Clinical Trials Logo

Clinical Trial 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 This study will utilize the patient registry diagnosed with ovarian and endometrial cancer. We assumed that several demography, clinical, and laboratory predictors might possess good screening performance with higher sensitivity and specificity (>80%).


Clinical Trial Description

Methodology : This study will involve two different stages 1. The first stage will conduct a cohort study to identify the possible predictors of each type of cancer 2. The second stage will cover the development of point-of-care testing based on an artificial intelligence model to predict cancer occurrence and prospective testing of the new participants using a diagnostic study method. The tools will predict the current histopathology result and possible future histopathology within one year. Participants and source of data In the study centre, women with or without gynaecology-associated symptoms underwent gynaecological and pathology assessments to rule out ovarian and endometrial cancer in our study centre were involved. Data is stored digitally and extraction will be done accordingly Variables and outcome measurement 1. Demographic data and health data this information is obtained from the initial assessment of the patients including age, body mass index, chronic diseases, gynaecological and obstetric profile, menstrual pattern, and contraception 2. Clinical and laboratory data this include, a complete blood count, selected cancer-associated biomarker (for example Cancer Antigen 125 (Ca-125)), involvement of lymph node, histopathology of pertinent tissues, and signs of metastases through clinical or radiological data 3. Outcome final histopathology type and classification assessed by at least two pathologists to determine the type of cancer. The guidelines of classification follow the World Health Organization's classification Development of Artificial-Intelligence-based screening tools 1. The researcher will develop - an information-based model where the user will provide a response to each predictor - an image-based model where the user will provide a captured image for prediction - a mixed-based model where the user can combine captured images and information for each predictor 2. proposed model - scoring-based derived from the coefficient of regression - decision tree - random forest - artificial neural network - convolutional neural network 3. Selection of model 1. Screening performance on split data (or using cross-validation technique) 2. evaluation of log-loss or likelihood Timeline 1. For the first stage of the study, there will be a time-varying assessment for each participant, however, at least participants undergo an Assessment of all factors and outcomes at baseline. Repeated evaluation as suggested by the physician will be done within one year after the baseline assessment. 2. The second study will apply prospective screening. The artificial intelligence-based screening tool will be used concurrently with the gold standard of diagnosis. Possible Bias procedural bias particularly in reliability outcome interpretation is handled by involving multiple pathologists. The pathologist and the screener will perform the screening independently to reduce the tendency of prior results provided by the newly-developed screening tools. Sample size 1. The first stage of the research assumes that a. The prevalence of both cancer among all cancers in women accounted for 5% b. Type I error set at 5% c. absolute error of the prevalence 1% using the one-sample proportion formula, the estimated sample size is 1825 participants. 2. Following the diagnostic study, we state that the new screening tools model will show non-inferiority performance to histopathology as gold-standard, assuming that a. the expected difference in sensitivity value is 5% assuming that the new screening tools will possess 85% sensitivity and the sensitivity of histopathology is 90% b. cross-over testing will be done, creating an equal allocation of screening intervention c. Type 1 error of the study set at 5% d. Power of the study set at 80% the total sample size for the prospective screening tool will be 1080 participants Data Quantification and discretization several clinical information will be classified according to the established guideline for example body mass index. Proposed Statistical Analysis 1. Descriptive statistic and bivariate analysis 2. A cox-regression will be conducted following the baseline-to-event timeline 3. Subgroup analysis will be done, particularly in certain demographic and comorbidity. as for the second stage, the analysis will identify the 1. sensitivity 2. specificity 3. accuracy 4. precision 5. The number Needed to Treat selected models will be deployed into an application. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05697601
Study type Observational
Source Hasanuddin University
Contact Bumi Herman, Ph.D
Phone +66638275008
Email bumi.h@chula.ac.th
Status Recruiting
Phase
Start date February 28, 2023
Completion date June 30, 2024

See also
  Status Clinical Trial Phase
Completed NCT02526017 - Study of Cabiralizumab in Combination With Nivolumab in Patients With Selected Advanced Cancers Phase 1
Withdrawn NCT05201001 - APX005M in Patients With Recurrent Ovarian Cancer Phase 2
Completed NCT02963831 - A Study to Investigate ONCOS-102 in Combination With Durvalumab in Subjects With Advanced Peritoneal Malignancies Phase 1/Phase 2
Not yet recruiting NCT06376253 - A Phase I Study of [177Lu]Lu-EVS459 in Patients With Ovarian and Lung Cancers Phase 1
Recruiting NCT05489211 - Study of Dato-Dxd as Monotherapy and in Combination With Anti-cancer Agents in Patients With Advanced Solid Tumours (TROPION-PanTumor03) Phase 2
Recruiting NCT03412877 - Administration of Autologous T-Cells Genetically Engineered to Express T-Cell Receptors Reactive Against Neoantigens in People With Metastatic Cancer Phase 2
Active, not recruiting NCT03667716 - COM701 (an Inhibitor of PVRIG) in Subjects With Advanced Solid Tumors. Phase 1
Active, not recruiting NCT03170960 - Study of Cabozantinib in Combination With Atezolizumab to Subjects With Locally Advanced or Metastatic Solid Tumors Phase 1/Phase 2
Recruiting NCT05156892 - Tamoxifen and SUBA-Itraconzole Combination Testing in Ovarian Cancer Phase 1
Suspended NCT02432378 - Intensive Locoregional Chemoimmunotherapy for Recurrent Ovarian Cancer Plus Intranodal DC Vaccines Phase 1/Phase 2
Recruiting NCT04533763 - Living WELL: A Web-Based Program for Ovarian Cancer Survivors N/A
Active, not recruiting NCT03371693 - Cytoreductive Surgery(CRS) Plus Hyperthermic Intraperitoneal Chemotherapy(HIPEC) With Lobaplatin in Advanced and Recurrent Epithelial Ovarian Cancer Phase 3
Withdrawn NCT03032614 - Combination of Carboplatin, Eribulin and Veliparib in Stage IV Cancer Patients Phase 2
Completed NCT02019524 - Phase Ib Trial of Two Folate Binding Protein Peptide Vaccines (E39 and J65) in Breast and Ovarian Cancer Patients Phase 1
Completed NCT01936363 - Trial of Pimasertib With SAR245409 or Placebo in Ovarian Cancer Phase 2
Terminated NCT00788125 - Dasatinib, Ifosfamide, Carboplatin, and Etoposide in Treating Young Patients With Metastatic or Recurrent Malignant Solid Tumors Phase 1/Phase 2
Active, not recruiting NCT05059522 - Continued Access Study for Participants Deriving Benefit in Pfizer-Sponsored Avelumab Parent Studies That Are Closing Phase 3
Active, not recruiting NCT04383210 - Study of Seribantumab in Adult Patients With NRG1 Gene Fusion Positive Advanced Solid Tumors Phase 2
Terminated NCT04586335 - Study of CYH33 in Combination With Olaparib an Oral PARP Inhibitor in Patients With Advanced Solid Tumors. Phase 1
Terminated NCT03146663 - NUC-1031 in Patients With Platinum-Resistant Ovarian Cancer Phase 2