CClinicalTrials.gg
Not yet recruitingNCT07825233Pix-RiskUpdated Sep 17, 2026

Pix-Risk: Early Detection of Rheumatoid Arthritis Via the DETECTRA Platform

An interventional study of DETECTRA and Standard of Care (SOC) in Rheumatoid Arthritis (RA, sponsored by Centre Hospitalier Universitaire Vaudois. Not yet recruiting at 5 sites in 4 countries. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-09-17.

Sponsored by Centre Hospitalier Universitaire Vaudois · Not applicable, Interventional, and Diagnostic

Phase
Not applicable
Study type
Interventional
Enrollment
142
Allocation
Randomized
Ages
18 Years and older
Sex
All
01

Study summary

The goal of this clinical trial is to learn if a remote monitoring application called DETECTRA can help doctors diagnose rheumatoid arthritis earlier in people who are at risk of developing the disease. It will also learn about the safety and usefulness of this approach.

The main questions it aims to answer are:

Does monitoring symptoms through the DETECTRA application help doctors diagnose rheumatoid arthritis earlier than standard medical follow-up? Does the use of the application help doctors identify signs of arthritis and arrange a medical consultation sooner? How does the disease progress in participants, and how well are their symptoms controlled?

A total of 142 adults will take part in the study. Participants will be randomly assigned to one of two groups:

  1. Receive standard medical care
  2. Receive standard medical care and use the DETECTRA application

Participants using the application will:

Answer questions about their symptoms every 2 weeks Take photographs of their hands using their smartphone Have their information reviewed remotely by doctors

The study will also look at how participants use the application and whether remote monitoring could be useful for the healthcare system.

Read the detailed description

The Pix-Risk study is an international clinical trial investigating whether a remote monitoring application called DETECTRA can help diagnose rheumatoid arthritis earlier in people who are at risk of developing the disease. These patients have recently developed joint pain and have a positive blood test indicating an increased risk, but they have not yet been diagnosed with the disease.

A total of 142 adults will participate in the study. They will be randomly assigned to two groups: one group will receive standard medical care, while the other will have access to the DETECTRA application in addition to standard care. Every two weeks, participants using the application will be asked to answer a few questions about their symptoms and take photographs of their hands using their smartphone. Doctors will be able to review this information remotely to identify signs of arthritis at an earlier stage and arrange a consultation if necessary.

The main objective is to determine whether this digital monitoring approach allows rheumatoid arthritis to be diagnosed more quickly than standard follow-up. The researchers will also assess disease progression, symptom control, use of the application, and its potential benefits for the healthcare system.

The study involves minimal risks, as it primarily relies on questionnaires, photographs, and routine medical examinations. The aim is to improve the early detection of the disease so that treatment can be started earlier and joint damage can be reduced.

02

Conditions studied

  • Rheumatoid Arthritis (RA

Keywords

  • pre-RA
  • software as a medical device
  • time-to-diagnosis
03

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  • Must provide and sign the study's Informed Consent prior to any study-related procedures
  • Able to understand and interact with the study team

    • Agree to comply in good faith with all conditions of the recordings, and to attend all required study procedures.
    • Arthralgia (including hand joints PIP and or MCP)
    • Joint symptoms (arthralgia or stiffness) of recent onset (symptoms \<1 year)
    • Known positive ACPA-titer with written proof
    • Aged 18 years-old or more

Exclusion criteria

Exclusion Criteria:

  • Deformation of the hands or patients who have undergone joint arthrodesis or arthroplasty
  • Known microcrystal disease (e.g. gout, calcium pyrophosphate deposition) if hands are affected or pre-existing immune-mediated rheumatic diseases such as systemic lupus erythematosus or Sjögren's disease
  • Fulfilling the ACR/EULAR 2010 classification criteria for diagnosis of RA (≥ 6 points)
  • Known or suspected clinical synovitis by physician in > 3 small joints (with or without involvement of large joints)
  • Any previous b, ts, and csDMARDs use
  • Lymphoedema in arms or hands following an axillary lymph node dissection
  • Inability to provide written informed consent
  • Severe cognitive impairment, severe psychiatric conditions or other inability to follow the procedures of the study
  • Immunosuppressive therapy for other autoimmune conditions \<2 years ago
  • Any Immunosuppressive therapy for other autoimmune conditions with B-cell depletion
  • Haematological or oncological treatments involving induction and / or maintenance chemotherapy within the last 5 years are not permitted
  • Participation in another investigation with an investigational drug or another MD within the 30 days preceding the trial or currently participating or planning to participate in an interventional trial
  • No regular (at least every 2 weeks) access to a smartphone
  • Adults who lack capacity to consent, known pregnant and breastfeeding women
  • Subjects for whom routine examination of the musculoskeletal system is not possible, or whose hands cannot be imaged (e.g., bandages that cannot be removed for hand picture taking, or injuries affecting the PIP joints both persisting for > 49 days)
  • Enrolment of the PI, his/her family members, employees and other dependent persons
04

Study design

Phase
Not applicable
Primary purpose
Diagnostic
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
142 participants (estimated)

Study arms

  • Other
    Control group

    Standard-of-care

    Other: Standard of Care (SOC)

  • Experimental
    DETECTRA

    The intervention group will receive the DETECTRA application on top of the standard-of-care and will use it every two weeks to upload hand images and report patient reported outcomes.

    Device: DETECTRA

Interventions

  • DeviceDETECTRA

    Intervention arm (DETECTRA): Participants receive standard of care plus use of the DETECTRA remote monitoring app. Every two weeks, patients capture hand images and report symptoms via smartphone. Data are reviewed remotely by clinicians to support early detection of rheumatoid arthritis. The intervention is non-invasive, software-based, and continues up to 24 months or until diagnosis.

  • OtherStandard of Care (SOC)

    Participants receive standard rheumatology care only, with in-person visits and follow-up according to routine clinical practice.

05

What researchers measure

Primary outcomes

  1. Time-to-diagnosis

    Time (in days) from study enrollment to confirmed clinical diagnosis of rheumatoid arthritis (with the ACR/EULAR 2010 classification criteria for RA (≥ 6 points) and / or physician diagnosis with start of DMARDs) in ACPA-positive arthralgia patients, comparing the DETECTRA group to the standard-of-care group.

    Time frame: From study enrollement to confirmed clinical diagnosis

Secondary outcomes

  1. Difference in DAS28-CRP and SDAI

    Difference in DAS28-CRP and SDAI after 24 months will be assessed by a trained rheumatologist in the DETECTRA group as compared to the standard-of-care group (only in RA confirmed patients).

    Time frame: From study enrollement until the end of the study (24months)

  2. Remission rates

    Percentage of patients in remission after 24 months will be assessed by a trained rheumatologist in the DETECTRA group as compared to the standard-of-care group (only in RA confirmed patients).

    Time frame: From study enrollement until the end of study (24months)

  3. Sensitivity

    Sensitivity: Missed onsets/diagnosis of clinical arthritis in the intervention group: This endpoint will be assessed if a patient comes for a visit based on his request and in the closure visit. Any confirmed RA is classified as a missed diagnosis if patients request a visit (or in the planned closure visit) and are diagnosed without that the physician had previously recognized signs via the platform of a potential onset of RA.

    Time frame: From study enrollement until the end of study (24months)

  4. Specificity

    Specificity: False diagnoses in the intervention group will be assessed at any interim visit and is reported if a patient got flagged via the platform, came in for confirmation but does not get diagnosed.

    Time frame: From enrolement until the end of study (24months).

  5. Adherence

    Percentage of submissions on the platform (totally expected submissions = every two weeks until diagnosis or end of trial) per patient during the duration of the study (2 years). Only for patients in the intervention group.

