Clinical trial NCT03563976: Multiparametric Image Analysis and Correlation With Outcomes in Lung Cancer Screening and Early Stage Lung Cancer
Official title: Multi Parametric Image Analysis and Correlation With Outcomes in Lung Cancer Screening and Early Stage Lung Cancer
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Lung Cancer
Keywords: Early Stage Lung Cancer
Lead sponsor: University of Texas Southwestern Medical Center
Sponsor class: OTHER
First posted: 2018-06-20
Enrollment: 2000
Sex: ALL
Minimum age (years): 18
Maximum age (years): 99
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The medical charts are the subjects. Risk will be minimized by protecting patient data through the use of de-identification of patient identifiers and password protected data collection. The information will be given only to faculty members and statisticians involved in the research project. The data will be disclosed only for analytical purposes.

Confidentiality will be maintained by adhering to HIPAA guidelines. The location of the data will be maintained at the worksite of the PI and the research coordinator in the Moncrief Radiation Oncology Department on the North Campus at UTSW. Risks will be minimized by protecting patient data and using it only for research purposes for retrospective analysis.

Brief summary: Determine whether CT-based multiparametric analytical models may improve prediction of biopsy and treatment outcome in patients undergoing screening CT scan and/or treatment for early stage lung cancer

Detailed description: The hypothesis is that multiparametric models that incorporate complex image information from screening CT scans will improve prediction of the outcome of subsequent lung biopsy, an invasive diagnostic procedure. In this project, we will construct an image feature-based multiparametric prognostic model for biopsy outcome from screening lung CT scans performed at our institution, and then validate it using theNLST imaging and clinical outcomes dataset.

This study involves no treatment or invasive procedures. Investigator will review all charts of patients who were treated for early stage lung cancer with definitive radiation therapy at UTSW or Parkland Memorial hospital, diagnosed with a malignancy from January 1, 2004 to October 31, 2014, to compile demographic, diagnostic, therapeutic, outcome, and toxicity data. Investigator expect that this will include approximately 200 patient charts. This data will be analyzed statistically and used for future directed research. Investigator will also analyze an anonymized dataset of patients from the National Lung Cancer Screening Trial (NLST) provided by the National Cancer Institute (NCI)

Eligibility criteria: Inclusion Criteria:

Patients that have been diagnosed with lung cancer, and are treated at Department of Radiation Oncology, UTSW or Parkland Memorial Hospital.

Exclusion Criteria:

There will be no absolute exclusion criteria as long as the inclusion criteria have been met.

Primary outcomes:
measure: Determine whether CT-based multiparametric analytical models may improve prediction of biopsy and treatment outcome in patients undergoing screening CT scan and/or treatment for early stage lung cancer
timeFrame: 10 years
Secondary outcomes:
Other outcomes:
Locations:
city: Dallas
country: United States
facility: UT Southwestern Medical Center
state: Texas
Study officials:
affiliation: UTSW Radiation Oncology
name: Jing Wang, MD
role: PRINCIPAL_INVESTIGATOR
References: