Vulvar Cancer Individualized Scoring System (VCISS)

NCT06007625 | Unknown

• 1 other identifier: MCOG-VC01
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 2

Brief Summary

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.

Conditions

Vulvar Cancer

Outcome Measures

Primary Outcomes (1)

• cancer-specific survival (CSS) rate 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.

  at 3 and 5 years

Secondary Outcomes (1)

• Recurrence-free survival (RFS) rate at 3 and 5 years

  at 3 and 5 years

Interventions

Machine learning-based prediction model OTHER

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.

Eligibility Criteria

• Age: 18 Years - 80 Years
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All women who will be diagnosed with primary vulvar cancer at any stage, of all histological types and grades eligible for the study

You may qualify if:

• 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.

You may not qualify if:

• 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

Sponsors & Collaborators

• Assiut University: lead

Study Sites (2)

Alexandria University Main Hospital

Alexandria, 21516, Egypt

Location

Assiut Hospitals university

Asyut, 71511, Egypt

Location

Related Publications (10)

• Shetty AS, Menias CO. MR Imaging of Vulvar and Vaginal Cancer. Magn Reson Imaging Clin N Am. 2017 Aug;25(3):481-502. doi: 10.1016/j.mric.2017.03.013. Epub 2017 May 27.

  PMID: 28668156 BACKGROUND

• Chow L, Tsui BQ, Bahrami S, Masamed R, Memarzadeh S, Raman SS, Patel MK. Gynecologic tumor board: a radiologist's guide to vulvar and vaginal malignancies. Abdom Radiol (NY). 2021 Dec;46(12):5669-5686. doi: 10.1007/s00261-021-03209-2. Epub 2021 Aug 25.

  PMID: 34435227 BACKGROUND

• Merlo S. Modern treatment of vulvar cancer. Radiol Oncol. 2020 Sep 22;54(4):371-376. doi: 10.2478/raon-2020-0053.

  PMID: 32960779 BACKGROUND

• Madsen BS, Jensen HL, van den Brule AJ, Wohlfahrt J, Frisch M. Risk factors for invasive squamous cell carcinoma of the vulva and vagina--population-based case-control study in Denmark. Int J Cancer. 2008 Jun 15;122(12):2827-34. doi: 10.1002/ijc.23446.

  PMID: 18348142 BACKGROUND

• Brinton LA, Thistle JE, Liao LM, Trabert B. Epidemiology of vulvar neoplasia in the NIH-AARP Study. Gynecol Oncol. 2017 May;145(2):298-304. doi: 10.1016/j.ygyno.2017.02.030. Epub 2017 Feb 22.

  PMID: 28236455 BACKGROUND

• de Koning MN, Quint WG, Pirog EC. Prevalence of mucosal and cutaneous human papillomaviruses in different histologic subtypes of vulvar carcinoma. Mod Pathol. 2008 Mar;21(3):334-44. doi: 10.1038/modpathol.3801009. Epub 2008 Jan 11.

  PMID: 18192968 BACKGROUND

• Halec G, Alemany L, Quiros B, Clavero O, Hofler D, Alejo M, Quint W, Pawlita M, Bosch FX, de Sanjose S. Biological relevance of human papillomaviruses in vulvar cancer. Mod Pathol. 2017 Apr;30(4):549-562. doi: 10.1038/modpathol.2016.197. Epub 2017 Jan 6.

  PMID: 28059099 BACKGROUND

• Virarkar M, Vulasala SS, Daoud T, Javadi S, Lall C, Bhosale P. Vulvar Cancer: 2021 Revised FIGO Staging System and the Role of Imaging. Cancers (Basel). 2022 Apr 30;14(9):2264. doi: 10.3390/cancers14092264.

  PMID: 35565394 BACKGROUND

• Salvo G, Odetto D, Pareja R, Frumovitz M, Ramirez PT. Revised 2018 International Federation of Gynecology and Obstetrics (FIGO) cervical cancer staging: A review of gaps and questions that remain. Int J Gynecol Cancer. 2020 Jun;30(6):873-878. doi: 10.1136/ijgc-2020-001257. Epub 2020 Apr 1.

  PMID: 32241876 BACKGROUND

• Miljanovic-Spika I, Madunic MD, Topolovec Z, Kujadin Kenjeres D, Vidosavljevic D. PROGNOSTIC FACTORS FOR VULVAR CANCER. Acta Clin Croat. 2021 Mar;60(1):25-32. doi: 10.20471/acc.2021.60.01.04.

  PMID: 34588718 BACKGROUND

MeSH Terms

Conditions

Vulvar Neoplasms

Condition Hierarchy (Ancestors)

Genital Neoplasms, Female; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Vulvar Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases

Central Study Contacts

Sherif Shazly

CONTACT

+4407554480388; sherif.shazly.mogge@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Sherif Abdelkarim Mohammed Shazly, Assistant lecturer, Assiut University

Study Record Dates

• First Submitted: August 17, 2023
• First Posted: August 23, 2023
• Study Start: January 1, 2024
• Primary Completion: October 1, 2024
• Study Completion: December 1, 2024
• Last Updated: August 23, 2023

Record last verified: 2023-08

Locations

EG (2)