## Protocol Section
### Identification Module
**NCT ID:** NCT06268379

**Brief Title:** BMA and Dynamic Nomogram for Survival Prediction in Patients With CRC

**Official 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

#### Organization Study ID Info
**ID:** #08-01-03-23
#### Organization
**Class:** OTHER
**Full Name:** Cabrini Health
### Status Module
#### Completion Date
**Date:** 2021-12-15

**Type:** ACTUAL

#### Expanded Access Info
#### Last Update Post Date
**Date:** 2024-02-20

**Type:** ACTUAL

**Last Update Submit Date:** 2024-02-13

**Overall Status:** COMPLETED

#### Primary Completion Date
**Date:** 2021-12-15

**Type:** ACTUAL

#### Start Date
**Date:** 2010-02-15

**Type:** ACTUAL

**Status Verified Date:** 2024-02

#### Study First Post Date
**Date:** 2024-02-20
**Type:** ACTUAL
**Study First Submit Date:** 2024-02-13
**Study First Submit QC Date:** 2024-02-13
### Sponsor Collaborators Module

#### Lead Sponsor

**Class:** OTHER

**Name:** Cabrini Health

#### Responsible Party

**Investigator Affiliation:** Cabrini Health

**Investigator Full Name:** Mohammad Asghari Jafarabadi

**Investigator Title:** A/Prof Mohamad Asghari Jafarabadi

**Type:** PRINCIPAL_INVESTIGATOR

### Oversight Module

**Is FDA Regulated Device:** False

**Is FDA Regulated Drug:** False

**Oversight Has DMC:** True

### Description Module

**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.

**Detailed Description:** Translational statistics merges biostatistics and clinical research to communicate research findings effectively. Nomograms, graphical representations integrating independent prognostic factors, are valuable tools in colorectal cancer (CRC) research. Bayesian models for variable selection in survival outcome prediction offer advantages through Bayesian model averaging (BMA). This study aimed to utilise BMA for variable selection and develop a clinician-friendly online dynamic nomogram for survival prediction.

A retrospective study utilised the Cabrini Monash colorectal neoplasia database, including colon cancer patients who underwent surgery. Data on demographics, perioperative risks, treatment details, mortality, morbidity, and survival were collected. BMA was employed for Bayesian variable selection to identify effective risk factors for survival prediction. Sensitivity analyses using Cox-LASSO and imputation of missing data were performed. Prognostic online dynamic nomograms were constructed using selected risk factors and the R-package DynNom.

### Conditions Module

**Conditions:**

- Colon Cancer

- Model Disease

**Keywords:**

- Colorectal cancer; Translational statistics; Online dynamic nomogram; Bayesian variable selection; Survival prediction

### Design Module

#### Design Info

**Observational Model:** OTHER

**Time Perspective:** PROSPECTIVE

#### Enrollment Info

**Count:** 2475

**Type:** ACTUAL

**Patient Registry:** True

**Study Type:** OBSERVATIONAL

**Target Duration:** 11 Years

### Arms Interventions Module

### Interventions

#### Intervention 1

**Description:** Not an interventional study, it is an observational, longitudinal study.

**Name:** Surgery

**Other Names:**

- Observational study

**Type:** PROCEDURE

### Outcomes Module

#### Primary Outcomes

**Description:** Overall Survival, time from sugary to death or last follow up

**Measure:** OS

**Time Frame:** 2011-2021

**Description:** Relapse-free Survival, time from sugary to death or last follow up for those without relapse.

**Measure:** RFS

**Time Frame:** 2011-2021

### Eligibility Module

**Eligibility Criteria:** 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.

Exclusion Criteria:

Patients with rectal cancer, neuroendocrine tumours, lymphomas and those who underwent trans-anal surgery were not included in the study.

**Maximum Age:** 101 Years

**Minimum Age:** 22 Years

**Sampling Method:** NON_PROBABILITY_SAMPLE

**Sex:** ALL

**Standard Ages:**

- ADULT

- OLDER_ADULT

**Study Population:** A retrospective study was conducted with the Cabrini Monash Colorectal Neoplasia Database 15. This prospectively maintained database includes data from both private (Cabrini) and public (The Alfred) hospitals in Melbourne, Australia. The study focused on patients who underwent surgery for colon cancer from January 2010 to December 2021.

### Contacts Locations Module

#### Locations

**Location 1:**

**City:** Melbourne

**Country:** Australia

**Facility:** Cabrini Health

**State:** Victoria

**Zip:** 3144

### IPD Sharing Statement Module

**IPD Sharing:** NO

### References Module

#### References

**Citation:** 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.

**PMID:** 33538338

**Citation:** 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.

**PMID:** 32133645

**Citation:** 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.

**PMID:** 31730633

**Citation:** 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.

**PMID:** 34360026

**Citation:** Maity AK, Basu S, Ghosh S. Bayesian criterion-based variable selection. Journal of the Royal Statistical Society Series C: Applied Statistics. 2021;70(4):835-857.

## Derived Section

### Condition Browse Module - Ancestors

- ID: D000015179

- Term: Colorectal Neoplasms

- ID: D000007414

- Term: Intestinal Neoplasms

- ID: D000005770

- Term: Gastrointestinal Neoplasms

- ID: D000004067

- Term: Digestive System Neoplasms

- ID: D000009371

- Term: Neoplasms by Site

- ID: D000009369

- Term: Neoplasms

- ID: D000004066

- Term: Digestive System Diseases

- ID: D000005767

- Term: Gastrointestinal Diseases

- ID: D000003108

- Term: Colonic Diseases

- ID: D000007410

- Term: Intestinal Diseases

### Condition Browse Module - Browse Branches

- Abbrev: BC04

- Name: Neoplasms

- Abbrev: BC06

- Name: Digestive System Diseases

- Abbrev: All

- Name: All Conditions

### Condition Browse Module - Browse Leaves

- ID: M6338

- Name: Colonic Neoplasms

- Relevance: HIGH

- As Found: Colon Cancer

- ID: M17890

- Name: Colorectal Neoplasms

- Relevance: LOW

- As Found: Unknown

- ID: M10448

- Name: Intestinal Neoplasms

- Relevance: LOW

- As Found: Unknown

- ID: M8886

- Name: Gastrointestinal Neoplasms

- Relevance: LOW

- As Found: Unknown

- ID: M7256

- Name: Digestive System Neoplasms

- Relevance: LOW

- As Found: Unknown

- ID: M7255

- Name: Digestive System Diseases

- Relevance: LOW

- As Found: Unknown

- ID: M8883

- Name: Gastrointestinal Diseases

- Relevance: LOW

- As Found: Unknown

- ID: M6336

- Name: Colonic Diseases

- Relevance: LOW

- As Found: Unknown

- ID: M10444

- Name: Intestinal Diseases

- Relevance: LOW

- As Found: Unknown

### Condition Browse Module - Meshes

- ID: D000003110

- Term: Colonic Neoplasms

### Intervention Browse Module - Browse Branches

- Abbrev: HB

- Name: Herbal and Botanical

- Abbrev: All

- Name: All Drugs and Chemicals

### Intervention Browse Module - Browse Leaves

- ID: T120

- Name: Cola

- Relevance: LOW

- As Found: Unknown

### Misc Info Module

- Version Holder: 2024-05-24
