Ignite Creation Date:
2025-12-25 @ 12:43 AM
Ignite Modification Date:
2025-12-25 @ 10:55 PM
Study NCT ID:
NCT07267767
Status:
COMPLETED
Last Update Posted:
2025-12-05
First Post:
2025-07-09
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Comparison of Six Different Machine Learning Methods With Traditional Model for Low Anterior Resection Syndrome After Minimally Invasive Surgery for Rectal Cancer -- Development and External Validation of a Nomogram : A Dual-center Cohort Study
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D012004', 'term': 'Rectal Neoplasms'}, {'id': 'D000094123', 'term': 'Low Anterior Resection Syndrome'}], 'ancestors': [{'id': 'D015179', 'term': 'Colorectal Neoplasms'}, {'id': 'D007414', 'term': 'Intestinal Neoplasms'}, {'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D007410', 'term': 'Intestinal Diseases'}, {'id': 'D012002', 'term': 'Rectal Diseases'}, {'id': 'D003108', 'term': 'Colonic Diseases'}, {'id': 'D011183', 'term': 'Postoperative Complications'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 3500}, 'targetDuration': '15 Months', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2015-04-10', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-11', 'completionDateStruct': {'date': '2024-06-20', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-11-25', 'studyFirstSubmitDate': '2025-07-09', 'studyFirstSubmitQcDate': '2025-11-25', 'lastUpdatePostDateStruct': {'date': '2025-12-05', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-12-05', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2023-10-07', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'low anterior resection syndrome', 'timeFrame': '1 and 3 months after surgery'}, {'measure': 'Comparison of Six Different Machine Learning Methods With Traditional Model for Low Anterior Resection Syndrome After Minimally Invasive Surgery for Rectal Cancer -- Development and External Validation of a Nomogram : A Dual-center Cohort Study', 'timeFrame': '3 months', 'description': 'using LARS Score to assess the LARS situation'}]}, 'conditionsModule': {'conditions': ['Rectal Cancer', 'LARS - Low Anterior Resection Syndrome']}, 'descriptionModule': {'briefSummary': 'Following thorough screening based on inclusion and exclusion criteria, patients from the two sizable medical centers were split up into two cohorts for this study. Cohort 1 served primarily as the training and internal validation set, while Cohort 2 was used for external validation of the predictive model constructed from Cohort 1. We used six distinct machine learning methodss, including DT, RF, XGBOOST, SVM, lightGBM, and SHLNN, in addition to conventional logistic regression to create the predictive model. We chose the approach with the best sensitivity and specificity by comparing the concordance index(C-index) akin to the area under the ROC curve (AUC) of these seven distinct model-building methods. The predictive model for Cohort 1 was then built using this method, and internal validation was finished. Lastly, Cohort 2 underwent external validation of the predictive model'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': "This retrospective analysis included 3,937 radical rectal cancer cases from two Chinese university hospitals (Northern Jiangsu People's Hospital 2015-2023, n=2612; Jilin University's China-Japan Union Hospital 2021-2023, n=1325), with rigorous selection criteria ensuring cohort homogeneity", 'eligibilityCriteria': 'Inclusion Criteria:(1) rectal adenocarcinoma (2) minimally invasive sphincter-preserving surgery (taTME/ISR/LAR) (3) intact baseline anal function (4) no emergent presentations or metastases.\n\n\\-\n\nExclusion Criteria:emergent presentations or metastases\n\n\\-'}, 'identificationModule': {'nctId': 'NCT07267767', 'briefTitle': 'Comparison of Six Different Machine Learning Methods With Traditional Model for Low Anterior Resection Syndrome After Minimally Invasive Surgery for Rectal Cancer -- Development and External Validation of a Nomogram : A Dual-center Cohort Study', 'organization': {'class': 'OTHER', 'fullName': "Northern Jiangsu People's Hospital"}, 'officialTitle': 'Comparison of Six Different Machine Learning Methods With Traditional Model for Low Anterior Resection Syndrome After Minimally Invasive Surgery for Rectal Cancer -- Development and External Validation of a Nomogram : A Dual-center Cohort Study', 'orgStudyIdInfo': {'id': 'jiangsuNorthen20'}}, 'armsInterventionsModule': {'interventions': [{'name': 'nCRT', 'type': 'PROCEDURE', 'description': 'neoadjuvant chemoradiotherapy'}, {'name': 'BMI', 'type': 'BEHAVIORAL', 'description': 'Body Mass Index'}, {'name': 'Distance from AV', 'type': 'DIAGNOSTIC_TEST', 'description': 'Distance from AV'}, {'name': 'Surgical type', 'type': 'PROCEDURE', 'description': 'laparoscopic and robotic surgery'}, {'name': 'Surgical approach', 'type': 'PROCEDURE', 'description': 'tatme + isr'}, {'name': 'LCA Preserving', 'type': 'PROCEDURE', 'description': 'LCA Preserving'}, {'name': 'Prophylactic stoma', 'type': 'PROCEDURE', 'description': 'Prophylactic stoma'}, {'name': 'Anastomotic leakage', 'type': 'PROCEDURE', 'description': 'Anastomotic leakage'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': "Northern Jiangsu People's Hospital", 'class': 'OTHER'}, 'collaborators': [{'name': 'China-Japan Union Hospital, Jilin University', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'NANJING UNIVERSITY', 'investigatorFullName': 'Daorong Wang', 'investigatorAffiliation': "Northern Jiangsu People's Hospital"}}}}