Spots Global Cancer Trial Database for The Prediction of Anastomotic Insufficiency Risk After Colorectal Surgery (PANIC) Study

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Trial Identification

Brief Title: The Prediction of Anastomotic Insufficiency Risk After Colorectal Surgery (PANIC) Study

Official Title: The Prediction of Anastomotic Insufficiency Risk After Colorectal Surgery (PANIC) Study: Development and External Validation of an International, Multicenter Machine Learning Algorithm for Prediction of Anastomotic Insufficiency After Colonic or Colorectal Anastomosis

Study ID: NCT04985981

Conditions

Interventions

Study Description

Brief Summary: The Prediction of Anastomotic Insufficiency risk after Colorectal surgery (PANIC) study aims to establish a machine-learning-based application that allows for accurate preoperative prediction of patients at risk for anastomotic insufficiency after colon and colorectal surgery.

Detailed Description: Anastomotic insufficiency leads to clinical strains for patients, and significantly increases morbidity and mortality. On average, hospital stay is extended by 12 days while healthcare-related expenses are increased by 30,000 USD when patients suffer from an anastomotic leak. In experienced centers, the approximated incidence of anastomotic insufficiency is 3,3% for colon and 8.6% for colorectal procedures. Multiple subgroups of patients with increased risk for anastomotic leaks have been described in previous publications. Meticulous preoperative recognition of patients with increased risk for anastomotic insufficiency is clinically beneficial, as it would permit improved ressource preparation, enhanced patient education and superior surgical decision-making. However, it is often difficult for clinicians to balance the plethora of crucial risk factors for anastomotic leaks for a single patient. Machine learning methods have been exceptionally effective at incorporating various clinical variables into one unified risk prediction model. To the authors' best knowledge, there does not yet exist a credible prediction model or a conclusive prediction score for anastomotic insufficiency after colon and colorectal anastomosis. The aim of the Prediction of Anastomotic Insufficiency risk after Colorectal surgery (PANIC) study is to establish and externally validate an efficient machine-learning-based prediction tool based on multicenter data from a range of international centers.

Keywords

Anastomotic Leak

Eligibility

Minimum Age: 18 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: ALL

Healthy Volunteers: No

Locations

Clinical Research and Artificial Intelligence in Surgery, Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland, Allschwil, Basel, Switzerland

Kantonsspital Winterthur, Winterthur, Zürich, Switzerland

Contact Details

Name: Michel Adamina, Prof. Dr. med.

Affiliation: Clinical Research and Artificial Intelligence in Surgery, Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland

Role: STUDY_CHAIR

Name: Anas Taha, Dr. med.

Affiliation: None currently

Role: PRINCIPAL_INVESTIGATOR

Name: Thomas Steffen

Affiliation: Cantonal Hospital of St. Gallen

Role: PRINCIPAL_INVESTIGATOR

Name: Stephanie Taha-Mehlitz, Dr. med.

Affiliation: Department of Visceral Surgery, Clarunis, University Hospital Basel, Basel, Switzerland

Role: PRINCIPAL_INVESTIGATOR

Name: Frédéric Ris, Prof. Dr. med.

Affiliation: Department of Surgery, Hôpitaux Universitaires de Genève