    Time frame: From study enrollement until diagnosis or end of study (24months)

  6. Adherence

    Average amount of reminders (calls by the study nurse but not the automatic reminders via the app) per patient needed for the duration of the study (2 years). Only for participants in the intervention group.

    Time frame: From enrolement until end of study (24months) or until diagnosis of RA.

  7. Cost-effectiveness estimates

    The primary outcome of interest for the health economic evaluation is cost-effectiveness, expressed as the incremental cost per Quality-Adjusted Life Year (QALY) gained through the use of DETECTRA compared to standard-of-care. Data for the evaluation will be collected from both the DETECTRA system and clinical records during the trial. Through the app, patients will report PROs including self-assessed joint counts (tender and swollen), global pain and stiffness scores (via VAS-like scales), medication use, free-text symptom notes, and joint-specific pain reports. At the clinic level, data will be collected on the timing and number of visits, formal RA diagnoses, and DMARD treatment initiations. These trial-derived endpoints-particularly time-to-diagnosis, time to DMARD start, and proportion diagnosed within defined timeframes-will inform a Markov model to extrapolate long-term costs and outcomes beyond the trial period. QALYs will be estimated using available health state information

    Time frame: Full study duration (24months)

Other outcomes

  1. Diagnostic accuracy

    Diagnostic accuracy of the Finger Fold Index to differentiate between presence and absence of synovitis (as defined by clinical examination and or ultrasound) will be assessed using the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

    Time frame: From study enrollement until the end of study

  2. Sensitivity to change

    Sensitivity to change will be calculated for each biomarker (FFI) using the Standardized Response Mean (SRM), defined as the mean change from baseline to follow-up divided by the standard deviation of the change scores. The correlation between the SRMs of CRP will then be evaluated to assess whether their responsiveness to change is related.

    Time frame: From study enrollement until the end of study (24months)

  3. Exploratory analysis of additional imaging-derived metrics

    Images from any time-point of the investigation taken via the DETECTRA system will be used to support future enhancements of the algorithms/biomarkers (FFI) integrated in the DETECTRA system. The predefined FFI implementation used within this clinical investigation is fixed and will not be modified during the study. Exploratory analyses will not influence device outputs, clinical assessments, or study endpoints. Any findings may be used to inform future biomarker development and algorithm refinement in subsequent device versions outside the scope of this investigation.

    Time frame: From study enrollement until end of study (24months)

  4. Thermal imaging dataset

    The outcome of interest regarding thermal imaging is the successful creation of the thermographic dataset. This includes: * Data completeness: The number of valid thermal images successfully linked with their corresponding comprehensive set of clinical, demographic, laboratory, and ultrasound reference data. * Data quality: Assessment of image technical quality (e.g., image noise, hand position, absence of artifacts) to ensure suitability for future image processing. * Repository integrity: The successful compilation of a structured database ready for transfer to Singularity Biomed.

    Time frame: From study enrollement until end of study (24months)

06

Study locations

5 sites
  • Medical University Vienna
    Vienna, Austria
  • Copenhagen Center for Arthritis Research (COPECARE), Rigshospitalet
    Copenhagen, Denmark
    • Lene Terslev · Contact
    • Lene Terslev, Prof. · Principal investigator
  • Charite Universitätsmedizin Berlin
    Berlin, Germany
  • Ruhr University Bochum
    Bochum, Germany
  • Centre Hospitalier Unversitaire Vaudois
    Lausanne, 1011, Switzerland
    • Thomas Hügle, Prof. · Contact · thomas.hugle@chuv.ch · +41795568068
    • Thomas hügle, Prof. · Principal investigator
07

