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Global cancer stigma research: a U.S. National Cancer Institute workshop report. 全球癌症耻辱化研究:美国国家癌症研究所研讨会报告。
Pub Date : 2024-06-05 DOI: 10.1093/jncimonographs/lgad038
Kathryn Heley, Robin C Vanderpool, Vidya Vedham

Stigma is a social process characterized by negative beliefs, attitudes, and stereotypes associated with a specific attribute or characteristic that leads to discrimination and social exclusion. Stigma manifests across the cancer control continuum and remains a key challenge for cancer prevention and control worldwide. In this commentary, we provide an overview of the U.S. National Cancer Institute's (NCI) Global Cancer Stigma Research Workshop, a multi-disciplinary international conference held virtually in September 2022, which focused on the intersection of cancer and stigma. The meeting was unique in its convening of researchers, advocates, clinicians, and non-governmental and governmental organizations, who-as a collective-provided overarching topics, cross-cutting considerations, and future directions for the cancer stigma research community to consider, which we describe herein. In summary, studying cancer stigma comprehensively requires a holistic, adaptive, and multifaceted approach-and should consider interrelated factors and their intersection within diverse cultural and social contexts worldwide. Collectively, there was a call for: an inclusive approach, encouraging researchers and practitioners to identify and measure cancer stigma as a driver for cancer health inequities globally; an expansion of existing research methodology to include diversity of experiences, contexts, and perspectives; and collaborations among diverse stakeholders to develop more effective strategies for reducing stigma and improving cancer outcomes. Such efforts are essential to cultivating effective and equitable approaches to preventing and treating cancer worldwide.

成见是一种社会过程,其特点是与特定属性或特征相关的负面信念、态度和成见,从而导致歧视和社会排斥。成见表现在癌症控制的各个环节,仍然是全球癌症预防和控制面临的主要挑战。在这篇评论中,我们概述了美国国家癌症研究所(NCI)全球癌症成见研究研讨会的情况,这是一个多学科国际会议,于 2022 年 9 月以虚拟方式举行,重点讨论癌症与成见的交叉问题。这次会议的独特之处在于它召集了研究人员、倡导者、临床医生、非政府组织和政府组织,他们作为一个集体,为癌症耻辱化研究界提供了首要议题、跨领域考虑因素和未来考虑方向,我们将在本文中加以介绍。总之,全面研究癌症污名化需要一种整体的、适应性的和多方面的方法,并应考虑相互关联的因素及其在全球不同文化和社会背景下的交集。总之,人们呼吁:采取一种包容性的方法,鼓励研究人员和从业人员将癌症耻辱感作为全球癌症健康不平等的驱动因素加以识别和衡量;扩展现有的研究方法,将经验、背景和观点的多样性纳入其中;不同利益相关者之间开展合作,以制定更有效的策略来减少耻辱感并改善癌症治疗效果。这些努力对于在全球范围内培养有效、公平的癌症预防和治疗方法至关重要。
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引用次数: 0
Feasibility, acceptability, and initial efficacy of empathic communication skills training to reduce lung cancer stigma in Nigeria: a pilot study. 在尼日利亚开展移情沟通技能培训以减少肺癌耻辱感的可行性、可接受性和初步效果:一项试点研究。
Pub Date : 2024-06-05 DOI: 10.1093/jncimonographs/lgae006
Smita C Banerjee, Chioma Asuzu, Boladale Mapayi, Blessing Olunloyo, Emeka Odiaka, Oluwafemi B Daramola, Jaime Gilliland, Israel Adeyemi Owoade, Peter Kingham, Olusegun I Alatise, Grace Fitzgerald, Rivka Kahn, Cristina Olcese, Jamie S Ostroff

Effective communication about cancer diagnosis and prognosis in sub-Saharan African oncology settings is often challenged by the cancer-related shame and stigma patients and families experience. Enhancing empathic communication between health care providers, including physicians and nurses, and oncology patients and their families can not only reduce cancer stigma but also improve patient engagement, treatment satisfaction, and quality of life. To reduce lung cancer stigma, we adapted an evidence-based empathic communication skills training intervention to reduce patients' experience of stigma in Nigeria and conducted a pilot study examining the feasibility and acceptability of the empathic communication skills training. Thirty health care providers, recruited from University College Hospital, Ibadan, and Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, participated in a 2.25-hour didactic and experiential training session. Participant surveys were completed before and after the training. Overall, participants reported highly favorable training evaluations, with at least 85% of health care providers agreeing or strongly agreeing to survey items assessing training relevance, novelty, clarity, and facilitator effectiveness. Self-efficacy to communicate empathically with patients increased significantly from before-training (Mean [SD] = 3.93 [0.28]) to after-training (Mean [SD] = 4.55 [0.15]; t29 = 3.51, P < .05). Significant improvements were observed in health care provider reports of empathy toward lung cancer survivors and attitude toward lung cancer care as well as significant reductions in lung cancer blame were noted. The empathic communication skills training was feasible, well received by oncology clinicians in Nigeria, and demonstrated improvements in health care provider-reported outcomes from before- to after-training.

在撒哈拉以南非洲地区的肿瘤治疗环境中,有关癌症诊断和预后的有效沟通常常受到患者和家属与癌症相关的羞耻感和耻辱感的挑战。加强医疗服务提供者(包括医生和护士)与肿瘤患者及其家属之间的移情沟通不仅能减少癌症耻辱感,还能提高患者的参与度、治疗满意度和生活质量。为了减少对肺癌的成见,我们改编了一项基于证据的移情沟通技能培训干预措施,以减少尼日利亚患者的成见体验,并开展了一项试点研究,考察移情沟通技能培训的可行性和可接受性。从伊巴丹大学学院医院和伊费岛奥巴费米-阿沃洛沃大学教学医院综合大楼招募的 30 名医护人员参加了 2.25 小时的授课和体验式培训。培训前后完成了学员调查。总体而言,参与者对培训的评价非常好,至少有 85% 的医疗服务提供者同意或非常同意评估培训相关性、新颖性、清晰度和主持人有效性的调查项目。从培训前(平均[标准差] = 3.93 [0.28])到培训后(平均[标准差] = 4.55 [0.15];t29 = 3.51,P.
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引用次数: 0
Impact of a multicomponent navigation strategy on stigma among people living with HIV and Kaposi's sarcoma in Kenya: a qualitative analysis. 肯尼亚艾滋病毒感染者和卡波西肉瘤患者对多成分导航战略的污名化影响:定性分析。
Pub Date : 2024-06-05 DOI: 10.1093/jncimonographs/lgae017
Sigrid M Collier, Aggrey Semeere, Linda Chemtai, Helen Byakwaga, Celestine Lagat, Miriam Laker-Oketta, Juliet Bramante, Ann Pacheco, Morvarid Zehtab, Alexis G Strahan, Merridy Grant, Laura M Bogart, Ingrid V Bassett, Naftali Busakhala, Jesse Opakas, Toby Maurer, Jeffrey Martin, Samson Kiprono, Esther E Freeman

Persons with HIV-associated Kaposi's sarcoma (KS) experience three co-existing stigmatizing health conditions: skin disease, HIV, and cancer, which contribute to a complex experience of stigmatization and to delays in diagnosis and treatment. Despite the importance of stigma among these patients, there are few proven stigma-reduction strategies for HIV-associated malignancies. Using qualitative methods, we explore how people with HIV-associated KS in western Kenya between August 2022 and 2023 describe changes in their stigma experience after participation in a multicomponent navigation strategy, which included 1) physical navigation and care coordination, 2) video-based education with motivational survivor stories, 3) travel stipend, 4) health insurance enrollment assistance, 5) health insurance stipend, and 6) peer mentorship. A purposive sample of persons at different stages of chemotherapy treatment were invited to participate. Participants described how a multicomponent navigation strategy contributed to increased knowledge and awareness, a sense of belonging, hope to survive, encouragement, and social support, which served as stigma mitigators, likely counteracting the major drivers of intersectional stigma in HIV-associated KS.

