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OpenTrials
Completed

NCT Number: NCT05589480

Machine Learning for Recurrence Risk of Pancreatic Cancer After Radical Resection

Recurrence of Pancreatic Cancer(PCa) is a multifactorial event. Based on the clinicopathological characteristics and imaging data of patients with PCa, the investigators used image processing and machine learning algorithms to build a more comprehensive and robust model, and added some unused features to explore its clinical application value.

A retrospective analysis of patients with PCa who underwent radical resection at Zhejiang Cancer Hospital (Hangzhou, China) from January 2013 to December 2020. The database was extracted from the preoperative demographics, blood markers, and surgical pathology information of patients undergoing radical PCa surgery in the investigators' hospital. The investigators used the PyRadiomics platform to extract image features.

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Key information

Conditions

Pancreatic Cancer Digestive System Diseases Digestive System Neoplasms Endocrine Gland Neoplasms Endocrine System Diseases Neoplasms Neoplasms by Site Pancreatic Diseases Pancreatic Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Zhejiang Province Cancer Hospital

Hangzhou, Zhejiang, 310000, China

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Have the results of enhanced CT examination of the pancreas within 1 month before surgery in our hospital;
  • Radical resection of pancreatic cancer was performed in our hospital;
  • There are follow-up results in our hospital, and the follow-up endpoints include disease recurrence or at least 12 months.
  • Complete clinical medical records and imaging data.

Exclusion criteria

  • non-R0 resection;
  • Combined with other malignant tumors
  • The patient's imaging data has technical problems or the lesion is too small (less than 1cm), which is not suitable for omics analysis.

Treatment and study plan

preoperative demographics, blood markers, surgical pathology information，and enhanced CT features.

Other

preoperative demographics, blood markers, surgical pathology information，and enhanced CT features.

Primary outcomes

  1. Recurrence-free survival

    Time frame: 1 year

Sponsors and collaborators

Lead sponsor

Luo Cong

Other

Registry information

Official study title

Multimodal Data Prediction Based on Machine Learning for Recurrence Risk of Pancreatic Cancer After Radical Resection

Acronym: PaC

Important dates

Study start
2022
Primary completion
2022
Study completion
2022
First posted
Oct 21, 2022
Registry last updated
Dec 11, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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