eRAPID: Online Symptom Reporting in Lung Cancer
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|ClinicalTrials.gov Identifier: NCT04324437|
Recruitment Status : Recruiting
First Posted : March 27, 2020
Last Update Posted : November 6, 2020
Lung cancer is a leading cause of cancer-related ill-health and death in the United Kingdom (UK), but with advances in systemic anti-cancer therapies the prognosis for people in later stages is improving. There is growing evidence that electronic systems which enable patients to monitor and report symptoms can help improve symptom control and patient care. This study aims to investigate optimal ways of introducing an electronic symptom reporting system (eRAPID) in lung cancer care at Leeds Cancer Centre. eRAPID was developed by the University of Leeds and its integration with the electronic health records at Leeds Cancer Centre enables staff to view patient symptom reports directly. eRAPID provides advice to patients about self-management of milder symptoms, for serious symptoms patients are encouraged to contact the hospital and an alert is sent to the nurse or doctor by email.
The aim of the study is to assess the feasibility and usefulness of an electronic symptom reporting system (eRAPID) for lung cancer patients and healthcare professionals during the treatment of lung cancer and during one year follow up.
Two groups of patients will be recruited on the basis of their access to the internet at home (rather than randomisation). It is anticipated that approximately 100 patients will enrol into one of two groups:
- Group 1: Patients with online access at home will be asked to report weekly using their own devices.
- Group 2: Patients without online access will be asked to report on a tablet computer before their planned clinic appointments.
The eRAPID questionnaire is based on existing eRAPID items with the addition of new items specific to lung cancer. These have been developed by the clinical team and patient groups have been consulted over the suitability of the wording used.
Analysis of patient reported symptoms, quality of life and clinical information will be descriptive. Disease-related symptoms and health-related quality of life will be compared across groups of patients with a diagnosis of lung cancer. Treatment-related side effects of patients will be compared across the different types of treatment received. To determine the best means of engaging patients in systematic electronic reporting, the recruitment and compliance rate will be compared between the two patient groups. The utility of patient reported information to healthcare staff will be assessed through staff interviews.
|Condition or disease||Intervention/treatment||Phase|
|Thoracic Cancer Non-small Cell Lung Cancer Small-cell Lung Cancer Pleural Mesothelioma||Other: eRAPID online symptom monitoring in lung cancer||Not Applicable|
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||100 participants|
|Intervention Model:||Single Group Assignment|
|Intervention Model Description:||Consecutive recruitment based on patient choice into two cohorts: access to internet at home or not|
|Masking:||None (Open Label)|
|Official Title:||eRAPID: Electronic Monitoring of Patient-reported Symptoms in Patients With a Diagnosis of Thoracic Cancer Managed at Leeds Cancer Centre|
|Actual Study Start Date :||July 20, 2020|
|Estimated Primary Completion Date :||October 2022|
|Estimated Study Completion Date :||October 2022|
eRAPID online symptom monitoring in lung cancer
Two groups of patients with differing internet access: access from home or access in clinic only
Other: eRAPID online symptom monitoring in lung cancer
The eRAPID in lung cancer intervention is an online symptom monitoring system which provides tailored advice depending on the severity of symptoms reported. The system is integrated into the electronic medical record and results can be viewed by the medical team.
- Number of participants recruited/number of patients approached (consent rate) [ Time Frame: Baseline ]Number of patients approached and recruited will be logged during recruitment
- Number of participant withdrawals [ Time Frame: 12 months ]Number of participant withdrawals will be logged at the time of withdrawal
- Reason for participant withdrawal [ Time Frame: 12 months ]Reasons for withdrawal will be captured in CRF at time of withdrawal
- Use of the intervention [ Time Frame: 6 month and 12 months ]Number of self-reported symptom monitoring reports and quality of life questionnaires completed
- Acceptability of intervention to patients [ Time Frame: 6 months and 12 months ]Interim and end of study interviews with patients
- Acceptability of intervention to clinicians [ Time Frame: 6 months and 12 months ]Interim and end of study interviews with clinicians
- Integrity of the system [ Time Frame: 6 months and 12 months ]Technical issues logged during the study
- Proportion of missing data in symptom reports and quality of life questionnaires [ Time Frame: 12 months ]Regular completions of symptom reports (either weekly or per scheduled clinical and quality of life questionnaires completed 12 weekly by participants
- Number of adverse event reports, severe adverse event alerts and patient deaths [ Time Frame: 12 months ]Descriptive statistics by cancer type, treatment and completion modality
- Use of hospital services (triage calls, acute admissions, ward stays) [ Time Frame: 12 months ]Descriptive statistics overall and completion modality
- Changes to supportive medication, treatment doses and planned therapy [ Time Frame: 12 months ]Descriptive statistics overall and completion modality
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04324437
|Contact: Galina Velikova, PhD||+44 113 206 email@example.com|
|Contact: Rosemary Peacock, PhD||+44 113 firstname.lastname@example.org|
|St James's University Hospital, Leeds Teaching Hospital Trust||Recruiting|
|Leeds, West Yorkshire, United Kingdom, LS9 7TF|
|Contact: Rosemary Peacock, PhD 0113 206 7516 email@example.com|
|Principal Investigator: Galina Velikova, PhD|
|Principal Investigator:||Galina Velikova||University of Leeds|