References and documents

Publications

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  • Sokka T, Pincus T. Most patients receiving routine care for rheumatoid arthritis in 2001 did not meet inclusion criteria for most recent clinical trials or american college of rheumatology criteria for remission. J Rheumatol. 2003 Jun;30(6):1138-46. PubMed 12784382 ↗
  • Finckh A, Liang MH, van Herckenrode CM, de Pablo P. Long-term impact of early treatment on radiographic progression in rheumatoid arthritis: A meta-analysis. Arthritis Rheum. 2006 Dec 15;55(6):864-72. doi: 10.1002/art.22353. PubMed 17139662 ↗
  • Raza K, Stack R, Kumar K, Filer A, Detert J, Bastian H, Burmester GR, Sidiropoulos P, Kteniadaki E, Repa A, Saxne T, Turesson C, Mann H, Vencovsky J, Catrina A, Chatzidionysiou A, Hensvold A, Rantapaa-Dahlqvist S, Binder A, Machold K, Kwiatkowska B, Ciurea A, Tamborrini G, Kyburz D, Buckley CD. Delays in assessment of patients with rheumatoid arthritis: variations across Europe. Ann Rheum Dis. 2011 Oct;70(10):1822-5. doi: 10.1136/ard.2011.151902. Epub 2011 Aug 7. PubMed 21821867 ↗
  • Rosa JE, Garcia MV, Luissi A, Pierini F, Sabelli M, Mollerach F, Soriano ER. Rheumatoid Arthritis Patient's Journey: Delay in Diagnosis and Treatment. J Clin Rheumatol. 2020 Oct;26(7S Suppl 2):S148-S152. doi: 10.1097/RHU.0000000000001196. PubMed 31609811 ↗
  • Kernder A, Thiele K, Chehab G, Schneider M, Callhoff J. Time interval between the onset of connective tissue disease symptoms and first contact with a rheumatologist: results from the German National Database of collaborative arthritis centers. Rheumatol Int. 2023 Aug;43(8):1453-1458. doi: 10.1007/s00296-023-05335-0. Epub 2023 Jun 1. PubMed 37258745 ↗
  • Morales-Ivorra I, Narvaez J, Gomez-Vaquero C, Moragues C, Nolla JM, Narvaez JA, Marin-Lopez MA. Assessment of inflammation in patients with rheumatoid arthritis using thermography and machine learning: a fast and automated technique. RMD Open. 2022 Jul;8(2):e002458. doi: 10.1136/rmdopen-2022-002458. PubMed 35840312 ↗
  • Morales-Ivorra I, Taverner D, Codina O, Castell S, Fischer P, Onken D, Martinez-Osuna P, Battioui C, Marin-Lopez MA. External Validation of the Machine Learning-Based Thermographic Indices for Rheumatoid Arthritis: A Prospective Longitudinal Study. Diagnostics (Basel). 2024 Jun 30;14(13):1394. doi: 10.3390/diagnostics14131394. PubMed 39001284 ↗
  • Pfeuffer N, Hartmann F, Grahammer M, Simon D, Schuster L, Kuhn S, Kronke G, Schett G, Knitza J, Kleyer A. Early detection of rheumatoid arthritis through patient empowerment by tailored digital monitoring and education: a feasibility study. Rheumatol Int. 2025 Feb 4;45(2):43. doi: 10.1007/s00296-025-05793-8. PubMed 39903294 ↗
  • van Mulligen E, Bour SS, Goossens LMA, de Jong PHP, Rutten-van Molken M, van der Helm-van Mil A. Is a 1-year course of methotrexate in patients with arthralgia at-risk for rheumatoid arthritis cost-effective? A cost-effectiveness analysis of the randomised, placebo-controlled TREAT EARLIER trial. Ann Rheum Dis. 2025 Jan;84(1):68-76. doi: 10.1136/ard-2024-226286. Epub 2025 Jan 2. PubMed 39874236 ↗
