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Trial details imported from ClinicalTrials.gov
For full trial details, please see the original record at
https://clinicaltrials.gov/study/NCT06268379
Registration number
NCT06268379
Ethics application status
Date submitted
13/02/2024
Date registered
20/02/2024
Titles & IDs
Public title
BMA and Dynamic Nomogram for Survival Prediction in Patients With CRC
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Scientific title
Developing a Clinician-friendly Online Tool for Survival Prediction in Colon Cancer Patients: A Bayesian Model Averaging for Risk Factor Selection and Dynamic Nomogram
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Secondary ID [1]
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#08-01-03-23
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Universal Trial Number (UTN)
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Trial acronym
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Colon Cancer
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Model Disease
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Condition category
Condition code
Cancer
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0
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Bowel - Back passage (rectum) or large bowel (colon)
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Intervention/exposure
Study type
Observational [Patient Registry]
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Patient registry
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Target follow-up duration
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Target follow-up type
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Description of intervention(s) / exposure
Treatment: Surgery - Surgery
Treatment: Surgery: Surgery
Not an interventional study, it is an observational, longitudinal study.
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Intervention code [1]
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Treatment: Surgery
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Comparator / control treatment
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Control group
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Outcomes
Primary outcome [1]
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OS
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Assessment method [1]
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Overall Survival, time from sugary to death or last follow up
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Timepoint [1]
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2011-2021
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Primary outcome [2]
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RFS
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Assessment method [2]
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Relapse-free Survival, time from sugary to death or last follow up for those without relapse.
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Timepoint [2]
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2011-2021
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Eligibility
Key inclusion criteria
In this study, patients were included based on specific selection criteria: being 18 years old or older, having a diagnosis of colon adenocarcinoma (or post polypectomy of the same condition), and having undergone surgery for colon cancer.
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Minimum age
22
Years
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Maximum age
101
Years
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Sex
Both males and females
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Can healthy volunteers participate?
No
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Key exclusion criteria
Patients with rectal cancer, neuroendocrine tumours, lymphomas and those who underwent trans-anal surgery were not included in the study.
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Study design
Purpose
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Duration
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Selection
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Timing
Prospective
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Statistical methods / analysis
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Recruitment
Recruitment status
Completed
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Data analysis
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Reason for early stopping/withdrawal
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Other reasons
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Date of first participant enrolment
Anticipated
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Actual
15/02/2010
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Date of last participant enrolment
Anticipated
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Actual
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Date of last data collection
Anticipated
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Actual
15/12/2021
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Sample size
Target
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Accrual to date
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Final
2475
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Recruitment in Australia
Recruitment state(s)
VIC
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Recruitment hospital [1]
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Cabrini Health - Melbourne
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Recruitment postcode(s) [1]
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3144 - Melbourne
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Funding & Sponsors
Primary sponsor type
Other
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Name
Cabrini Health
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Address
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Country
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Ethics approval
Ethics application status
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Summary
Brief summary
This project will examine the outstanding statistical techniques for predicting the survival of patients with colorectal cancer (CRC) (colorectal neoplasia database). The motivating clinical question that led to proposing this project is based on the general assumption that: "Right-sided colorectal cancer (CRC) has worse survival than left-sided CRC." The question is, which aspects of the patient's characteristics are responsible for this difference? This led us to BMA model selection and provide a clinician-friendly online nomogram.
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Trial website
https://clinicaltrials.gov/study/NCT06268379
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Trial related presentations / publications
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4. Siegel RL, Miller KD, Goding Sauer A, Fedewa SA, Butterly LF, Anderson JC, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2020. CA Cancer J Clin. 2020 May;70(3):145-164. doi: 10.3322/caac.21601. Epub 2020 Mar 5. Jalali A, Alvarez-Iglesias A, Roshan D, Newell J. Visualising statistical models using dynamic nomograms. PLoS One. 2019 Nov 15;14(11):e0225253. doi: 10.1371/journal.pone.0225253. eCollection 2019. Borumandnia N, Doosti H, Jalali A, Khodakarim S, Charati JY, Pourhoseingholi MA, Talebi A, Agah S. Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study. Int J Environ Res Public Health. 2021 Jul 21;18(15):7734. doi: 10.3390/ijerph18157734. Maity AK, Basu S, Ghosh S. Bayesian Criterion Based Variable Selection. J R Stat Soc Ser C Appl Stat. 2021 Aug;70(4):835-857. doi: 10.1111/rssc.12488. Epub 2021 Aug 7.
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Public notes
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Contacts
Principal investigator
Name
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Address
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Country
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Phone
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Fax
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Email
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Contact person for public queries
Name
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Address
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Country
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Phone
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Fax
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Email
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Contact person for scientific queries
Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
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No/undecided IPD sharing reason/comment
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What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Type
Citations or Other Details
Journal
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjom...
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More Details
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Journal
Siegel RL, Miller KD, Goding Sauer A, Fedewa SA, B...
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Journal
Jalali A, Alvarez-Iglesias A, Roshan D, Newell J. ...
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More Details
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Journal
Borumandnia N, Doosti H, Jalali A, Khodakarim S, C...
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Journal
Maity AK, Basu S, Ghosh S. Bayesian Criterion Base...
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More Details
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Results not provided in
https://clinicaltrials.gov/study/NCT06268379