Patient Characteristics and Outcomes of Nodular Lymphocyte Predominant Hodgkin Lymphoma at a Safety-Net System Compared to an Academic Comprehensive Cancer Center

Patient Characteristics and Outcomes of Nodular Lymphocyte Predominant Hodgkin Lymphoma at a Safety-Net System Compared to an Academic Comprehensive Cancer Center | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Patient Characteristics and Outcomes of Nodular Lymphocyte Predominant Hodgkin Lymphoma at a Safety-Net System Compared to an Academic Comprehensive Cancer Center Luise Froessl, Theo Sottero, Steven Brown, Hsiao Li, Radhika Kainthla, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4131304/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2023 Read the published version in Blood → Version 1 posted You are reading this latest preprint version Abstract Nodular lymphocyte-predominant Hodgkin's lymphoma often follows an indolent course but carries a risk of late recurrence and transformation. Given its rarity, there is significant variability in the treatment patterns at various healthcare centers. This study aimed to compare the patient characteristics and outcomes of NLPHL patients treated at Parkland Health, the safety-net system for uninsured/underinsured patients in Dallas County with patients treated at the neighboring NCI-designated Harold C. Simmons Comprehensive Cancer Center (SCCC). Our cohort included 53 adult patients (25 at PH vs 28 at SCCC). PH patients were more likely to belong to racial/ethnic minority groups (Black non-Hispanic 84% at PH vs 32% at SCCC; Hispanic 16% at PH vs 0% at SCCC, p <0.01) and to be uninsured (60% at PH vs. 0% at SCCC, p <0.01). Overall, 38% of patients presented at a late stage (stage III-IV) and was not different based on site of care (11 at PH vs 9 at SCCC; p=0.37). Site of care (PH vs SCCC) or race/ethnicity did not impact the treatment choice. At a median follow-up of 60 months (IQR 21, 83), 6 recurrences and 5 transformations were noted. Overall median survival was 62 months (IQR 21.5-84.5). Despite health inequities that typically impact safety-net patients, we did not observe differences in treatment patterns or outcomes of Nodular lymphocyte-predominant Hodgkin Lymphoma between patients treated at PH compared to SCCC. Hodgkin’s Disease Nodular Lymphocyte Predominant Hodgkin’s Lymphoma Epidemiology Health Disparities 1. Introduction Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) constitutes a rare subtype of Hodgkin lymphoma (HL), accounting for about 5% of cases with an annual incidence of 0.1-0.2/100,000 (1). Like classic Hodgkin lymphoma (cHL), the malignant cells in NLPHL are derived from germinal center B cells, however, they are immunophenotypically distinct and generally exhibit CD20 positivity, CD30, and CD15 negativity (2). NLPHL resembles cHL in its predominance in the male population and has a bimodal age distribution, peaking in childhood and early adulthood. It is more prevalent in African Americans than in White Americans (3) (4). It has a favorable prognosis with approximately 80% of patients presenting at an early disease stage. In these patients, data has shown that even with involved field radiation therapy alone, progression-free survival can exceed 80% at 15 – 20 years (5). However, there is a risk of late recurrence and transformation, often to diffuse large B-cell lymphoma (DLBCL) (6). Management guidelines for NLPHL are extrapolated from cHL and/or draw from smaller retrospective studies. Active surveillance (AS) or involved-site radiation therapy (ISRT) is considered for non-bulky early-stage NLPHL, while combined modality therapy (CMT) is reserved for higher-risk patients, balancing the relatively indolent nature of the disease against the potential treatment toxicity (7). Given the rarity of NLPHL and the scarcity of data in the field, understanding the racial disparities in treatment patterns becomes a unique challenge. To explore the impact of factors such as race/ethnicity, insurance status, and access to care we compared patient characteristics and outcomes of patients with NLPHL treated at a safety-net system with those treated at an academic comprehensive cancer center. 2. Materials & Methods Parkland Health (PH) is the safety-net system for uninsured or underinsured patients in Dallas County and is affiliated with the UT Southwestern NCI-designated Harold C. Simmons Comprehensive Cancer Center (SCCC). An IRB-approved review of electronic health records of patients at both sites was performed. Patients (age > 18) diagnosed with NLPHL between January 1st, 2007, and December 31 st , 2022, were reviewed, and data on demographics, disease characteristics, treatments, and outcomes were collected. Statistical analysis was performed. Percentages were compared using the chi-square test, means with their respective standard deviation were calculated using the t-test, and medians with interquartile ranges (IQRs) were assessed using the rank-sum test. All confidence intervals were set at 95%, with statistical significance achieved at an alpha value of <0.05. The statistical software used was SPSS (version 25). Table 1 Total Patients (N =53) SCCC (N=28) PH (N=25) P-value* Female, n (%) 18 (34) 7 (25) 11 (44) 0.15 Age at Diagnosis, Mean ± SD 44.2 ± 15.0 46.5 ± 16.2 41.7 ± 13.5 0.26 Race/Ethnicity, n (%) White Non-Hispanic Black Non-Hispanic Hispanic Other 18 (34) 30 (57) 4 (8) 1 (2) 18 (64) 9 (32) 0 (0) 1 (4) 0 (0) 21 (84) 4 (16) 0 (0) <0.01 Insurance, n (%) Private Medicare Medicaid PFA Unknown 20 (37) 9 (17) 4 (7) 15 (28) 5 (9) 16 (57) 8 (29) 1 (4) 0 (0) 3 (11) 4 (16) 1 (4) 3 (12) 15 (60) 2 (8) <0.01 Stage I/II Stage III/IV 33 (62) 20 (37) 19 (68) 9 (32) 14 (56) 11 (44) 0.37 Treatment, n (%) Chemo only Combined modality Observation Radiation only SCT Unknown 22 (42) 12 (23) 4 (7) 11 (21) 3 (6) 1 (2) 14 (50) 5 (18) 1 (4) 5 (18) 2 (7) 1 (4) 8 (32) 7 (28) 3 (12) 6 (24) 1 (4) 0 (0) 0.52 Response to Therapy, n (%) CR PR SD Unknown 40 (75) 5 (9) 4 (7) 4 (7) 21 (75) 3 (11) 1 (4) 3 (11) 19 (76) 2 (8) 3 (12) 1 (4) 0.54 Progression free survival, Median (IQR) 37.0 (13.0, 65.0) 46.5 (13.75, 65.75) 28.5 (12.25, 64.25) 0.52 Overall Survival, Median (IQR) 62.0 (21.0, 100.5) 60.0 (37.75, 82.75) 62.0 (19.0, 137.0) 0.72 Follow up, Median (IQR) 58.0 (20.0, 83.0) 60.0 (36.0, 82.25) 53.0 (17.5, 111.0) 0.96 *n (%) compared with Chi-square; Mean ± SD compared with T-test; Median (IQR) compared with Rank sum test 3. Results 53 patients were included in the study, with 25 at PH and 28 at SCCC. Among them, 18 patients were White Non-Hispanic (WNH), 30 were Black Non-Hispanic (BNH), 4 were Hispanic (HISP), and 1 belonged to another racial group. The median age at diagnosis was 42 (IQR 32, 54.5) and not significantly different between institutions (41.7 at PH vs. 46.5 at SCCC) or racial groups (48.4 for WNH, 41.7 for BNH, 43.8 for HISP). Male predominance was more evident at SCCC compared to PH (75% vs 56% male, p = 0.15) and was less significant in the BNH population (WNH 78%, BNH 57%, HISP 75% male, p = 0.4) though not achieving statistical significance. PH patients were more likely to be from racial/ethnic minority groups (BNH 84% at PH vs 32% at SCCC; HISP 16% at PH vs 0% at SCCC, p <0.01) and to be uninsured (60% at PH vs. 0% at SCCC, p <0.01). The stage at presentation was similar between the two sites (Stage I/II 68% at SCCC vs 56% at PH, p = 0.37; Stage III-IV 32% at SCCC vs 44% at PH, p = 0.37) and among racial groups (Stage I/II: 61% of WNH, 67% of BNH, 25% of HISP, p = 0.36). Treatment modalities included observation alone (n = 4, 7%), radiation alone (n = 11, 21%), combination chemotherapy and/or rituximab (n = 22, 42%), or combined modality treatment (n = 12, 23%). Of the patients that received chemotherapy, either alone or as a combined treatment, 10 (29%) patients received an ABVD-based regimen, 15 (34%) received a CHOP-based regimen, and 9 (26%) received a different regimen. Site of care or race/ethnicity did not impact the treatment choice. At a median follow-up of 60 months (IQR 21, 83), 6 recurrences and 5 transformations were observed, with 3 deaths occurring during this period, resulting in an overall median survival (OS) of 62 months (IQR 21.5, 84.5). Comparing the two sites of care, no statistically significant differences were noted in median progression-free survival (PFS) (28.5 months at PH vs 46.5 months at SCCC, p = 0.52) or median OS (62 months at PH vs 60 months at SCCC), with a comparable median follow-up period (53 months at PH vs 60 months at SCCC). Similarly, no significant differences in median PFS (WNH 44.5 months, BNH 36 months, HISP 12 months, p = 0.65) or median OS (WNH 54.5 months, BNH 65.5 months, HISP 37 months, p = 0.68) were observed between racial groups, with comparable median follow up periods (WNH 54.5 months, BNH 65.5 months, HISP 11.5 months, p = 0.19). 4. Discussion Existing data on various hematological malignancies has revealed notable disparities among racial and ethnic minority groups, as well as individuals with limited or no insurance coverage. This trend is seen both in aggressive malignancies such as DLBCL and more indolent conditions such as follicular lymphoma (FL). Patients from traditionally underserved groups tend to present at a younger age with often more advanced disease (8) (9). Disparities extend to treatment modalities, with notable differences in both the selection of treatment and outcomes among racial and ethnic minority groups, even when controlling for the administered treatment (9). Insurance status has also been shown to impact treatment choices and survival rates. Han et al. demonstrated that uninsured patients or Medicaid-insured patients with DLBCL experienced poorer survival compared to their privately insured counterparts (10). These findings underscore the existence of significant discrepancies in care for specific patient subgroups, highlighting the need for a thorough examination of these gaps and the implementation of appropriate remedies. To the best of our knowledge, no prior data comparing treatment patterns and outcomes for patients with NLPHL treated at a safety-net system versus a comprehensive cancer center in the same geographic location exists. Given the rarity of NLPHL and the absence of a standardized treatment approach, some degree of variability in management practices is anticipated. This variability could potentially pose an additional risk for underserved groups with limited healthcare access, leading to worse outcomes. The patient populations served by PH and SCCC exhibit distinct levels of access to health care, as evidenced by the notably higher percentage of uninsured individuals at PH. Furthermore, patients at PH were more likely to belong to a racial or ethnic minority group, with our analysis revealing that 84% and 32% of the populations at PH and SCCC respectively, consisted of African-American patients and 16% and 0% were of Hispanic ethnicity. Notably, NLPHL occurs approximately twice as frequently in African-American individuals compared to their white-American counterparts with unique characteristics within the African American subgroup, such as a lack of male preponderance and younger age at presentation (9), a pattern that is reflected in our cohort. Existing data highlights the disparities faced by this patient subgroup in terms of treatment. Olszewski et al. conducted a race-based analysis of patients with NLPHL using data from the National Cancer Database (NCDB) spanning from 1998 to 2011. Despite the inclusion of a substantial number of patients in this analysis (n = 1,366), the study faced limitations due to the nature of the data source, which restricted the extraction of certain pertinent details and precluded central pathology review. Nevertheless, the analysis of NCBD NLPHL patients revealed several differences between African-American and white individuals, including prolonged treatment delays, a significantly higher percentage of individuals with no recorded treatment in early-stage disease, and a lengthier time to treatment initiation in the African American subgroup. However, no disparities in overall survival or treatment outcomes were observed. In contrast, our analysis indicated no significant differences in the stage at presentation or the initial treatment modality between the PH population (with a higher proportion of African Americans) and the SCCC group possibly attributable to a smaller sample size. Survival outcomes also did not differ between sites of care or racial groups in our analysis. The absence of statistically significant differences in survival outcomes among subgroups traditionally facing healthcare disparities in NLPHL may, in part, stem from the inherently indolent nature of this disease, which persists even at more advanced stages. In our study, with a median follow-up of 60 months, the indolent behavior of NLPHL is evident, aligning with other studies reporting progression-free survival rates of 95% and 89% at 5 and 10 years, respectively, in early-stage disease (1). This suggests that more extended follow-up periods may be necessary to discern statistically significant differences in mortality outcomes. However, it is crucial to acknowledge the unique model of PH. Beyond providing inpatient and emergency care, PH provides an extensive network of outpatient care clinics. Uninsured or underfunded patients can access these services through the 'Patient Financial Assistance' charity program, which operates on a graded scale based on income, offering up to 100% coverage. It is plausible that traditionally disadvantaged