Clinical trial Recruiting at 1 site Observational Ages 18 and up

Predictive model using CT scans, blood tests, and pathology to forecast pancreatic cancer outcomes

Official title: A Study on a Predictive Model for Efficacy and Prognosis of Pancreatic Carcinoma Based on Multimodal Data

Run by Shanghai Zhongshan Hospital · NCT07561814 · Data updated 2026-11-12

This project will try to see if combining CT scans, blood tests, and pathology reports can better predict outcomes for adults who had surgery for pancreatic cancer.

Quick facts

Study typeObservational
Ages18 Years and up
SexAll
Enrollment1030 (estimated)
SponsorShanghai Zhongshan Hospital
Academic / other
Locations1 site (Shanghai, Shanghai Municipality)
StatusRecruiting
StartedDecember 9, 2025
Main results expectedJuly 31, 2029
Study endsDecember 31, 2029
Registry record updatedJuly 2, 2026
Trial IDNCT07561814 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Adults (age ≥18) with histologically or cytologically confirmed pancreatic cancer who had surgical treatment at a participating center and have available pre- and postoperative CT images, clinical data, pathology reports, and blood test results are ideal candidates.

Probably not a fit

Patients without the required imaging or pathology data, those with other severe comorbidities, minors, pregnant or breastfeeding women, or people unable to consent or complete follow-up are unlikely to benefit.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational project will use preoperative and postoperative contrast-enhanced CT images, routine blood tests, and pathology reports from patients who underwent surgery for pancreatic cancer to build a multimodal predictive model using deep learning methods. Researchers will extract clinical and imaging features from existing medical records without adding tests or treatments and will conduct telephone follow-up about every three months for up to three years to capture outcomes. The main goals are to improve estimates of overall survival and risk of recurrence by integrating multiple data types. Data quality checks and exclusion of cases with excessive missing data or extreme outliers will be applied before modeling.

Why it matters

Potential benefit: If successful, the model could help clinicians give more accurate survival and recurrence estimates and better personalize follow-up and treatment planning.

How similar studies have gone: Previous radiomics and multimodal machine-learning studies in pancreatic and other cancers have shown promising but mixed results, so the approach is supported by preliminary evidence but not yet standard practice.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Age ≥ 18 years.
* Histologically or cytologically confirmed diagnosis of pancreatic cancer.
* Availability of preoperative and postoperative contrast-enhanced CT images at the participating center; patient records include corresponding clinical data, postoperative pathological reports, and preoperative and postoperative blood test results.
* Underwent surgical treatment for pancreatic cancer at a participating center of this study.

Exclusion Criteria:

* Age \< 18 years (minors).
* Presence of other severe diseases (e.g., severe liver or kidney failure, cardiovascular or cerebrovascular diseases, malignancies other than pancreatic cancer); pregnant or breastfeeding women; individuals with mental illness;
* patients unable to comply with follow-up or provide informed consent.
* Presence of significant outliers (e.g., laboratory values exceeding 10 times the normal range without clinically reasonable explanation) or samples with excessive missing data.

Where it's running

  • Zhongshan Hospital Affiliated to Fudan University
    Shanghai, Shanghai Municipality, China
    Recruiting

Similar studies

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How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.