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Medical Device for Sustained Remission in Rheumatoid Arthritis Treated With Biological Therapy (REMRABIT-Plus)

24 de junio de 2026 actualizado por: Francisco J. Blanco

Efficacy, Safety and Cost-effectiveness of a Biomarker-based Predictive Model for Persistent Remission in Rheumatoid Arthritis Patients Undergoing Biological Therapy Optimization

This study aims to evaluate a new tool designed to help doctors decide whether it is safe to reduce medication in patients with rheumatoid arthritis (RA) who are in remission.

Rheumatoid arthritis is a chronic inflammatory disease that affects the joints, causing pain, stiffness, and reduced mobility. Many patients receive long-term treatment with biological drugs to control the disease. When the disease is well controlled (remission), doctors may gradually reduce the medication dose. However, deciding when and in whom to reduce treatment is currently based on experience and trial-and-error.

The study evaluates a predictive tool (called OPTIBIO) that uses information from blood samples, genetic data, and clinical characteristics to estimate the risk that the disease will flare up if treatment is reduced.

Participants in the study will be randomly assigned to one of two groups:

  • In one group, the decision to reduce medication will be made by their usual doctor.
  • In the other group, the decision will be guided by the predictive tool.

The study lasts 12 months and includes several hospital visits. During these visits, participants will:

  • Answer questionnaires about their health and quality of life
  • Have physical examinations
  • Provide blood samples for routine tests and additional research purposes
  • Possibly undergo joint ultrasound (if they consent) Some additional blood samples may be stored in authorized biobanks for future research related to rheumatoid arthritis, but only if participants explicitly agree. These samples will be coded to protect personal identity and will only be used in ethically approved research projects.

Participation in the study is entirely voluntary. Participants can choose which procedures they agree to and may withdraw at any time without affecting their medical care.

The study may not provide direct benefit to participants, but it could help improve future treatment decisions and the overall management of rheumatoid arthritis.

Descripción general del estudio

Estado

Reclutamiento

Descripción detallada

Background Rheumatoid arthritis (RA) is a chronic, immune-mediated inflammatory disease characterized by persistent synovitis, progressive joint damage, and reduced quality of life. The introduction of biological therapies, particularly tumor necrosis factor inhibitors (TNFi), has substantially improved disease outcomes, allowing many patients to achieve sustained remission.

In patients who reach remission, clinical guidelines recommend considering treatment optimization strategies, including dose tapering or discontinuation. However, in routine clinical practice, such decisions remain largely empirical and are primarily based on physician judgment. This approach introduces clinical uncertainty, as treatment reduction may lead to disease reactivation in a subset of patients, while continued treatment may expose patients to unnecessary risks and increase healthcare costs.

Rationale There is a clear unmet need for tools that support personalized treatment decisions in patients with RA in remission. A reliable method to predict the risk of disease flare could enable clinicians to better identify patients in whom treatment reduction can be safely implemented.

The OPTIBIO model has been developed as a predictive tool to address this need. It integrates clinical variables with biomarker data derived from peripheral blood, including protein expression, cellular components, and genetic information. By combining these data sources, the model aims to provide individualized risk predictions of disease reactivation following treatment optimization.

Study Purpose The purpose of this study is to evaluate the clinical utility of the OPTIBIO predictive model when incorporated into routine clinical decision-making, compared with standard practice.

The study assesses whether use of the model can support safer and more effective treatment optimization in patients with rheumatoid arthritis in remission receiving TNFi therapy.

Scientific and Clinical Contribution In addition to its clinical focus, the study includes the prospective collection of clinical data and biological samples to further investigate biomarkers associated with disease activity and relapse. These data will contribute to improving the predictive performance of the OPTIBIO model and to identifying novel molecular and cellular signatures associated with disease reactivation.

With participant consent, residual biological samples may be stored in authorized biobanks for future research. These samples may be used in ethically approved studies related to rheumatoid arthritis, contributing to a better understanding of disease mechanisms and to the development of new diagnostic and therapeutic approaches.

Health and Economic Relevance The study also addresses the broader impact of treatment optimization strategies on healthcare systems. By collecting data on healthcare resource utilization, it aims to explore the potential cost-effectiveness of incorporating predictive tools into routine care.

