The DETECT Study

PAH-SSc Findings

DETECT was a large, international, prospective, cross-sectional study funded and supported by Actelion Pharmaceuticals Ltd that sought to develop an algorithm to help assess risk of pulmonary arterial hypertension (PAH) in patients with systemic sclerosis (SSc), or scleroderma, to optimize diagnostic right heart catheterization (RHC) and minimize missed PAH diagnoses. Sixty-two experienced centers across 18 countries performed RHCs on 466 patients with SSc at increased risk for PAH.1*

Person and Heart Icon

PAH-SSc IS MORE COMMON THAN PREVIOUS STUDIES HAVE SUGGESTED1-3
Nearly 1 in 5 patients with SSc (18.7%, 87/466) were found to have associated PAH via RHC1

Clipboard Icon

SCREENING OF PATIENTS WITH NONSYMPTOMATIC SSc CAN HELP EARLY DIAGNOSIS
PAH was mild in nearly two-thirds of patients with PAH-SSc (64%, 56/87): WHO FC I/II with moderately elevated mPAP and pulmonary vascular resistance and preserved mean cardiac index1

Warning Icon

PAH-SSc CAN PROGRESS QUICKLY
44% of patients with PAH-SSc with follow-up data (25/57) progressed during a short time (median observation time, 12.6 months)4†

For more details about the DETECT study, read the publication from the Annals of the Rheumatic Diseases.

PAH associated with connective tissue diseases such as SSc is the second most
prevalent form of PAH in the US and Europe.5 Learn More About How Many People Are Living With PAH-CTD Today >

DETECT Algorithm

From 112 initial variables, 13 were selected based on their discriminatory ability to detect PAH and these variables formed the basis of the detection algorithm. Multivariable analysis resulted in 8 measures that together aid in the referral to RHC to identify PAH-SSc, even in patients with milder disease, while reducing missed diagnoses and unnecessary testing.1

THE DETECT ALGORITHM 2-STEP DECISION TREE1

Step 1

Nonechocardiographic
variables
TOTAL RISK
POINTS >300
  • FVC % predicted/Dlco % predicted
  • Current/past telangiectasias
  • Serum anticentromere antibodies
  • Serum NT-proBNP
  • Serum urate
  • Right-axis deviation on electrocardiogram
TOTAL RISK
POINTS >300

Step 2

Echocardiogram
TOTAL RISK
POINTS >35
  • Right atrium area
  • TR velocity
TOTAL RISK
POINTS >35
  Stacked document icon

Referral
for RHC

The DETECT algorithm had a 4% (n=3) rate of missed PAH diagnoses compared with 29% (n=24) using the 2009 ESC/ERS Guidelines.1

  • Sensitivity and specificity analysis using the 408 SSc patients in the DETECT study (87 with RHC-confirmed PAH and 321 without)
  • Exclusion of any single variable from the DETECT algorithm had only a small impact on model performance. If more than one variable is missing, the model cannot be used reliably

The DETECT study included patients with SSc who1:

  • Were 18 years or older
  • Were diagnosed more than 3 years ago
  • Had a predicted Dlco <60%
Learn about annual screening for PAH in patients with SSc.5 Learn More About Screening Guidelines >

DETECT Video

Play the video below to learn how the DETECT screening tool helps identify patients with SSc who should be evaluated for PAH.

DETECT Screening Tool for PAH-SSc

The DETECT Screening Tool for PAH-SSc using the algorithm developed by Actelion Pharmaceuticals US, Inc., a Janssen Pharmaceutical Company, and validated in the DETECT study is available for download to your iPhone and Android devices. It can help you identify patients with SSc who should be evaluated for PAH using electrocardiography and may be in need of an RHC for confirmation of PAH-SSc.

Available on the App Store icon
Get it on Google Play icon

The DETECT Screening Tool for PAH-SSc is limited for use by healthcare specialists who treat patients with SSc, and who are familiar with PAH as a complication of SSc. It is not intended to replace the medical or professional judgment of healthcare providers. It does not provide professional advice and should not be considered a diagnosis. Healthcare professionals using the tool should exercise clinical judgment as to the information they provide to the patient based upon the tool.

PAH-SSc screening tool on a mobile device PAH-SSc screening tool on a mobile device
A website-based version of the DETECT Screening Tool for PAH-SSc is also available. Go to DETECT Screening Tool Online Calculator >
*488 patients with SSc were enrolled between 2008 and 2011; patients with >3 years’ duration from first non-Raynaud’s symptom and a predicted Dlco of <60% were considered at increased risk of PAH.1
Disease progression was defined as FC worsening, combination therapy for PAH, PAH-related hospitalization, or death.4
Dlco=diffusing capacity of the lungs for carbon monoxide; ERS=European Respiratory Society; ESC=European Society of Cardiology; FC=Functional Class; FVC=forced vital capacity; mPAP=mean pulmonary arterial pressure; NT-proBNP=N-terminal pro-brain natriuretic peptide; PAH-CTD=pulmonary arterial hypertension associated with connective tissue disease; PAH-SSc=pulmonary arterial hypertension associated with systemic sclerosis; TR=tricuspid regurgitation; WHO=World Health Organization.
References: 1. Coghlan JG, Denton CP, Grünig E, et al; DETECT study group. Evidence-based detection of pulmonary arterial hypertension in systemic sclerosis: the DETECT study. Ann Rheum Dis. 2014;73(7):1340-1349. 2. Mukerjee D, St George D, Coleiro B, et al. Prevalence and outcome in systemic sclerosis associated pulmonary arterial hypertension: application of a registry approach. Ann Rheum Dis. 2003;62(11):1088-1093. 3. Hachulla E, Gressin V, Guillevin L, et al. Early detection of pulmonary arterial hypertension in systemic sclerosis: a French nationwide prospective multicenter study. Arthritis Rheum. 2005;52(12):3792-3800. 4. Mihai C, Antic M, Dobrota R, et al. Factors associated with disease progression in early-diagnosed pulmonary arterial hypertension associated with systemic sclerosis: longitudinal data from the DETECT cohort. Ann Rheum Dis. 2018;77(1):128-132. 5. Galiè N, Humbert M, Vachiéry J-L, et al. 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension. Eur Respir J. 2015;46(4):903-975.

App Store, the Apple logo, and iPhone are trademarks of Apple Inc. Google Play and the Google Play logo are trademarks of Google LLC.