Clinical trial NCT04819074: Prediction of Outcomes After Surgery for Unruptured Intracranial Aneurysms
Official title: The Prediction of Adverse Events After Microsurgery for Intracranial Unruptured Aneurysms (PRAEMIUM) Study
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Aneurysm, Brain
Keywords: machine learning
unruptured aneurysm
Lead sponsor: University of Zurich
Sponsor class: OTHER
Collaborators: name: Macquarie University, Australia
name: University of Melbourne
name: Kepler University Hospital
name: Medical University Innsbruck
name: General University Hospital, Prague
name: Universitätsklinikum Köln
name: Goethe University
name: University Medical Center Mainz
name: University of Göttingen
name: University Hospital Dresden
name: Charite University, Berlin, Germany
name: Heinrich-Heine University, Duesseldorf
name: University of Roma La Sapienza
name: University of Padova
name: University of Florence
name: Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta
name: University of Messina
name: Universita di Verona
name: Uniuversity of Genua, Italy
name: Leiden University Medical Center
name: Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
name: UMC Utrecht
name: Burdenko Neurosurgery Institute
name: Sahlgrenska University Hospital
name: University of Bern
name: Barrow Neurological Institute
name: Stanford University
name: Emory University
name: University of Wisconsin, Madison
name: University of California, San Francisco
name: University of Illinois at Chicago
name: Brigham and Women's Hospital
name: Mayo Clinic
name: University of California, Los Angeles
name: Endeavor Health
name: Fondazione Policlinico Universitario Agostino Gemelli IRCCS
First posted: 2021-03-26
Enrollment: 4000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: We will include all adult patients (18 years or older) undergoing microsurgical treatment for UIAs. No specific exclusion criteria will be set. Patients with prior SAH may only be included when surgical treatment occurred at least 4 weeks after ictus. Only patients treated from January 1st 2010 onwards can be included in this study.

Brief summary: Accurate preoperative identification of patients at high risk for adverse outcomes would be clinically advantageous, as it would allow enhanced resource preparation, better surgical decision-making, enhanced patient education and informed consent, and potentially even modification of certain modifiable risk factors. The aim of the Prediction of adverse events after microsurgery for intracranial unruptured aneurysms (PRAEMIUM) study is therefore to develop and externally validate a clinically applicable, robust ML-based prediction tool based on multicenter data from a range of international centers.

Detailed description: Introduction Unruptured intracranial aneurysms (UIAs) are incidentally detected at an increasing rate, mostly owing to the rise in availability of non-invasive cranial imaging. Decision-making in UIAs is complex and requires consideration of many risk factors for aneurysm growth and rupture to balance the benefits and risks of treatment versus observation. This is due to: 1) the high morbidity and case fatality inherent to aneurysmal subarachnoid hemorrhage (SAH) 2) the relatively low rupture rate of unruptured aneurysms; 3) the potential morbidity and mortality rate associated with either microsurgical or endovascular treatment.

Some consistent risk factors for rupture have been identified, including involvement of the posterior circulation, larger diameter, higher age, and some specific populations such as Japanese and Finnish patients. Many other risk factors have been suggested based on varying levels of evidence. However, it is difficult to integrate this considerable number of factors into a single risk assessment and to present a clear clinical decision making algorithm to patients. A range of scoring systems have been developed and validated to approximate the risk of rupture (PHASES) and growth (ELAPSS) or to balance the risks and benefits of microsurgical treatment versus follow-up imaging directly (UIATS) by integrating some of these risk factors. Still, these scores are focused on predicting rupture events instead of neurological outcome. In addition, they usually are focused on solely one outcome, instead of providing a wide range of objective predictive analytics that may then improve shared decision-making.

Machine learning (ML) methods have been extraordinarily effective at integrating many clinical patient variables into one holistic risk prediction tailored to each patient. A previous pilot study has been carried out to assess the feasibility of predicting surgical outcomes after surgery for UIAs in a small single-center sample, and it was found that prediction was feasible with good performance metrics, and the most important factors to be included in such models were also identified. A robust, multicenter, externally validated prediction model or predictive score for surgical outcome after microsurgery for UIAs does not yet exist.

Methods Data will be collected by a range of international centers. Overall, the model will be built and publication will be compiled according to the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines.

Each center will collect their data either retrospectively, or from a prospective registry, or from a prospective registry supplemented by retrospectively collected variables. Data from patients operated from January 1st 2010 and onwards will be eligible for inclusion. Data collection should be completed, and deidentified data should be sent to the sponsor institution.

A standardized Excel spreadsheet will be provided by the sponsor. The data will be entered in standardized and anonymized form. This spreadsheet will only contain a study-specific patient number. The data set is anonymized source data that includes clinical data extracted from electronic health records (retrospectively or from a prospective registry of already existing data). The data will be anonymized upon entering them into the PRAEMIUM Excel spreadsheet, after which the patients will be numbered consecutively and there will be no way to trace the data back to individual patients. No identifiable data such as date of birth will be included. Whenever the PRAEMIUM Excel spreadsheet is transferred, it will be encrypted using a password and sent through a secure institutional e-mail server. The password will be sent in a separate e-mail. Some missing data is acceptable, but should be kept to a minimum (i.e. must be \< 10%)

Endpoint Definitions Models will be developed for the following three endpoints at discharge: Poor neurological outcome (1), as well as presence of (2) new sensorimotor neurological deficits and (3) any complications (surgical or non-surgical). Neurological outcome was assessed by the modified Rankin scale (mRS), and a favorable neurological outcome was defined as mRS 0, 1, or 2. Complications will be assessed using the modified 2009 Clavien-Dindo grading (CDG), and occurrence of a complication was defined as any deviation from CDG 0.The Clavien-Dindo grading system is a classification of surgical complications: Grad 0 signifying no complication, Grade I identifying complications with any deviation from the normal intra- or postoperative course requiring medical treatment, and so forth. Detailed definitions are provided in the Excel spreadsheet. Surgery-related as well as none-surgery-related complications are counted. In case of multiple complications, only the complication with the highest CDG was counted per patient.