与艾滋病病毒相关的卡波西肉瘤(KS)患者同时患有皮肤病、艾滋病病毒(HIV)和癌症这三种令人鄙视的健康问题,这导致了复杂的鄙视体验,并延误了诊断和治疗。尽管污名化在这些患者中非常重要,但很少有针对艾滋病相关恶性肿瘤的行之有效的减少污名化策略。我们采用定性方法,探讨了 2022 年 8 月至 2023 年期间肯尼亚西部的艾滋病相关 KS 患者如何描述他们在参与多成分导航策略(包括 1) 物理导航和护理协调、2) 基于幸存者励志故事的视频教育、3) 旅行津贴、4) 医疗保险注册援助、5) 医疗保险津贴和 6) 同伴指导)后在污名化体验方面的变化。我们邀请了处于不同化疗阶段的患者进行有目的的抽样调查。参与者描述了多成分导航策略如何有助于提高知识和意识、归属感、生存希望、鼓励和社会支持,这些都是减轻污名化的因素,很可能抵消了艾滋病毒相关 KS 中交叉污名化的主要驱动因素。
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引用次数: 0
Black-White disparities in colorectal cancer outcomes: a simulation study of screening benefit. 结直肠癌癌症结果的黑白差异:筛查益处的模拟研究。
Pub Date : 2023-11-08 DOI: 10.1093/jncimonographs/lgad019
Carolyn M Rutter, Pedro Nascimento de Lima, Christopher E Maerzluft, Folasade P May, Caitlin C Murphy

The US Black population has higher colorectal cancer (CRC) incidence rates and worse CRC survival than the US White population, as well as historically lower rates of CRC screening. The Surveillance, Epidemiology, and End Results incidence rate data in people diagnosed between the ages of 20 and 45 years, before routine CRC screening is recommended, were analyzed to estimate temporal changes in CRC risk in Black and White populations. There was a rapid rise in rectal and distal colon cancer incidence in the White population but not the Black population, and little change in proximal colon cancer incidence for both groups. In 2014-2018, CRC incidence per 100 000 was 17.5 (95% confidence interval [CI] = 15.3 to 19.9) among Black individuals aged 40-44 years and 16.6 (95% CI = 15.6 to 17.6) among White individuals aged 40-44 years; 42.3% of CRCs diagnosed in Black patients were proximal colon cancer, and 41.1% of CRCs diagnosed in White patients were rectal cancer. Analyses used a race-specific microsimulation model to project screening benefits, based on life-years gained and lifetime reduction in CRC incidence, assuming these Black-White differences in CRC risk and location. The projected benefits of screening (via either colonoscopy or fecal immunochemical testing) were greater in the Black population, suggesting that observed Black-White differences in CRC incidence are not driven by differences in risk. Projected screening benefits were sensitive to survival assumptions made for Black populations. Building racial disparities in survival into the model reduced projected screening benefits, which can bias policy decisions.

与美国白人相比,美国黑人的结直肠癌癌症(CRC)发病率更高,结直肠癌生存率更差,结直肠癌筛查率历史上也更低。在建议进行常规CRC筛查之前,对20至45岁诊断人群的监测、流行病学和最终结果发病率数据进行了分析,以估计黑人和白人人群CRC风险的时间变化。白人人群的直肠和远端结肠癌癌症发病率迅速上升,但黑人人群没有,而两组的癌症近端发病率变化不大。2014-2018年,每100人中CRC发病率 000在40-44岁的黑人中为17.5(95%置信区间[CI]=15.3至19.9) 年龄为16.6岁(95%CI=15.6至17.6)的白人 年;黑人患者中42.3%的CRC为癌症近端,白人患者中41.1%的CRC为癌症。分析使用了一个特定种族的微观模拟模型来预测筛查的益处,基于获得的寿命和CRC发病率的寿命减少,假设CRC风险和位置存在这些黑白差异。筛查(通过结肠镜检查或粪便免疫化学检测)的预期益处在黑人人群中更大,这表明观察到的CRC发病率的黑白差异不是由风险差异驱动的。预计的筛查效益对黑人人口的生存假设很敏感。将生存方面的种族差异纳入模型会减少预计的筛查福利,这可能会使政策决策产生偏见。
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引用次数: 0
Contribution of smoking, disease history, and survival to lung cancer disparities in Black individuals. 吸烟、病史和存活率对黑人肺癌癌症差异的贡献。
Pub Date : 2023-11-08 DOI: 10.1093/jncimonographs/lgad016
Sarah Skolnick, Pianpian Cao, Jihyoun Jeon, Rafael Meza

Background: Lung cancer is the leading cause of cancer deaths and disproportionately affects self-identified Black or African American ("Black") people, especially considering their relatively low self-reported smoking intensity rates. This study aimed to determine the relative impact of smoking history and lung cancer incidence risk, histology, stage, and survival on these disparities.

Methods: We used 2 lung cancer models (MichiganLung-All Races and MichiganLung-Black) to understand why Black people have higher rates of lung cancer deaths. We studied how different factors, such as smoking behaviors, cancer development, histology, stage at diagnosis, and lung cancer survival, contribute to these differences.

Results: Adjusted for smoking history, approximately 90% of the difference in lung cancer deaths between the overall and Black populations (born in 1960) was the result of differences in the risk of getting lung cancer. Differences in the histology and stage of lung cancer and survival had a small impact (4% to 6% for each). Similar results were observed for the 1950 and 1970 birth cohorts, regardless of their differences in smoking patterns from the 1960 cohort.

Conclusions: After taking smoking into account, the higher rate of lung cancer deaths in Black people can mostly be explained by differences in the risk of developing lung cancer. As lung cancer treatments and detection improve, however, other factors may become more important in determining differences in lung cancer mortality between the Black and overall populations. To prevent current disparities from becoming worse, it is important to make sure that these improvements are available to everyone in an equitable way.

背景:癌症是癌症死亡的主要原因,对自我认同的黑人或非裔美国人(“黑人”)的影响尤为严重,尤其是考虑到他们自我报告的吸烟强度相对较低。本研究旨在确定吸烟史和癌症发病风险、组织学、分期和生存率对这些差异的相对影响。方法:我们使用两种癌症模型(密歇根龙人种和密歇根龙黑人)来了解为什么黑人的肺癌癌症死亡率较高。我们研究了不同的因素,如吸烟行为、癌症发展、组织学、诊断阶段和癌症生存率,是如何导致这些差异的。结果:经吸烟史调整后,总体人群与黑人(1960年出生)之间癌症死亡人数的差异约90%是由于患癌症风险的差异所致。癌症组织学、分期和生存率的差异影响较小(各4%至6%)。1950年和1970年出生的队列也观察到了类似的结果,无论他们与1960年队列在吸烟模式上的差异如何。结论:考虑吸烟后,黑人肺癌癌症死亡率较高,主要可以解释为患癌症风险的差异。然而,随着癌症治疗和检测的改善,其他因素在确定黑人和整体人群之间癌症死亡率差异方面可能变得更加重要。为了防止目前的差距变得更大,重要的是要确保每个人都能以公平的方式获得这些改进。
{"title":"Contribution of smoking, disease history, and survival to lung cancer disparities in Black individuals.","authors":"Sarah Skolnick, Pianpian Cao, Jihyoun Jeon, Rafael Meza","doi":"10.1093/jncimonographs/lgad016","DOIUrl":"10.1093/jncimonographs/lgad016","url":null,"abstract":"<p><strong>Background: </strong>Lung cancer is the leading cause of cancer deaths and disproportionately affects self-identified Black or African American (\"Black\") people, especially considering their relatively low self-reported smoking intensity rates. This study aimed to determine the relative impact of smoking history and lung cancer incidence risk, histology, stage, and survival on these disparities.</p><p><strong>Methods: </strong>We used 2 lung cancer models (MichiganLung-All Races and MichiganLung-Black) to understand why Black people have higher rates of lung cancer deaths. We studied how different factors, such as smoking behaviors, cancer development, histology, stage at diagnosis, and lung cancer survival, contribute to these differences.</p><p><strong>Results: </strong>Adjusted for smoking history, approximately 90% of the difference in lung cancer deaths between the overall and Black populations (born in 1960) was the result of differences in the risk of getting lung cancer. Differences in the histology and stage of lung cancer and survival had a small impact (4% to 6% for each). Similar results were observed for the 1950 and 1970 birth cohorts, regardless of their differences in smoking patterns from the 1960 cohort.</p><p><strong>Conclusions: </strong>After taking smoking into account, the higher rate of lung cancer deaths in Black people can mostly be explained by differences in the risk of developing lung cancer. As lung cancer treatments and detection improve, however, other factors may become more important in determining differences in lung cancer mortality between the Black and overall populations. To prevent current disparities from becoming worse, it is important to make sure that these improvements are available to everyone in an equitable way.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":"2023 62","pages":"204-211"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637023/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72016281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Data gaps and opportunities for modeling cancer health equity. 癌症健康公平建模的数据缺口和机会。
Pub Date : 2023-11-08 DOI: 10.1093/jncimonographs/lgad025
Amy Trentham-Dietz, Douglas A Corley, Natalie J Del Vecchio, Robert T Greenlee, Jennifer S Haas, Rebecca A Hubbard, Amy E Hughes, Jane J Kim, Sarah Kobrin, Christopher I Li, Rafael Meza, Christine M Neslund-Dudas, Jasmin A Tiro