  • Barber CEH, Lacaille D, Croxford R, Barnabe C, Marshall DA, Abrahamowicz M, Xie H, Avina-Zubieta JA, Esdaile JM, Hazlewood GS, Faris P, Katz S, MacMullan P, Mosher D, Widdifield J. Investigating Associations Between Access to Rheumatology Care, Treatment, Continuous Care, and Healthcare Utilization and Costs Among Older Individuals With Rheumatoid Arthritis. J Rheumatol. 2023 May;50(5):617-624. doi: 10.3899/jrheum.220729. Epub 2023 Jan 15. PubMed 36642438 ↗
  • Hugle T, Caratsch L, Caorsi M, Maglione J, Dan D, Dumusc A, Blanchard M, Kalweit G, Kalweit M. Dorsal Finger Fold Recognition by Convolutional Neural Networks for the Detection and Monitoring of Joint Swelling in Patients with Rheumatoid Arthritis. Digit Biomark. 2022 Jun 8;6(2):31-35. doi: 10.1159/000525061. eCollection 2022 May-Aug. PubMed 35949225 ↗
  • Studenic P, Hensvold A, Kleyer A, van der Helm-van Mil A, Pratt AG, Sieghart D, Kronke G, Williams R, de Souza S, Karlfeldt S, Johannesson M, Krogh NS, Klareskog L, Catrina AI. Prospective Studies on the Risk of Rheumatoid Arthritis: The European Risk RA Registry. Front Med (Lausanne). 2022 Feb 22;9:824501. doi: 10.3389/fmed.2022.824501. eCollection 2022. PubMed 35273981 ↗
  • van der Woude D, van der Helm-van Mil AHM. Update on the epidemiology, risk factors, and disease outcomes of rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2018 Apr;32(2):174-187. doi: 10.1016/j.berh.2018.10.005. Epub 2018 Nov 16. PubMed 30527425 ↗
  • Kleyer A, Krieter M, Oliveira I, Faustini F, Simon D, Kaemmerer N, Cavalcante A, Tabosa T, Rech J, Hueber A, Schett G. High prevalence of tenosynovial inflammation before onset of rheumatoid arthritis and its link to progression to RA-A combined MRI/CT study. Semin Arthritis Rheum. 2016 Oct;46(2):143-150. doi: 10.1016/j.semarthrit.2016.05.002. Epub 2016 May 18. PubMed 27342772 ↗
  • van Steenbergen HW, Aletaha D, Beaart-van de Voorde LJ, Brouwer E, Codreanu C, Combe B, Fonseca JE, Hetland ML, Humby F, Kvien TK, Niedermann K, Nuno L, Oliver S, Rantapaa-Dahlqvist S, Raza K, van Schaardenburg D, Schett G, De Smet L, Szucs G, Vencovsky J, Wiland P, de Wit M, Landewe RL, van der Helm-van Mil AH. EULAR definition of arthralgia suspicious for progression to rheumatoid arthritis. Ann Rheum Dis. 2017 Mar;76(3):491-496. doi: 10.1136/annrheumdis-2016-209846. Epub 2016 Oct 6. PubMed 27991858 ↗
  • Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO 3rd, Birnbaum NS, Burmester GR, Bykerk VP, Cohen MD, Combe B, Costenbader KH, Dougados M, Emery P, Ferraccioli G, Hazes JM, Hobbs K, Huizinga TW, Kavanaugh A, Kay J, Kvien TK, Laing T, Mease P, Menard HA, Moreland LW, Naden RL, Pincus T, Smolen JS, Stanislawska-Biernat E, Symmons D, Tak PP, Upchurch KS, Vencovsky J, Wolfe F, Hawker G. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum. 2010 Sep;62(9):2569-81. doi: 10.1002/art.27584. PubMed 20872595 ↗
  • Zhao SS, Duffield SJ, Goodson NJ. The prevalence and impact of comorbid fibromyalgia in inflammatory arthritis. Best Pract Res Clin Rheumatol. 2019 Jun;33(3):101423. doi: 10.1016/j.berh.2019.06.005. Epub 2019 Jul 17. PubMed 31703796 ↗
