, 0.828; P = .0026), but not for other histopathologic subtypes.ConclusionsInitial care at an AC was associated with lower likelihood of death for patients with TC, especially for those with follicular or Hurthle cell subtypes. Optimal resource use with consideration of patients' socioeconomic and demographic factors is imperative to ensure the most appropriate management of patients with TC in various treatment settings.
Exploring Disease Biology in Hispanic Versus Non-Hispanic Patients with Diffuse Large B-Cell Lymphoma (DLBCL) to Explain Survival Disparities
Abstract Background: DLBCL is the most common adult NHL and despite significant advancements, outcomes in ethnic minorities remain suboptimal. Factors responsible for these disparities in ethnic minorities, especially variability in clinical and pathological features with evaluation of patient-level data have not been studied. Methods: A multi-institutional database of DLBCL patients seen at Mayo Clinic in Florida, University of Miami and University of Southern California between 1996-2016 was developed. Patient demographics, clinical disease characteristics and details of DLBCL immunophenotype [CD10, MUM1, BCL6 (Han's classification), Ki 67, MYC, BCL2) were reviewed. Comparisons between Hispanic and Non-Hispanic patients were made by Chi-square, Fischer's exact and Signed rank tests, where applicable. Patients with missing data on a certain feature were not included in the statistical analysis of that specific characteristic. Results: A total of 966 DLBCL patients with 69 Hispanics and 752 non-Hispanics were identified. These included 52% males (N=36) and 48% females (N=33) in Hispanics versus 58% males (N=436) and 42% females (N=316) in Non-Hispanics (p=0.35). Median age at diagnosis was significantly lower at 61 years (range 27-89) in Hispanics versus 66 in non-Hispanics (p=0.014). Extranodal disease was seen significantly more commonly in Hispanics (74%) than in non-Hispanics (60%) (p=0.037). There was no significant difference in disease stage at presentation between the two cohorts (p=0.189) although the proportion of patients with stage III and IV disease was higher among Hispanics (80.4%) as compared to non-Hispanics (68.5%). Similarly there was no significant difference in presence of primary CNS DLBCL at diagnosis between the two groups (p=0.74). GCB phenotype per the Hans' classification was seen in 59% (N=29) in both, Hispanics and Non-Hispanics (N=241) (p=0.99). Similarly, the median ki67 index of 80% was seen in both cohorts (p=0.48). MYC was positive in 59% in Hispanics versus only 37.5% in non-Hispanics (p=0.024). BCL2 expression by itself and also combined BCL2 and MYC double expression were not significantly different between the two groups (p=0.58 and p=0.11, respectively). Median overall survival (OS) was 22.5 months in Hispanics compared 54.9 months in Non-Hispanics (p<0.0001) (Figure 1). Conclusion: Survival outcome disparities in racial and ethnic minorities have been previously reported from population-based analyses. Lack of patient-level clinical data makes these analyses hypothesis generating, but not conclusive. We confirmed some prior findings including younger age at diagnosis for Hispanics with DLBCL. We also reported greater incidence of extranodal as well as stage III or IV disease at the time of presentation among Hispanics which may contribute to poor outcomes in this population. From DLBCL pathology standpoint, we found increased expression of MYC among Hispanics but no other significant immunohistochemical differences including double expression or non-GCB phenotype. The inferior OS despite uniform treatment practices at large Cancer Centers suggest multifactorial influences on patient outcomes which may at least in part include some of the differences we report here. Disclosures Ailawadhi: Pharmacyclics: Research Funding; Janssen: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy.
Disparity in Clinical Trial Opportunities for Patients with B-Cell Malignancies in the United States
Abstract Background: Clinical trials are fundamental to advance therapeutics systematically and improve patient outcomes. Despite this, enrollment on clinical trials remains dismal in the United States (US) and is a constant focus of healthcare policy. We studied distribution of clinical trials for B-cell malignancies over time across the US and unique clinical trial opportunities i.e. individual clinical trials for the given diagnosis at a site that patients may have access to participate. Methods: We abstracted data from clinicaltrials.gov for all trials that had non-Hodgkin lymphoma (NHL) or multiple myeloma (MM) as an inclusion indication between 1999-2018. Clinical trial characteristics and distribution over US geographical divisions (West, Midwest, Northeast, and South) were studied, and differences were assessed by Chi-square test. Results: A total of 1930 trials were identified (NHL: 982, MM: 948), of which 483 were recruiting at the time of data abstraction (NHL: 250, MM: 233). Over the past 2 decades, 182691 patients were enrolled on the various trials (NHL: 81592, MM: 101099). Trials by phase of study included phase 1: 629, phase 1/2: 316, phase 2: 813, phase 2/3: 11 and phase 3: 161. Number of trials by phase separated by NHL and MM are shown in Figure 1. Of these, 197 trials were randomized (NHL: 67, MM: 130). Geographical distribution of trials by diagnosis type is shown in Figure 2. A total of 31806 unique trial opportunities were noted for MM and NHL, of which 9,513 were international and 22,293 were in the US, with a geographical distribution of 5080 in West, 8198 in Midwest, 3944 in Northeast, and 5071 in South. 4,883 of the unique trial opportunities were available at NCI/NCCN accredited sites and 17,410 were at non-NCI/NCCN sites in the US. Treatment characteristics of the trials included monoclonal antibodies in 1218, other targeted agents in 2641, stem cell transplant in 526, and other agents in 517 trials with several trials utilizing more than one of these therapeutic options. There was no statistically significant difference in the distribution of clinical trials by phase of study across various US geographical regions for MM (p=0.71), NHL (p=0.98) or combined MM+NHL (p=0.16). On the other hand, unique trial opportunities were significantly different by study phase and geographical distribution for MM, NHL or MM+NHL (all p<0.001) (Figure 3). Conclusions: Widespread access to clinical trials within a cancer diagnosis is imperative for generalizability of trial results. In a comprehensive, national analysis we noted that while it may appear that clinical trials are available across the US, sites where they are open are distributed unevenly, giving rise to a disparity in access to evidence-based therapeutic advancements for patients. Disclosures Ailawadhi: Janssen: Consultancy; Amgen: Consultancy; Pharmacyclics: Research Funding; Takeda: Consultancy; Celgene: Consultancy. Sher:Affimed: Research Funding.