Body Composition Analysis for Patient With Lung Cancer Using Computed Tomography Image Analysis

NCT01887769 | Unknown DMC

• 1 other identifier: 20824
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

Rationale: With 1.6 million new cases diagnosed each year and 1.3 million deaths, lung cancer is the leading cancer-related death worldwide and it represents a pressing health issue. Patients with lung cancer are more likely to experience cachexia, a severe debilitating disorder causing fatigue, weight loss, muscle wasting and associated with reduced physical function, increased chemotherapy toxicity and reduced survival. This syndrome occurring in about 80% of advanced cancer patients is the direct cause of death in about 20% of cases. However, despite the importance of cachexia in lung cancer, it has been mainly studied from several assessment methods which do not usually differentiate muscle from other tissues. Aim: To analyze body composition of patients with lung cancer at diagnosis using computed tomography (CT-Scan) image analysis. Methods: This is a retrospective study extending over a period of 3 years conducted at the Institut universitaire de cardiologie et de pneumologie de Québec (2009-2012). We listed patients newly diagnosed with lung cancer who had a thoraco-abdominal CT-scan performed in our institution. Following the collection of clinical data from patient records, we used SliceOmatic software to quantify muscle area, visceral fat area and subcutaneous fat area from a single abdominal cross-sectional image at the level of the third lumbar vertebra.

Conditions

Lung Cancer

Keywords

Lung cancer; Body composition analysis; Ct-Scan; Muscle mass; Cachexia

Outcome Measures

Primary Outcomes (2)

• Change of muscle area (cm2/m2) at the level of the third lumbar vertebra

  at the time of the diagnosis of lung cancer and one year following it.

• Change of fat area (cm2/m2) at the level of the third lumbar vertebra

  at the time of the diagnosis of lung cancer and one year following it.

Secondary Outcomes (1)

• days of survival

  From the time of the diagnosis of lung cancer until one year

Study Arms (1)

Lung cancer patient at diagnosis

Eligibility Criteria

• Age: 40 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Lung cancer patients, at diagnosis, following in oncology clinic

You may qualify if:

• Men or women
• Between 40-80 years of age
• Primary lung cancer diagnosed between 2009 and 2012
• CT-Scan done at the time of the diagnosis

You may not qualify if:

• Chemotherapy, radiotherapy or surgery at the time of the first Ct-Scan image
• History of other cancer (during the last five years)

Sponsors & Collaborators

• Centre de Recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Quebec: lead

Study Sites (1)

Institut universitaire de cardiologie et de pneumologie de Québec

Québec, Quebec, G1V 4G5, Canada

RECRUITING

MeSH Terms

Conditions

Lung Neoplasms; Cachexia

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases; Weight Loss; Body Weight Changes; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Thinness

Study Officials

• Didier Saey, PhD

  Institut universitaire de cardiologie et de pneumologie de Québec, University Laval

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD

Study Record Dates

• First Submitted: February 13, 2013
• First Posted: June 27, 2013
• Study Start: May 1, 2012
• Primary Completion: July 1, 2017
• Study Completion: October 1, 2017
• Last Updated: January 6, 2017

Record last verified: 2017-01

Locations

CA (1)