Biologic, clinical, and sociodemographic predictors of multi-agent systemic therapy for non-Hodgkin lymphoma in people living with HIV: a population-based investigation in the state of Georgia

Abstract

We conducted a population-based study of biologic, clinical, and sociodemographic factors associated with receipt of multi-agent systemic therapy (MAST) by people living with HIV (PLWH) who were diagnosed with non-Hodgkin lymphoma (NHL). Building on recent registry-based analyses, we linked records from the Georgia Cancer Registry, Georgia HIV/AIDS Surveillance Registry, and the Georgia Hospital Discharge Database to identify 328 PLWH adults (age ≥ 18) diagnosed with NHL within 2004–2012. Through logistic regression modeling, we examined factors associated with patients receiving MAST for NHL. Robust predictors included CD4 count ≥200 cells/mm³ around the time of cancer diagnosis, an advanced stage (III or IV) diagnosis of NHL, MSM HIV transmission, and having private health insurance. The strongest single predictor of MAST was CD4 count. Because there is now guideline-integrated evidence that PLWH receiving standard-of-care cancer therapy can achieve substantially improved outcomes, it is vital they have access to regimens routinely provided to HIV-negative cancer patients.

Keywords:

• Non-Hodgson lymphoma
• HIV/AIDS
• multi-agent systemic therapy
• standard-of-care therapy

Acknowledgments

The authors have benefitted significantly from earlier discussions about the conceptualization of standard-of-care treatment for cancer patients with an HIV diagnosis with the following colleagues: Mary Jo Lechowicz, MD; Clifford Gunthel, MD; Taofeek Owonikoko, MD; Saurabh Chawla, MD; and Maria Russell, MD (all at Emory University). We have also benefitted from the early guidance and general advice provided by Eric Engels, PhD, of the National Cancer Institute. None of these individuals bear any responsibility for the analyses or conclusions presented here.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported in part by National Institutes of Health grant P30AI050409, with additional funding from the Winship Cancer Institute of Emory University. The collection of cancer incidence data in Georgia was supported by contract HHSN261201800003I, Task Order HHSN26100001 from the National Cancer Institute and cooperative agreement 5NU58DP003875-04 from the Centers for Disease Control and Prevention. The research reported in this paper was supported in part by the Biostatistics and Bioinformatics Shared Resource of the Winship Cancer Institute and the National Cancer Institute under award number P30CA138292. The contents are solely the responsibilities of the authors and do not necessarily represent the official views of the NCI, the CDC, or the GA Department of Public Health.