groups in safety-net systems with fewer resources may experience prolonged delays in accessing care, potentially resulting in poorer outcomes. This underscores the importance of considering not only the disease characteristics but also the intricacies of the healthcare delivery system when interpreting survival data in NLPHL. The available data guiding management strategies and chemotherapy regimen selection for NLPHL is limited, with a lack of randomized controlled trials and only limited prospective data available for this condition. The current treatment consensus largely relies on extrapolation from guidelines in cHL, or on trials encompassing both cHL and NLPHL patients, despite the perceived clinical and pathological distinctions between these entities (7) (11). Notably, NLPHL's pathogenesis is thought to be more related to DLBCL in certain aspects, evidenced by its propensity to transform into this entity (12). Variant type NLPHL, observed in 25% of cases, presents a more aggressive histopathological pattern, resembling certain B-cell lymphomas such as T-cell histiocyte-rich large B-cell lymphoma (13). The prognosis of NLPHL, in both the typical and variant histology, remains favorable. However, the variant-type disease tends to present at a later stage and with more frequent and earlier relapses (14). This histological distinction is not presently a factor guiding treatment selection. Treatment options range from limited-field RT alone in stage IA to CMT in early and intermediate-stage disease to chemotherapy alone in advanced stages. The choice of chemotherapy regimen typically draws from what has demonstrated efficacy in cHL and DLBCL (11). In certain instances, high-dose chemotherapy and stem cell transplant may be considered in high-risk advanced-stage or transformed disease (15). However, evidence suggests that this approach may not always be suitable in NLPHL. When controlling for stage, NLPHL patients generally exhibit a more favorable prognosis than cHL patients (16). Yet, a matched pair outcome analysis by Xing et al in 2020 revealed a shorter time to progression in advanced-stage NLPHL patients treated with an ABVD regimen compared to cHL patients, suggesting a fundamentally different disease pathogenesis requiring unique management (17). The considerable variability in treatment patterns adds complexity to comparing outcomes in distinct populations across different treatment sites. Recent data also indicates that less aggressive treatment approaches may yield equally favorable outcomes with potentially fewer toxicities, particularly in early-stage disease (18) (19). This suggests that what may be perceived as undertreatment according to current recommendations might not necessarily result in worse survival outcomes. Nevertheless, our analysis did not reveal a significant difference in treatment choices between the two care sites, despite variations in the proportion of traditionally disadvantaged subgroups treated at each site of care. Our study adds valuable insights to the limited pool of existing data on NLPHL. Unlike previous studies, our data comes from a more recent timeframe, offering a contemporary perspective. Additionally, diagnoses were confirmed by central pathology review at an academic medical center. We manually verified the gathered data and missing data points were collected as necessary. It is important to acknowledge the inherent limitations of our study, which, in part, stems from the retrospective design. The small number of included patients is an unavoidable constraint given the rarity of the disease entity. Furthermore, the relatively short follow-up period poses challenges, especially when studying an indolent disease like NLPHL. Longer observation periods would likely be required to detect significant differences in outcomes. In conclusion, despite the differences in patient demographics and insurance status, our analysis revealed no significant disparities in treatment approaches or mortality outcomes between the PH safety net system and the SCCC. This intriguing finding may be attributed to the unique attributes of the PH system, emphasizing the importance of understanding not only the disease's intricacies but also the impact of healthcare delivery models on treatment outcomes. Despite certain limitations, our study contributes valuable insights into the complex landscape of NLPHL, prompting consideration of not only the disease's unique characteristics but also the complexities of healthcare systems in influencing outcomes. Future investigations with larger cohorts and prolonged follow-up periods are warranted to refine our understanding of NLPHL and inform more robust management strategies. Declarations Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request. Funding Statement: No funding was received for the production of this research. Conflict of Interest Disclosure: None of the authors listed have any conflicts of interest to disclose. Ethics Approval Statement: N/A Patient Consent Statement: N/A Permission to reproduce material from other sources: N/A Clinical Trial Registration: N/A References Eichenauer DA, Engert A. Nodular lymphocyte-predominant Hodgkin lymphoma: a unique disease deserving unique management. Hematology. 2017 Dec 8;2017(1):324–8. Savage KJ, Mottok A, Fanale M. Nodular lymphocyte-predominant Hodgkin lymphoma. Seminars in Hematology. 2016 Jul 1;53(3):190–202. Morton LM, Wang SS, Devesa SS, Hartge P, Weisenburger DD, Linet MS. Lymphoma incidence patterns by WHO subtype in the United States, 1992-2001. Blood. 2006 Jan 1;107(1):265–76. Olszewski AJ, Shrestha R, Cook NM. Race-specific features and outcomes of nodular lymphocyte-predominant Hodgkin lymphoma: Analysis of the National Cancer Data Base: Race-Specific Features of NLPHL. Cancer. 2015 Oct 1;121(19):3472–80. Wirth A, Yuen K, Barton M, Roos D, Gogna K, Pratt G, et al. Long-term outcome after radiotherapy alone for lymphocyte-predominant Hodgkin lymphoma. Cancer. 2005;104(6):1221–9. Al-Mansour M, Connors JM, Gascoyne RD, Skinnider B, Savage KJ. Transformation to Aggressive Lymphoma in Nodular Lymphocyte-Predominant Hodgkin’s Lymphoma. JCO. 2010 Feb 10;28(5):793–9. Eichenauer DA, Engert A. How I treat nodular lymphocyte-predominant Hodgkin lymphoma. Blood. 2020 Dec 24;136(26):2987–93. Nabhan C, Byrtek M, Taylor MD, Friedberg JW, Cerhan JR, Hainsworth JD, et al. Racial differences in presentation and management of follicular non-Hodgkin lymphoma in the United States: report from the National LymphoCare Study. Cancer. 2012 Oct 1;118(19):4842–50. Flowers CR, Shenoy PJ, Borate U, Bumpers K, Douglas-Holland T, King N, et al. Examining Racial Differences in Diffuse Large B-Cell Lymphoma Presentation and Survival. Leuk Lymphoma. 