Clinical trial NCT06690606: EOCRCPred: an AI Model to Predict Survival in EOCRC Patients After Surgery
Official title: EOCRCPred: an AI Model for Predicting Overall Survival in Early-Onset Stage I-III Colorectal Cancer Patients Post-Radical Resection-A SEER Database and Dual-Center Chinese Medical Institutions Study
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Colorectal Cancer
Keywords: AI model
prediction
Early-Onset Colorectal Cancer (EOCRC)
postoperative survival
surgery
Lead sponsor: Shanghai University of Traditional Chinese Medicine
Sponsor class: OTHER
First posted: 2024-11-15
Enrollment: 250
Sex: ALL
Minimum age (years): 18
Maximum age (years): 49
Standard ages: ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Consecutive patients with early-onset, Stage I-III colorectal cancer who underwent radical resection at Putuo Hospital and Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, both affiliated with Shanghai University of Traditional Chinese Medicine, were retrospectively collected between January 2014 and June 2024.

Brief summary: The goal of this observational study is to develop a predictive model for overall survival in patients under the age of 50 who have undergone surgery for early-onset colorectal cancer (EOCRC). The main question it aims to answer is:

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.

Detailed description: To avoid duplicating information that will be entered or uploaded elsewhere in the record, here is a concise summary of the key components of the study:

* 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.

Eligibility criteria: Inclusion Criteria:

* Primary EOCRC confirmed by pathological histological examination (ICD-10 codes: C18.0, C18.2-18.9, C19.9, C20.9)
* 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:

* Patients with multiple primary cancers or other malignancies
* Survival time of less than 1 month, or absence of postoperative follow-up information
* Incomplete critical clinical feature information

Primary outcomes:
measure: Assessment of Clinical Characteristics and Survival Status of Subjects Using the CRF Scale
timeFrame: 2024.11
Secondary outcomes:
Other outcomes:
Locations:
city: Shanghai
country: China
facility: Putuo Hospital, Shanghai University of Traditional Chinese Medicine
city: Shanghai
country: China
facility: Yueyang Hospital of Integrated Traditional Chinese and Western Medicine
Study officials:
affiliation: Putuo Hospital, Shanghai University of Traditional Chinese Medicine
name: Wanli Deng
role: PRINCIPAL_INVESTIGATOR
References: