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Gremese E, Bruno D, Nagy G, Ferraccioli G. Difficult to treat rheumatoid arthritis: Sequential therapy with different personalized biological targets could be an option. Eur J Intern Med 2024; 123:146-147. [PMID: 38296659 DOI: 10.1016/j.ejim.2024.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 01/16/2024] [Indexed: 02/02/2024]
Affiliation(s)
- Elisa Gremese
- Clinical Immunology Unit, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Catholic University of the Sacred Heart, Rome, Italy.
| | - Dario Bruno
- Clinical Immunology Unit, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Catholic University of the Sacred Heart, Rome, Italy
| | - György Nagy
- Department of Rheumatology and Clinical Immunology, Department of Internal Medicine and Oncology, Semmelweis University, Budapest, Hungary; Heart and Vascular Center, Semmelweis University, Budapest, Hungary; Department of Genetics, Cell- and Immunobiology, Semmelweis University, Budapest, Hungary; Hospital of the Hospitaller Order of Saint John of God, Budapest, Hungary
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Conran C, Kolfenbach J, Kuhn K, Striebich C, Moreland L. A Review of Difficult-to-Treat Rheumatoid Arthritis: Definition, Clinical Presentation, and Management. Curr Rheumatol Rep 2023; 25:285-294. [PMID: 37776482 DOI: 10.1007/s11926-023-01117-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/02/2023]
Abstract
PURPOSE OF REVIEW A subset of patients with rheumatoid arthritis (RA) who fail multiple biologic therapies are deemed to have "difficult-to-treat" (D2T) RA. In 2021, a European Alliance of Associations for Rheumatology (EULAR) task force proposed a clinical definition of D2T RA. Here we review RA phenotypes and clinical assessment of RA, propose a different definition of D2T RA, discuss possible D2T RA risk factors, and summarize existing literature on the management of D2T RA. RECENT FINDINGS High disease activity at the time of diagnosis or prior to treatment with a biologic is associated with the development of D2T RA. Prolonged time from diagnosis to beginning treatment has been consistently associated with the development of D2T RA. Other clinical factors such as burden of disease, extraarticular disease, obesity, smoking, pain, fatigue, and psychological conditions have inconsistent associations with D2T RA according to current literature. D2T RA is a relatively new concept that represents an area of great need for research regarding the characterization of those with the disease as well as how best to treat the disease. With this gained knowledge, rheumatologists will be able to better identify patients at the time of diagnosis that are likely to develop D2T RA to help guide management.
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Affiliation(s)
- Carly Conran
- Department of Medicine, University of Colorado Denver - Anschutz Medical Campus, 12631 East 17th Avenue, Aurora, CO, 80045, USA.
| | - Jason Kolfenbach
- Department of Medicine, Division of Rheumatology, University of Colorado Denver - Anschutz Medical Campus, 12631 East 17th Avenue, Aurora, CO, 80045, USA
| | - Kristine Kuhn
- Department of Medicine, Division of Rheumatology, University of Colorado Denver - Anschutz Medical Campus, 12631 East 17th Avenue, Aurora, CO, 80045, USA
| | - Christopher Striebich
- Department of Medicine, Division of Rheumatology, University of Colorado Denver - Anschutz Medical Campus, 12631 East 17th Avenue, Aurora, CO, 80045, USA
| | - Larry Moreland
- Department of Medicine, Division of Rheumatology, University of Colorado Denver - Anschutz Medical Campus, 12631 East 17th Avenue, Aurora, CO, 80045, USA
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Gilvaz VJ, Reginato AM. Artificial intelligence in rheumatoid arthritis: potential applications and future implications. Front Med (Lausanne) 2023; 10:1280312. [PMID: 38034534 PMCID: PMC10687464 DOI: 10.3389/fmed.2023.1280312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 10/13/2023] [Indexed: 12/02/2023] Open
Abstract
The widespread adoption of digital health records, coupled with the rise of advanced diagnostic testing, has resulted in an explosion of patient data, comparable in scope to genomic datasets. This vast information repository offers significant potential for improving patient outcomes and decision-making, provided one can extract meaningful insights from it. This is where artificial intelligence (AI) tools like machine learning (ML) and deep learning come into play, helping us leverage these enormous datasets to predict outcomes and make informed decisions. AI models can be trained to analyze and interpret patient data, including physician notes, laboratory testing, and imaging, to aid in the management of patients with rheumatic diseases. As one of the most common autoimmune diseases, rheumatoid arthritis (RA) has attracted considerable attention, particularly concerning the evolution of diagnostic techniques and therapeutic interventions. Our aim is to underscore those areas where AI, according to recent research, demonstrates promising potential to enhance the management of patients with RA.
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Affiliation(s)
- Vinit J. Gilvaz
- Division of Rheumatology, Department of Medicine, Rhode Island Hospital, Warren Alpert Medical School of Brown University, Providence, RI, United States
| | - Anthony M. Reginato
- Division of Rheumatology, Department of Medicine, Rhode Island Hospital, Warren Alpert Medical School of Brown University, Providence, RI, United States
- Department of Dermatology, Rhode Island Hospital, Warren Alpert Medical School of Brown University, Providence, RI, United States
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Chaplin H, Bosworth A, Simpson C, Wilkins K, Meehan J, Nikiphorou E, Moss-Morris R, Lempp H, Norton S. Refractory inflammatory arthritis definition and model generated through patient and multi-disciplinary professional modified Delphi process. PLoS One 2023; 18:e0289760. [PMID: 37556424 PMCID: PMC10411820 DOI: 10.1371/journal.pone.0289760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 07/25/2023] [Indexed: 08/11/2023] Open
Abstract
OBJECTIVE Various definitions have been proposed for Refractory Disease in people with Rheumatoid Arthritis; however, none were generated for Polyarticular Juvenile Idiopathic Arthritis or involving adult and paediatric multidisciplinary healthcare professionals and patients. The study aim is to redefine Refractory Disease, using Delphi methodology. METHODS Three rounds of surveys (one nominal group and two online (2019-2020)) to achieve consensus using a predetermined cut-off were conducted voting on: a) name, b) treatment and inflammation, c) symptoms and impact domains, and d) rating of individual components within domains. Theoretical application of the definition was conducted through a scoping exercise. RESULTS Votes were collected across three rounds from Patients, Researchers and nine multi-disciplinary healthcare professional groups (n = 106). Refractory Inflammatory Arthritis was the most popular name. Regarding treatment and inflammation, these were voted to be kept broad rather than specifying numbers/cut-offs. From 10 domains identified to capture symptoms and disease impact, six domains reached consensus for inclusion: 1) Disease Activity, 2) Joint Involvement, 3) Pain, 4) Fatigue, 5) Functioning and Quality of Life, and 6) Disease-Modifying Anti-Rheumatic Drug Experiences. Within these domains, 18 components, from an initial pool (n = 73), were identified as related and important to capture multi-faceted presentation of Refractory Inflammatory Arthritis, specifically in Rheumatoid Arthritis and Polyarticular Juvenile Idiopathic Arthritis. Feasibility of the revised definition was established (2022-2023) with good utility as was applied to 82% of datasets (n = 61) incorporating 20 outcome measures, with two further measures added to increase its utility and coverage of Pain and Fatigue. CONCLUSION Refractory Inflammatory Arthritis has been found to be broader than not achieving low disease activity, with wider biopsychosocial components and factors incorporating Persistent Inflammation or Symptoms identified as important. This definition needs further refinement to assess utility as a classification tool to identify patients with unmet needs.
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Affiliation(s)
- Hema Chaplin
- Health Psychology Section, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Ailsa Bosworth
- National Rheumatoid Arthritis Society, White Waltham, United Kingdom
| | - Carol Simpson
- Centre for Rheumatic Diseases, King’s College London, London, United Kingdom
| | - Kate Wilkins
- Centre for Rheumatic Diseases, King’s College London, London, United Kingdom
| | - Jessica Meehan
- Health Psychology Section, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Elena Nikiphorou
- Centre for Rheumatic Diseases, King’s College London, London, United Kingdom
| | - Rona Moss-Morris
- Health Psychology Section, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Heidi Lempp
- Centre for Rheumatic Diseases, King’s College London, London, United Kingdom
| | - Sam Norton
- Health Psychology Section, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Centre for Rheumatic Diseases, King’s College London, London, United Kingdom
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Broadwell A, Schechtman J, Conaway D, Kivitz A, Shiff NJ, Black S, Xu S, Langholff W, Schwartzman S, Curtis JR. Effectiveness and safety of intravenous golimumab with and without concomitant methotrexate in patients with rheumatoid arthritis in the prospective, noninterventional AWARE study. BMC Rheumatol 2023; 7:5. [PMID: 36973741 PMCID: PMC10045110 DOI: 10.1186/s41927-023-00329-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 03/07/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Biologic therapies are often prescribed for patients with rheumatoid arthritis (RA) who have inadequate responses to or are intolerant of methotrexate (MTX) and patients with poor prognostic indicators. This post hoc analysis evaluated effectiveness and safety of intravenous golimumab + MTX vs golimumab without MTX in RA patients. METHODS AWARE, a real-world, prospective and pragmatic, Phase 4 study, compared effectiveness and safety of golimumab and infliximab in biologic-naïve and biologic-experienced patients. All treatment decisions were at the discretion of the treating rheumatologist. Effectiveness was evaluated by mean change in CDAI scores at Months 6 and 12. Safety was monitored through approximately 1 year. RESULTS Among 685 golimumab-treated patients, 420 (61%) received concomitant MTX during the study and 265 (39%) did not receive MTX after enrollment; 63% and 72%, respectively, discontinued the study. Relative to golimumab without MTX, golimumab + MTX patients had shorter mean disease duration (8.7 vs 10.0 years) and a lower proportion received prior biologics (60% vs 72%); mean ± standard deviation (SD) baseline CDAI scores were similar (30.8 ± 15.1 and 32.6 ± 15.4). Mean ± SD changes from baseline in CDAI scores at Months 6 and 12, respectively, were similar with golimumab + MTX (- 10.2 ± 14.2 and - 10.8 ± 13.8) and golimumab without MTX (- 9.6 ± 12.9 and - 9.9 ± 13.1). The incidence of adverse events/100 patient-years (PY) (95% confidence interval [CI]) was 155.6 (145.6, 166.1) for golimumab + MTX and 191.2 (176.2, 207.1) for golimumab without MTX; infections were the most common type. The incidence of infusion reactions/100PY (95% CI) was 2.1 (1.1, 3.6) for golimumab + MTX versus 5.1 (2.9, 8.3) for golimumab without MTX; none were considered serious. For golimumab + MTX versus golimumab without MTX, rates/100PY (95% CI) of serious infections, opportunistic infections, and malignancies were 2.6 (1.5, 4.3) versus 7.0 (4.4, 10.6), 0.9 (0.3, 2.0) versus 2.6 (1.1, 5.0), and 3.0 (1.7, 4.7) versus 1.0 (0.2, 2.8), respectively. CONCLUSIONS Mean change in CDAI score in the golimumab without MTX group was generally similar to that of the golimumab + MTX group through 1 year, regardless of prior biologic therapy. Adverse events were consistent with the known IV golimumab safety profile. These results provide real world evidential data that may assist healthcare providers and patients with RA in making informed treatment decisions. TRIAL REGISTRATION clinicaltrials.gov NCT02728934 05/04/2016.
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Affiliation(s)
- Aaron Broadwell
- Rheumatology and Osteoporosis Specialists, 820 Jordan Street, Suite 201, Shreveport, LA, 71101, USA.
| | | | | | - Alan Kivitz
- Altoona Center for Clinical Research, Duncansville, PA, USA
| | - Natalie J Shiff
- Janssen Scientific Affairs, LLC, Horsham, PA, USA
- Adjunct, Community Health and Epidemiology, University of Saskatchewan, Saskatoon, Canada
| | - Shawn Black
- Janssen Research and Development, LLC, Spring House, PA, USA
| | - Stephen Xu
- Janssen Research and Development, LLC, Spring House, PA, USA
| | - Wayne Langholff
- Janssen Research and Development, LLC, Spring House, PA, USA
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Leon L, Madrid-Garcia A, Lopez-Viejo P, González-Álvaro I, Novella-Navarro M, Freites Nuñez D, Rosales Z, Fernandez-Gutierrez B, Abasolo L. Difficult-to-treat rheumatoid arthritis (D2T RA): clinical issues at early stages of disease. RMD Open 2023; 9:rmdopen-2022-002842. [PMID: 36889800 PMCID: PMC10008455 DOI: 10.1136/rmdopen-2022-002842] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 02/20/2023] [Indexed: 03/10/2023] Open
Abstract
OBJECTIVES Most studies on difficult-to-treat rheumatoid arthritis (D2T RA) have focused on established RA. Here, we analyse whether disease activity in the early stages of RA could influence progression to a D2T RA under real-life conditions. Other clinical and treatment-related factors were also analysed. METHODS A longitudinal multicentre study of patients with RA was conducted from 2009 to 2018. Patients were followed up until January 2021. D2T RA was defined based on EULAR criteria (treatment failure, signs suggestive of currently active/progressive disease and management being perceived as problematic by the rheumatologist and/or patient). The main variable was disease activity in the early stages. The covariates were sociodemographic, clinical and treatment-related factors. We ran a multivariable logistic regression analysis to investigate risk factors associated with progression to D2T RA. RESULTS The study population comprised 631 patients and 35 (5.87%) developed D2T RA. At the time of diagnosis, the D2T RA group were younger, with a higher disability, 28-joint Disease Activity Score (DAS28) score, tender joint count and pain scores. In our final model, DAS28 was not statistically significantly associated with D2T RA. No differences were found between groups for therapy. Disability was independently associated with D2T RA (OR: 1.89; p=0.01). CONCLUSIONS In this cohort of patients newly diagnosed with RA, our results do not allow us to prove the influence of active disease according to DAS28. However, we did find that younger patients and those with elevated initial disability scores are more likely to develop D2T RA regardless of other factors.
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Affiliation(s)
- Leticia Leon
- IdISSC and Rheumatology, Hospital Clinico Universitario San Carlos, Madrid, Spain .,Health Sciences, Universidad Camilo Jose Cela, Villafranca del Castillo, Spain
| | | | | | | | | | | | - Zulema Rosales
- Rheumatology, Hospital Clinico Universitario San Carlos, Madrid, Spain
| | | | - Lydia Abasolo
- IdISSC and Rheumatology, Hospital Clinico Universitario San Carlos, Madrid, Spain
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Luppino AF, Cincinelli G, Orenti A, Boracchi P, Favalli EG, Caporali R, Ingegnoli F. Tight control in patients with rheumatoid arthritis treated with targeted therapies across the COVID-19 pandemic era. J Telemed Telecare 2023:1357633X221150724. [PMID: 36694430 PMCID: PMC9892820 DOI: 10.1177/1357633x221150724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 12/27/2022] [Indexed: 01/26/2023]
Abstract
OBJECTIVES To analyze the impact of different patterns of healthcare delivery on remission of rheumatoid arthritis (RA) patients treated with targeted therapies during the first wave (2020) and second/third waves (2021) of the pandemic compared to the pre-pandemic period (2019). METHODS In this observational real-life study, data from RA patients treated with biologic or targeted synthetic drugs were extracted from a longitudinal registry. Clinical Disease Activity Index (CDAI) was analyzed in the same period from the 22nd of February to the 18th of May for three consecutive years. These three periods were characterized by different patterns of healthcare delivery: (1) before the pandemic (2019) only in-person visits, (2) during the first wave (2020) both in-person visits and telehealth, and (3) during the second/third waves (2021) only in-person visits. A generalized linear model with the binomial error was fitted to evaluate the difference in the proportion of patients in CDAI remission. Quantile regression was used to compare the median of CDAI in difficult-to-treat (D2T) patients. RESULTS In the three periods, we included 407, 450, and 540 RA patients respectively. The percentages of patients in CDAI remission were similar in the three periods (prevalence ratio 1.07, p value 0.423 between 2020 and 2019, and 1.01, p-value 0.934 between 2021 and 2019). The CDAI remission rate was 40.55% (N = 163), 43.18% (N = 155) and 40.82% (N = 220) in 2019, 2020 and 2021, respectively. Among our cohort of D2T patients, CDAI remission was similar across the three periods (N = 30, 22.22%; N = 27, 23.68%; and N = 34, 21.52% respectively). CONCLUSION Although the pandemic has imposed changes in our healthcare delivery, these different strategies seem to be effective in ensuring satisfactory management of RA treated with targeted therapies. The approaches modulated in the context of the different periods have been a feasible compensation for ensuring disease control even in D2T patients.
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Affiliation(s)
- Angela Flavia Luppino
- Clinical Rheumatology Unit, ASST Gaetano Pini-CTO, Department of Clinical Sciences & Community Health, Università degli Studi di Milano, Milano, Italy
| | - Gilberto Cincinelli
- Clinical Rheumatology Unit, ASST Gaetano Pini-CTO, Department of Clinical Sciences & Community Health, Università degli Studi di Milano, Milano, Italy
| | - Annalisa Orenti
- Lab of Medical Statistics, Biometry and Epidemiology “GA Maccacaro”, Department of Clinical Sciences & Community Health, Università degli Studi di Milano, Milano, Italy
| | - Patrizia Boracchi
- Department of Biomedical and Clinical Sciences “L. Sacco”, Università degli Studi di Milano, Milano, Italy
| | - Ennio Giulio Favalli
- Clinical Rheumatology Unit, ASST Gaetano Pini-CTO, Department of Clinical Sciences & Community Health, Università degli Studi di Milano, Milano, Italy
| | - Roberto Caporali
- Clinical Rheumatology Unit, ASST Gaetano Pini-CTO, Department of Clinical Sciences & Community Health, Università degli Studi di Milano, Milano, Italy
| | - Francesca Ingegnoli
- Clinical Rheumatology Unit, ASST Gaetano Pini-CTO, Department of Clinical Sciences & Community Health, Università degli Studi di Milano, Milano, Italy
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Watanabe R, Okano T, Gon T, Yoshida N, Fukumoto K, Yamada S, Hashimoto M. Difficult-to-treat rheumatoid arthritis: Current concept and unsolved problems. Front Med (Lausanne) 2022; 9:1049875. [PMID: 36353219 PMCID: PMC9637686 DOI: 10.3389/fmed.2022.1049875] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 10/06/2022] [Indexed: 08/15/2023] Open
Abstract
Over the past several decades, the treatment of rheumatoid arthritis (RA) has advanced significantly, and clinical, structural, and functional remission are achievable therapeutic goals. However, a substantial number of patients show resistance to multiple drugs. In particular, patients whose disease activity cannot be controlled despite the use of two or more biological disease-modifying antirheumatic drugs (DMARDs) or targeted synthetic DMARDs (tsDMARDs) with different mechanisms of action (MOA) have recently been referred to as having difficult-to-treat RA (D2T RA). D2T RA is a heterogeneous and multifactorial disease state, and the major problems are uncontrolled disease activity and decreased quality of life, as well as the economic burden due to frequent healthcare utilization and multiple admissions. Since the concept of D2T RA is relatively new and publication regarding D2T RA is limited, the mechanism underlying DMARD inefficacy and which factors form a "difficult-to-treat" state in such patients are not yet fully understood. It is also possible that factors contributing to D2T RA may differ by patient, sex, country, and race. The present Mini Review introduces the current concept and unsolved problems of D2T RA, including the definition, prevalence, and factors contributing to D2T RA. We then discuss the management and therapeutic strategies for D2T RA. Finally, we explore a clinical approach to prevent patients from developing D2T RA.
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Affiliation(s)
- Ryu Watanabe
- Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Tadashi Okano
- Department of Orthopaedic Surgery, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Takaho Gon
- Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Naofumi Yoshida
- Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Kazuo Fukumoto
- Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Shinsuke Yamada
- Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Motomu Hashimoto
- Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
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Momtazmanesh S, Nowroozi A, Rezaei N. Artificial Intelligence in Rheumatoid Arthritis: Current Status and Future Perspectives: A State-of-the-Art Review. Rheumatol Ther 2022; 9:1249-1304. [PMID: 35849321 PMCID: PMC9510088 DOI: 10.1007/s40744-022-00475-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 06/24/2022] [Indexed: 11/23/2022] Open
Abstract
Investigation of the potential applications of artificial intelligence (AI), including machine learning (ML) and deep learning (DL) techniques, is an exponentially growing field in medicine and healthcare. These methods can be critical in providing high-quality care to patients with chronic rheumatological diseases lacking an optimal treatment, like rheumatoid arthritis (RA), which is the second most prevalent autoimmune disease. Herein, following reviewing the basic concepts of AI, we summarize the advances in its applications in RA clinical practice and research. We provide directions for future investigations in this field after reviewing the current knowledge gaps and technical and ethical challenges in applying AI. Automated models have been largely used to improve RA diagnosis since the early 2000s, and they have used a wide variety of techniques, e.g., support vector machine, random forest, and artificial neural networks. AI algorithms can facilitate screening and identification of susceptible groups, diagnosis using omics, imaging, clinical, and sensor data, patient detection within electronic health record (EHR), i.e., phenotyping, treatment response assessment, monitoring disease course, determining prognosis, novel drug discovery, and enhancing basic science research. They can also aid in risk assessment for incidence of comorbidities, e.g., cardiovascular diseases, in patients with RA. However, the proposed models may vary significantly in their performance and reliability. Despite the promising results achieved by AI models in enhancing early diagnosis and management of patients with RA, they are not fully ready to be incorporated into clinical practice. Future investigations are required to ensure development of reliable and generalizable algorithms while they carefully look for any potential source of bias or misconduct. We showed that a growing body of evidence supports the potential role of AI in revolutionizing screening, diagnosis, and management of patients with RA. However, multiple obstacles hinder clinical applications of AI models. Incorporating the machine and/or deep learning algorithms into real-world settings would be a key step in the progress of AI in medicine.
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Affiliation(s)
- Sara Momtazmanesh
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
- Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Dr. Gharib St, Keshavarz Blvd, Tehran, Iran
| | - Ali Nowroozi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
- Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Nima Rezaei
- Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
- Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Dr. Gharib St, Keshavarz Blvd, Tehran, Iran.
- Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
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10
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Tesolin P, Bertinetto FE, Sonaglia A, Cappellani S, Concas MP, Morgan A, Ferrero NM, Zabotti A, Gasparini P, Amoroso A, Quartuccio L, Girotto G. High Throughput Genetic Characterisation of Caucasian Patients Affected by Multi-Drug Resistant Rheumatoid or Psoriatic Arthritis. J Pers Med 2022; 12:jpm12101618. [PMID: 36294757 PMCID: PMC9605087 DOI: 10.3390/jpm12101618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/14/2022] [Accepted: 09/23/2022] [Indexed: 11/07/2022] Open
Abstract
Rheumatoid and psoriatic arthritis (RA and PsA) are inflammatory rheumatic disorders characterised by a multifactorial etiology. To date, the genetic contributions to the disease onset, severity and drug response are not clearly defined, and despite the development of novel targeted therapies, ~10% of patients still display poor treatment responses. We characterised a selected cohort of eleven non-responder patients aiming to define the genetic contribution to drug resistance. An accurate clinical examination of the patients was coupled with several high-throughput genetic testing, including HLA typing, SNPs-array and Whole Exome Sequencing (WES). The analyses revealed that all the subjects carry very rare HLA phenotypes which contain HLA alleles associated with RA development (e.g., HLA-DRB1*04, DRB1*10:01 and DRB1*01). Additionally, six patients also carry PsA risk alleles (e.g., HLA-B*27:02 and B*38:01). WES analysis and SNPs-array revealed 23 damaging variants with 18 novel “drug-resistance” RA/PsA candidate genes. Eight patients carry likely pathogenic variants within common genes (CYP21A2, DVL1, PRKDC, ORAI1, UGT2B17, MSR1). Furthermore, “private” damaging variants were identified within 12 additional genes (WNT10A, ABCB7, SERPING1, GNRHR, NCAPD3, CLCF1, HACE1, NCAPD2, ESR1, SAMHD1, CYP27A1, CCDC88C). This multistep approach highlighted novel RA/PsA candidate genes and genotype-phenotype correlations potentially useful for clinicians in selecting the best therapeutic strategy.
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Affiliation(s)
- Paola Tesolin
- Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy
| | - Francesca Eleonora Bertinetto
- Department of Medical Sciences, University of Turin, and Immunogenetic and Transplant Biology Service, University Hospital “Città della Salute e della Scienza”, 10124 Turin, Italy
| | - Arianna Sonaglia
- Division of Rheumatology, Department of Medicine (DAME), ASUFC, University of Udine, 33100 Udine, Italy
| | - Stefania Cappellani
- Institute for Maternal and Child Health—IRCCS, Burlo Garofolo, 34137 Trieste, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health—IRCCS, Burlo Garofolo, 34137 Trieste, Italy
- Correspondence: ; Tel.: +39-0403785539
| | - Anna Morgan
- Institute for Maternal and Child Health—IRCCS, Burlo Garofolo, 34137 Trieste, Italy
| | - Norma Maria Ferrero
- Department of Medical Sciences, University of Turin, and Immunogenetic and Transplant Biology Service, University Hospital “Città della Salute e della Scienza”, 10124 Turin, Italy
| | - Alen Zabotti
- Division of Rheumatology, Department of Medicine (DAME), ASUFC, University of Udine, 33100 Udine, Italy
| | - Paolo Gasparini
- Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy
- Institute for Maternal and Child Health—IRCCS, Burlo Garofolo, 34137 Trieste, Italy
| | - Antonio Amoroso
- Department of Medical Sciences, University of Turin, and Immunogenetic and Transplant Biology Service, University Hospital “Città della Salute e della Scienza”, 10124 Turin, Italy
| | - Luca Quartuccio
- Division of Rheumatology, Department of Medicine (DAME), ASUFC, University of Udine, 33100 Udine, Italy
| | - Giorgia Girotto
- Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy
- Institute for Maternal and Child Health—IRCCS, Burlo Garofolo, 34137 Trieste, Italy
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De Cock D, Myasoedova E, Aletaha D, Studenic P. Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs). Ther Adv Musculoskelet Dis 2022; 14:1759720X221105978. [PMID: 35794905 PMCID: PMC9251966 DOI: 10.1177/1759720x221105978] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Accepted: 05/22/2022] [Indexed: 11/17/2022] Open
Abstract
Health care processes are under constant development and will need to embrace advances in technology and health science aiming to provide optimal care. Considering the perspective of increasing treatment options for people with rheumatic and musculoskeletal diseases, but in many cases not reaching all treatment targets that matter to patients, care systems bare potential to improve on a holistic level. This review provides an overview of systems and technologies under evaluation over the past years that show potential to impact diagnosis and treatment of rheumatic diseases in about 10 years from now. We summarize initiatives and studies from the field of electronic health records, biobanking, remote monitoring, and artificial intelligence. The combination and implementation of these opportunities in daily clinical care will be key for a new era in care of our patients. This aims to inform rheumatologists and healthcare providers concerned with chronic inflammatory musculoskeletal conditions about current important and promising developments in science that might substantially impact the management processes of rheumatic diseases in the 2030s.
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Affiliation(s)
- Diederik De Cock
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
| | - Elena Myasoedova
- Division of Rheumatology, Department of Internal Medicine and Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Daniel Aletaha
- Division of Rheumatology, Department of Internal Medicine 3, Medical University Vienna, Vienna, Austria
| | - Paul Studenic
- Division of Rheumatology, Department of Internal Medicine 3, Medical University Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
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Rastogi S, Pandey P. Grand rounds in Ayurvedic rheumatology: Fine-tuning the clinical precepts and appropriating the interventions for improving the outcome in Ayurvedic rheumatology clinics. Int J Ayurveda Res 2022. [DOI: 10.4103/ijar.ijar_3_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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