Rapid Learning for Lung Cancer

NCT ID: NCT01949259

Last Updated: 2016-09-30

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

10000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2013-09-30

Study Completion Date

2014-08-31

Brief Summary

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A retrospective, data mining project that re-uses routine patient care data for decision support systems.

Detailed Description

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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.

Conditions

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Lung Cancer

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Retrospective collection

Retrospective collection of data from included lung cancer patients.

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

\- Patients notes as suffering from lung cancer in at least one clinical data source.
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Liverpool Cancer Therapy Centre

OTHER_GOV

Sponsor Role collaborator

Macarthur Cancer Therapy Centre, Liverpool

OTHER

Sponsor Role collaborator

Ingham Institute Hospital, Liverpool

UNKNOWN

Sponsor Role collaborator

NSW, Australia

UNKNOWN

Sponsor Role collaborator

Maastricht Radiation Oncology

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Andre Dekker, Dr

Role: PRINCIPAL_INVESTIGATOR

Maastro Clinic, The Netherlands

Locations

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MAASTRO clinic

Maastricht, Limburg, Netherlands

Site Status

Countries

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Netherlands

Other Identifiers

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Rapid learning lung cancer

Identifier Type: -

Identifier Source: org_study_id

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