Trial Review

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Trial registered on ANZCTR


Registration number
ACTRN12613001141730
Ethics application status
Approved
Date submitted
3/10/2013
Date registered
14/10/2013
Date last updated
14/10/2013
Type of registration
Prospectively registered

Titles & IDs
Public title
Improving Prediction of Outcomes from Lung Cancer Surgery Using Quantitative Computed Tomography
Scientific title
In patients undergoing resection of lung cancer, how well does quantitative computed tomography, compared to tests of pulmonary function and exercise capacity, predict postoperative outcomes?
Secondary ID [1] 283199 0
Nil known
Universal Trial Number (UTN)
U1111-1147-9063
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Non-small cell lung cancer 290061 0
Chronic obstructive pulmonary disease 290086 0
Emphysema 290087 0
Condition category
Condition code
Cancer 290436 290436 0 0
Lung - Non small cell
Respiratory 290463 290463 0 0
Chronic obstructive pulmonary disease
Respiratory 290688 290688 0 0
Other respiratory disorders / diseases

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
Quantitative CT software provides the ability to measure airway wall thickness on chest CT images, which is a potentially useful measure of airway obstruction. We intend to analyse participants' CT images using quantitative CT to determine airway wall thickness and attenuation values in the individual lobes. We hope to add these variables to the conventional measures used to predict postoperative outcomes in order to determine if this will be a useful tool to contribute to the prediction of postoperative outcomes. The CT images which will be used include a preoperative CT scan as well as a low-dose CT scan 6 months postoperatively for each patient.
Intervention code [1] 287925 0
Not applicable
Comparator / control treatment
All participants in this study will be receiving the usual standard of clinical care with respect to the treatment of their lung cancer. We will only be selecting patients who will be undergoing resection of their lung cancer. The use of quantitative CT measures will therefore be compared to the usual tests used to determine eligibility for surgery (pulmonary function tests and six minute walk distance). These tests will be performed preoperatively and 6 months postoperatively.
Control group
Active

Outcomes
Primary outcome [1] 290473 0
Quality of life score as determined by the EORTC QLQ-C30 and EORTC QLQ-LC13 questionnaires
Timepoint [1] 290473 0
Baseline and at 6 months following lung resection
Primary outcome [2] 290474 0
All cause mortality as determined from medical records and other sources
Timepoint [2] 290474 0
6 months following lung resection
Secondary outcome [1] 304569 0
Accuracy of prediction of postoperative lung function based on quantitative CT measures of attenuation and airway wall thickness
Timepoint [1] 304569 0
6 months following lung resection

Eligibility
Key inclusion criteria
-Histologically confirmed non-small cell lung cancer
-Pulmonary resection to treat the lung cancer, in the form of pneumonectomy, lobectomy or limited resection
-Available CT images compatible with quantitative CT software
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
-Inability to provide informed consent
-Inability to attend follow up at 6 months
-Inability to speak English
-Pregnant women

Study design
Purpose
Natural history
Duration
Longitudinal
Selection
Defined population
Timing
Prospective
Statistical methods / analysis
Statistical power was calculated by assuming that linear regression will be used to determine the association between Pi10, which is a measure of airway wall thickness, and quality of life, represented by the EORTC QLQ-C30 score. The estimated standard deviations for these variables were determined based on previous studies by other investigators. We determined that a sample size of 50 would be sufficient to provide 80% power at a significance level of 0.05.

We intend to employ multiple regression to determine the effect of multiple variables (such as pulmonary function tests, six minute walk distance, airway wall thickness) on quality of life scores and mortality. Linear regression will be used to determine the accuracy of prediction of postoperative lung function based on quantitative CT measures.

Recruitment
Recruitment status
Not yet recruiting
Date of first participant enrolment
Anticipated
15/10/2013
Actual
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
Sample size
Target
50
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
QLD
Recruitment hospital [1] 1510 0
The Prince Charles Hospital - Chermside
Recruitment postcode(s) [1] 7350 0
4032 - Chermside

Funding & Sponsors
Funding source category [1] 287964 0
Hospital
Name [1] 287964 0
The Prince Charles Hospital
Country [1] 287964 0
Australia
Funding source category [2] 287965 0
University
Name [2] 287965 0
The University of Queensland
Country [2] 287965 0
Australia
Primary sponsor type
Hospital
Name
The Prince Charles Hospital
Address
The Prince Charles Hospital
Rode Rd
Chermside
QLD 4032
Country
Australia
Secondary sponsor category [1] 286683 0
University
Name [1] 286683 0
The University of Queensland
Address [1] 286683 0
The University of Queensland
St Lucia
QLD 4072
Country [1] 286683 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 289888 0
The Prince Charles Hospital HREC
Ethics committee address [1] 289888 0
The Prince Charles Hospital
Administration Building, Lower Ground
Rode Rd
Chermside QLD 4032
Ethics committee country [1] 289888 0
Australia
Date submitted for ethics approval [1] 289888 0
25/07/2013
Approval date [1] 289888 0
09/08/2013
Ethics approval number [1] 289888 0
HREC/13/QPCH/218

Summary
Brief summary
This study is evaluating whether quantitative computed tomography (CT) can enable us to more accurately predict postoperative outcomes in patients undergoing lung cancer surgery.

Who is it for?
You may be eligible to join this study if you are aged 18 years or above and have been diagnosed with non-small cell lung cancer for which you will undergo lung resection surgery.

Study details
All participants in this study will receive standard care by their treating physicians and quantitative CT software will be used to analyse their CT images. Quantitative CT provides the ability to measure airway wall thickness on chest CT images, which is a potentially useful measure of airway obstruction. We hope to add these variables to the conventional measures used to predict postoperative outcomes in order to determine if this will be a useful tool to contribute to the prediction of postoperative outcomes, including quality of life and mortality. Prediction of postoperative outcomes following lung resection for lung cancer is important because it enables the selection of suitable surgical candidates.
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 42866 0
Mr Xiang-Wen Lee
Address 42866 0
Department of Thoracic Medicine
The Prince Charles Hospital
Rode Rd
Chermside
QLD 4032
Country 42866 0
Australia
Phone 42866 0
+61450102822
Fax 42866 0
Email 42866 0
[email protected]
Contact person for public queries
Name 42867 0
Mr Xiang-Wen Lee
Address 42867 0
Department of Thoracic Medicine
The Prince Charles Hospital
Rode Rd
Chermside
QLD 4032
Country 42867 0
Australia
Phone 42867 0
+61450102822
Fax 42867 0
Email 42867 0
[email protected]
Contact person for scientific queries
Name 42868 0
Prof Kwun Fong
Address 42868 0
Department of Thoracic Medicine
The Prince Charles Hospital
Rode Rd
Chermside
QLD 4032
Country 42868 0
Australia
Phone 42868 0
+61731394314
Fax 42868 0
Email 42868 0
[email protected]

No information has been provided regarding IPD availability


What supporting documents are/will be available?

No Supporting Document Provided



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.