Population models of cancer reflect the overall US population by drawing on numerous existing data resources for parameter inputs and calibration targets. Models require data inputs that are appropriately representative, collected in a harmonized manner, have minimal missing or inaccurate values, and reflect adequate sample sizes. Data resource priorities for population modeling to support cancer health equity include increasing the availability of data that 1) arise from uninsured and underinsured individuals and those traditionally not included in health-care delivery studies, 2) reflect relevant exposures for groups historically and intentionally excluded across the full cancer control continuum, 3) disaggregate categories (race, ethnicity, socioeconomic status, gender, sexual orientation, etc.) and their intersections that conceal important variation in health outcomes, 4) identify specific populations of interest in clinical databases whose health outcomes have been understudied, 5) enhance health records through expanded data elements and linkage with other data types (eg, patient surveys, provider and/or facility level information, neighborhood data), 6) decrease missing and misclassified data from historically underrecognized populations, and 7) capture potential measures or effects of systemic racism and corresponding intervenable targets for change.

癌症的人口模型通过利用大量现有数据资源进行参数输入和校准目标,反映了美国的总体人口。模型要求数据输入具有适当的代表性,以协调的方式收集,具有最小的缺失或不准确值,并反映足够的样本量。支持癌症健康公平的人口建模的数据资源优先事项包括增加数据的可用性,这些数据1)来自未投保和保险不足的个人以及传统上不包括在医疗保健提供研究中的个人,3)分解类别(种族、民族、社会经济地位、性别、性取向等)及其交叉点,以掩盖健康结果的重要变化,4)在健康结果研究不足的临床数据库中确定感兴趣的特定人群,5)通过扩展数据元素和与其他数据类型(例如,患者调查、提供者和/或设施级别的信息、社区数据)的联系来增强健康记录,6)减少历史上被低估的人群中缺失和错误分类的数据,7)捕捉系统性种族主义的潜在措施或影响以及相应的可干预的变革目标。
{"title":"Data gaps and opportunities for modeling cancer health equity.","authors":"Amy Trentham-Dietz, Douglas A Corley, Natalie J Del Vecchio, Robert T Greenlee, Jennifer S Haas, Rebecca A Hubbard, Amy E Hughes, Jane J Kim, Sarah Kobrin, Christopher I Li, Rafael Meza, Christine M Neslund-Dudas, Jasmin A Tiro","doi":"10.1093/jncimonographs/lgad025","DOIUrl":"10.1093/jncimonographs/lgad025","url":null,"abstract":"<p><p>Population models of cancer reflect the overall US population by drawing on numerous existing data resources for parameter inputs and calibration targets. Models require data inputs that are appropriately representative, collected in a harmonized manner, have minimal missing or inaccurate values, and reflect adequate sample sizes. Data resource priorities for population modeling to support cancer health equity include increasing the availability of data that 1) arise from uninsured and underinsured individuals and those traditionally not included in health-care delivery studies, 2) reflect relevant exposures for groups historically and intentionally excluded across the full cancer control continuum, 3) disaggregate categories (race, ethnicity, socioeconomic status, gender, sexual orientation, etc.) and their intersections that conceal important variation in health outcomes, 4) identify specific populations of interest in clinical databases whose health outcomes have been understudied, 5) enhance health records through expanded data elements and linkage with other data types (eg, patient surveys, provider and/or facility level information, neighborhood data), 6) decrease missing and misclassified data from historically underrecognized populations, and 7) capture potential measures or effects of systemic racism and corresponding intervenable targets for change.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":"2023 62","pages":"246-254"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11009506/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72016282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Racial disparities in prostate cancer mortality: a model-based decomposition of contributing factors. 前列腺癌症死亡率的种族差异:基于模型的促成因素分解。
Pub Date : 2023-11-08 DOI: 10.1093/jncimonographs/lgad018
Roman Gulati, Yaw A Nyame, Jane M Lange, Jonathan E Shoag, Alex Tsodikov, Ruth Etzioni

To investigate the relative contributions of natural history and clinical interventions to racial disparities in prostate cancer mortality in the United States, we extended a model that was previously calibrated to Surveillance, Epidemiology, and End Results (SEER) incidence rates for the general population and for Black men. The extended model integrated SEER data on curative treatment frequencies and cancer-specific survival. Starting with the model for all men, we replaced up to 9 components with corresponding components for Black men, projecting age-standardized mortality rates for ages 40-84 years at each step. Based on projections in 2019, the increased frequency of developing disease, more aggressive tumor features, and worse cancer-specific survival in Black men diagnosed at local-regional and distant stages explained 38%, 34%, 22%, and 8% of the modeled disparity in mortality. Our results point to intensified screening and improved care in Black men as priority areas to achieve greater equity.

