Uterine Cervical Neoplasms

The purpose of this study is to find out whether the study drug, LY4170156, is safe, tolerable and effective in participants with advanced solid tumors. The study is conducted in two parts - phase Ia (dose-escalation, dose-optimization) and phase Ib (dose-expansion). The study will last up to approximately 4 years.

This study is a randomized controlled field experiment embedded in the medical institution Early Diagnosis Program in Chile. Participants with two exams pending (a cancer screening test and a chronic disease test for diabetes and dyslipidemia) will be randomly assigned across a 3 × 3 factorial design: three message framing conditions (Basic, Risk/Importance, Peace of Mind) crossed with three exam-type conditions (cancer screening only, chronic disease test only, or both exams). Participants with only a cancer screening pending will be assigned to the 3 framing conditions and be encouraged to get the cancer screening. In both cases, participants are assigned to each experimental arm at twice the rate of an additional arm receiving the standard message currently used by the medical institution. This standard-message arm is included for operational purposes, is not part of the pre-specified analyses, and is thus not described in the "Arms and Intervention" section (or counted for "number of arms").

Purpose: To evaluate the efficacy and safety of neoadjuvant treatment with iparomlimab and tuvonralimab (QL1706), a dual PD1and CTLA4 bispecific antibody, in combination with paclitaxel and either cisplatin or carboplatin (TP/TC regimen) for patients with locally advanced cervical cancer. Eligibility Criteria: Women aged 18 to 70 years with newly diagnosed, histologically confirmed cervical cancer (squamous cell carcinoma, adenocarcinoma, or adenosquamous carcinoma), FIGO stage IB3 or IIA2, with no evidence of significant lymph node involvement (pelvic and paraaortic lymph nodes \<1.5 cm in short diameter), and who have not received any prior anticancer therapy. Study Procedures: Participants will receive up to 4 cycles of QL1706 plus TP/TC chemotherapy (once every 3 weeks) prior to surgery. After 2 cycles, clinical assessment will be performed to evaluate tumor response. If tumor shrinkage is observed, treatment may continue for 2 additional cycles, followed by imaging evaluation. Depending on the response, participants with complete or partial response may undergo less extensive surgery (cervical conization plus sentinel lymph node biopsy) rather than standard radical hysterectomy. After surgery, participants who achieve a major pathological response will receive QL1706 maintenance therapy as a single agent for up to 8 additional cycles (once every 3 weeks). For participants with insufficient tumor response, standard radical hysterectomy will be performed. Postoperative adjuvant therapy (radiation or chemotherapy) will follow standard clinical guidelines. Primary and Secondary Objectives: The primary endpoint is the pathological complete response (pCR) rate in the resected tissue following neoadjuvant treatment. Secondary endpoints include safety (treatment related adverse events), objective response rate (ORR), 3 years overall survival, 3 years disease free survival, and quality of life. Study Duration: Total participation time depends on treatment response and surgical scheduling, with an expected duration of approximately 9 to 12 months (including neoadjuvant treatment, surgery, and potential maintenance therapy).

This is a Phase 2 study of GV20-0251 in combination with anti-PD-1 monoclonal antibodies (including tislelizumab and toripalimab) for the treatment of participants with unresectable, locally advanced, or metastatic solid tumors who are refractory to, intolerant of, or ineligible for standard of care.

This is a multicenter, prospective study aimed at providing information on the psychological effects (including post-traumatic stress symptoms) of utero-vaginal brachytherapy in patients with cervical cancer using self-administered questionnaires. The study also aims to assess the persistence of these symptoms over time, up to 5 years after brachytherapy. The results could help identify patients at risk of post-traumatic stress in this context and develop appropriate psychological interventions to improve their psychological well-being during and after treatment.

This study is testing a new way to help people who are unhoused get screened for cervical cancer. Cervical cancer can often be prevented if it is found early. Many people who lack stable housing usually do not receive regular screenings. Through this project, the investigators will bring screening to community locations in Tucson, Arizona, using a mobile health unit (MHU) from the University of Arizona (UA) and El Rio Health. At these sites, participants will receive easy-to-understand education about cervical cancer, learn how to collect their own sample for human papillomavirus (HPV) testing, and get follow-up care if needed. The study has two goals: * First, the investigators will see if this community-based approach helps more people complete cervical cancer screening. * Second, the investigators will ask participants, clinicians, and outreach staff for their opinions about the program and its practicality and acceptability. By testing this approach, the investigators hope to find a way to make cervical cancer screening more accessible and effective for unhoused individuals.

