Clinical Prediction Model for COPD

Recruiting at 1 trial location

Overseen By Don Sin, MD, MPH

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of British Columbia

Disqualifiers: Under 35 years

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Approved in 1 Jurisdiction This treatment is already approved in other countries

Compensation: Varies

Number of Visits: 31

Duration: 24 months

1130 Participants Needed

Trial Summary

What is the purpose of this trial?

This trial tests a computer tool called ACCEPT that helps doctors predict severe lung attacks in COPD patients. By analyzing electronic health records, the tool aims to provide personalized care to prevent these attacks and improve patient outcomes.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the ACCEPT Decision Intervention Tool for COPD?

The ACCEPT Decision Intervention Tool is designed to predict COPD exacerbations, and research shows it is well-calibrated and effective at distinguishing between patients with different risks, although it may overestimate risk in those without recent exacerbations. ^{1 2 3 4 5}

Is the ACCEPT Decision Intervention Tool safe for humans?

The research does not provide specific safety data for the ACCEPT Decision Intervention Tool, but it is a decision support tool designed to improve discharge recommendations for COPD patients, which suggests it is non-invasive and likely safe for use in humans. ^{3 4 6 7 8}

Eligibility Criteria

This trial is for Canadian residents aged 35 or older who have been diagnosed with Chronic Obstructive Pulmonary Disease (COPD) and can communicate in English. It's not open to those under the age of 35.

Inclusion Criteria

I have been diagnosed with COPD.

Legal Canadian resident

Can speak English

Exclusion Criteria

I am younger than 35 years old.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

1 month

1 visit (in-person)

Treatment

Implementation of the ACCEPT tool in routine COPD care to provide personalized treatment recommendations

24 months

Multiple visits (in-person) as per routine care

Follow-up

Participants are monitored for safety and effectiveness after treatment

6 months

Data collection until month 30

Data Collection and Analysis

Data collected for primary and secondary outcomes, including prescription appropriateness and medication adherence

Throughout the trial

Treatment Details

Interventions

• ACCEPT Decision Intervention

Trial Overview The study tests a digital tool called ACCEPT, integrated into electronic health records, to predict COPD patients' risk of lung attacks and improve personalized care at two hospitals in Vancouver, BC.

Participant Groups

Group I: ACCEPT Decision Intervention Experimental Treatment 1 Intervention

Clinical prediction model (ACCEPT)-based treatment recommendations: The ACCEPT tool will display the predicted risk of exacerbations, and the corresponding treatment recommendations to the physicians. These recommendations will be provided in a non-mandatory 'directive' format where the physician can override the recommendation, but is required to provide a justification (pre-set choices and a free text).

Group II: Usual care (Control) Active Control 1 Intervention

Routine COPD patient care.

Who Is Running the Clinical Trial?

University of British Columbia

Lead Sponsor

Trials

1,506

Recruited

2,528,000+

Providence Health & Services

Collaborator

Trials

131

Recruited

827,000+

Vancouver Coastal Health

Collaborator

Trials

41

Recruited

717,000+

Findings from Research

This study evaluated the prognostic ability of the ADO, BODEx, and DOSE indices in predicting mortality among 477 COPD patients in primary care across 36 health centers in Europe, highlighting the need for individualized patient assessment.

The research aims to enhance the predictive capacity of these indices by considering the interval between exacerbations and incorporating lifestyle factors, which could improve communication and treatment strategies among healthcare professionals.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

External validation of multidimensional prognostic indices (ADO, BODEx and DOSE) in a primary care international cohort (PROEPOC/COPD cohort). Espantoso-Romero, M., Román Rodríguez, M., Duarte-Pérez, A., et al.[2019]

A predictive model was developed to screen for Chronic Obstructive Pulmonary Disease (COPD) in smokers, using simple parameters like age, smoking history, and respiratory symptoms, based on a study of 222 smokers without a prior COPD diagnosis.

The model showed good internal validation for predicting fixed airflow limitation, with 25.7% of participants exhibiting this condition, and can be integrated into a mobile app for easier access, although it requires external validation in other regions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A scoring system to detect fixed airflow limitation in smokers from simple easy-to-use parameters. Román-Conejos, E., Palazón-Bru, A., Folgado-de la Rosa, DM., et al.[2019]

A systematic review of 217 studies revealed that COPD patients prioritize symptom relief over adverse events, highlighting the importance of managing symptoms in treatment plans.

