Trial Title:
Psychosocial eHealth in Advanced Lung Cancer
NCT ID:
NCT05497973
Condition:
Lung Cancer, Nonsmall Cell, Stage IIIA
Lung Cancer Non-Small Cell Stage IIIB
Lung Cancer Non-Small Cell Stage III
Lung Cancer Stage IV
Lung Cancer
Conditions: Official terms:
Lung Neoplasms
Carcinoma, Non-Small-Cell Lung
Conditions: Keywords:
Psychooncology
Psychosocial care
Palliative care
eHealth
Continuity of patient care
Telemedicine
Well-being
Psychosocial Functioning
Patient Engagement
Emotional Distress
Quality of Life
Health Knowledge, Attitudes, Practice
End of life care
Study type:
Interventional
Study phase:
N/A
Overall status:
Recruiting
Study design:
Allocation:
Randomized
Intervention model:
Parallel Assignment
Intervention model description:
Non-inferiority randomized trial testing two experimental conditions: 1) ehealth
ecosystem, 2) usual psychosocial care. Assessment of main outcomes are conducted at
recruitment (T0), 3 months from T0 (T1), 6 months from T0 (T2), and 9 months from T0
(T3). Hence, the design is 2 (treatment conditions) X 4 (assessments). The whole
project's methodology adheres to the principles of Responsible Research and Innovation
(RRI).
The sample size has been estimated with the support of the R software (R Core Team,
2020), setting a non-inferiority margin of 5 points in the Hospital Anxiety and
Depression Scale (Vaganian et al., 2020), with power at 80% and one-tailed α of 2.5%. A
dropout rate of 25% was assumed. It was anticipated that 152 participants were necessary
(n = 76 per arm) to ensure that a two-sided 95% confidence interval would exclude the
non-inferiority threshold.
Primary purpose:
Supportive Care
Masking:
None (Open Label)
Intervention:
Intervention type:
Behavioral
Intervention name:
E-health ecosystem of stepped psychosocial care
Description:
1. Screening and monitoring: weekly administration of an emotional state thermometer.
If the score is >5, participants are asked to complete the HADS. If HADS' score >10,
step 2 is assigned. The same procedure is followed for steps 3 & 4. Participants
remain in each step for 2 weeks, and all level changes are preceded by a
videoconference with a health professional
2. Online psychoeducation campus: displays co-constructed videos and posts developed by
health professionals and patients about LC diagnosis and treatment aspects.
3. Online support community: anonymous survivors with LC diagnoses are included.
Professionals and patient mentors supervise and foster debate, peer support, and
resolve health Q&As.
4. Weekly online group psychotherapy led by a clinical psychologist and composed of
eight 90-minute sessions. Eligible users are placed on a waiting list, starting when
5-6 users are available.
Arm group label:
eHealth ecosystem of stepped psychosocial care
Other name:
ICOnnecta't
Intervention type:
Behavioral
Intervention name:
Usual psychosocial care
Description:
Usual psychosocial care for cancer survivors at ICOHospitalet centre led by a clinical
psychologist. Usual psychosocial care consists of 7 individual sessions of 45-60 minutes,
with 2-3 weeks of space between sessions, based on Individual Meaning-Centered
Psychotherapy (IMCP) for Patients With Advanced Cancer (Breitbart et al., 2012).
Moreover, they will be offered the education materials from the 2nd step of the platform,
as they are compiled on a website open to all patients and relatives.
Arm group label:
Usual psychosocial care
Summary:
Being diagnosed with cancer impairs many areas of a person's life. Although efficacious
educational, emotional and social interventions exist in this regard, they often reach
few survivors and late. This project, carried out by a specialized centre in cancer care
and health research, will study the effectiveness, costs, and utility associated with a
digital ecosystem tailored to meet the needs of patients with advanced lung cancer. This
solution bridges the gap between patients and professionals to offer health services
precisely when they are needed. The project is developed in the first year of an advanced
lung cancer diagnosis, comparing the effects of the digital ecosystem with usual care in
terms of their capacity to improve various psychosocial indicators. A comparative
economic analysis will be carried out as well, to prove the cost-utility of the digital
ecosystem presented.
Detailed description:
Palliative Care (PC) for patients with advanced life-limiting diseases and the management
of their symptoms during the trajectory of illness has evolved considerably (Clark,
2007). PC is conceptualized as an approach to improve the quality of life of patients and
their relatives "through the prevention and relief of suffering by means of early
identification and impeccable assessment and treatment of pain and other physical,
psychosocial and spiritual problems". In recent years, survival rates have increased for
most cancer diagnoses, in both early and advanced stages. Therefore, patients suffering a
disease considered incurable are living longer with cumulative psychosocial comorbidity
derived from both the illness itself and its associated treatments. The American and
European societies for medical oncology have recently recommended integrating early
psychosocial PC into standard oncological practice for patients with metastatic or
advanced stage diseases like lung cancer (LC) in their professional guidelines. This
decision has been recently supported by meta-analytic results as well. Those studies show
that palliative interventions including physical and psychological aspects have
beneficial effects on patients, both on short-term quality of life and in general symptom
burden.
Despite the advantages of such integrated PC interventions, healthcare systems usually
encounter several barriers to implementing psychosocial care in palliative settings, like
in advanced LC. The most typical include poor early detection of such needs; long waiting
lists; and mobility restrictions, with many patients unable to attend visits in person.
The literature strongly suggests that emotional distress is associated with worse quality
of life, lower adherence to oncological treatments and adoption of unhealthy lifestyles.
Actually, it is also demonstrated that stress reduction may even extend survival years.
Since LC patients show great symptom variability, erratic evolution and high emotional
impact along with a limited prognosis, it is urgent to increase the currently small
proportion of patients with early screening, close and intensive monitoring and prompt
referral to PC teams. To this aim, new approaches in psychosocial PC are needed to
overcome the barriers experienced today.
In the last years, two main actions have been proposed to improve the implementation of
psychosocial care in PC, placing a focus on its accessibility and efficiency. For
example, recent studies have introduced earlier stepped (low to high intensity) and
adaptive treatments as an ingenious and sensible response to the challenge of offering
proper psychosocial interventions, with high cost-effectiveness in cancer. Another
comprehensive action is to make use of Information and Communication Technologies (ICT).
ICT has emerged in the last few years as an innovative resource to set this new wave of
health practices in motion, with an exponential increase in its use and implementation
during the COVID pandemic, to guarantee continuity of care in vulnerable advanced cancer
patients. ICT have also shown their capability to overcome most of the limitations
expressed in conventional care settings. These tools have provided faster and more
intense follow-up options to monitor patients' warning signs, facilitating better
communication between patients and professionals, and also leveraging cheaper and more
accessible clinical treatments compared to traditional alternatives, even at the end of
life. Nevertheless, the few studies comparing ICT and usual psychosocial interventions
have found mixed effectiveness results so far.
Recently, ONCOMMUN, a European proposal for creating an e-health ecosystem
(https://oncommun.eu/), has combined these two promising actions to facilitate early
psychosocial care in an online and stepped psychosocial program. ONCOMMUN has shown
promising preliminary results on breast cancer (BC) and a high potential for therapeutic
application in advanced and palliative settings, like LC. The first level of care in this
program is an online screening and monitoring tool, followed by a patient's campus
comprising educational interventions (second level), a psychosocial support community
(third level), and psychotherapeutic treatment groups through videoconference (fourth
level).
The current project has been designed as a randomized non-inferiority controlled trial to
compare an e-health ecosystem of psychosocial care, based on the ONCOMMUN proposal,
against traditional in-person psychosocial treatment in PC during advanced LC. Our group
proposes the development and adaptation of this digital ecosystem by integrating
screening and monitoring tools with educational and psychological interventions, building
upon the results of its recent implementation in BC. This innovative e-health ecosystem
intends to foster healthy experiences, integrating a four-stepped psychosocial program of
early PC focused on patients with a diagnosis of non-small cell lung carcinoma (NSCLC) at
advanced stages (III and IV).
OBJECTIVES (3 years)
General
1. To offer early detection and tailored treatment of psychosocial and physical needs
of advanced LC survivors.
2. To implement and assess an online stepped ecosystem for psychosocial and educational
screening, monitoring and care, through the use of an e-health platform specifically
developed for advanced LC patients.
Specific objectives
1. To compare the capacity of the digital ecosystem to detect and deliver early
psychosocial care compared to treatment as usual.
