EOCRCPred: an AI Model to Predict Survival in EOCRC Patients After Surgery
NCT ID: NCT06690606
Last Updated: 2024-11-15
Study Results
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Basic Information
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NOT_YET_RECRUITING
250 participants
OBSERVATIONAL
2024-11-12
2025-05-11
Brief Summary
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Can machine learning models accurately predict the long-term survival of EOCRC patients after surgical treatment?
Participants who have already undergone surgery for EOCRC as part of their regular medical care will have their clinical data analyzed, with survival outcomes tracked through follow-up assessments. An online survival calculator will also be developed to aid clinicians and patients in predicting personalized survival outcomes.
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Detailed Description
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* Study Title\*\*: \*EOCRCPred: An AI Model to Predict Survival in Early-onset Colorectal Cancer Patients After Surgery\*
* Introduction\*\*:
This study addresses the increasing incidence and mortality of early-onset colorectal cancer (EOCRC) in patients under 50. EOCRC exhibits distinct clinical and pathological features compared to late-onset CRC, including higher recurrence rates and advanced disease stages at diagnosis. Current predictive models for postoperative outcomes in EOCRC are limited, highlighting the need for specialized tools to guide treatment decisions.
* Objectives\*\*:
1. Develop AI models for predicting overall survival (OS) in postoperative M0 EOCRC patients.
2. Propose a new survival risk stratification system.
3. Deploy an online survival calculator to assist clinical decision-making.
* Methods\*\*:
* \*\*Data Source\*\*: SEER database (2010-2019) for training/testing; two Chinese hospitals for external validation (2014-2024).
* \*\*Inclusion Criteria\*\*: Pathologically confirmed primary EOCRC, radical surgery (stage I-III), and complete follow-up.
* \*\*Models\*\*: Six predictive models, including CoxPH, RSF, S-SVM, XGBSE, GBSA, and DeepSurv.
* \*\*Evaluation Metrics\*\*: Discrimination (C-index, time-dependent AUC), calibration (Brier score, calibration curves), and clinical utility (Decision Curve Analysis).
* Statistical Analysis\*\*:
Comparisons were made using t-tests, Mann-Whitney U tests, and chi-square tests, with P \< 0.05 indicating significance.
\*\*Risk Stratification\*\*: Risk groups were classified based on RSF-derived scores (low, intermediate, high), and survival differences were assessed via Kaplan-Meier curves and log-rank tests.
This streamlined summary covers the primary goals, methodology, and analysis without repeating specifics that will be detailed in other sections of the record.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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external validation cohort
The external validation cohort was composed of primary EOCRC patients who underwent radical resection at Putuo Hospital and Yueyang Hospital, both affiliated with Shanghai University of Traditional Chinese Medicine. The cohort includes patients diagnosed between January 2014 and June 2024.
Inclusion criteria: Patients with pathologically confirmed primary EOCRC, aged under 50 years, and who received radical surgery (stages I-III according to the AJCC 7th edition).
Exclusion criteria: Patients with multiple primary cancers, survival time under 1 month, or missing critical data.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Radical surgery performed (Specific Surgery Codes 30-70, including partial/subtotal colectomy, hemicolectomy, right/left colectomy, and total colectomy, as well as partial or total removal of other organs and regional lymph nodes)
* Stage I-III disease according to the 7th AJCC-TNM system
Exclusion Criteria
* Survival time of less than 1 month, or absence of postoperative follow-up information
* Incomplete critical clinical feature information
18 Years
49 Years
ALL
No
Sponsors
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Shanghai University of Traditional Chinese Medicine
OTHER
Responsible Party
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Wanli Deng, MD
Principal Investigator
Principal Investigators
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Wanli Deng
Role: PRINCIPAL_INVESTIGATOR
Putuo Hospital, Shanghai University of Traditional Chinese Medicine
Locations
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Putuo Hospital, Shanghai University of Traditional Chinese Medicine
Shanghai, , China
Yueyang Hospital of Integrated Traditional Chinese and Western Medicine
Shanghai, , China
Countries
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Central Contacts
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Facility Contacts
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Wanli Deng
Role: primary
Other Identifiers
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2021tszk01
Identifier Type: OTHER_GRANT
Identifier Source: secondary_id
2023-BSH-02
Identifier Type: OTHER_GRANT
Identifier Source: secondary_id
PTEC-A-2024-61 (S)
Identifier Type: -
Identifier Source: org_study_id
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