Influence of Sociodemographic Determinants on the Hodgkin Lymphoma Baseline Characteristics in Long Survivors Patients Enrolled in the Prospective Phase 3 Trial AHL2011

Author:

Chevreux Steeve,de Barros Sandra,Laurent Camille,Durand Amandine,Delpierre Cyrille,Robert Philippine,Joubert Clémentine,Griolet Samuel,Kanoun SalimORCID,Bastie Jean-Noël,Casasnovas René-Olivier,Rossi Cédric

Abstract

Introduction: Whereas numerous studies on several cancers describe the link between social conditions and disease severity, little is known about the social and demographic characteristics of Hodgkin lymphoma (HL) patients. At diagnosis, 10–15% of the patients in the advanced stages have a well-known poor outcome owing to their chemoresistance, but the determinants of the more advanced stages remain elusive. The objective of the present study was to decipher the potential impact of social disparities on the disease features at diagnosis and analyze how the sociodemographic patient features could impact the HL outcome of patients with advanced-stage HL enrolled in the AHL2011 trial. Methods: This ancillary study was conducted on a cohort of patients from French centers that had recruited more than five patients in the phase III AHL2011 study (NCT0135874). Patients had to be alive at the time of the ancillary study and had to have given their consent to answer the questionnaire. Pre-treatment data (age, gender, stage, B symptoms, IPS), the treatment received, the responses to PET-CT, and the presence of serious adverse events (serious adverse events—SAEs) were all extracted from the AHL2011 trial database. Sociodemographic data—marital status, living area, level of education, socio-professional category, and professional situation—were extracted from the questionnaires. The population density at the point of diagnosis was determined based on ZIP Code, and the distance from the reference medical center was then calculated by the road network. Baseline PET acquisition was performed before any treatment. PET images at baseline were centrally reviewed. The total metabolic tumor volume (TMTV) at the baseline was calculated using a 41% SUVmax cutoff for each lesion. Progression-free survival was defined as the time from randomization to the first progression, relapse, or death from any cause or the last follow-up. The data cutoff for the analyses presented here was 31 October 2017. The progression-free survival was analyzed on an intention-to-treat basis. Results: Among the 823 patients enrolled in the AHL2011 study, the questionnaire was sent to 394 patients, of whom 232 (58.9%) responded. At the time of HL diagnosis, 61.9% (N = 143) of patients declared that they were not socially isolated, 38.1% (N = 88) that they were single, 163 (71.2%) had a professional activity, and 66 (28.8%) were inactive owing to unemployment, retirement, or sick leave. Of the patients, 31.1% (N = 71) lived in a rural region, compared to 68.9% (N = 157) that lived in an urban region. The residence ZIP Code at the time of HL diagnosis was available for 163 (70%). Sociodemographic characteristics did not influence the presence of usual prognostic factors (ECOG, B symptoms, bulky mass, IPS) except for professional activity, which was associated with more frequent low IPS (0–2) (79 (48.5%) active versus 20 (30.3%) inactive patients; p = 0.012). Likewise, no correlation was observed between TMTV and sociodemographic characteristics. However, the TMTV quartile distribution was different according to the living area, with the two upper quartiles being enriched with patients living in a rural area (p = 0.008). Moreover, a negative correlation between the average number of the living area’s inhabitants and TMTV (R Pearson = −0.29, p = 0.0004) was observed. Conclusion: This study focused on sociodemographic parameters in advanced-stage HL patients and shows that professional activity is associated with more favorable disease features (low IPS), while patients living in rural or low-populated areas are more likely to have an unfavorable HL presentation with a high tumor burden (high TMTV). These data suggest that some patient sociodemographic characteristics might impact either access to medical care or environmental exposure, leading to a higher frequency of unfavorable presentations. Further prospective sociodemographic studies are necessary to confirm these preliminary results.

Publisher

MDPI AG

Subject

Cancer Research,Oncology

Reference28 articles.

1. Le Guyader-Peyrou, S., Delossez, G., Dantony, E., Mounier, M., Cornet, E., Uhry, Z., Cowppli-Bony, A., Maynadié, M., Troussard, X., and Delafosse, P. (2019). Estimations Nationales de L’incidence et de la Mortalité par Cancer en France Métropolitaine Entre 1990 et 2018, Santé Publique. Volume 2—Hémopathies malignes; Étude à partir des registres des cancers du réseau Francim.

2. (2019, June 25). SEER Cancer Statistics Review, Available online: https://seer.cancer.gov/archive/csr/1975_2015/results_merged/sect_09_hodgkins.pdf.

3. Predictive Value of PET Response Combined with Baseline Metabolic Tumor Volume in Peripheral T-Cell Lymphoma Patients;Cottereau;J. Nucl. Med. Off. Publ. Soc. Nucl. Med.,2018

4. Baseline metabolic tumour volume is an independent prognostic factor in Hodgkin lymphoma;Kanoun;Eur. J. Nucl. Med. Mol. Imaging,2014

5. The impact of health insurance status on the stage of cervical cancer diagnosis at a tertiary care center in Massachusetts;Davis;Gynecol. Oncol.,2018

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3