2. To improve or cushion the consequences of the advanced lung cancer course and
treatment in terms of emotional distress, demoralization and quality of life.
3. To explore the potential mediating and facilitating role of spirituality in an
optimal psychosocial adaptation.
4. To study the cost-utility associated with both interventions in terms of
Quality-Adjusted Life Years (QALY), through the estimation of patients' use of
additional health services, their degree of pharmacological adherence, intake of
psychotropic medication, and time spent in disability leaves.
5. To disseminate to cancer patients, professionals and the general public the results
of the study.
Procedure and data acquisition
1. Development of an LC platform: LC platform will be adapted from the BC platform and
fed by the results of the pilot LC system and focus groups with professionals and
patients. The LC solution will share a set of structural items (e.g., measurement
instruments, instant symptom management), to which specific resources for LC will be
added. Patients' experience will be at the centre of this development stage to
maximize usability and understanding of all resources.
2. Validation with users: Patients with advanced LC diagnosis will be invited to
participate by their medical team. If interested, they will be contacted by our
group and a face-to-face meeting will be scheduled, where the study will be
described and informed consent signed in case of acceptance. Participants will be
then randomized to 1) e-health ecosystem or 2) usual psychosocial care by an
external researcher blind to the research questions and treatment conditions, using
a random sequence of numbers generated by REDCap software. In the eHealth ecosystem
group, participants lacking equipment will be offered webcams and tablets as needed.
There are specific processes of the system that will only apply to ICOnnecta't
branch as they will measure the platform usability and their associate emotional
state during the study (see Interventions section below). All other measures will be
administered from T0 to T3 through a professional online survey platform compliant
with the latest European General Data Protection Regulation (GDPR; EC/2016/679).
Data collection and analysis
Two databases will be created: The first one will associate participants' identifiable
personal data (e.g., names, patient ID) with an alphanumeric code, and will be saved in
an encrypted external hard drive stored in a key-protected closet within the office of
the PI. The second database, created via REDCap system, will record all data to be
analyzed making use of alphanumeric codes and will be stored in a secure collaborative
cloud also GDPR-compliant. This procedure will allow us to conduct the analyses
anonymously. Data will be monthly downloaded from REDCap and backed up in a second
encrypted external hard drive. Every 3 months one researcher will conduct a data
integrity check. While online systems automatically keep a registry of users' access, a
notebook will remain next to the hard drives for researchers authorized by PIs to record
their name, date and time when drives are retrieved and returned. Finally, the
information collected through the eHealth ecosystem will also be stored in a
GDPR-compliant server.
Descriptive results will be provided for sociodemographic and clinical variables, as well
as for education, usability and satisfaction indicators, while between-group differences
will be assessed with Student's t-test and chi-square tests as appropriate. Multilevel
linear models (MLM) will be used to compare both groups in outcome variables, while
effect sizes (Hedges' g) will be reported and non-inferiority tested. For QALY analyses,
results from the EQ-5D-3L will be used together with costs associated with professional
salaries, adherence, infrastructure, psychotropic medication and sick leaves. The effect
of any potential confounding variable will be analyzed. Analyses will be conducted using
SPSS v24.021 (IBM SPSS Statistics 21, 2017) by the IDIBELL biostatistics department.
Criteria for eligibility:
Criteria:
Inclusion Criteria:
- Being adult (≥18 years)
- LC diagnosis in advanced stages -III-IV
- Access to internet and user-level experience
- Reading and writing skills in Spanish
Exclusion Criteria:
- Current major depressive episode
- Risk of self-harm
- Active psychotic symptoms
- Substance abuse
Gender:
All
Minimum age:
18 Years
Maximum age:
80 Years
Healthy volunteers:
No
Locations:
Facility:
Name:
Institut Català d'Oncologia
Address:
City:
L'Hospitalet De Llobregat
Zip:
08908
Country:
Spain
Status:
Recruiting
Start date:
November 15, 2022
Completion date:
June 2024
Lead sponsor:
Agency:
Institut Català d'Oncologia
Agency class:
Other
Collaborator:
Agency:
Asociación Española contra el Cáncer
Agency class:
Other
Collaborator:
Agency:
Institut d'Investigació Biomèdica de Bellvitge
Agency class:
Other
Source:
Institut Català d'Oncologia
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05497973
https://euroqol.org/publications/user-guides/