Among the outcomes, COPD patients rated exacerbations and hospitalizations due to exacerbations as the most critical factors affecting their quality of life.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A systematic review of how patients value COPD outcomes. Zhang, Y., Morgan, RL., Alonso-Coello, P., et al.[2019]

The updated Acute Chronic Obstructive Pulmonary Disease Exacerbation Prediction Tool (ACCEPT 2.0) demonstrated improved accuracy in predicting COPD exacerbations, achieving an area-under-the-curve (AUC) of 0.76 compared to the standard method, which had an AUC of 0.68.

ACCEPT 2.0 was well calibrated for patients with both positive and negative exacerbation histories, indicating its effectiveness across different patient profiles, and it provided a positive net benefit over traditional methods for predicting exacerbation risk.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

ACCEPT 2·0: Recalibrating and externally validating the Acute COPD exacerbation prediction tool (ACCEPT). Safari, A., Adibi, A., Sin, DD., et al.[2022]

The BOSA index, developed from a study of 300 patients and validated in a larger cohort of 772 patients, effectively predicts mortality in COPD patients by assessing factors like BMI, airflow obstruction, and health-related quality of life.

Compared to the GOLD 2011 criteria, the BOSA index shows similar prognostic utility, making it a simple and accessible tool for categorizing COPD patients without the need for complex equipment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Role of BMI, airflow obstruction, St George's Respiratory Questionnaire and age index in prognostication of Asian COPD. Chan, HP., Mukhopadhyay, A., Chong, PL., et al.[2022]

The COLIBRI-COPD web portal has successfully collected comprehensive data from 1079 COPD patients, highlighting significant variability in patient characteristics and treatment responses even among those with the same GOLD stage of the disease.

The high data quality and completeness suggest that this real-life data collection method can provide valuable longitudinal insights into COPD management, influenced by the usability of the web tool and self-assessment features for practitioners.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[COLIBRI: Improving clinical practice and producing relevant scientific data]. Kelkel, E., Herengt, F., Ben Saidane, H., et al.[2022]

The implementation of a decision support tool for COPD patients significantly improved adherence to discharge recommendations, with long-acting medication prescriptions increasing from 42% to 84% and smoking cessation advice from 32% to 91%.

Patients who received prescriptions for long-acting bronchodilators were more likely to purchase them after discharge (54% vs. 20%), indicating that the tool not only improved guideline adherence but also had the potential to enhance patient outcomes post-hospitalization.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical Decision Support System: A Pragmatic Tool to Improve Acute Exacerbation of COPD Discharge Recommendations. Epstein, D., Barak-Corren, Y., Isenberg, Y., et al.[2020]

The GOLD3D classification system, which incorporates lung function and exacerbation history, significantly improves the prediction of adverse events in COPD patients compared to the previous GOLD2011 and GOLD2017 systems, based on a study of 1303 patients over an average follow-up of 45 months.

GOLD3D demonstrated a higher accuracy in predicting both mortality and severe exacerbations, indicating that assessing lung function alongside exacerbation history provides a more comprehensive risk assessment for COPD patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A new, three-dimensional approach to the GOLD COPD assessment tool. Golpe, R., Figueira-GonÇalves, JM., Amado, CA., et al.[2022]

References

1. England pubmed.ncbi.nlm.nih.gov

External validation of multidimensional prognostic indices (ADO, BODEx and DOSE) in a primary care international cohort (PROEPOC/COPD cohort). [2019]

2. England pubmed.ncbi.nlm.nih.gov

A scoring system to detect fixed airflow limitation in smokers from simple easy-to-use parameters. [2019]

3. England pubmed.ncbi.nlm.nih.gov

A systematic review of how patients value COPD outcomes. [2019]

4. England pubmed.ncbi.nlm.nih.gov

ACCEPT 2·0: Recalibrating and externally validating the Acute COPD exacerbation prediction tool (ACCEPT). [2022]

5. Australia pubmed.ncbi.nlm.nih.gov

Role of BMI, airflow obstruction, St George's Respiratory Questionnaire and age index in prognostication of Asian COPD. [2022]

6. France pubmed.ncbi.nlm.nih.gov

[COLIBRI: Improving clinical practice and producing relevant scientific data]. [2022]

7. England pubmed.ncbi.nlm.nih.gov

Clinical Decision Support System: A Pragmatic Tool to Improve Acute Exacerbation of COPD Discharge Recommendations. [2020]

8. France pubmed.ncbi.nlm.nih.gov

A new, three-dimensional approach to the GOLD COPD assessment tool. [2022]