为了调查自然病史和临床干预对美国前列腺癌症死亡率种族差异的相对贡献,我们扩展了一个模型,该模型之前已校准为普通人群和黑人男性的监测、流行病学和最终结果(SEER)发病率。扩展模型综合了SEER关于治疗频率和癌症特异性生存率的数据。从所有男性的模型开始,我们用黑人男性的相应成分替换了多达9个成分,预测了40-84岁的年龄标准化死亡率 年。根据2019年的预测,在局部区域和远处阶段诊断的黑人男性中,疾病发生频率增加、肿瘤特征更具侵袭性以及癌症特异性生存率更差,解释了38%、34%、22%和8%的死亡率模型差异。我们的研究结果表明,加强对黑人男性的筛查和改善护理是实现更大公平的优先领域。
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引用次数: 0
Adapting a model of cervical carcinogenesis to self-identified Black women to evaluate racial disparities in the United States. 将宫颈癌发生模型应用于自我认同的黑人女性,以评估美国的种族差异。
Pub Date : 2023-11-08 DOI: 10.1093/jncimonographs/lgad015
Jennifer C Spencer, Emily A Burger, Nicole G Campos, Mary Caroline Regan, Stephen Sy, Jane J Kim

Background: Self-identified Black women in the United States have higher cervical cancer incidence and mortality than the general population, but these differences have not been clearly attributed across described cancer care inequities.

Methods: A previously established microsimulation model of cervical cancer was adapted to reflect demographic, screening, and survival data for Black US women and compared with a model reflecting data for all US women. Each model input with stratified data (all-cause mortality, hysterectomy rates, screening frequency, screening modality, follow-up, and cancer survival) was sequentially replaced with Black-race specific data to arrive at a fully specified model reflecting Black women. At each step, we estimated the relative contribution of inputs to observed disparities.

Results: Estimated (hysterectomy-adjusted) cervical cancer incidence was 8.6 per 100 000 in the all-race model vs 10.8 per 100 000 in the Black-race model (relative risk [RR] = 1.24, range = 1.23-1.27). Estimated all-race cervical cancer mortality was 2.9 per 100 000 vs 5.5 per 100 000 in the Black-race model (RR = 1.92, range = 1.85-2.00). We found the largest contributors of incidence disparities were follow-up from positive screening results (47.3% of the total disparity) and screening frequency (32.7%). For mortality disparities, the largest contributor was cancer survival differences (70.1%) followed by screening follow-up (12.7%).

Conclusion: To reduce disparities in cervical cancer incidence and mortality, it is important to understand and address differences in care access and quality across the continuum of care. Focusing on the practices and policies that drive differences in treatment and follow-up from cervical abnormalities may have the highest impact.

背景:在美国,自我认同的黑人女性的宫颈癌症发病率和死亡率高于普通人群,但这些差异并没有明确归因于所描述的癌症护理不公平。方法:采用先前建立的癌症微刺激模型来反映美国黑人女性的人口统计学、筛查和生存数据,并与反映所有美国女性数据的模型进行比较。每个模型输入的分层数据(全因死亡率、子宫切除率、筛查频率、筛查方式、随访和癌症生存率)依次替换为黑随机特异性数据,以获得反映黑人女性的完全指定模型。在每一步中,我们都估计了投入对观察到的差异的相对贡献。结果:估计(子宫切除术调整后)宫颈癌症发病率为8.6/100 000比10.8/100 000(相对风险[RR]=1.24,范围=1.23-12.7)。估计全种族癌症死亡率为2.9% 000对5.5/100 000(RR=1.92,范围=1.85-2.00)。我们发现,发病率差异的最大因素是阳性筛查结果的随访(占总差异的47.3%)和筛查频率(32.7%)。对于死亡率差异,最大的因素是癌症生存率差异(70.1%),其次是筛查随访(12.7%)。关注导致宫颈异常治疗和随访差异的做法和政策可能会产生最大的影响。
{"title":"Adapting a model of cervical carcinogenesis to self-identified Black women to evaluate racial disparities in the United States.","authors":"Jennifer C Spencer, Emily A Burger, Nicole G Campos, Mary Caroline Regan, Stephen Sy, Jane J Kim","doi":"10.1093/jncimonographs/lgad015","DOIUrl":"10.1093/jncimonographs/lgad015","url":null,"abstract":"<p><strong>Background: </strong>Self-identified Black women in the United States have higher cervical cancer incidence and mortality than the general population, but these differences have not been clearly attributed across described cancer care inequities.</p><p><strong>Methods: </strong>A previously established microsimulation model of cervical cancer was adapted to reflect demographic, screening, and survival data for Black US women and compared with a model reflecting data for all US women. Each model input with stratified data (all-cause mortality, hysterectomy rates, screening frequency, screening modality, follow-up, and cancer survival) was sequentially replaced with Black-race specific data to arrive at a fully specified model reflecting Black women. At each step, we estimated the relative contribution of inputs to observed disparities.</p><p><strong>Results: </strong>Estimated (hysterectomy-adjusted) cervical cancer incidence was 8.6 per 100 000 in the all-race model vs 10.8 per 100 000 in the Black-race model (relative risk [RR] = 1.24, range = 1.23-1.27). Estimated all-race cervical cancer mortality was 2.9 per 100 000 vs 5.5 per 100 000 in the Black-race model (RR = 1.92, range = 1.85-2.00). We found the largest contributors of incidence disparities were follow-up from positive screening results (47.3% of the total disparity) and screening frequency (32.7%). For mortality disparities, the largest contributor was cancer survival differences (70.1%) followed by screening follow-up (12.7%).</p><p><strong>Conclusion: </strong>To reduce disparities in cervical cancer incidence and mortality, it is important to understand and address differences in care access and quality across the continuum of care. Focusing on the practices and policies that drive differences in treatment and follow-up from cervical abnormalities may have the highest impact.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":"2023 62","pages":"188-195"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637021/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72016276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Approaches to developing de novo cancer population models to examine questions about cancer and race in bladder, gastric, and endometrial cancer and multiple myeloma: the Cancer Intervention and Surveillance Modeling Network incubator program. 开发新癌症人群模型的方法,以检查膀胱、胃和子宫内膜癌症和多发性骨髓瘤中的癌症和种族问题:癌症干预和监测建模网络孵化器计划。
Pub Date : 2023-11-08 DOI: 10.1093/jncimonographs/lgad021
Yuliia Sereda, Fernando Alarid-Escudero, Nina A Bickell, Su-Hsin Chang, Graham A Colditz, Chin Hur, Hawre Jalal, Evan R Myers, Tracy M Layne, Shi-Yi Wang, Jennifer M Yeh, Thomas A Trikalinos

Background: We are developing 10 de novo population-level mathematical models in 4 malignancies (multiple myeloma and bladder, gastric, and uterine cancers). Each of these sites has documented disparities in outcome that are believed to be downstream effects of systemic racism.

Methods: Ten models are being independently developed as part of the Cancer Intervention and Surveillance Modeling Network incubator program. These models simulate trends in cancer incidence, early diagnosis, treatment, and mortality for the general population and are stratified by racial subgroup. Model inputs are based on large population datasets, clinical trials, and observational studies. Some core parameters are shared, and other parameters are model specific. All models are microsimulation models that use self-reported race to stratify model inputs. They can simulate the distribution of relevant risk factors (eg, smoking, obesity) and insurance status (for multiple myeloma and uterine cancer) in US birth cohorts and population.

Discussion: The models aim to refine approaches in prevention, detection, and management of 4 cancers given uncertainties and constraints. They will help explore whether the observed racial disparities are explainable by inequities, assess the effects of existing and potential cancer prevention and control policies on health equity and disparities, and identify policies that balance efficiency and fairness in decreasing cancer mortality.

背景:我们正在开发4种恶性肿瘤(多发性骨髓瘤和膀胱癌、胃癌和子宫癌)的10个新的群体水平数学模型。每个网站都记录了结果的差异,这些差异被认为是系统性种族主义的下游影响。方法:10个模型正在独立开发,作为癌症干预和监测建模网络孵化器计划的一部分。这些模型模拟了普通人群癌症发病率、早期诊断、治疗和死亡率的趋势,并按种族分组进行了分层。模型输入基于大型人群数据集、临床试验和观察性研究。一些核心参数是共享的,其他参数是特定于模型的。所有模型都是微观模拟模型,使用自我报告的种族来对模型输入进行分层。他们可以模拟相关风险因素(如吸烟、肥胖)和保险状况(多发性骨髓瘤和子宫癌症)在美国出生队列和人群中的分布。讨论:在不确定性和限制条件下,这些模型旨在完善4种癌症的预防、检测和管理方法。他们将帮助探索观察到的种族差异是否可以用不平等来解释,评估现有和潜在的癌症预防和控制政策对健康公平和差异的影响,并确定在降低癌症死亡率方面平衡效率和公平的政策。
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引用次数: 0
Commentary: Some water in the data desert: the Cancer Intervention and Surveillance Modeling Network's capacity to guide mitigation of cancer health disparities. 评论:数据沙漠中的一些水:癌症干预和监测建模网络指导缓解癌症健康差异的能力。
Pub Date : 2023-11-08 DOI: 10.1093/jncimonographs/lgad032
Robert A Winn, Katherine Y Tossas, Chyke Doubeni

Despite significant progress in cancer research and treatment, a persistent knowledge gap exists in understanding and addressing cancer care disparities, particularly among populations that are marginalized. This knowledge deficit has led to a "data divide," where certain groups lack adequate representation in cancer-related data, hindering their access to personalized and data-driven cancer care. This divide disproportionately affects marginalized and minoritized communities such as the U.S. Black population. We explore the concept of "data deserts," wherein entire populations, often based on race, ethnicity, gender, disability, or geography, lack comprehensive and high-quality health data. Several factors contribute to data deserts, including underrepresentation in clinical trials, poor data quality, and limited access to digital technologies, particularly in rural and lower-socioeconomic communities.The consequences of data divides and data deserts are far-reaching, impeding equitable access to precision medicine and perpetuating health disparities. To bridge this divide, we highlight the role of the Cancer Intervention and Surveillance Modeling Network (CISNET), which employs population simulation modeling to quantify cancer care disparities, particularly among the U.S. Black population. We emphasize the importance of collecting quality data from various sources to improve model accuracy. CISNET's collaborative approach, utilizing multiple independent models, offers consistent results and identifies gaps in knowledge. It demonstrates the impact of systemic racism on cancer incidence and mortality, paving the way for evidence-based policies and interventions to eliminate health disparities. We suggest the potential use of voting districts/precincts as a unit of aggregation for future CISNET modeling, enabling targeted interventions and informed policy decisions.

尽管癌症研究和治疗取得了重大进展,但在理解和解决癌症护理差异方面,尤其是在边缘化人群中,仍存在持续的知识差距。这种知识缺失导致了“数据鸿沟”,某些群体在癌症相关数据中缺乏足够的代表性,阻碍了他们获得个性化和数据驱动的癌症护理。这种差异对边缘化和少数族裔社区(如美国黑人)的影响尤为严重。我们探讨了“数据沙漠”的概念,即整个人口,通常基于种族、民族、性别、残疾或地理,缺乏全面和高质量的健康数据。有几个因素导致了数据沙漠,包括临床试验中的代表性不足、数据质量差以及获得数字技术的机会有限,特别是在农村和社会经济地位较低的社区。数据鸿沟和数据沙漠的后果是深远的,阻碍了公平获得精准医疗,并使健康差距长期存在。为了弥合这一分歧,我们强调了癌症干预和监测建模网络(CISNET)的作用,该网络采用人口模拟建模来量化癌症护理差异,特别是美国黑人人口中的差异。我们强调从各种来源收集高质量数据以提高模型准确性的重要性。CISNET的协作方法利用了多个独立的模型,提供了一致的结果并确定了知识差距。它展示了系统性种族主义对癌症发病率和死亡率的影响,为消除健康差距的循证政策和干预措施铺平了道路。我们建议潜在地使用投票区/选区作为未来CISNET建模的聚合单元,从而实现有针对性的干预和知情的政策决策。
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Journal of the National Cancer Institute. Monographs
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