Rapid Learning for Lung Cancer
- Conditions
- Lung Cancer
- Registration Number
- NCT01949259
- Lead Sponsor
- Maastricht Radiation Oncology
- Brief Summary
A retrospective, data mining project that re-uses routine patient care data for decision support systems.
- Detailed Description
By installing tools that extract clinical data from electronic health records and image data from the Picture Archiving and Communication System, decision support systems are built and validated that can predict survival and treatment toxicities of lung cancer patients treated with radiotherapy.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 10000
- Patients notes as suffering from lung cancer in at least one clinical data source.
Not provided
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Survival From radiotherapy until death Retrospective data will be collected from each included patient from start of radiotherapy until end of study or death (an expected average of 10 years).
- Secondary Outcome Measures
Name Time Method Local control From start of treatment until death, Data will be collected from inclusion in the study until end of study of death (an expected average time frame of 10 years) concerning the local control of this tumour.
Distant metastases From treatment until end of study Data concerning the possible occurence of distant metastases will be collected from each patient from inclusion until end of study or date of death (an expected average time frame of 10 years).
Dyspnea From inclusion until end of study From each included patient, dyspnea scores will be collected from start of treatment until end of study or date of death (an expected average time frame of 10 years).
Dysphagia From treatment until end of study Dysphagia scores will be collected from each participating patient from treatment until end of study or date of death (an average time frame of 10 years)
Trial Locations
- Locations (1)
MAASTRO clinic
🇳🇱Maastricht, Limburg, Netherlands