Predictors of Para-aortic Lymph Node Metastasis of Cervical Cancer
Predictors of Para-aortic Lymph Node Metastasis in Patients With Locally Advanced Cervical Cancer Based on the Pooled Analysis of Surgical Staging Results
The goal of this observational study is to identify predictive factors and to develop a risk model predicting para-aortic lymph node metastasis in patients with locally advanced cervical cancer based on the analysis of surgical staging results. The main questions it aims to answer are:
- What are the risk factors to predict para-aortic lymph node metastasis in patients with locally advanced cervical cancer?
- What is the indication for prophylactic extended-field radiation therapy in patients with locally advanced cervical cancer Individual data of patients with locally advanced cervical cancer treated with surgical staging at our institution from 2020 to 2022 were pooled analysed.Multivariate Logistic regression analysis was used to identify the predictive factors and to develop the prediction model.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
-
-
Chongqing
-
Chongqing, Chongqing, China, 400030
- Chongqing University Cancer Hospital
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
The primary cohort of this study comprised an evaluation of the institutional database for medical records from January 2020 to August 2022 to identify patients with locally advanced cervical cancer who underwent surgical staging.
From March 2018 to December 2019, an independent validation cohort of 116 consecutive patients was screened using the same criteria as that for the primary cohort.
Description
Inclusion Criteria:
- In 2018, the International Federation of Obstetrics and Gynecology (FIGO) stage was Ib3 IIA2-IVA;
- It was treated initially without surgical and chemotherapy.
- Squamous cell carcinoma, adenocarcinoma and adeno-squamous cell carcinoma were confirmed by histopathology.
- Abdominal pelvic CT, MRI or PET/CT were performed before treatment.
- Patients with successful surgical staging and the pathological data of para-aortic lymph node were obtained.
Exclusion Criteria:
- Patients were excluded if the histopathological type was not squamous cell carcinoma or Adenocarcinoma, and the data of LN status was not available.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
experimental group
locally advanced cervical cancer treated with surgical staging
|
para-aortic lymphadenectomy from the inferior mesenteric artery cranially to the aorta caudally via laparoscopy or laparotomy
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Predictors of para-aortic lymph node metastasis
Time Frame: 3 months
|
We evaluate the institutional database for medical records to identify patients who underwent surgical staging, then comprised the primary and the independent validation cohort, respectively.
The variables were collected from each patient.
We assess the bivariate relationship between each variable and para-aortic lymph node metastasis via logistic regression analysis.
The potential predictive variables of a P-value<0.05
on univariate analysis were considered as risk factors.
|
3 months
|
|
The prediction model of para-aortic lymph node metastasis
Time Frame: 3 months
|
The multivariable logistic regression analysis between predictors and para-aortic lymph node metastasis was conducted and evaluated odds ratio.
To facilitate practical application, a score chart was developed to present the final prediction model.
The risk score of predictive variables were calculated and rounded based on its beta-coefficients from the multivariate logistic regression analysis.
The prediction model was then developed by combining all scores, and the sum of scores for each predictor represented the risk score for every patient.
|
3 months
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
validation of the prediction model
Time Frame: 3 months
|
We adopted an internal and independent validation to assess the performance of the prediction model.The internal validation of the model was performed with respect to discrimination which was measured by the concordance index and calibration which was assessed by the Hosmer-Lemeshow test and Brier score.
The independent validation was performed with respect to sensitivity, specificity and Youden index, which calculated by sensitivity+specificity-1 is a global measure of diagnostic effectiveness.
|
3 months
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Study Director: Dongling Zou, M.D., Chongqing University Cancer Hospital
Study record dates
Study Major Dates
Study Start (ACTUAL)
Study Start
Primary Completion (ACTUAL)
Primary Completion
Study Completion (ACTUAL)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (ACTUAL)
First Posted
Study Record Updates
Last Update Posted (ACTUAL)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- CQGOG0110
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
Clinical Trials on Locally Advanced Cervical Cancer
-
NCT07450963Not yet recruitingLocally Advanced Cervical Cancer
-
NCT07600515Not yet recruitingLocally Advanced Cervical Cancer | Prognostic Biomarker
-
NCT07205497Active, not recruitingLocally Advanced Cervical Cancer | Neoadjuvant Immunotherapy
-
NCT07435987Not yet recruitingLocally Advanced Cervical Cancer | Uterine Carcinoma
-
NCT07286253RecruitingNeoadjuvant Treatment for Locally Advanced Cervical Cancer
-
NCT05975593RecruitingCervical Cancer | Pancreatic Cancer | Pancreas Cancer | Locally Advanced Cervical Carcinoma | Locally Advanced Cervical Cancer | Cancer of the Pancreas | Locally Advanced Pancreatic Carcinoma | Locally Advanced Pancreatic Cancer | Cancer of the Cervix | Locally Advanced Pancreas Cancer
-
NCT07613567Not yet recruitingLocally Advanced Cervical Carcinoma
-
NCT07400536RecruitingLocally Advanced Cervical Carcinoma
-
NCT07213427Not yet recruitingLOCALLY ADVANCED CERVICAL CANCERS
-
NCT04789941Not yet recruitingLocally Advanced Cervical Carcinoma
Clinical Trials on surgical staging
-
NCT07546825RecruitingLaparoscopic | Gynaecological Malignancies | Gynaecological Oncology
-
NCT01049100Unknown
-
NCT00432640CompletedCarcinoma, Non-Small-Cell Lung
-
NCT01679522Completed
-
NCT06068387RecruitingLocally Advanced Cervical Cancer
-
NCT04570553Recruiting
-
NCT07027046RecruitingEndometrial Cancer
-
NCT05969405Recruiting
-
NCT05657483RecruitingInflammatory Response | Endometrial Neoplasms
-
NCT07514078Not yet recruitingTreatment Endometrial Cancer