Understanding Lung Cancer Screening and Treatment Outcomes
This observational study aims to improve how we predict the results of lung biopsies and treatment for early-stage lung cancer. Researchers are looking at information from past medical records and CT scans to see if advanced image analysis can better predict outcomes. They will review charts of patients aged 18 to 99 who were diagnosed with lung cancer and treated with radiation therapy at UTSW or Parkland Memorial Hospital between 2004 and 2014. The goal is to develop better models to understand how patients respond to screening and treatment, with results measured over 10 years. This study does not involve new treatments or procedures for participants.
- Study design
- This is an observational study reviewing existing medical records of approximately 200 patients. It is not a randomized trial and does not involve new treatments.
- What's involved
- This study involves reviewing your past medical charts; you will not need to attend appointments or undergo any new tests or procedures.
- Compensation
- Not stated in the trial record.
- Follow-up
- The primary outcome of the study will be measured at 10 years after treatment.
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Multiparametric Image Analysis and Correlation With Outcomes in Lung Cancer Screening and Early Stage Lung Cancer
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Jing Wang, MD · PRINCIPAL_INVESTIGATOR · UTSW Radiation Oncology
Who to contact
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What this trial measures
- 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 cancer10 years
We 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. The data will be subject to standard descriptive, parametric, and nonparametric hypothesis testing with biostatistical analyses. We will also analyze an anonymized dataset of patients from the National Lung Cancer Screening Trial (NLST) provided by the National Cancer Institute (NCI) including screening images and diagnostic outcomes to validate models generated using institutional data.