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Spots Global Cancer Trial Database for Effect of Different Treatments on the Prognosis of Early Cervical Cancer: A Multicenter, Prospective, Real-world Study

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Trial Identification

Brief Title: Effect of Different Treatments on the Prognosis of Early Cervical Cancer: A Multicenter, Prospective, Real-world Study

Official Title: Effect of Different Treatments on the Prognosis of Early Cervical Cancer: A Multicenter, Prospective, Real-world Study

Study ID: NCT04272190

Conditions

Cervical Cancer

Study Description

Brief Summary: To observe the effects of different treatments on the oncological outcome and complications of early cervical cancer (2018 FIGO stage IA1 with lymphovascular space invasion and IA2-IIA2 cervical cancer). This study prospectively collecting enrolled cervical cancer patients clinical data and outcome from June 2020 to June 2025. (Classification factors: preoperative neoadjuvant treatment , surgical approach, type of hysterectomy, whether to receive radiochemotherapy) . This study is an observational study, and segmented analysis according to different treatment methods.

Detailed Description: Objectives: To observe the effects of different treatments on the oncological outcome and complications of early cervical cancer (2018 FIGO stage IA1 with lymphovascular space invasion and IA2-IIA2 cervical cancer). Study Design: We obtained the demographic, clinical, treatment hospital and complication data of patients with cervical cancer undergoing radical hysterectomy from 2004 to 2015 at 37 hospitals. The patients were assigned into groups. Classification factors: preoperative neoadjuvant treatment (not received, neoadjuvant chemotherapy, preoperative radiotherapy) , surgical approach (abdomincal, laparoscopic, vaginal, robotic surgery), type of hysterectomy (type B, type C1, type C2), primary treatment (radiochemotherapy or surgery). laparoscopic and abdominal surgery groups. The differences in the survival, complication rates, quality of life, and cost were analyzed using univariate and multivariable logistic regression models.

Eligibility

Minimum Age: 18 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: FEMALE

Healthy Volunteers: No

Locations

Nanfang Hospital of Southern Medical University, Guangzhou, Guangdong, China

Contact Details

Name: Chen Chunlin, PhD

Affiliation: Nanfang Hospital, Southern Medical University

Role: PRINCIPAL_INVESTIGATOR

Useful links and downloads for this trial

Clinicaltrials.gov

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