Search

Background: Despite advances in cervical cancer (CC) prevention, detection, and treatment in the US, health disparities persist, disproportionately affecting underserved populations or regions. This study analyzes the geographical distribution of both CC and recurrent/metastatic CC (r/mCC) in the US and explores potential risk factors of higher disease burden to inform potential strategies to address disparities in CC and r/mCC., Methods: We estimated CC screening rates, as well as CC burden (number of patients with CC diagnosis per 100,000 eligible enrollees) and r/mCC burden (proportion of CC patients receiving systemic therapy not in conjunction with surgery or radiation), at the geographic level between 2017-2022 using administrative claims. Data on income and race/ethnicity were obtained from US Census Bureau's American Community Survey. Brachytherapy centers were proxies for guideline-conforming care for locally advanced CC. Associations among demographic, socioeconomic, and healthcare resource variables, with CC and r/mCC disease burden were assessed., Results: Between 2017-2022, approximately 48,000 CC-diagnosed patients were identified, and approximately 10,000 initiated systemic therapy treatment. Both CC and r/mCC burden varied considerably across the US. Higher screening was significantly associated with lower CC burden only in the South. Lower income level was significantly associated with lower screening rates, higher CC and r/mCC burden. Higher proportion of Hispanic population was also associated with higher CC burden. The presence of ≥1 brachytherapy center in a region was significantly associated with a reduction in r/mCC burden (2.7%)., Conclusion: CC and r/mCC disparities are an interplay of certain social determinants of health, behavior, and race/ethnicity. Our findings may inform targeted interventions for a geographic area, and further highlight the importance of guideline-conforming care to reduce disease burden., Competing Interests: Tara Castellano has received consulting fees from Glaxo-Smith-Klein; Andrew K. ElHabr and Ezgi Berksoy are paid employees of Value Analytics Labs, a healthcare consultancy company; Jie Ting and Yitong J. Zhang are employees and stack holders of Pfizer Inc.; Kathleen Moore has participated in data monitoring or advisory boards for Astra Zeneca, Aravive, Alkemeres, Aadi, Blueprint pharma, Clovis, Caris, Duality, Elevar, Eisai, EMD Serono, GSK/Tesaro, Genentech/Roche, Hengrui, Immunogen, Janssen, Lilly, Mersana, Merck, Myriad, Mereo, Novartis, OncXerna, Onconova, SQZ, Tarveda, VBL Therapeutics, Verastem and Zentalis, received support for attending meetings from Astra Zeneca, GSK/Tesaro, and BioNTech, and holds a leadership role with GOG partners; Leslie Randall reports personal fees from Seagen Inc. for an educational webinar at drug launch and speaker’s bureau and personal fees from Merck for an unbranded educational video for cervical cancer. Her institute receives research funding for clinical research from Seagen and Merck. She reports personal fees from BluPrint Oncology, PER, CurioScience, Projects in Knowledge, AstraZeneca, Tesaro, Merck, Mersana, Agenus, Rubius Therapeutics, Myriad Genetics, EMD Serono, Genentech/Roche, Seattle Genetics, Novartis, and Eisai, all outside the submitted work; Jagpreet Chhatwal and Turgay Ayer are co-owners of Value Analytics Labs; Charles A. Leath III has received consulting fees from Seagen Inc. for service on Scientific Advisory boards, cervical cancer research funding from Agenus, Rubius Therapeutics, and Seagen Inc., and funding from the NCI UG1 CA23330 and P50 CA098252; Fernanda Musa and Christina Washington have no competing interests to disclose., (Copyright: © 2024 Castellano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Cervical cancer (CC) disproportionately affects women based on socioeconomic status and racial/ethnic background. There is limited research in quantifying and visualizing whether substantial geographical disparities in the US exist with respect to CC burden, and especially with respect to recurrent or metastatic CC (r/mCC) disease burden. Identifying regions with higher r/mCC burden may help inform effective healthcare resource allocation and navigating patients to appropriate care., Methods: We conducted a retrospective analysis of the 2015-2020 MarketScan® Commercial and Supplemental Medicare claims data; r/mCC burden was estimated as the number of patients initiating r/mCC systemic therapy over CC-diagnosed patients for each of the 410 metropolitan statistical areas (MSAs) considered. We developed a public, web-based tool, the Cervical Cancer Geographical Disease Burden Analyzer (Cervical Cancer Geo-Analyzer, http://www.geo-analyzer.org), that allows users to visualize r/mCC burden across MSAs over multiple years., Results: There was considerable variation in r/mCC burden across MSAs, with a range of 0-83.3%. Burden increased in Boston-Cambridge-Newton, MA (r/mCC to CC ratio: 41% in 2018 to 50% in 2020), and Sacramento-Roseville-Arden-Arcade, CA (33% in 2018 to 50% in 2020). On the other hand, while r/mCC burden remained high, it decreased in Grand Rapids, MI (55% in 2018 to 31% in 2020) and San Francisco-Oakland-Hayward, CA (40% in 2018 to 26% in 2020). There were regions with sparse or no data, suggesting a need for more representative data capture., Conclusion: The Cervical Geo-Analyzer is a tool to visualize areas with high need for CC interventions. It also builds the foundation for further work to understand local risk factors of disease burden, identify populations of interest, characterize health disparities of CC or r/mCC and inform targeted interventions., Competing Interests: Declaration of Competing Interest Kathleen Moore has received consulting fees from Green Fire Bio, and payment or honoria from, and participated in data monitoring or advisory boards for Astra Zeneca, Aravive, Alkemeres, Addi, Blueprint pharma, Clovis, Elevar, Eisai, EMD Serono, GSK/Tesaro, Genentech/Roche, Hengrui, Immunogen, INxmed, IMab, Mersana, Merck, Myriad, Mereo, Novartis, OncXerna, Onconova, SQZ, Tarveda, VBL Therapeutics and Verastem, received support for attending meetings from Astra Zeneca, GSK/Tesaro and holds a leadership role with GOG partners; Jie Ting is an employee of, and holds stock in Seagen Inc.; Yasin Yildiz is a paid employee of Value Analytics Labs, which received funding from Seagen Inc. in connection with this study; Andy Surinach is an employee of Genesis Research, which received consulting fees from Seagen Inc. in connection with this study; Kalyani Sonawane has received consulting fees from, and has held a leadership role with Value Analytics Labs; Jagpreet Chhatwal is a co-owner of Value Analytics Labs, which received funding from Seagen Inc. in connection with this study, and he has received consulting fees and honoria from Novo Nordisk, and Bayer; Turgay Ayer is a co-owner of Value Analytics Labs, which received funding from Seagen Inc. in connection with this study. Tara Castellano and Christina Washington have no competing interests to disclose., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background and Objective: In diagnosis of cervical cancer patients, lymph node (LN) metastasis is a highly important indicator for the following treatment management. Although CT/PET (i.e., computed tomography/positron emission tomography) examination is the most effective approach for this detection, it is limited by the high cost and low accessibility, especially for the rural areas in the U.S.A. or other developing countries. To address this challenge, this investigation aims to develop and test a novel radiomics-based CT image marker to detect lymph node metastasis for cervical cancer patients., Methods: A total of 1,763 radiomics features were first computed from the segmented primary cervical tumor depicted on one CT image with the maximal tumor region. Next, a principal component analysis algorithm was applied on the initial feature pool to determine an optimal feature cluster. Then, based on this optimal cluster, the prediction models (i.e., logistic regression or support vector machine) were trained and optimized to generate an image marker to detect LN metastasis. In this study, a retrospective dataset containing 127 cervical cancer patients were established to build and test the model. The model was trained using a leave-one-case-out (LOCO) cross-validation strategy and image marker performance was evaluated using the area under receiver operation characteristic (ROC) curve (AUC)., Results: The results indicate that the SVM based imaging marker achieved an AUC value of 0.841 ± 0.035. When setting an operating threshold of 0.5 on model-generated prediction scores, the imaging marker yielded a positive and negative predictive value (PPV and NPV) of 0.762 and 0.765 respectively, while the total accuracy is 76.4%., Conclusions: This study initially verified the feasibility of utilizing CT image and radiomics technology to develop a low-cost image marker to detect LN metastasis for assisting stratification of cervical cancer patients., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interests with other persons or organizations., (Copyright © 2020. Published by Elsevier B.V.)

Objective: The aim of this study is to describe risk factors associated with either false-negative cervical cancer screening or deviations from screening guidelines that result in incidentally found invasive cervical cancer at the time of simple hysterectomy for benign indications., Materials and Methods: This is a retrospective review from 1990 to 2017 of subjects with incidental cervical cancer. Baseline demographics, preoperative evaluations, surgical data, and histopathologic characteristics were recorded. Deviations from screening guidelines or false-negative screenings were identified. Associations of independent risk factors according to age, insurance status, and histology were assessed., Results: Fifty-nine subjects with a median age of 43 years were found. Abnormal uterine bleeding was the most common indication for hysterectomy (61%, n = 36) and cervical dysplasia was present in 42% (n = 25) of these cases. Of those with inappropriate screening, 38% (n = 17) did not have documented Pap test, 22% (n = 10) had Pap that was not triaged appropriately, 18% (n = 8) received Pap and colposcopy but no indicated excisional procedure, and 22% (n = 10) had an excisional procedure that was not managed according to guidelines. False-negative screening occurred in 25% subjects (n = 15). There was no significant association between age, insurance status, or histology and risk of false-negative screening or inadequate screening., Conclusions: The most common cause of incidental cervical cancer at the time of simple hysterectomy was failure to properly adhere to screening guidelines. Less frequently, false-negative screening was the cause. No independent risk factor in either group was identified in this single institutional study. Illustrated is the importance of continuing education of surgeons about adequate screening in the preoperative evaluation for benign hysterectomy.