  • Bernard L, Valsecchi V, Mura T, Aouinti S, Padern G, Ferreira R, Pastor J, Jorgensen C, Mercier G, Pers YM. Management of patients with rheumatoid arthritis by telemedicine: connected monitoring. A randomized controlled trial. Joint Bone Spine. 2022 Oct;89(5):105368. doi: 10.1016/j.jbspin.2022.105368. Epub 2022 Mar 4. PubMed 35248737 ↗
  • Skovsgaard CV, Kruse M, Hjollund N, Maribo T, de Thurah A. Cost-effectiveness of a telehealth intervention in rheumatoid arthritis: economic evaluation of the Telehealth in RA (TeRA) randomized controlled trial. Scand J Rheumatol. 2023 Mar;52(2):118-128. doi: 10.1080/03009742.2021.2008604. Epub 2022 Jan 20. PubMed 35048793 ↗
  • Song Y, Bernard L, Jorgensen C, Dusfour G, Pers YM. The Challenges of Telemedicine in Rheumatology. Front Med (Lausanne). 2021 Oct 13;8:746219. doi: 10.3389/fmed.2021.746219. eCollection 2021. PubMed 34722584 ↗
  • Krijbolder DI, Verstappen M, van Dijk BT, Dakkak YJ, Burgers LE, Boer AC, Park YJ, de Witt-Luth ME, Visser K, Kok MR, Molenaar ETH, de Jong PHP, Bohringer S, Huizinga TWJ, Allaart CF, Niemantsverdriet E, van der Helm-van Mil AHM. Intervention with methotrexate in patients with arthralgia at risk of rheumatoid arthritis to reduce the development of persistent arthritis and its disease burden (TREAT EARLIER): a randomised, double-blind, placebo-controlled, proof-of-concept trial. Lancet. 2022 Jul 23;400(10348):283-294. doi: 10.1016/S0140-6736(22)01193-X. PubMed 35871815 ↗
  • Finckh A, Gilbert B, Hodkinson B, Bae SC, Thomas R, Deane KD, Alpizar-Rodriguez D, Lauper K. Global epidemiology of rheumatoid arthritis. Nat Rev Rheumatol. 2022 Oct;18(10):591-602. doi: 10.1038/s41584-022-00827-y. Epub 2022 Sep 6. PubMed 36068354 ↗
  • Rech J, Tascilar K, Hagen M, Kleyer A, Manger B, Schoenau V, Hueber AJ, Kleinert S, Baraliakos X, Braun J, Kiltz U, Fleck M, Rubbert-Roth A, Kofler DM, Behrens F, Feuchtenberger M, Zaenker M, Voll R, Venhoff N, Thiel J, Glaser C, Feist E, Burmester GR, Karberg K, Strunk J, Canete JD, Senolt L, Filkova M, Naredo E, Largo R, Kronke G, D'Agostino MA, Ostergaard M, Schett G. Abatacept inhibits inflammation and onset of rheumatoid arthritis in individuals at high risk (ARIAA): a randomised, international, multicentre, double-blind, placebo-controlled trial. Lancet. 2024 Mar 2;403(10429):850-859. doi: 10.1016/S0140-6736(23)02650-8. Epub 2024 Feb 13. PubMed 38364841 ↗

Individual participant data

Plan to share: No

08

Registry details

Key details

Study ID
NCT07825233
Lead sponsor
Centre Hospitalier Universitaire Vaudois
Collaborators
Staatssekretariat für Bildung Forschung und Innovation SBFI, European Commission
Responsible party
Thomas Hügle (Prof. Dr. Thomas Hügle - Head of departement, Centre Hospitalier Universitaire Vaudois) — Principal investigator
First posted
Sep 17, 2026
Start date
Sep 28, 2026 (estimated)
Primary completion
Jul 31, 2029 (estimated)
Completion
Jul 31, 2029 (estimated)
Last update
Sep 17, 2026

Study contacts

Thomas Hügle, Prof.
Contact
thomas.hugle@chuv.ch
+41795568068
Thomas hügle, Prof.
principal investigator · Centre hospitalier universitaire vaudois (CHUV)

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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