Improving Prediction of Outcomes from Lung Cancer Surgery Using Quantitative Computed Tomography

Not Applicable

• Conditions: on-small cell lung cancer; Chronic obstructive pulmonary disease; Emphysema; Non-small cell lung cancer; Cancer - Lung - Non small cell; Respiratory - Chronic obstructive pulmonary disease; Respiratory - Other respiratory disorders / diseases

• Registration Number: ACTRN12613001141730
• Lead Sponsor: The Prince Charles Hospital

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Results First Posted: 1900-01-01
• Study Start: 2013-10-14
• Last Update Posted: 13 January 2020

Recruitment & Eligibility

• Status: ot yet recruiting
• Sex: All
• Target Recruitment: 50

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

Exclusion Criteria

-Inability to provide informed consent
-Inability to attend follow up at 6 months
-Inability to speak English
-Pregnant women

Study & Design

• Study Type: Observational
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Quality of life score as determined by the EORTC QLQ-C30 and EORTC QLQ-LC13 questionnaires[Baseline and at 6 months following lung resection];All cause mortality as determined from medical records and other sources[6 months following lung resection]

Secondary Outcome Measures

Name	Time	Method
Accuracy of prediction of postoperative lung function based on quantitative CT measures of attenuation and airway wall thickness[6 months following lung resection]