Predictors of Ovarian Cancer and Endometrial Cancer for Artificial-Intelligence-Based Screening Tools
Associated Factors of Ovarian Cancer and Endometrial Cancer in Indonesia. A Study for Developing Artificial-Intelligence-Based Screening Tools
1 other identifier
observational
2,905
1 country
1
Brief Summary
The goal of this observational study is to explore the possible associated factors of ovarian cancer and endometrial cancer in Indonesia and develop screening tools that could predict the risk of both types of cancer The specific objectives of the study are
- 1.Elaborating the situation of ovarian and endometrial cancer in Indonesia
- 2.Exploring the possible clinical, demography and laboratory predictors of these diseases
- 3.Develop artificial-intelligence-based screening tools for both type of cancer based on possible predictors
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Feb 2023
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
January 14, 2023
CompletedFirst Posted
Study publicly available on registry
January 26, 2023
CompletedStudy Start
First participant enrolled
February 28, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
February 28, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
June 30, 2024
CompletedNovember 27, 2023
November 1, 2023
1 year
January 14, 2023
November 24, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Number of People developing ovarian cancer
Number of people developing ovarian cancer diagnosed with gynaecology and pathology assessment
from baseline to twelve month after entering cohort
Number of People developing endometrial cancer
Number of people developing endometrial cancer diagnosed with gynaecology and pathology assessment
from baseline to twelve month after entering cohort
Secondary Outcomes (1)
Screening Performance of Artificial-Intelligence-based Screening tools
from baseline assessment up to one year
Study Arms (3)
Suspect of Ovarian Cancer
The participant with high suspicion of ovarian cancer and undergo gynaecology and pathology assessment
Suspect of Endometrial Cancer
The participant with high suspicion of Endometrial cancer (and or endometrial hyperplasia) and undergo gynaecology and pathology assessment
Normal Cohort
The participant with lower suspicion of both types of cancer and undergo gynaecology and pathology assessment
Interventions
Artificial-Intelligence Based Screening Tools build on machine learning models
Pathology assessment of cells and tissues from respective organs
Eligibility Criteria
As this study is utilizing a patient registry, we will involve all eligible participants who undergo gynaecological and pathology assessment for ovarian and endometrial cancer in study centres, based on suggestive signs and symptoms
You may qualify if:
- Women with gynaecological symptoms but not limited to
- Irregular menstruation
- Heavy bleeding during menstruation
- pelvic pain
- vaginal discharge
- sudden weight loss
- pain during sexual intercourse
- Women who underwent routine gynaecological examination
You may not qualify if:
- unable to undergo serial gynaecological follow-up
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Hasanuddin Universitylead
- Chulalongkorn Universitycollaborator
Study Sites (1)
Hasanuddin University Hospital
Makassar, South Sulawesi, 90245, Indonesia
Related Publications (6)
Atallah GA, Abd Aziz NH, Teik CK, Shafiee MN, Kampan NC. New Predictive Biomarkers for Ovarian Cancer. Diagnostics (Basel). 2021 Mar 7;11(3):465. doi: 10.3390/diagnostics11030465.
PMID: 33800113BACKGROUNDElias KM, Guo J, Bast RC Jr. Early Detection of Ovarian Cancer. Hematol Oncol Clin North Am. 2018 Dec;32(6):903-914. doi: 10.1016/j.hoc.2018.07.003. Epub 2018 Sep 28.
PMID: 30390764BACKGROUNDTanha K, Mottaghi A, Nojomi M, Moradi M, Rajabzadeh R, Lotfi S, Janani L. Investigation on factors associated with ovarian cancer: an umbrella review of systematic review and meta-analyses. J Ovarian Res. 2021 Nov 11;14(1):153. doi: 10.1186/s13048-021-00911-z.
PMID: 34758846BACKGROUNDZhao J, Hu Y, Zhao Y, Chen D, Fang T, Ding M. Risk factors of endometrial cancer in patients with endometrial hyperplasia: implication for clinical treatments. BMC Womens Health. 2021 Aug 25;21(1):312. doi: 10.1186/s12905-021-01452-9.
PMID: 34433451BACKGROUNDFelix AS, Weissfeld JL, Stone RA, Bowser R, Chivukula M, Edwards RP, Linkov F. Factors associated with Type I and Type II endometrial cancer. Cancer Causes Control. 2010 Nov;21(11):1851-6. doi: 10.1007/s10552-010-9612-8. Epub 2010 Jul 14.
PMID: 20628804BACKGROUNDHerman B, Sirichokchatchawan W, Pongpanich S, Nantasenamat C. Development and performance of CUHAS-ROBUST application for pulmonary rifampicin-resistance tuberculosis screening in Indonesia. PLoS One. 2021 Mar 25;16(3):e0249243. doi: 10.1371/journal.pone.0249243. eCollection 2021.
PMID: 33765092BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- STUDY CHAIR
Rina Masadah, Ph.D
Hasanuddin University
- PRINCIPAL INVESTIGATOR
Bumi Herman, Ph.D
Chulalongkorn University
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Assistant Lecturer
Study Record Dates
First Submitted
January 14, 2023
First Posted
January 26, 2023
Study Start
February 28, 2023
Primary Completion
February 28, 2024
Study Completion
June 30, 2024
Last Updated
November 27, 2023
Record last verified: 2023-11
Data Sharing
- IPD Sharing
- Will not share
The individual participant data will be shared after de-identification and the purpose of the data utilization is verified by the investigators