This is particularly relevant in chronic diseases such as RA, where long-term treatment costs and resource utilization are significant, and where more efficient, personalized treatment strategies could have substantial clinical and economic benefits.

Expected Impact This study is expected to generate evidence on the usefulness of a biomarker-based predictive approach to guide treatment decisions in rheumatoid arthritis. The implementation of such tools has the potential to improve patient outcomes, reduce the risk of disease flare, minimize unnecessary treatment exposure, and support more efficient use of healthcare resources.

Tipo de estudio

Intervencionista

Inscripción (Estimado)

184

Fase

  • No aplica

Contactos y Ubicaciones

Esta sección proporciona los datos de contacto de quienes realizan el estudio e información sobre dónde se lleva a cabo este estudio.

Estudio Contacto

  • Nombre: Francisco J. Blanco, MD, PhD
  • Número de teléfono: +34981176399
  • Correo electrónico: fblagar@sergas.es

Ubicaciones de estudio

    • A Coruña
      • A Coruña, A Coruña, España, 15006
        • Reclutamiento
        • Complejo Hospitalario Universitario de A Coruña
        • Contacto:
    • Alava
      • Alava, Alava, España, 01009
        • Reclutamiento
        • Hospital Universitario Araba
        • Contacto:
    • Barcelona
      • Barcelona, Barcelona, España, 08003
        • Reclutamiento
        • Hospital Del Mar
        • Contacto:
          • Jordi Monfort
          • Número de teléfono: +34932483000
          • Correo electrónico: webinfo@hmar.cat
    • Madrid
      • Madrid, Madrid, España, 28040
        • Reclutamiento
        • Hospital Clinico San Carlos
        • Contacto:
      • Madrid, Madrid, España, 28041
        • Reclutamiento
        • Hospital Universitario 12 de Octubre
        • Contacto:
      • Madrid, Madrid, España, 28007
        • Reclutamiento
        • Hospital General Universitario Gregorio Marañón
        • Contacto:
      • Madrid, Madrid, España, 28006
        • Reclutamiento
        • Hospital Universitario La Princesa
        • Contacto:
    • Málaga
      • Málaga, Málaga, España, 29010
        • Reclutamiento
        • Hospital Regional Universitario de Málaga
        • Contacto:
          • Natalia Mena
          • Número de teléfono: +34951 29 00 00
          • Correo electrónico: fblagar@sergas.es
    • Santa Cruz de Tenerife
      • San Cristóbal de La Laguna, Santa Cruz de Tenerife, España, 38320
        • Reclutamiento
        • Hospital Universitario de Canarias
        • Contacto:
          • Jose Federico Díaz
          • Número de teléfono: +34922 67 80 00
          • Correo electrónico: fblagar@sergas.es

Criterios de participación

Los investigadores buscan personas que se ajusten a una determinada descripción, denominada criterio de elegibilidad. Algunos ejemplos de estos criterios son el estado de salud general de una persona o tratamientos previos.

Criterio de elegibilidad

Edades elegibles para estudiar

  • Adulto
  • Adulto Mayor

Acepta Voluntarios Saludables

No

Descripción

Inclusion Criteria:

  • Adults aged ≥18 years.
  • Diagnosis of rheumatoid arthritis according to either the 1987 American College of Rheumatology (ACR) criteria or the 2010 ACR/EULAR classification criteria.
  • Clinical remission for at least 6 months prior to the baseline visit, defined as DAS28-CRP < 2.6.
  • Receiving biological anti-TNF therapy (infliximab, adalimumab, etanercept, golimumab, or certolizumab).
  • Ability and willingness to provide written informed consent to participate in the study.

Exclusion Criteria:

  • Patients in whom biological therapy was prescribed due to systemic manifestations of rheumatoid arthritis.
  • Patients with rheumatoid arthritis and any known associated condition that may interfere with the assessment of study outcomes (e.g., fibromyalgia or concomitant chronic inflammatory diseases).
  • Patients receiving chronic anti-TNF biological therapy who are already undergoing treatment tapering or are on reduced or extended dosing regimens prior to study inclusion.

Plan de estudios

Esta sección proporciona detalles del plan de estudio, incluido cómo está diseñado el estudio y qué mide el estudio.

