Prognostic value of quantitative HPV viral load in determining cervical cancer treatment response and recurrence

定量 HPV 病毒载量在确定宫颈癌治疗反应和复发方面的预后价值

基本信息

批准号：
10631906
负责人：
Surbhi Grover
金额：
$ 21.7万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10631906
关键词：
Acquired Immunodeficiency Syndrome Aftercare Biometry Biopsy Botswana Cancer Patient Cervical Cessation of life Chemotherapy and/or radiation Clinical Clinical Trials Clinical assessments Cohort Studies Combination Drug Therapy Detection Development Diagnosis Early identification Early treatment Enrollment Ensure Evaluation Foundations Future Goals Grant HIV HIV Infections High Prevalence Human Human Papilloma Virus-Related Malignant Neoplasm Human Papillomavirus Human papilloma virus infection Image Immunologic Deficiency Syndromes In complete remission Intervention Intervention Studies Investigation Lesion Locally Advanced Malignant Neoplasm Malaria Malignant Neoplasms Malignant neoplasm of cervix uteri Mentors Methodology Methods Modeling Molecular Monitor Natural History Outcome Parents Patient-Focused Outcomes Patients Pennsylvania Performance Persons Play Polymerase Chain Reaction Prediction of Response to Therapy Prognostic Factor Public Health Radiation Radiation Oncologist Radiation Oncology Recommendation Recurrence Recurrent disease Recurrent tumor Regimen Relapse Research Research Personnel Research Project Grants Resource-limited setting Role Salvage Therapy Swab Testing Time Tissues Training Training and Infrastructure Treatment Failure Tuberculosis Tumor Burden Universities Videoconferencing Viral Load result Visit Woman Work cancer therapy career chemotherapy clinical care co-infection cohort cost cost effective experience follow-up global health high risk improved improved outcome individualized medicine innovation low and middle-income countries meetings mortality multidisciplinary parent grant personalized approach personalized intervention personalized management personalized medicine prognostic tool prognostic value programs risk stratification screening skill acquisition therapeutic HPV vaccine tool translational cancer research translational scientist treatment response tumor

项目摘要

ABSTRACT Cervical cancer is the most common cancer in women worldwide, with the highest burden in low- and middle- income countries (LMICs). Treatment of locally advanced cervical cancer includes radiation and concurrent chemotherapy (CRT). However, high rates of relapse and recurrence remain a significant problem, despite recommended treatment, particularly in LMICs. Therefore, identifying patients at high risk for treatment failure and recurrence is a critical initial step in the development of individualized management and follow-up of those patients. The overarching goal of the line of investigation proposed in this application is to allow for individualized treatment of cervical cancer patients in resource-limited settings using risk stratification models. We believe that quantification of the burden of human papillomavirus (HPV) infection will be a valuable prognostic tool for the individualized management of cervical cancer patients. More precisely, we hypothesize that quantification of the total and subtype-specific burden of HPV will predict treatment response and recurrence of cervical cancer, allowing clinicians to stratify high-risk patients at initial diagnosis and early stages of treatment. Further, quantitative HPV viral load is more accessible and cost-effective than currently recommended approaches for individualized cancer treatment, making it ideal for use in resource-limited settings. In this K08 proposal, Dr. Surbhi Grover, a trained radiation oncologist experienced in studying cervical cancer cohorts in LMICs, will determine the performance of total and subtype-specific HPV viral load as a predictor of treatment response and recurrence in cervical cancer patients treated with CRT in Botswana. Dr. Grover's overall career goal is to became an independent investigator in cervical cancer translational research and clinical trials, and to identify prognostic factors that will guide personalized interventions studied in future clinical trials to improve outcomes of cervical cancer patients in LMICs. With support from the Department of Radiation Oncology at the University of Pennsylvania (UPenn), she has been based in Botswana for the past three years working with cervical cancer patients. Dr. Grover and her multi-disciplinary team of mentors have developed a training plan that will leverage our ongoing studies in Botswana and enable her to acquire the skills needed to become a leading cervical cancer translational researcher focusing on clinical trials in LMICs. Training in clinical trials in LMICs, advanced biostatistics, and molecular methods of HPV detection and quantification will augment her training in radiation oncology and public health. The proposed study for the K08 grant will be nested in an ongoing University of Botswana and UPenn U54 consortia grant on which Dr. Grover currently plays a major role. During the course of the K08, she will continue to be based in Botswana to implement this study. She will continue to have regular video- conferencing calls and face-to-face meetings with her mentors, who will ensure that she is successful in carrying out this K08 project, in achieving her training goals, and in advancing her overall career goals.

抽象的宫颈癌是全世界女性中最常见的癌症，中低收入人群的负担最高收入国家（LMIC）。局部晚期宫颈癌的治疗包括放射治疗和同步治疗化疗（CRT）。然而，高复发率和复发率仍然是一个重大问题，尽管推荐的治疗方法，特别是在中低收入国家。因此，识别治疗失败高风险患者复发是制定个体化管理和随访的关键第一步患者。本申请中提出的调查路线的总体目标是允许使用风险分层模型在资源有限的环境中对宫颈癌患者进行个体化治疗。我们相信，人乳头瘤病毒 (HPV) 感染负担的量化将具有重要价值。宫颈癌患者个体化管理的预后工具。更准确地说，我们假设 HPV 总负担和亚型特异性负担的量化将预测治疗反应宫颈癌复发，使临床医生能够在初次诊断和早期对高危患者进行分层治疗阶段。此外，定量 HPV 病毒载量比目前更容易获得且更具成本效益推荐的个体化癌症治疗方法，使其非常适合资源有限的情况设置。在这项 K08 提案中，Surbhi Grover 博士是一位训练有素的放射肿瘤学家，在研究宫颈癌方面经验丰富。中低收入国家的癌症队列将确定总和亚型特异性 HPV 病毒载量的性能博茨瓦纳接受 CRT 治疗的宫颈癌患者治疗反应和复发的预测因子。 Grover 博士的总体职业目标是成为宫颈癌转化领域的独立研究者研究和临床试验，并确定指导个性化干预研究的预后因素在未来的临床试验中，以改善中低收入国家宫颈癌患者的预后。在来自以下机构的支持下她一直在宾夕法尼亚大学 (UPenn) 放射肿瘤学系工作博茨瓦纳过去三年与宫颈癌患者一起工作。格罗弗博士和她的多学科导师团队制定了一项培训计划，该计划将利用我们在博茨瓦纳正在进行的研究，并使她获得成为领先的宫颈癌转化研究人员所需的技能，重点关注中低收入国家的临床试验。中低收入国家临床试验、高级生物统计学和分子方法培训 HPV 检测和定量将增强她在放射肿瘤学和公共卫生方面的培训。这 K08 补助金的拟议研究将由博茨瓦纳大学和宾夕法尼亚大学 U54 正在进行格罗弗博士目前在财团资助中发挥着重要作用。在K08课程期间，她将继续驻扎在博茨瓦纳实施这项研究。她将继续定期发布视频- 与她的导师进行电话会议和面对面的会议，他们将确保她在以下方面取得成功开展这个 K08 项目，实现她的培训目标，并推进她的总体职业目标。

项目成果

期刊论文数量（46）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Patterns of cervical cancer brachytherapy in India: results of an online survey supported by the Indian Brachytherapy Society.

印度宫颈癌近距离放射治疗的模式：印度近距离放射治疗协会支持的在线调查结果。

DOI：
发表时间：
2019-12
期刊：
影响因子：
0
作者：
Chatterjee, Abhishek;Grover, Surbhi;Gurram, Lavanya;Sastri, Supriya;Mahantshetty, Umesh
通讯作者：
Mahantshetty, Umesh

Augmented Package of Palliative Care for Women With Cervical Cancer: Responding to Refractory Suffering.

针对宫颈癌女性的姑息治疗增强方案：应对难治性痛苦。

DOI：
发表时间：
2021
期刊：
影响因子：
4.5
作者：
Krakauer, Eric L;Kane, Khadidjatou;Kwete, Xiaoxiao;Afshan, Gauhar;Bazzett;Ruthnie Bien;Borges, Lawrence F;Byrne;Connor, Stephen;Correa, Raimundo;Devi, C R Beena;Diop, Mamadou;Elmore, Shekinah N
通讯作者：
Elmore, Shekinah N

The state of gynecologic radiation therapy in low- and middle-income countries.

低收入和中等收入国家的妇科放射治疗状况。

DOI：
发表时间：
2022-03
期刊：
影响因子：
0
作者：
Bhatia, Rohini;Lichter, Katie E;Gurram, Lavanya;MacDuffie, Emily;Lombe, Dorothy;Sarria, Gustavo R;Grover, Surbhi
通讯作者：
Grover, Surbhi

The global burden of cervical cancer requiring surgery: database estimates.

需要手术的宫颈癌的全球负担：数据库估计。

DOI：
发表时间：
2024-02-26
期刊：
影响因子：
0
作者：
Allanson, Emma R;Zafar, Syed Nabeel;Anakwenze, Chidinma P;Schmeler, Kathleen M;Trimble, Edward L;Grover, Surbhi
通讯作者：
Grover, Surbhi

The role and contribution of treatment and imaging modalities in global cervical cancer management: survival estimates from a simulation-based analysis.

治疗和成像方式在全球宫颈癌管理中的作用和贡献：基于模拟分析的生存估计。

DOI：
10.1016/s1470-2045(20)30316-8
发表时间：
2020-08
期刊：
The Lancet. Oncology
影响因子：
0
作者：
Ward ZJ;Grover S;Scott AM;Woo S;Salama DH;Jones EC;El-Diasty T;Pieters BR;Trimble EL;Vargas HA;Hricak H;Atun R
通讯作者：
Atun R