2013 Feb;54(2):268–76. Han X, Jemal A, Flowers CR, Sineshaw H, Nastoupil LJ, Ward E. Insurance status is related to diffuse large B-cell lymphoma survival. Cancer. 2014 Apr 15;120(8):1220–7. Fanale M. Lymphocyte-predominant Hodgkin lymphoma: what is the optimal treatment? Hematology Am Soc Hematol Educ Program. 2013;2013:406–13. Huang JZ, Weisenburger DD, Vose JM, Greiner TC, Aoun P, Chan WC, et al. Diffuse large B-cell lymphoma arising in nodular lymphocyte predominant Hodgkin lymphoma: a report of 21 cases from the Nebraska Lymphoma Study Group. Leuk Lymphoma. 2004 Aug;45(8):1551–7. Hartmann S, Eichenauer DA. Nodular lymphocyte predominant Hodgkin lymphoma: pathology, clinical course and relation to T-cell/histiocyte rich large B-cell lymphoma. Pathology. 2020 Jan 1;52(1):142–53. Fan Z, Natkunam Y, Bair E, Tibshirani R, Warnke RA. Characterization of variant patterns of nodular lymphocyte predominant hodgkin lymphoma with immunohistologic and clinical correlation. Am J Surg Pathol. 2003 Oct;27(10):1346–56. Lo AC, Major A, Super L, Appel B, Shankar A, Constine LS, et al. Practice patterns for the management of nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL): an international survey by the Global NLPHL One Working Group (GLOW). Leukemia & Lymphoma. 2022 Jul 3;63(8):1997–2000. Gerber NK, Atoria CL, Elkin EB, Yahalom J. Characteristics and Outcomes of Patients With Nodular Lymphocyte-Predominant Hodgkin Lymphoma Versus Those With Classical Hodgkin Lymphoma: A Population-Based Analysis. International Journal of Radiation Oncology, Biology, Physics. 2015 May 1;92(1):76–83. Xing KH, Connors JM, Lai A, Al-Mansour M, Sehn LH, Villa D, et al. Advanced-stage nodular lymphocyte predominant Hodgkin lymphoma compared with classical Hodgkin lymphoma: a matched pair outcome analysis. Blood. 2014 Jun 5;123(23):3567–73. Borchmann S, Joffe E, Moskowitz CH, Zelenetz AD, Noy A, Portlock CS, et al. Active surveillance for nodular lymphocyte-predominant Hodgkin lymphoma. Blood. 2019 May 16;133(20):2121–9. Appel BE, Chen L, Buxton AB, Hutchison RE, Hodgson DC, Ehrlich PF, et al. Minimal Treatment of Low-Risk, Pediatric Lymphocyte-Predominant Hodgkin Lymphoma: A Report From the Children’s Oncology Group. J Clin Oncol. 2016 Jul 10;34(20):2372–9. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2023 Read the published version in Blood → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4131304","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":286209890,"identity":"ce7f783b-b905-4e8e-9f89-f6877647ed11","order_by":0,"name":"Luise Froessl","email":"data:image/png;base64,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","orcid":"","institution":"UT Southwestern Medical Center","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Luise","middleName":"","lastName":"Froessl","suffix":""},{"id":286209892,"identity":"b9256547-b4e4-4135-9646-33ff6e9b154b","order_by":1,"name":"Theo Sottero","email":"","orcid":"","institution":"UT Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Theo","middleName":"","lastName":"Sottero","suffix":""},{"id":286209894,"identity":"0cf24f39-eb34-4296-b9a2-a6eca6b3fb76","order_by":2,"name":"Steven Brown","email":"","orcid":"","institution":"Parkland Health and Hospital System","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Steven","middleName":"","lastName":"Brown","suffix":""},{"id":286209896,"identity":"9f612866-528b-4928-8419-1e3e6790c24b","order_by":3,"name":"Hsiao Li","email":"","orcid":"","institution":"UT Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hsiao","middleName":"","lastName":"Li","suffix":""},{"id":286209898,"identity":"c80ca13c-38e8-4619-b762-b983ff4cb770","order_by":4,"name":"Radhika Kainthla","email":"","orcid":"","institution":"UT Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Radhika","middleName":"","lastName":"Kainthla","suffix":""},{"id":286209901,"identity":"1181136d-fdcf-429a-ba9d-0b87d77b5ac5","order_by":5,"name":"Navid Sadeghi","email":"","orcid":"","institution":"UT Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Navid","middleName":"","lastName":"Sadeghi","suffix":""}],"badges":[],"createdAt":"2024-03-19 14:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4131304/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4131304/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1182/blood-2023-173465","type":"published","date":"2023-11-28T10:36:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54084135,"identity":"75d180d5-b333-4013-ac32-ffd161f9f73c","added_by":"auto","created_at":"2024-04-04 10:44:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":181408,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4131304/v1/399ee920-e759-47b3-8154-833f8cf584bf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Patient Characteristics and Outcomes of Nodular Lymphocyte Predominant Hodgkin Lymphoma at a Safety-Net System Compared to an Academic Comprehensive Cancer Center","fulltext":[{"header":"1.\tIntroduction","content":"\u003cp\u003eNodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) constitutes a rare subtype of Hodgkin lymphoma (HL), accounting for about 5% of cases with an annual incidence of 0.1-0.2/100,000\u0026nbsp;(1). Like classic Hodgkin lymphoma (cHL), the malignant cells in NLPHL are derived from germinal center B cells, however, they are immunophenotypically distinct and generally exhibit CD20 positivity, CD30, and CD15 negativity\u0026nbsp;(2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;NLPHL resembles cHL in its predominance in the male population and has a bimodal age distribution, peaking in childhood and early adulthood. It is more prevalent in African Americans than in White Americans\u0026nbsp;(3)\u0026nbsp;(4). It has a favorable prognosis with approximately 80% of patients presenting at an early disease stage. In these patients, data has shown that even with involved field radiation therapy alone, progression-free survival can exceed 80% at 15 \u0026ndash; 20 years\u0026nbsp;(5). However, there is a risk of late recurrence and transformation, often to diffuse large B-cell lymphoma (DLBCL)\u0026nbsp;(6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eManagement guidelines for NLPHL are extrapolated from cHL and/or draw from smaller retrospective studies. Active surveillance (AS) or involved-site radiation therapy (ISRT) is considered for non-bulky early-stage NLPHL, while combined modality therapy (CMT) is reserved for higher-risk patients, balancing the relatively indolent nature of the disease against the potential treatment toxicity\u0026nbsp;(7).\u003c/p\u003e\n\u003cp\u003eGiven the rarity of NLPHL and the scarcity of data in the field, understanding the racial disparities in treatment patterns becomes a unique challenge. To explore the impact of factors such as race/ethnicity, insurance status, and access to care we compared patient characteristics and outcomes of patients with NLPHL treated at a safety-net system with those treated at an academic comprehensive cancer center.\u003c/p\u003e"},{"header":"2.\tMaterials \u0026 Methods","content":"\u003cp\u003eParkland Health (PH) is the safety-net system for uninsured or underinsured patients in Dallas County and is affiliated with the UT Southwestern NCI-designated Harold C. Simmons Comprehensive Cancer Center (SCCC). An IRB-approved review of electronic health records of patients at both sites was performed. Patients (age \u0026gt; 18) diagnosed with NLPHL between January 1st, 2007, and December 31\u003csup\u003est\u003c/sup\u003e, 2022, were reviewed, and data on demographics, disease characteristics, treatments, and outcomes were collected. Statistical analysis was performed. Percentages were compared using the chi-square test, means with their respective standard deviation were calculated using the t-test, and medians with interquartile ranges (IQRs) were assessed using the rank-sum test. All confidence intervals were set at 95%, with statistical significance achieved at an alpha value of \u0026lt;0.05. \u0026nbsp;The statistical software used was SPSS (version 25). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003eTotal Patients (N =53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003eSCCC (N=28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003ePH (N=25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003eP-value*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eFemale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e18 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e7 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e11 (44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eAge at Diagnosis, Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e44.2 \u0026plusmn; 15.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e46.5 \u0026plusmn; 16.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e41.7 \u0026plusmn; 13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eRace/Ethnicity, n (%)\u003c/p\u003e\n \u003cp\u003eWhite Non-Hispanic\u003c/p\u003e\n \u003cp\u003eBlack Non-Hispanic\u003c/p\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (34)\u003c/p\u003e\n \u003cp\u003e30 (57)\u003c/p\u003e\n \u003cp\u003e4 (8)\u003c/p\u003e\n \u003cp\u003e1 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (64)\u003c/p\u003e\n \u003cp\u003e9 (32)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e21 (84)\u003c/p\u003e\n \u003cp\u003e4 (16)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eInsurance, n (%)\u003c/p\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003cp\u003ePFA\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20 (37)\u003c/p\u003e\n \u003cp\u003e9 (17)\u003c/p\u003e\n \u003cp\u003e4 (7)\u003c/p\u003e\n \u003cp\u003e15 (28)\u003c/p\u003e\n \u003cp\u003e5 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16 (57)\u003c/p\u003e\n \u003cp\u003e8 (29)\u003c/p\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e3 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (16)\u003c/p\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003cp\u003e3 (12)\u003c/p\u003e\n \u003cp\u003e15 (60)\u003c/p\u003e\n \u003cp\u003e2 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eStage I/II\u003c/p\u003e\n \u003cp\u003eStage III/IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e33 (62)\u003c/p\u003e\n \u003cp\u003e20 (37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e19 (68)\u003c/p\u003e\n \u003cp\u003e9 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e14 (56)\u003c/p\u003e\n \u003cp\u003e11 (44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eTreatment, n (%)\u003c/p\u003e\n \u003cp\u003eChemo only\u003c/p\u003e\n \u003cp\u003eCombined modality\u003c/p\u003e\n \u003cp\u003eObservation\u003c/p\u003e\n \u003cp\u003eRadiation only\u003c/p\u003e\n \u003cp\u003eSCT\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22 (42)\u003c/p\u003e\n \u003cp\u003e12 (23)\u003c/p\u003e\n \u003cp\u003e4 (7)\u003c/p\u003e\n \u003cp\u003e11 (21)\u003c/p\u003e\n \u003cp\u003e3 (6)\u003c/p\u003e\n \u003cp\u003e1 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14 (50)\u003c/p\u003e\n \u003cp\u003e5 (18)\u003c/p\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003cp\u003e5 (18)\u003c/p\u003e\n \u003cp\u003e2 (7)\u003c/p\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8 (32)\u003c/p\u003e\n \u003cp\u003e7 (28)\u003c/p\u003e\n \u003cp\u003e3 (12)\u003c/p\u003e\n \u003cp\u003e6 (24)\u003c/p\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eResponse to Therapy, n (%)\u003c/p\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40 (75)\u003c/p\u003e\n \u003cp\u003e5 (9)\u003c/p\u003e\n \u003cp\u003e4 (7)\u003c/p\u003e\n \u003cp\u003e4 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21 (75)\u003c/p\u003e\n \u003cp\u003e3 (11)\u003c/p\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003cp\u003e3 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (76)\u003c/p\u003e\n \u003cp\u003e2 (8)\u003c/p\u003e\n \u003cp\u003e3 (12)\u003c/p\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eProgression free survival, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e37.0 (13.0, 65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e46.5 (13.75, 65.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e28.5 (12.25, 64.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eOverall Survival, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e62.0 (21.0, 100.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e60.0 (37.75, 82.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e62.0 (19.0, 137.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.96629213483146%\" valign=\"top\"\u003e\n \u003cp\u003eFollow up, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.003210272873194%\" valign=\"top\"\u003e\n \u003cp\u003e58.0 (20.0, 83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.261637239165328%\" valign=\"top\"\u003e\n \u003cp\u003e60.0 (36.0, 82.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.21187800963082%\" valign=\"top\"\u003e\n \u003cp\u003e53.0 (17.5, 111.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*n (%) compared with Chi-square; Mean \u0026plusmn; SD compared with T-test; Median (IQR) compared with Rank sum test\u003c/p\u003e"},{"header":"3.\tResults","content":"\u003cp\u003e53 patients were included in the study, with 25 at PH and 28 at SCCC. Among them, 18 patients were White Non-Hispanic (WNH), 30 were Black Non-Hispanic (BNH), 4 were Hispanic (HISP), and 1 belonged to another racial group. The median age at diagnosis was 42 (IQR 32, 54.5) and not significantly different between institutions (41.7 at PH vs. 46.5 at SCCC) or racial groups (48.4 for WNH, 41.7 for BNH, 43.8 for HISP). Male predominance was more evident at SCCC compared to PH (75% vs 56% male, p = 0.15) and was less significant in the BNH population (WNH 78%, BNH 57%, HISP 75% male, p = 0.4) though not achieving statistical significance. PH patients were more likely to be from racial/ethnic minority groups (BNH 84% at PH vs 32% at SCCC; HISP 16% at PH vs 0% at SCCC, p \u0026lt;0.01) and to be uninsured (60% at PH vs. 0% at SCCC, p \u0026lt;0.01). The stage at presentation was similar between the two sites (Stage I/II 68% at SCCC vs 56% at PH, p = 0.37; Stage III-IV 32% at SCCC vs 44% at PH, p = 0.37) and among racial groups (Stage I/II: 61% of WNH, 67% of BNH, 25% of HISP, p = 0.36). Treatment modalities included observation alone (n = 4, 7%), radiation alone (n = 11, 21%), combination chemotherapy and/or rituximab (n = 22, 42%), or combined modality treatment (n = 12, 23%). Of the patients that received chemotherapy, either alone or as a combined treatment, 10 (29%) patients received an ABVD-based regimen, 15 (34%) received a CHOP-based regimen, and 9 (26%) received a different regimen. Site of care or race/ethnicity did not impact the treatment choice. At a median follow-up of 60 months (IQR 21, 83), 6 recurrences and 5 transformations were observed, with 3 deaths occurring during this period, resulting in an overall median survival (OS) of 62 months (IQR 21.5, 84.5). Comparing the two sites of care, no statistically significant differences were noted in median progression-free survival (PFS) (28.5 months at PH vs 46.5 months at SCCC, p = 0.52) or median OS (62 months at PH vs 60 months at SCCC), with a comparable median follow-up period (53 months at PH vs 60 months at SCCC). Similarly, no significant differences in median PFS (WNH 44.5 months, BNH 36 months, HISP 12 months, p = 0.65) or median OS (WNH 54.5 months, BNH 65.5 months, HISP 37 months, p = 0.68) were observed between racial groups, with comparable median follow up periods (WNH 54.5 months, BNH 65.5 months, HISP 11.5 months, p = 0.19).\u003c/p\u003e"},{"header":"4.\tDiscussion","content":"\u003cp\u003eExisting data on various hematological malignancies has revealed notable disparities among racial and ethnic minority groups, as well as individuals with limited or no insurance coverage. This trend is seen both in aggressive malignancies such as DLBCL and more indolent conditions such as follicular lymphoma (FL). Patients from traditionally underserved groups tend to present at a younger age with often more advanced disease\u0026nbsp;(8)\u0026nbsp;(9). Disparities extend to treatment modalities, with notable differences in both the selection of treatment and outcomes among racial and ethnic minority groups, even when controlling for the administered treatment\u0026nbsp;(9). Insurance status has also been shown to impact treatment choices and survival rates. Han et al. demonstrated that uninsured patients or Medicaid-insured patients with DLBCL experienced poorer survival compared to their privately insured counterparts\u0026nbsp;(10). These findings underscore the existence of significant discrepancies in care for specific patient subgroups, highlighting the need for a thorough examination of these gaps and the implementation of appropriate remedies. To the best of our knowledge, no prior data comparing treatment patterns and outcomes for patients with NLPHL treated at a safety-net system versus a comprehensive cancer center in the same geographic location exists.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Given the rarity of NLPHL and the absence of a standardized treatment approach, some degree of variability in management practices is anticipated. This variability could potentially pose an additional risk for underserved groups with limited healthcare access, leading to worse outcomes. The patient populations served by PH and SCCC exhibit distinct levels of access to health care, as evidenced by the notably higher percentage of uninsured individuals at PH. Furthermore, patients at PH were more likely to belong to a racial or ethnic minority group, with our analysis revealing that 84% and 32% of the populations at PH and SCCC respectively, consisted of African-American patients and 16% and 0% were of Hispanic ethnicity. Notably, NLPHL occurs approximately twice as frequently in African-American individuals compared to their white-American counterparts with unique characteristics within the African American subgroup, such as a lack of male preponderance and younger age at presentation\u0026nbsp;(9), a pattern that is reflected in our cohort. Existing data highlights the disparities faced by this patient subgroup in terms of treatment. Olszewski et al. conducted a race-based analysis of patients with NLPHL using data from the National Cancer Database (NCDB) spanning from 1998 to 2011. Despite the inclusion of a substantial number of patients in this analysis (n = 1,366), the study faced limitations due to the nature of the data source, which restricted the extraction of certain pertinent details and precluded central pathology review. Nevertheless, the analysis of NCBD NLPHL patients revealed several differences between African-American and white individuals, including prolonged treatment delays, a significantly higher percentage of individuals with no recorded treatment in early-stage disease, and a lengthier time to treatment initiation in the African American subgroup. However, no disparities in overall survival or treatment outcomes were observed. In contrast, our analysis indicated no significant differences in the stage at presentation or the initial treatment modality between the PH population (with a higher proportion of African Americans) and the SCCC group possibly attributable to a smaller sample size. Survival outcomes also did not differ between sites of care or racial groups in our analysis.\u003c/p\u003e\n\u003cp\u003eThe absence of statistically significant differences in survival outcomes among subgroups traditionally facing healthcare disparities in NLPHL may, in part, stem from the inherently indolent nature of this disease, which persists even at more advanced stages. In our study, with a median follow-up of 60 months, the indolent behavior of NLPHL is evident, aligning with other studies reporting progression-free survival rates of 95% and 89% at 5 and 10 years, respectively, in early-stage disease\u0026nbsp;(1). This suggests that more extended follow-up periods may be necessary to discern statistically significant differences in mortality outcomes.\u003c/p\u003e\n\u003cp\u003eHowever, it is crucial to acknowledge the unique model of PH. Beyond providing inpatient and emergency care, PH provides an extensive network of outpatient care clinics. Uninsured or underfunded patients can access these services through the \u0026apos;Patient Financial Assistance\u0026apos; charity program, which operates on a graded scale based on income, offering up to 100% coverage. It is plausible that traditionally disadvantaged groups in safety-net systems with fewer resources may experience prolonged delays in accessing care, potentially resulting in poorer outcomes. This underscores the importance of considering not only the disease characteristics but also the intricacies of the healthcare delivery system when interpreting survival data in NLPHL.\u003c/p\u003e\n\u003cp\u003eThe available data guiding management strategies and chemotherapy regimen selection for NLPHL is limited, with a lack of randomized controlled trials and only limited prospective data available for this condition. The current treatment consensus largely relies on extrapolation from guidelines in cHL, or on trials encompassing both cHL and NLPHL patients, despite the perceived clinical and pathological distinctions between these entities\u0026nbsp;(7)\u0026nbsp;(11). Notably, NLPHL\u0026apos;s pathogenesis is thought to be more related to DLBCL in certain aspects, evidenced by its propensity to transform into this entity\u0026nbsp;(12). Variant type NLPHL, observed in 25% of cases, presents a more aggressive histopathological pattern, resembling certain B-cell lymphomas such as T-cell histiocyte-rich large B-cell lymphoma\u0026nbsp;(13). The prognosis of NLPHL, in both the typical and variant histology, remains favorable. However, the variant-type disease tends to present at a later stage and with more frequent and earlier relapses\u0026nbsp;(14). This histological distinction is not presently a factor guiding treatment selection.\u003c/p\u003e\n\u003cp\u003eTreatment options range from limited-field RT alone in stage IA to CMT in early and intermediate-stage disease to chemotherapy alone in advanced stages. The choice of chemotherapy regimen typically draws from what has demonstrated efficacy in cHL and DLBCL\u0026nbsp;(11). In certain instances, high-dose chemotherapy and stem cell transplant may be considered in high-risk advanced-stage or transformed disease\u0026nbsp;(15). However, evidence suggests that this approach may not always be suitable in NLPHL. When controlling for stage, NLPHL patients generally exhibit a more favorable prognosis than cHL patients\u0026nbsp;(16). Yet, a matched pair outcome analysis by Xing et al in 2020 revealed a shorter time to progression in advanced-stage NLPHL patients treated with an ABVD regimen compared to cHL patients, suggesting a fundamentally different disease pathogenesis requiring unique management\u0026nbsp;(17). The considerable variability in treatment patterns adds complexity to comparing outcomes in distinct populations across different treatment sites.\u003c/p\u003e\n\u003cp\u003eRecent data also indicates that less aggressive treatment approaches may yield equally favorable outcomes with potentially fewer toxicities, particularly in early-stage disease\u0026nbsp;(18)\u0026nbsp;(19). This suggests that what may be perceived as undertreatment according to current recommendations might not necessarily result in worse survival outcomes. Nevertheless, our analysis did not reveal a significant difference in treatment choices between the two care sites, despite variations in the proportion of traditionally disadvantaged subgroups treated at each site of care.\u003c/p\u003e\n\u003cp\u003eOur study adds valuable insights to the limited pool of existing data on NLPHL. Unlike previous studies, our data comes from a more recent timeframe, offering a contemporary perspective. Additionally, diagnoses were confirmed by central pathology review at an academic medical center. We manually verified the gathered data and missing data points were collected as necessary. It is important to acknowledge the inherent limitations of our study, which, in part, stems from the retrospective design.\u0026nbsp;The small number of included patients is an unavoidable constraint given the rarity of the disease entity. Furthermore, the relatively short follow-up period poses challenges, especially when studying an indolent disease like NLPHL. Longer observation periods would likely be required to detect significant differences in outcomes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn conclusion, despite the differences in patient demographics and insurance status, our analysis revealed no significant disparities in treatment approaches or mortality outcomes between the PH safety net system and the SCCC. This intriguing finding may be attributed to the unique attributes of the PH system, emphasizing the importance of understanding not only the disease\u0026apos;s intricacies but also the impact of healthcare delivery models on treatment outcomes. Despite certain limitations, our study contributes valuable insights into the complex landscape of NLPHL, prompting consideration of not only the disease\u0026apos;s unique characteristics but also the complexities of healthcare systems in influencing outcomes. Future investigations with larger cohorts and prolonged follow-up periods are warranted to refine our understanding of NLPHL and inform more robust management strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eData Availability Statement:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFunding Statement:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for the production of this research.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConflict of Interest Disclosure:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eNone of the authors listed have any conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eEthics Approval Statement:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ePatient Consent Statement:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ePermission to reproduce material from other sources:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eClinical Trial Registration:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEichenauer DA, Engert A. Nodular lymphocyte-predominant Hodgkin lymphoma: a unique disease deserving unique management. Hematology. 2017 Dec 8;2017(1):324\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eSavage KJ, Mottok A, Fanale M. Nodular lymphocyte-predominant Hodgkin lymphoma. Seminars in Hematology. 2016 Jul 1;53(3):190\u0026ndash;202. \u003c/li\u003e\n\u003cli\u003eMorton LM, Wang SS, Devesa SS, Hartge P, Weisenburger DD, Linet MS. Lymphoma incidence patterns by WHO subtype in the United States, 1992-2001. Blood. 2006 Jan 1;107(1):265\u0026ndash;76. \u003c/li\u003e\n\u003cli\u003eOlszewski AJ, Shrestha R, Cook NM. Race-specific features and outcomes of nodular lymphocyte-predominant Hodgkin lymphoma: Analysis of the National Cancer Data Base: Race-Specific Features of NLPHL. Cancer. 