Vulvar Cancer Individualized Scoring System
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 1,000
- 试验地点
- 2
- 主要终点
- cancer-specific survival (CSS) rate at 3 and 5 years
研究概览
简要总结
This study aims to develop a machine learning-based prediction model for patients with vulvar cancer. This model will utilize patient characteristics and disease features to determine the disease's prognosis. The scoring system will also include management information to facilitate prediction of clinical outcomes of different management strategies and potential management that would yield the best prognosis.
详细描述
Vulvar cancer (VC) is a relatively rare gynecological cancer accounting for 5-8% of all cases [1].
It comes the fourth among the commonest gynecological cancers and tends to affect women after menopause with a median age of 68 years [2,3].
Risk factors include cervical intraepithelial neoplasia, prior history of cervical cancer, smoking, lichen sclerosus, and immunodeficiency syndromes [4-5]. As squamous cell carcinoma is considered the most common type of VC, there are two potential pathogenic pathways for squamous cell carcinoma of the vulva include chronic inflammatory processes and human papillomavirus (HPV) infection [6-7].
While VC may be asymptomatic, most cases are present with bleeding, discharge, vulvar mass, ulcer and/or pruritis. Furthermore, it can be presented by a groin mass which reflects inguinal lymph node involvement. VC may be confined to the primary site in 59% of cases while 30% and 6% of cases spread to regional lymph nodes and distant areas, respectively [8].
FIGO staging is considered the standard classification system that determines prognosis and management of newly diagnosed VC. However, there are numerous gaps in the current staging system that would limit full interpretation of prognosis and management guidance [9]. Although staging system primarily determines disease prognosis, the staging system does not consider all prognostic factors, such as disease stage and histopathology. In fact, factors other than lymph node metastasis may have a stronger predictive influence such as the severity of the disease, age, histologic type and adjuvant radiotherapy and chemotherapy [10].
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 80 Years(Adult, Older Adult)
- 性别
- Female
- 接受健康志愿者
- 是
入选标准
- •Women diagnosed with Vulvar cancer and treated at collaborating centers between January 1st, 2008, and December 31st, 2017
- •women aged 18 years old or older, complete follow-up on for at least 3 years, unless censored by mortality.
排除标准
- •Women will be excluded from the study if there were lost to follow-up before 3 years post-treatment
- •If the patient did not receive their treatment in the receptive centers
- •If the patient were diagnosed with synchronous cancers
结局指标
主要结局
cancer-specific survival (CSS) rate at 3 and 5 years
时间窗: at 3 and 5 years
Primary outcome of the study will be cancer-specific survival (CSS) rate at 3 and 5 years after initiation of treatment.
次要结局
- Recurrence-free survival (RFS) rate at 3 and 5 years(at 3 and 5 years)
研究者
Sherif Abdelkarim Mohammed Shazly
Sherif Abdelkarim Mohammed Shazly, Assistant lecturer, Assiut University
Middle-Eastern College of Obstetricians and Gynecologists
