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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
Date last updated
20/02/2024

Titles & IDs
Public title
BMA and Dynamic Nomogram for Survival Prediction in Patients With CRC
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
Secondary ID [1] 0 0
#08-01-03-23
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Colon Cancer 0 0
Model Disease 0 0
Condition category
Condition code
Cancer 0 0 0 0
Bowel - Back passage (rectum) or large bowel (colon)

Intervention/exposure
Study type
Observational [Patient Registry]
Patient registry
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
Treatment: Surgery - Surgery

Treatment: Surgery: Surgery
Not an interventional study, it is an observational, longitudinal study.
Intervention code [1] 0 0
Treatment: Surgery
Comparator / control treatment
Control group

Outcomes
Primary outcome [1] 0 0
OS
Timepoint [1] 0 0
2011-2021
Primary outcome [2] 0 0
RFS
Timepoint [2] 0 0
2011-2021

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.
Minimum age
22 Years
Maximum age
101 Years
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
Patients with rectal cancer, neuroendocrine tumours, lymphomas and those who underwent trans-anal surgery were not included in the study.

Study design
Purpose
Duration
Selection
Timing
Prospective
Statistical methods / analysis

Recruitment
Recruitment status
Completed
Data analysis
Reason for early stopping/withdrawal
Other reasons
Date of first participant enrolment
Anticipated
Actual
15/02/2010
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
15/12/2021
Sample size
Target
Accrual to date
Final
2475
Recruitment in Australia
Recruitment state(s)
VIC
Recruitment hospital [1] 0 0
Cabrini Health - Melbourne
Recruitment postcode(s) [1] 0 0
3144 - Melbourne

Funding & Sponsors
Primary sponsor type
Other
Name
Cabrini Health
Address
Country

Ethics approval
Ethics application status

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.
Trial website
https://clinicaltrials.gov/study/NCT06268379
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.
Public notes

Contacts
Principal investigator
Name 0 0
Address 0 0
Country 0 0
Phone 0 0
Fax 0 0
Email 0 0
Contact person for public queries
Name 0 0
Address 0 0
Country 0 0
Phone 0 0
Fax 0 0
Email 0 0
Contact person for scientific queries



Summary Results

For IPD and results data, please see https://clinicaltrials.gov/study/NCT06268379