This trial will look at a drug called sigvotatug vedotin (SGN-B6A) alone and with pembrolizumab, with or without chemotherapy, to find out whether it is safe for people who have solid tumors. It will study sigvotatug vedotin to find out what its side effects are. A side effect is anything the drug does besides treating cancer. It will also study whether sigvotatug vedotin works to treat solid tumors. The study will have four parts. * Part A of the study will find out how much sigvotatug vedotin should be given to participants. * Part B will use the dose found in Part A to find out how safe sigvotatug vedotin is and if it works to treat solid tumors. * Part C of the study will find out how safe sigvotatug vedotin is in combination with these other drugs. * Part D will include people who have not received treatment. This part of the study will find out how safe sigvotatug vedotin is in combination with these other drugs and if these combinations work to treat solid tumors. * In Parts C and D, participants will receive sigvotatug vedotin with either: * Pembrolizumab or, * Pembrolizumab and carboplatin, or * Pembrolizumab and cisplatin.

This clinical trial is looking at UCB4594. This is the first time the drug is being tested in humans. UCB4594 is a type of drug called a monoclonal antibody. It has been designed to work by targeting a protein called human leucocyte antigen G (HLA-G) that is found in high levels on some cancer cells. By attaching itself to this protein it may help the immune system to attack and kill the cancer cells. The four main aims of the clinical trial are to find out: 1. The best dose of UCB4594 that can be given safely to participants in the trial. 2. What the side effects of UCB4594 are and how they can be managed. 3. What happens to UCB4594 inside the body and how it affects cancer cells. 4. Whether UCB4594 can cause cancer to shrink.

Multicenter, randomized, open-label, phase II clinical study comparing Dostarlimab +/- Bevacizumab with standard chemotherapy in patients with gynecological clear cell carcinoma. 198 subjects will be enrolled in this study and will be assigned to three groups in a 1:1:1 ratio. 1. Group A: Dostarlimab monotherapy * First 3 cycles: Dostalimab 500mg every 3 weeks, IV * 4 cycles \~ up to 24 months: Dostalimab 1000mg every 6 weeks, IV 2. Group B: Dostarlimab + Bevacizumab combination therapy * First 3 cycles: Dostalimab 500mg every 3 weeks, IV * 4 cycles \~ up to 24 months: Dostalimab 1000mg every 6 weeks, IV * Bevacizumab administered IV at 15 mg/kg every 3 weeks until disease progression or unacceptable toxicity 3. Group C: General chemotherapy (one of Pegylated liposomal doxorubicin, Doxorubicin, Paclitaxel, and Gemcitabine)

The goal of this clinical trial is to test whether an interactive, video-based patient navigation program can improve cervical cancer screening among African American women who are currently overdue for screening. The main questions it aims to answer are: Can an interactive video navigation tool (mNav), when paired with in-person navigation, improve screening adherence compared to a standard educational video alone? Does the intervention improve knowledge, reduce barriers, and increase intentions to get screened? Researchers will compare participants who receive both the interactive video (guided by an on-screen navigator) and in-person navigation to those who receive only a standard educational video to see if the tailored support increases screening rates. Participants will: Complete two phone surveys (one at the beginning and one six months later) Be randomly assigned to one of two groups: One group will receive an interactive video experience tailored to their concerns plus support from an in-person navigator The other group will receive a standard educational video designed for African American women Have their clinic records reviewed six months later to check for cervical cancer screening completion

This quasi-experimental study aims to determine whether a breast and cervical cancer awareness training program can increase participation in cancer screening among women with visual impairments. The study also aims to identify barriers to screening and improve knowledge about cancer risk factors and screening methods. The main questions this study will address are: * Does the training increase the rate at which women with visual impairments attend cancer screening appointments? * Does the training improve participants' knowledge about breast and cervical cancer? Participants will: * Receive training on breast and cervical cancer risk factors and screening methods. * Learn how to apply to the Cancer Early Diagnosis, Screening, and Training Center. * Be encouraged to attend cancer screening during the study period. * Have knowledge and screening status assessed before the training, immediately after, and three months later.

The purpose of this study is to validate Automated Visual Evaluation (AVE), specifically the CINFinder version developed by DL Analytics, a point-of-care screening and triage diagnostic tool for cervical cancer based on the assessment of digital images through artificial intelligence. Several teams around the world have developed versions of AVE as a triage technology but none as a screening tool.

Cervical cancer is the fourth most common cancer in women worldwide, with approximately 604,000 new cases in 2020.Treatment for locally advanced cervical cancer is based on a combination of radiotherapy and chemotherapy. The response to concomitant chemoradiotherapy vary from one woman to another. Predicting the response to these treatments would allow early consideration of alternative therapies for patients identified as less responsive to standard treatments. A 5-year recurrence-free survival is approximately 79% for stages IB and IIA and 59% for stages III and IVA, with approximately 36% of local failures despite chemoradiotherapy. In a few studies,the radiomic MRI approach in locally advanced cervical cancers has shown to be prognostic for locoregional recurrence or survival but these models still need to be explored and validated.The EPICOL cohort, a clinical-biological cohort of 136 patients treated with chemoradiotherapy for locally advanced cervical cancer at the Montpellier Cancer Institute or Nîmes University Hospital, will be used to develop a predictive model of response to chemoradiotherapy based on radiomic data from pelvic MRIs before and after treatment.

Cervical large cell neuroendocrine carcinoma (LCNEC) exhibits highly aggressive biological behavior, including strong invasiveness, a high propensity for metastasis, drug resistance, and poor prognosis, necessitating heightened clinical and pathological awareness. This study aims to summarize the clinical characteristics of LCNEC and analyze various prognostic factors to enhance understanding and vigilance toward this disease. Combined with precise pathological diagnosis, improving diagnostic accuracy is crucial for formulating treatment strategies and assessing patient prognosis.

The purpose of this trial is to evaluate a new drug, HTL0039732, that will be administered on its own (as a monotherapy) and in combination with atezolizumab or with other approved anti-cancer therapies, in participants with advanced solid tumours.

This is a mixed-methods survey study including a 2-phased sequential-explanatory design. This study is to understand the patient journey in conventional therapy for newly diagnosed stage III or IV CC or EC in China, including ①patients' treatment decision making factors and treatment experiences and ② patients' unmet needs during post-treatment surveillance.

In the comprehensive dataset of clinical diagnoses and treatments for cervical cancer in China, 49.8% of patients with stage IB3 and IIA2 receive surgical intervention following neoadjuvant chemotherapy. This indicates a pressing need to optimize neoadjuvant chemotherapy regimens for locally advanced cervical cancer. While paclitaxel combined with cisplatin is the conventional approach, 9.8% to 30.6% of patients demonstrate suboptimal responses, with a pathological complete response rate of approximately 10%. Currently, the efficacy of antibody-drug conjugates in neoadjuvant chemotherapy for cervical cancer remains unexplored. This study seeks to address this gap by evaluating the combination of Disitamab Vedotin and Cisplatin in patients with stage IB3 and IIA2 cervical cancer with positive HER2 expression.The study will assess the impact of this regimen on pathological complete response rates, surgical complications, surgical resection rates, and overall survival.

The goal of this exploratory study is to exploring the lymph node metastasis, tumor margin, blood vessels, ureters, and nerve imaging in cervical cancer surgery using near-infrared fluorescence imaging technology combined with indocyanine green, and establishing an artificial intelligence model for predicting lymph node metastasis of cervical cancer to guide the advancement of refined surgical procedures.And the focus of this study is to investigate the situation of pelvic lymph node metastasis.The sole medication used in this experiment is the fluorescent contrast agent that has been clinically used for over 40 years - Indocyanine Green (ICG).Subsequent pathology results after the surgery will be used as the gold standard to determine the detection rate of lymph node metastasis and the accuracy of the complete resection rate of the surgical margin in cervical cancer.The researchers will also follow up on the quality of life of patients after the surgery. The main question it aims to answer is: can artificial intelligence multimodal fusion prediction models improve the accuracy of preoperative diagnosis of pelvic lymph node metastasis in cervical cancer? The researchers compared the AI multimodal fusion prediction model with traditional imaging physician assessments to see if the prediction model could yield more accurate lymph node metastasis determinations. Participants will undergo pelvic MRI after pathologically confirming a diagnosis of cervical cancer, and the results will be used to determine pelvic lymph node metastasis status by the predictive model and the imaging physician, respectively. Subsequent pathology results after surgical lymph node clearance will be used as the gold standard to determine the accuracy of the two preoperative lymph node diagnostic modalities.

Primary objective of the study is to determine the extent that offering of self-sampling in addition to clinician-sampling Human Papillomavirus (HPV) DNA testing will increase detection of HPV DNA through an increase in uptake rates of cervical cancer screening as compared to offering clinician-sampling HPV DNA testing alone. The hypothesis is that offering additional self-sampling will increase the detection of high-risk HPV DNA by at least 7.7%.

Cervical cancer is a significant health issue, particularly in low-income countries, where late diagnosis and limited access to screenings contribute to high mortality rates. This study aims to develop and evaluate an artificial intelligence (AI) model to analyze colposcopic images for detecting cervical cancer more accurately and efficiently. Colposcopy, a procedure used to examine the cervix for signs of cancer, relies heavily on doctors' expertise, leading to inconsistent results. The current gold standard, colposcopy-directed biopsy, is invasive and can cause complications. The hypothesis is that an AI model can outperform traditional methods in identifying cervical abnormalities, providing a reliable and scalable solution for early detection, especially in underserved areas. By automating the analysis process, the AI model aims to reduce reliance on trained personnel, making cervical cancer screening more accessible and improving early diagnosis and treatment outcomes. The study will create a diverse dataset of colposcopy images from various sources and develop the AI model. The model's performance will be validated in clinical settings, assessing its accuracy in classifying cancer stages and identifying transformation zones. The impact on early detection, patient outcomes, and model usability will be evaluated, as well as its generalizability across different healthcare environments. The goal is to enhance the accuracy and efficiency of cervical cancer screening, ultimately reducing mortality rates and improving patient care.

The goal of this prospective cohort study is to learn whether artificial intelligence multimodal fusion prediction models are effective in diagnosing pelvic lymph node metastasis in cervical cancer. The main question it aims to answer is: can artificial intelligence multimodal fusion prediction models improve the accuracy of preoperative diagnosis of pelvic lymph node metastasis in cervical cancer? The researchers compared the AI multimodal fusion prediction model with traditional imaging physician assessments to see if the prediction model could yield more accurate lymph node metastasis determinations. Participants will undergo pelvic MRI after pathologically confirming a diagnosis of cervical cancer, and the results will be used to determine pelvic lymph node metastasis status by the predictive model and the imaging physician, respectively. Subsequent pathology results after surgical lymph node clearance will be used as the gold standard to determine the accuracy of the two preoperative lymph node diagnostic modalities.

Radical hysterectomy and radiation therapy are standard treatments for cervical cancer. However, there are no reported studies on the frequency of side effects and treatment outcomes when hypofractionated radiation therapy and intensity modulated radiation therapy(IMRT) are used during radiation therapy. Hypofractionated radiation therapy increases the daily dose and reduces the number of treatment sessions, which may increase the risk of side effects, but its safety has been confirmed in some cases of early cervical cancer and endometrial cancer. Additionally, applying IMRT, a technique designed to protect normal tissue, during concurrent chemoradiotherapy has shown positive results in reducing the incidence of acute side effects. Investigators previously demonstrated that combining hypofractionated IMRT with chemotherapy for high-risk postoperative cervical cancer patients resulted in high survival rates and low toxicity in a phase 2 exploratory study. Base on this result, this study aimed to compare the efficacy and safety of conventional fractionated radiation therapy and hypofractionated radiation therapy.

The main objectives of this study are to construct a multi-omics-based prognostic and side-effect prediction model for cervical cancer based on pre-treatment imaging, digital pathology, genomics, proteomics, molecular biology, metabolomics, and intestinal flora characteristics data of cervical cancer patients, combined with patients' clinical information, to guide the precise treatment of cervical cancer patients; and to deeply excavate the characteristics related to recurrent cervical cancer based on time-series multi-omics data. Construct an artificial intelligence auxiliary model for dynamic monitoring of cervical cancer recurrence based on longitudinal multi-omics. To provide a real-time and timely tool for clinical early prediction, early identification, early diagnosis and early intervention of cervical cancer, to prolong the survival time and improve the quality of patients' survival. 1. To realize multi-omics feature extraction of cervical cancer patients before treatment, and build a prognosis and side-effect prediction model of cervical cancer to guide accurate treatment; 2. To make iterative, comprehensive, real-time assessment of the risk of recurrence of cervical cancer based on time-series multi-omics data, and to build an early warning model for early identification and early diagnosis of recurrent cervical cancer; 3. To establish a prognostic and side-effect prediction and risk dynamic assessment model for cervical cancer, to build an intelligent decision support system, to implement the application of prognostic and side-effect prediction and dynamic monitoring model, to further assist in the precise diagnosis and treatment of cervical cancer, and to provide an accurate prognostic tool for identifying, diagnosing, and intervening in cervical cancer during the follow-up process.

A total of 112 patients with locally advanced cervical cancer will be randomized 1:1 to standard therapy with cisplatin-based chemoradiation or nivolumab-ipilimumab induction followed by cisplatin-based chemoradiation. The primary outcome will be 3-year disease-free survival.

This prospective, multicenter, nonrandomized phase-II-trial investigates in clinical practice the differences between intensity modulated proton therapy (IMPT) and standard intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT) in the effects on dose-volume parameters and treatment-related morbidity for women with locally advanced cervical cancer undergoing chemoradiation.