2015 Oct 1;121(19):3472\u0026ndash;80. \u003c/li\u003e\n\u003cli\u003eWirth A, Yuen K, Barton M, Roos D, Gogna K, Pratt G, et al. Long-term outcome after radiotherapy alone for lymphocyte-predominant Hodgkin lymphoma. Cancer. 2005;104(6):1221\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eAl-Mansour M, Connors JM, Gascoyne RD, Skinnider B, Savage KJ. Transformation to Aggressive Lymphoma in Nodular Lymphocyte-Predominant Hodgkin\u0026rsquo;s Lymphoma. JCO. 2010 Feb 10;28(5):793\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eEichenauer DA, Engert A. How I treat nodular lymphocyte-predominant Hodgkin lymphoma. Blood. 2020 Dec 24;136(26):2987\u0026ndash;93. \u003c/li\u003e\n\u003cli\u003eNabhan C, Byrtek M, Taylor MD, Friedberg JW, Cerhan JR, Hainsworth JD, et al. Racial differences in presentation and management of follicular non-Hodgkin lymphoma in the United States: report from the National LymphoCare Study. Cancer. 2012 Oct 1;118(19):4842\u0026ndash;50. \u003c/li\u003e\n\u003cli\u003eFlowers CR, Shenoy PJ, Borate U, Bumpers K, Douglas-Holland T, King N, et al. Examining Racial Differences in Diffuse Large B-Cell Lymphoma Presentation and Survival. Leuk Lymphoma. 2013 Feb;54(2):268\u0026ndash;76. \u003c/li\u003e\n\u003cli\u003eHan X, Jemal A, Flowers CR, Sineshaw H, Nastoupil LJ, Ward E. Insurance status is related to diffuse large B-cell lymphoma survival. Cancer. 2014 Apr 15;120(8):1220\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eFanale M. Lymphocyte-predominant Hodgkin lymphoma: what is the optimal treatment? Hematology Am Soc Hematol Educ Program. 2013;2013:406\u0026ndash;13. \u003c/li\u003e\n\u003cli\u003eHuang JZ, Weisenburger DD, Vose JM, Greiner TC, Aoun P, Chan WC, et al. Diffuse large B-cell lymphoma arising in nodular lymphocyte predominant Hodgkin lymphoma: a report of 21 cases from the Nebraska Lymphoma Study Group. Leuk Lymphoma. 2004 Aug;45(8):1551\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eHartmann S, Eichenauer DA. Nodular lymphocyte predominant Hodgkin lymphoma: pathology, clinical course and relation to T-cell/histiocyte rich large B-cell lymphoma. Pathology. 2020 Jan 1;52(1):142\u0026ndash;53. \u003c/li\u003e\n\u003cli\u003eFan Z, Natkunam Y, Bair E, Tibshirani R, Warnke RA. Characterization of variant patterns of nodular lymphocyte predominant hodgkin lymphoma with immunohistologic and clinical correlation. Am J Surg Pathol. 2003 Oct;27(10):1346\u0026ndash;56. \u003c/li\u003e\n\u003cli\u003eLo AC, Major A, Super L, Appel B, Shankar A, Constine LS, et al. Practice patterns for the management of nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL): an international survey by the Global NLPHL One Working Group (GLOW). Leukemia \u0026amp; Lymphoma. 2022 Jul 3;63(8):1997\u0026ndash;2000. \u003c/li\u003e\n\u003cli\u003eGerber NK, Atoria CL, Elkin EB, Yahalom J. Characteristics and Outcomes of Patients With Nodular Lymphocyte-Predominant Hodgkin Lymphoma Versus Those With Classical Hodgkin Lymphoma: A Population-Based Analysis. International Journal of Radiation Oncology, Biology, Physics. 2015 May 1;92(1):76\u0026ndash;83. \u003c/li\u003e\n\u003cli\u003eXing KH, Connors JM, Lai A, Al-Mansour M, Sehn LH, Villa D, et al. Advanced-stage nodular lymphocyte predominant Hodgkin lymphoma compared with classical Hodgkin lymphoma: a matched pair outcome analysis. Blood. 2014 Jun 5;123(23):3567\u0026ndash;73. \u003c/li\u003e\n\u003cli\u003eBorchmann S, Joffe E, Moskowitz CH, Zelenetz AD, Noy A, Portlock CS, et al. Active surveillance for nodular lymphocyte-predominant Hodgkin lymphoma. Blood. 2019 May 16;133(20):2121\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eAppel BE, Chen L, Buxton AB, Hutchison RE, Hodgson DC, Ehrlich PF, et al. Minimal Treatment of Low-Risk, Pediatric Lymphocyte-Predominant Hodgkin Lymphoma: A Report From the Children\u0026rsquo;s Oncology Group. J Clin Oncol. 2016 Jul 10;34(20):2372\u0026ndash;9. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hodgkin’s Disease, Nodular Lymphocyte Predominant Hodgkin’s Lymphoma, Epidemiology, Health Disparities","lastPublishedDoi":"10.21203/rs.3.rs-4131304/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4131304/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Nodular lymphocyte-predominant Hodgkin's lymphoma often follows an indolent course but carries a risk of late recurrence and transformation. Given its rarity, there is significant variability in the treatment patterns at various healthcare centers. This study aimed to compare the patient characteristics and outcomes of NLPHL patients treated at Parkland Health, the safety-net system for uninsured/underinsured patients in Dallas County with patients treated at the neighboring NCI-designated Harold C. Simmons Comprehensive Cancer Center (SCCC). Our cohort included 53 adult patients (25 at PH vs 28 at SCCC). PH patients were more likely to belong to racial/ethnic minority groups (Black non-Hispanic 84% at PH vs 32% at SCCC; Hispanic 16% at PH vs 0% at SCCC, p \u003c0.01) and to be uninsured (60% at PH vs. 0% at SCCC, p \u003c0.01). Overall, 38% of patients presented at a late stage (stage III-IV) and was not different based on site of care (11 at PH vs 9 at SCCC; p=0.37). Site of care (PH vs SCCC) or race/ethnicity did not impact the treatment choice. At a median follow-up of 60 months (IQR 21, 83), 6 recurrences and 5 transformations were noted. Overall median survival was 62 months (IQR 21.5-84.5). Despite health inequities that typically impact safety-net patients, we did not observe differences in treatment patterns or outcomes of Nodular lymphocyte-predominant Hodgkin Lymphoma between patients treated at PH compared to SCCC.","manuscriptTitle":"Patient Characteristics and Outcomes of Nodular Lymphocyte Predominant Hodgkin Lymphoma at a Safety-Net System Compared to an Academic Comprehensive Cancer Center","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-04 10:36:09","doi":"10.21203/rs.3.rs-4131304/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2255ed00-68ea-4a28-bb7c-b218121d5332","owner":[],"postedDate":"April 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-04-04T10:36:53+00:00","versionOfRecord":{"articleIdentity":"rs-4131304","link":"https://doi.org/10.1182/blood-2023-173465","journal":{"identity":"blood","isVorOnly":true,"title":"Blood"},"publishedOn":"2023-11-28 10:36:53","publishedOnDateReadable":"November 28th, 2023"},"versionCreatedAt":"2024-04-04 10:36:09","video":"","vorDoi":"10.1182/blood-2023-173465","vorDoiUrl":"https://doi.org/10.1182/blood-2023-173465","workflowStages":[]},"version":"v1","identity":"rs-4131304","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4131304","identity":"rs-4131304","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}