¿Cómo está diseñado el estudio?

Detalles de diseño

  • Propósito principal: Investigación de servicios de salud
  • Asignación: Aleatorizado
  • Modelo Intervencionista: Asignación paralela
  • Enmascaramiento: Doble

Armas e Intervenciones

Grupo de participantes/brazo
Intervención / Tratamiento
Sin intervención: Standard of care
Treatment optimization decisions are made by the treating physician according to routine clinical practice.
Experimental: OPTIBIO-guided decision
Treatment optimization decisions are guided by the OPTIBIO predictive model, which integrates clinical and biomarker data to estimate the risk of disease flare.
Treatment optimization decisions are guided by the OPTIBIO predictive model, which integrates clinical variables with biomarker data derived from peripheral blood, including protein expression and genetic information. The model provides an individualized estimation of the risk of disease flare associated with treatment reduction and generates a recommendation on whether to maintain or taper biological therapy.

¿Qué mide el estudio?

Medidas de resultado primarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Percentage of patients maintaining sustained remission.
Periodo de tiempo: Up to 12 months
Proportion of patients who remain in sustained remission throughout the entire follow-up period, defined as DAS28-CRP < 2.6 based on tender joint count (28 joints), swollen joint count (28 joints), C-reactive protein levels, and patient global assessment
Up to 12 months
Incidence of adverse events
Periodo de tiempo: Baseline to 70 days after last dose
Incidence and characteristics of adverse events, including serious infections requiring systemic antibiotics or hospitalization, serious treatment-related adverse events, and specific adverse reactions (e.g., infusion or injection reactions), including severity.
Baseline to 70 days after last dose

Medidas de resultado secundarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Proportion of patients achieving sustained acceptable therapeutic target
Periodo de tiempo: Up to 12 months
Proportion of patients maintaining an acceptable therapeutic target throughout follow-up, defined as low disease activity (DAS28-CRP < 3.2) and absence of persistent inflammation in major joints (shoulders, elbows, hips, and knees).
Up to 12 months
Proportion of patients experiencing disease flare (0-6 months).
Periodo de tiempo: Up to 6 months
Proportion of patients experiencing disease flare during the first 6 months of follow-up, defined as DAS28-CRP > 2.6.
Up to 6 months
Proportion of patients experiencing disease flare (6-12 months)
Periodo de tiempo: 6 to 12 months
Proportion of patients experiencing disease flare between months 6 and 12 of follow-up, defined as DAS28-CRP > 2.6.
6 to 12 months
Number of disease flares (0-6 months)
Periodo de tiempo: Up to 6 months
Total number of disease flares occurring during the first 6 months of follow-up.
Up to 6 months
Number of disease flares (6-12 months)
Periodo de tiempo: 6 to 12 months
Total number of disease flares occurring between months 6 and 12 of follow-up.
6 to 12 months
Proportion of patients achieving acceptable therapeutic target at final visit
Periodo de tiempo: At 12 months
Proportion of patients meeting the acceptable therapeutic target definition at the last study visit.
At 12 months
Proportion of patients in remission at final visit
Periodo de tiempo: At 12 months
Proportion of patients in remission at the last study visit, defined as DAS28-CRP < 2.6.
At 12 months
Time to disease flare
Periodo de tiempo: Up to 12 months
Time from baseline to the first occurrence of disease flare, defined as DAS28-CRP > 2.6.
Up to 12 months
Change in clinical disease activity parameters (joint count)
Periodo de tiempo: Baseline to 12 months
Changes over time in clinical parameters: tender joint count (28 joints).
Baseline to 12 months
Change in clinical disease activity parameters (joint count)
Periodo de tiempo: Baseline to 12 months
Changes over time in clinical parameters: swollen joint count (28 joints).
Baseline to 12 months
Change in clinical disease activity parameters: patient and physician global assessment
Periodo de tiempo: Baseline to 12 months
Changes over time in clinical parameters: patient and physician global assessment (0-100 mm scale).
Baseline to 12 months
Change in clinical disease activity parameters: CRP
Periodo de tiempo: Baseline to 12 months
Changes over time in clinical parameters: acute phase reactants, CRP (mg/L)
Baseline to 12 months
Change in health-related quality of life (EQ-5D-5L)
Periodo de tiempo: Baseline to 12 months
Change in health-related quality of life measured using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) questionnaire. The score ranges from 0 to 1, where 1 represents perfect health
Baseline to 12 months
Change in functional disability (HAQ)
Periodo de tiempo: Baseline to 12 months
Change in functional disability assessed using the Health Assessment Questionnaire (HAQ). The HAQ score can range from 0 (no disability) to 3 (maximum disability).
Baseline to 12 months
Direct and indirect healthcare costs and cost-effectiveness
Periodo de tiempo: Up to 12 months
Assessment of direct and indirect healthcare costs and incremental cost-effectiveness and cost-utility ratios.
Up to 12 months
Use of concomitant medication
Periodo de tiempo: Up to 12 months
Use of analgesics, non-steroidal anti-inflammatory drugs, and corticosteroids, including route of administration.
Up to 12 months
Radiographic structural damage progression
Periodo de tiempo: Baseline and 12 months
Progression of structural damage assessed by blinded independent evaluators using the modified Sharp/van der Heijde scoring method on radiographs of hands, wrists, and feet.
Baseline and 12 months
Change in clinical disease activity parameters (ESR)
Periodo de tiempo: Baseline to 12 months
Changes over time in clinical parameters: acute phase reactants, ESR (mm/h).
Baseline to 12 months

Otras medidas de resultado

Medida de resultado
Medida Descripción
Periodo de tiempo
Performance of predictive models based on molecular biomarkers
Periodo de tiempo: Up to 12 months
Evaluation of sensitivity, specificity, and predictive values of models based on PRIME and RETRO biomarkers using clinical outcomes.
Up to 12 months
Performance of predictive models based on imaging biomarkers
Periodo de tiempo: Up to 12 months
Evaluation of predictive performance of ultrasound-based biomarkers, including validation of deep learning models for inflammation assessment.
Up to 12 months
Biobank sample collection
Periodo de tiempo: Baseline
Collection and storage of peripheral blood samples (serum, plasma, RNA, DNA) for future biomarker research.
Baseline

Colaboradores e Investigadores

Aquí es donde encontrará personas y organizaciones involucradas en este estudio.

Patrocinador

Investigadores

  • Investigador principal: Francisco J. Blanco, MD, PhD, Complejo Hospitalario Universitario de A Coruña

Fechas de registro del estudio

Estas fechas rastrean el progreso del registro del estudio y los envíos de resultados resumidos a ClinicalTrials.gov. Los registros del estudio y los resultados informados son revisados ​​por la Biblioteca Nacional de Medicina (NLM) para asegurarse de que cumplan con los estándares de control de calidad específicos antes de publicarlos en el sitio web público.

Fechas importantes del estudio

Inicio del estudio (Actual)

28 de agosto de 2025

Finalización primaria (Estimado)

1 de agosto de 2027

Finalización del estudio (Estimado)

1 de agosto de 2027

Fechas de registro del estudio

Enviado por primera vez

18 de junio de 2026

Primero enviado que cumplió con los criterios de control de calidad

24 de junio de 2026

Publicado por primera vez (Actual)

1 de julio de 2026

Actualizaciones de registros de estudio

Última actualización publicada (Actual)

1 de julio de 2026

Última actualización enviada que cumplió con los criterios de control de calidad

24 de junio de 2026

Última verificación

1 de junio de 2026

Más información

Términos relacionados con este estudio

Plan de datos de participantes individuales (IPD)

¿Planea compartir datos de participantes individuales (IPD)?

INDECISO

Información sobre medicamentos y dispositivos, documentos del estudio

Estudia un producto farmacéutico regulado por la FDA de EE. UU.

No

Estudia un producto de dispositivo regulado por la FDA de EE. UU.

No

Esta información se obtuvo directamente del sitio web clinicaltrials.gov sin cambios. Si tiene alguna solicitud para cambiar, eliminar o actualizar los detalles de su estudio, comuníquese con register@clinicaltrials.gov. Tan pronto como se implemente un cambio en clinicaltrials.gov, también se actualizará automáticamente en nuestro sitio web. .

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