Input Feature Definitions All features are measured preoperatively. Recorded baseline variables will include age, gender, maximum aneurysm diameter, anatomical location (artery), total number of aneurysms per patient, if multiple aneurysms were treated during the index session, calcification of the aneurysm wall or neck, aneurysm morphology (saccular, dissecting, fusiform, or other), involvement of critical perforating or branch vessels, and intraluminal thrombosis.

In addition, the investigators will capture prior SAH, mRS at admission, prior aneurysm treatment, presence of anticoagulation/antiplatelet therapy preoperatively, and hypertension, as well as American Society of Anesthesiologists (ASA) grading, the PHASES, ELAPSS, and UIATS scores including the UIATS "pro-repair" and "pro-conservative treatment" subscores. The unruptured intracranial aneurysm treatment score (UIATS) consists of two subscores: One that represents the strength of recommendation for invasive repair of an unruptured aneurysm, and one that represents the strength of recommendation for conservative management of an unruptured aneurysm. The final overall UIATS score is subsequently calculated as the difference between the two subscores. Also included was the surgical approach: minimally invasive or standard approach, and whether a bypass was performed.

Eligibility criteria: Inclusion Criteria:

* Adult patients (18 or older)
* Undergone microsurgical treatment for unruptured intracranial aneurysm
* Patients with prior SAH may only be included when surgical treatment occurred at least 4 weeks after ictus.
* Treated from January 1st 2010 onwards

Exclusion Criteria:

* No specific exclusion criteria

Primary outcomes:
measure: modified Rankin Scale
timeFrame: Within 24 hours of admission to discharge, assessed up to 30 days
measure: Sensorimotor neurological deficits
timeFrame: Within 24 hours of admission to discharge, assessed up to 30 days
measure: Clavien Dindo Complication Grading
timeFrame: Within 24 hours of admission to discharge, assessed up to 30 days
Secondary outcomes:
Other outcomes:
Locations:
city: Phoenix
country: United States
facility: Barrow Neurological Institute
state: Arizona
city: Los Angeles
country: United States
facility: UCLA
state: California
city: San Francisco
country: United States
facility: UCSF
state: California
city: Stanford
country: United States
facility: Stanford University
state: California
city: Atlanta
country: United States
facility: Emory University Hospital
state: Georgia
city: Chicago
country: United States
facility: University of Illinois
state: Illinois
city: Boston
country: United States
facility: Brigham and Women's Hospital
state: Massachusetts
city: Rochester
country: United States
facility: Mayo Clinic
state: Minnesota
city: Manhasset
country: United States
facility: North Shore University Hospital
state: New York
city: Madison
country: United States
facility: University of Wisconsin
state: Wisconsin
city: Melbourne
country: Australia
facility: Royal Melbourne Hospital
city: Sydney
country: Australia
facility: Macquarie University
city: Innsbruck
country: Austria
facility: Innsbruck University
city: Linz
country: Austria
facility: Linz Kepler Klinikum
city: Praha
country: Czechia
facility: Prague University
city: Berlin
country: Germany
facility: Charité Univesitätsmedizin
city: Dresden
country: Germany
facility: Dresden Uniklinikum
city: Düsseldorf
country: Germany
facility: Düsseldorf Universitätsmedizin
city: Frankfurt
country: Germany
facility: Frankfurt University
city: Göttingen
country: Germany
facility: Universitätsmedizin Göttingen
city: Köln
country: Germany
facility: University of Cologne
city: Mainz
country: Germany
facility: Unimedizin Mainz
city: Florence
country: Italy
facility: University of Florence - Careggi
city: Genoa
country: Italy
facility: University of Genoa
city: Messina
country: Italy
facility: University of Messina
city: Milan
country: Italy
facility: Carlo Besta
city: Padova
country: Italy
facility: Padova University
city: Roma
country: Italy
facility: Gemelli University Hospital
city: Roma
country: Italy
facility: Sapienza University
city: Verona
country: Italy
facility: University of Verona
city: Amsterdam
country: Netherlands
facility: Amsterdam UMC
city: Leiden
country: Netherlands
facility: Leiden University
city: Utrecht
country: Netherlands
facility: UMC Utrecht
city: Moscow
country: Russian Federation
facility: Burdenko Hospital
city: Göteborg
country: Sweden
facility: Sahlgrenska Hospital
city: Bern
country: Switzerland
facility: Inselspital Bern
city: Zürich
country: Switzerland
facility: University Hospital Zurich
Study officials:
affiliation: USZ
name: Victor Staartjes
role: PRINCIPAL_INVESTIGATOR
affiliation: USZ
name: Giuseppe Esposito
role: PRINCIPAL_INVESTIGATOR
References: