Rectal CancerNCT07267767
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
An observational study of Rectal Cancer and LARS - Low Anterior Resection Syndrome, run by Northern Jiangsu People's Hospital.
Trial summary
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… Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Rectal Cancer, LARS - Low Anterior Resection Syndrome
- What is being tested?
- nCRT, BMI and Distance from AV
- Type of treatment
- Surgery or procedure, Lifestyle or therapy programme
- How many people
- 3,500 participants
- Where
- No sites listed yet
- Study dates
- 10 Apr 2015to 20 Jun 2024
- How long will I take part?
- 15 Months
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Child, Adult, Older adult
Study population: 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
Who may be able to join
None listed.
Who cannot join
- -
About this study
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
- Being tested
- nCRT, BMI, Distance from AV, Surgical type, Surgical approach
- Medical subject headings
- Rectal Neoplasms, Low Anterior Resection Syndrome
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
nCRTProcedure or surgery
neoadjuvant chemoradiotherapy
BMIBehavioural
Body Mass Index
Distance from AVDiagnostic test
Distance from AV
Surgical typeProcedure or surgery
laparoscopic and robotic surgery
Surgical approachProcedure or surgery
tatme + isr
LCA PreservingProcedure or surgery
LCA Preserving
Prophylactic stomaProcedure or surgery
Prophylactic stoma
Anastomotic leakageProcedure or surgery
Anastomotic leakage
What is being measured
The primary outcome is the main question the study is designed to answer.
low anterior resection syndrome
Measured: 1 and 3 months after surgery
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
using LARS Score to assess the LARS situation
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Dec 2025
- Study start10 Apr 2015
- Primary completion7 Oct 2023
- Study completion20 Jun 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Rectal CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 3,500 participants (actual)
- Target duration
- 15 Months
Sponsor and investigators
- Lead sponsor
- Northern Jiangsu People's Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- China-Japan Union Hospital, Jilin University
- Responsible party
- Principal investigator, Daorong Wang, Northern Jiangsu People's Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07267767
- Sponsor's protocol ID
- jiangsuNorthen20
- Status last verified
- Nov 2025
- First submitted
- 9 Jul 2025
- Last updated
- 5 Dec 2025
- Results posted
- No
Study at a glance
From the registry record, last updated by the sponsor on 5 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official 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
- ClinicalTrials.gov ID
- NCT07267767
- Acronym / sponsor ID
- jiangsuNorthen20
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 3,500 participants (actual)
- Lead sponsor
- Northern Jiangsu People's HospitalUniversity, hospital or other
- Collaborators
- China-Japan Union Hospital, Jilin University
- Study start
- 10 Apr 2015 (actual)
- Primary completion
- 7 Oct 2023 (actual)
- Study completion
- 20 Jun 2024 (actual)
- First posted
- 5 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Target follow-up
- 15 Months
Who may qualify
- Sex
- All
- Age groups
- Child, Adult, Older adult
- Study population
- 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
Key inclusion criteria (0 listed)
Key exclusion criteria (1 listed)
- -
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| nCRTneoadjuvant chemoradiotherapy | Procedure or surgery | – |
| BMIBody Mass Index | Behavioural | – |
| Distance from AVDistance from AV | Diagnostic test | – |
| Surgical typelaparoscopic and robotic surgery | Procedure or surgery | – |
| Surgical approachtatme + isr | Procedure or surgery | – |
| LCA PreservingLCA Preserving | Procedure or surgery | – |
| Prophylactic stomaProphylactic stoma | Procedure or surgery | – |
| Anastomotic leakageAnastomotic leakage | Procedure or surgery | – |
Primary outcome
low anterior resection syndrome
Time frame: 1 and 3 months after surgery
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
Time frame: 3 months
using LARS Score to assess the LARS situation
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Dec 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Rectal Cancer and LARS - Low Anterior Resection Syndrome, run by Northern Jiangsu People's Hospital.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 0 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 5 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
low anterior resection syndrome (time frame: 1 and 3 months after surgery). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Dec 2025.