Dataset Information

Associations between race and survival in pediatric patients with diffuse large B-cell lymphoma.

ABSTRACT:

Background

The purpose of this study was to examine the factors associated with disparities in overall survival (OS) by race in pediatric diffuse large B-cell lymphoma (DLBCL) patients.

Methods

We evaluated clinical features and survival among patients ?21 years of age diagnosed with stage I-IV DLBCL from 2004 to 2014 from the National Cancer Database (NCDB) using a multivariable Cox proportional hazards model.

Results

Among 1386 pediatric patients with DLBCL, 1023 patients met eligibility criteria. In unadjusted analysis, Black patients had a significantly higher overall death rate than White patients (HR_{Black vs. White} 1.51; 95% CI: 1.02-2.23, p = 0.041). The survival disparity did not remain significant in adjusted analysis, though controlling for covariates had little effect on the magnitude of the disparity (HR 1.46; 95% CI 0.93-2.31, p = 0.103). In adjusted models, presence of B symptoms, receipt of chemotherapy, stage of disease, and Other insurance were significantly associated with OS. Specifically, patients with B symptoms and those with Other insurance were more likely to die than those without B symptoms or private insurance, respectively (HR 1.75; 95% CI 1.22-2.50, p = 0.002) and (HR 2.56; 95% CI, 1.39-4.73, p = 0.0027), patients who did not receive chemotherapy were three times more likely to die than those who received chemotherapy (HR 3.10; CI 1.80-5.35, p < 0.001), and patients who presented with earlier stage disease were less likely to die from their disease than those with stage IV disease (stages I-III HR 0.34, CI 0.18-0.64, p < 0.001; HR 0.50, CI 0.30-0.82, p = 0.006, HR 0.72, CI 0.43-1.13, p = 0.152, respectively).

Conclusions

Our results suggest that racial disparities in survival may be mediated by clinical and treatment parameters.

SUBMITTER: Khullar K

PROVIDER: S-EPMC7926019 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Associations between race and survival in pediatric patients with diffuse large B-cell lymphoma.

Khullar Karishma K Plascak Jesse J JJ Drachtman Richard R Cole Peter D PD Parikh Rahul R RR

Cancer medicine 20210127 4

<h4>Background</h4>The purpose of this study was to examine the factors associated with disparities in overall survival (OS) by race in pediatric diffuse large B-cell lymphoma (DLBCL) patients.<h4>Methods</h4>We evaluated clinical features and survival among patients ≤21 years of age diagnosed with stage I-IV DLBCL from 2004 to 2014 from the National Cancer Database (NCDB) using a multivariable Cox proportional hazards model.<h4>Results</h4>Among 1386 pediatric patients with DLBCL, 1023 patients ...[more]

PMID: 33503323

Similar Datasets

Project description:Objectives/hypothesisThis study utilizes a large population national database to comprehensively analyze prognosticators and overall survival (OS) outcomes of varying treatment modalities in a large cohort of sinonasal diffuse large B-cell lymphoma (SN-DLBCL) patients.Study designRetrospective database study.MethodsThe National Cancer Database was queried for all SN-DLBCL cases diagnosed from 2004 to 2015. Kaplan-Meier log-rank test determined differences in OS based on clinical covariates. Cox proportional-hazards analysis was used to determine clinical and sociodemographic covariates predictive of mortality.ResultsA total of 2,073 SN-DLBCL patients were included, consisting of 48% female with a mean age of 66.0 ± 16.2 years. Overall, 82% of patients were Caucasian, 74% had early-stage disease, and 49% had primary tumors in the paranasal sinuses. Early-stage patients were more likely to receive multi-agent chemoradiotherapy compared to multi-agent chemotherapy alone (P < .001). Multivariable Cox proportional-hazards analysis revealed chemoradiotherapy to confer significantly greater OS improvements than chemotherapy alone (hazard ratio [HR]: 0.61; P < .001). However, subset analysis of late-stage patients demonstrated no significant differences in OS between these treatment modalities (P = .245). On multivariable analysis of chemotherapy patients treated post-2012, immunotherapy (HR = 0.51; P = .024) demonstrated significant OS benefits. However, subset analysis showed no significant advantage in OS with administering immunotherapy for late-stage patients (P = .326). Lastly, for all patients treated post-2012, those receiving immunotherapy had significantly improved OS compared to those not receiving immunotherapy (P < .001).ConclusionsTreatment protocol selection differs between early- and late-stage SN-DLBCL patients. Early-stage patients receiving chemotherapy may benefit from immunotherapy as part of their treatment paradigm.Level of evidence3 Laryngoscope, 131:E2727-E2735, 2021.

Project description:BackgroundThirty to forty percent of patients with Diffuse Large B-cell Lymphoma (DLBCL) have an adverse clinical evolution. The increased understanding of DLBCL biology has shed light on the clinical evolution of this pathology, leading to the discovery of prognostic factors based on gene expression data, genomic rearrangements and mutational subgroups. Nevertheless, additional efforts are needed in order to enable survival predictions at the patient level. In this study we investigated new machine learning-based models of survival using transcriptomic and clinical data.MethodsGene expression profiling (GEP) of in 2 different publicly available retrospective DLBCL cohorts were analyzed. Cox regression and unsupervised clustering were performed in order to identify probes associated with overall survival on the largest cohort. Random forests were created to model survival using combinations of GEP data, COO classification and clinical information. Cross-validation was used to compare model results in the training set, and Harrel's concordance index (c-index) was used to assess model's predictability. Results were validated in an independent test set.ResultsTwo hundred thirty-three and sixty-four patients were included in the training and test set, respectively. Initially we derived and validated a 4-gene expression clusterization that was independently associated with lower survival in 20% of patients. This pattern included the following genes: TNFRSF9, BIRC3, BCL2L1 and G3BP2. Thereafter, we applied machine-learning models to predict survival. A set of 102 genes was highly predictive of disease outcome, outperforming available clinical information and COO classification. The final best model integrated clinical information, COO classification, 4-gene-based clusterization and the expression levels of 50 individual genes (training set c-index, 0.8404, test set c-index, 0.7942).ConclusionOur results indicate that DLBCL survival models based on the application of machine learning algorithms to gene expression and clinical data can largely outperform other important prognostic variables such as disease stage and COO. Head-to-head comparisons with other risk stratification models are needed to compare its usefulness.

Dataset Information

Associations between race and survival in pediatric patients with diffuse large B-cell lymphoma.

Background

Methods

Results

Conclusions

Publications

Associations between race and survival in pediatric patients with diffuse large B-cell lymphoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets