Treatment delays for patients with new‐onset rheumatoid arthritis presenting to an Australian early arthritis clinic

Ison, Matthew; Duggan, Emily; Mehdi, Ahmed M.; Thomas, Ranjeny; Benham, Helen

doi:10.1111/imj.13972

Cited by 10 publications

(13 citation statements)

References 34 publications

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“…Polanco et al [4] found that the first consultation with a general practitioner at a public health center as well as with an orthopedic surgeon were the main factors associated with the increasing of the delay of the diagnosis and the introduction of cDMARDs. In agreement with the results of Matthew et al [2] who found that the factors that are associated with a delay in cDMARDs introduction were the presentation of the patient to the general practitioner, the delay of referral from the general practitioner to the rheumatologist as well as the socio-economic disadvantage, fatigue score and low DAS28.…”

Section: Discussionsupporting

confidence: 91%

“…In an American study by Kimsey and al [1], the time between symptoms onset and initiation of cDMARDs was 4 months (SD 5.8), and in an Australian study was 6,6 months (18-52.1) [2].…”

Section: Discussionmentioning

confidence: 94%

“…Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that affects large and small joints causing bone erosions, joint deformities, and comorbidities [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

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The lag time from symptoms onset of rheumatoid arthritis to initiation of Methotrexate: data from the Moroccan register of biotherapies

Eddaoudi¹,

Rostom²,

Hmamouchi³

et al. 2021

Rheumatol Orthop Med

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Objective: The purpose of this study is to determine the time between the onset of rheumatoid arthritis (RA) symptoms and the introduction of methotrexate, as well as the associated factors. Methods:A multicenter cross-sectional study that included data from the Moroccan register of biologic patients with rheumatoid arthritis. Sociodemographic, economic patient data and disease data were collected. A logistic regression was performed to determine the factors that are associated with the change in the delay between the onset of symptoms and the initiation of cDMARD.Results: A total of 225 RA patients were included. The mean age was 51 ± 11 years, with a female predominance of 88% (n=197). The diagnosis lag time was 12 months (12-48). Seventy-three percent of the cases were housewives. Seventy-nine percent of patients received Methotrexate as the first CDMARDS. Salazopyrine was the second prescribed CDMARDS with 7%. Hydroxychloroquine was the third prescribed cDMARDs which 2.2%. The median lag time from symptoms onset to initiation of Methotrexate was 24 months (0.16-71). The factors, associated with the change in the delay between the onset of symptoms and the introduction of methotrexate in univariate analysis, were delay in diagnosis and corticosteroids Taking (p<0.05), only the delay of diagnosis in multivariate analysis persists p=0.0001. Conclusions:Our study suggests that there is a significant delay between diagnosis and the introduction of methotrexate as a first line cDMARDs. In multivariate analysis only the time to diagnosis was associated with the time to start methotrexate.

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Section: Discussionsupporting

confidence: 91%

“…In an American study by Kimsey and al [1], the time between symptoms onset and initiation of cDMARDs was 4 months (SD 5.8), and in an Australian study was 6,6 months (18-52.1) [2].…”

Section: Discussionmentioning

confidence: 94%

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The lag time from symptoms onset of rheumatoid arthritis to initiation of Methotrexate: data from the Moroccan register of biotherapies

Eddaoudi¹,

Rostom²,

Hmamouchi³

et al. 2021

Rheumatol Orthop Med

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“…Hastaların yaklaşık üçte ikisinden fazlası doktor nedenli tedavi gecikmesinin olduğunu beyan etmiştir (Tablo 2,3). Bu çalışmadan farklı olarak, Avustralya'da hasta beyanlı ve Birleşik Krallık'ta kesitsel özellikte yapılan çalışmalarda tedavi gecikmesinin hasta nedenli olduğu belirlenmiştir (20,21). Hastalarımız tanı gecikmesini doktor kaynaklı olarak görmekle birlikte diğer nedenlerin de ortaya konulabilmesi için hasta ve doktor değerlendirmelerini birlikte içeren çalışmalara ihtiyaç olduğu açıktır.…”

Section: Discussionunclassified

Çorum Bölgesinde Yaşayan İnflamatuar Romatizmal Hastalıkları Olan Kişilerde Tanı ve Tedavi Gecikmesinin Değerlendirilmesi

Öztekin¹,

Doğan²,

Özkara³

et al. 2019

Konuralp Tıp Dergisi

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Bu çalışma ile Çorum bölgesinde yaşayan inflamatuar romatizmal hastalıkları olan kişilerde tanı ve tedavi gecikmesinin değerlendirilmesi amaçlanmıştır. Gereç ve Yöntem: Tanımlayıcı özellikteki bu çalışma Eylül-Kasım 2018 tarihleri arasında Çorum ilinde yapıldı. Araştırmaya 119 hasta dahil edildi. Araştırmada verilerin analizi SPSS 22.0 paket programı ile gerçekleştirildi. Verilerin değerlendirilmesinde yüzdelik, ortalama, Ki-kare (Chi-square) testi kullanıldı. Değerlendirmelerde p<0.05 değeri anlamlı kabul edildi. Bulgular: Araştırma grubunun yaş ortalaması 46,00±14,00 yıl olup katılımcıların %63,0'ü kadın ve %86,7'si lise ve daha az eğitime sahipti. Katılımcıların üçte birinden fazlası romatoid artrit tanısı almıştı. Herhangi bir inflamatuar romatizmal hastalık tanısını ilk olarak romatolog tarafından alan bireylerin oranı %50,4 iken aile hekimleri tarafından ilk tanıyı alanların oranı %2,5'dir. Katılımcıların %49,6'sında tanıda gecikme olduğu belirlendi. Katılımcılar tarafından tedaviye başlamada gecikmenin en önemli nedeni olarak %63,6 ile doktor gösterildi. Katılımcıların sosyodemografik özelliklerinin tedaviye başlamada gecikmenin üzerinde etkisinin olmadığı belirlendi (p<0.05). Sonuç: Çalışmamızda inflamatuar hastalıklarda tanı gecikmesinin sosyo-demografik özelliklerden etkilenmeksizin yüksek olduğu saptanmıştır. Geriatrik dönem nüfusunun giderek arttığı ülkemizde mezuniyet öncesi ve sonrası romatolojik hastalıkla ilgili eğitim programlarının artırılması, hastaların tanı, tedavileri ve komplikasyonlardan korunmaları kapsamında faydalar sağlayabilir.

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“…Significant progress has been made with IA treatment over the past two decades, including biological and targeted synthetic disease modifying medication. In contrast, screening methods have not evolved, leading to significant delays in accurate identification and treatment, compounding the burden of disability [ 7 – 9 ]. There is a need for reliable, accessible and cost-effective methods to help identify IA in primary care settings.…”

Section: Introductionmentioning

confidence: 99%

A multicentre validation study of a smartphone application to screen hand arthritis

Reed

Rampono²,

Turner³

et al. 2022

BMC Musculoskelet Disord

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Background Arthritis is a common condition, and the prompt and accurate assessment of hand arthritis in primary care is an area of unmet clinical need. We have previously developed and tested a screening tool combining machine-learning algorithms, to help primary care physicians assess patients presenting with arthritis affecting the hands. The aim of this study was to assess the validity of the screening tool among a number of different Rheumatologists. Methods Two hundred and forty-eight consecutive new patients presenting to 7 private Rheumatology practices across Australia were enrolled. Using a smartphone application, each patient had photographs taken of their hands, completed a brief 9-part questionnaire, and had a single examination result (wrist irritability) recorded. The Rheumatologist diagnosis was entered following a 45-minute consultation. Multiple machine learning models were applied to both the photographic and survey/examination results, to generate a screening outcome for the primary diagnoses of osteoarthritis, rheumatoid and psoriatic arthritis. Results The combined algorithms in the application performed well in identifying and discriminating between different forms of hand arthritis. The algorithms were able to predict rheumatoid arthritis with accuracy, precision, recall and specificity of 85.1, 80.0, 88.1 and 82.7% respectively. The corresponding results for psoriatic arthritis were 95.2, 76.9, 90.9 and 95.8%, and for osteoarthritis were 77.4, 78.3, 80.6 and 73.7%. The results were maintained when each contributor was excluded from the analysis. The median time to capture all data across the group was 2 minutes and 59 seconds. Conclusions This multicentre study confirms the results of the pilot study, and indicates that the performance of the screening tool is maintained across a group of different Rheumatologists. The smartphone application can provide a screening result from a combination of machine-learning algorithms applied to hand images and patient symptom responses. This could be used to assist primary care physicians in the assessment of patients presenting with hand arthritis, and has the potential to improve the clinical assessment and management of such patients.

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Treatment delays for patients with new‐onset rheumatoid arthritis presenting to an Australian early arthritis clinic

Abstract: In this Australian EAC setting, patient delay was the greatest contributor to RA treatment delay. Delays in treatment were associated with lower disease severity and socioeconomic disadvantage. Remission was more likely after prompt initiation of treatment.

Cited by 10 publications

References 34 publications

The lag time from symptoms onset of rheumatoid arthritis to initiation of Methotrexate: data from the Moroccan register of biotherapies

The lag time from symptoms onset of rheumatoid arthritis to initiation of Methotrexate: data from the Moroccan register of biotherapies

Çorum Bölgesinde Yaşayan İnflamatuar Romatizmal Hastalıkları Olan Kişilerde Tanı ve Tedavi Gecikmesinin Değerlendirilmesi

A multicentre validation study of a smartphone application to screen hand arthritis

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