ORCID Profile
0000-0001-8451-8883
Current Organisations
Department of Health
,
Austin Health
,
University of Melbourne
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Publisher: Informa UK Limited
Date: 04-09-2023
Publisher: Wiley
Date: 18-09-2019
DOI: 10.1002/JPPR.1610
Publisher: Cold Spring Harbor Laboratory
Date: 13-12-2021
DOI: 10.1101/2021.12.11.21267504
Abstract: The detection of adverse drug reactions (ADRs) is critical to our understanding of the safety and risk-benefit profile of medications. With an incidence that has not changed over the last 30 years, ADRs are a significant source of patient morbidity, responsible for 5-10% of acute care hospital admissions worldwide. Spontaneous reporting of ADRs has long been the standard method of reporting, however this approach is known to have high rates of under-reporting, a problem that limits pharmacovigilance efforts. Automated ADR reporting presents an alternative pathway to increase reporting rates, although this may be limited by over-reporting of other drug-related adverse events. We developed a deep learning natural language processing algorithm to identify ADRs in discharge summaries at a single academic hospital centre. Our model was developed in two stages: first, a pre-trained model (DeBERTa) was further pre-trained on 1.1 million unlabelled clinical documents secondly, this model was fine-tuned to detect ADR mentions in a corpus of 861 annotated discharge summaries. This model was compared to a version without the pre-training step, and a model finetuned from the ClinicalBERT model, which has demonstrated state-of-the-art performance on other pharmacovigilance tasks. To ensure that our algorithm could differentiate ADRs from other drug-related adverse events, the annotated corpus was enriched for both validated ADR reports and confounding drug-related adverse events using. The final model demonstrated good performance with a ROC-AUC of 0.955 (95% CI 0.946 - 0.963) for the task of identifying discharge summaries containing ADR mentions, significantly outperforming the two comparator models.
Publisher: Elsevier BV
Date: 2023
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 2008
DOI: 10.1097/01.ANES.0000296077.32685.26
Abstract: Propofol, sevoflurane, and desflurane may cause hemodynamic compromise during anesthesia and critical care management. The aim of the study was to compare these anesthetics during increased dose and recovery to maintenance level. Anesthetized, open-chest New Zealand White rabbits were used to acquire dose-response curves with sevoflurane, desflurane, and propofol, followed by reduction to baseline infusion. Simultaneous high-fidelity left ventricular pressure and volume data were acquired during caval occlusion with a dual-field conductance catheter inserted via an apical stab. The preload recruitable stroke work and the end-diastolic pressure-volume relationship were used as the primary measures of contractility and diastolic function. The time-matched controls were stable over time. Propofol and desflurane but not sevoflurane caused dose-dependent reductions in myocardial contractility, although sevoflurane reduced contractility more at 1 minimal alveolar concentration. All anesthetics reduced mean arterial pressure, and significant recovery occurred for sevoflurane and desflurane but not for propofol. The end-diastolic pressure-volume relationship was increased by sevoflurane. Ejection fraction decreased with sevoflurane only. All anesthetics caused dose-dependent vasodilation, with recovery for desflurane and sevoflurane but not propofol. Heart rate was decreased with propofol without significant recovery. Propofol plasma concentrations remained elevated after dose return to baseline infusion rate, suggestive of distribution compartment saturation. All three anesthetics caused dose-dependent decreases in cardiovascular function. Recovery of cardiovascular function occurred rapidly with sevoflurane and desflurane, but persistent depression of contractility, vasodilation, mean arterial pressure, and heart rate occurred with propofol during a 30-min recovery period.
Publisher: The Journal of Rheumatology
Date: 12-2019
Publisher: Elsevier BV
Date: 09-2022
Publisher: Wiley
Date: 22-11-2018
Publisher: BMJ
Date: 09-2021
Abstract: Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy but can result in toxicities, known as immune-related adverse events (irAEs), due to a hyperactivated immune system. ICI-related inflammatory arthritis has been described in literature, but herewith we introduce and characterize post-ICI-activated osteoarthritis (ICI-aOA). We conducted a multicenter, retrospective, observational study of patients with cancer treated with ICIs and diagnosed with ICI-aOA by a rheumatologist. ICI-aOA was defined by (1) an increase in non-inflammatory joint pain after ICI initiation, (2) in joints characteristically affected by osteoarthritis, and (3) lack of inflammation on exam. Cases were graded using the Common Terminology Criteria for Adverse Events (CTCAE) V.6.0 rubric for arthralgia. Response Evaluation Criteria in Solid Tumors V.1.1 (v.4.03) guidelines determined tumor response. Results were analyzed using χ 2 tests of association and multivariate logistic regression. Thirty-six patients had ICI-aOA with a mean age at time of rheumatology presentation of 66 years (51–81 years). Most patients had metastatic melanoma (10/36, 28%) and had received a PD-1/PD-L1 inhibitor monotherapy (31/36, 86%) with 5/36 (14%) combination therapy. Large joint involvement (hip/knee) was noted in 53% (19/36), small joints of hand 25% (9/36), and spine 14% (5/36). Two-thirds (24/36) suffered multiple joint involvement. Three of 36 (8%) had CTCAE grade 3, 14 (39%) grade 2 and 19 (53%) grade 1 manifestations. Symptom onset ranged from 6 days to 33.8 months with a median of 5.2 months after ICI initiation five patients suffered from ICI-aOA after ICI cessation (0.6, 3.5, 4.4, 7.3, and 15.4 months after ICI cessation). The most common form of therapy was intra-articular corticosteroid injections only (15/36, 42%) followed by non-steroidal anti-inflammatory drugs only (7/36, 20%). Twenty patients (56%) experienced other irAEs, with rheumatic and dermatological being the most common. All three patients with high-grade ICI-aOA also had another irAE diagnosis at some point after ICI initiation. ICI-aOA should be recognized as an adverse event of ICI immunotherapy. Early referral to a rheumatologist can facilitate the distinction between ICI induced inflammatory arthritis from post-ICI mechanical arthropathy, the latter of which can be managed with local therapy that will not compromise ICI efficacy.
Publisher: Begell House
Date: 2022
DOI: 10.1615/CRITREVIMMUNOL.2023047272
Abstract: Immunotherapies, such as immune checkpoint inhibitors (ICIs), have significantly advanced the treatment of cancer and other conditions. However, these therapies can also cause immune-related adverse events (irAEs), which are unintended side effects due to their effects on the immune system of the treated patient. These effects can be classified as organ-specific or systemic, with the latter being of particular interest due to their potential overlap with systemic autoimmune diseases (SADs). Autoantibodies, which are proteins produced by the immune system that react with self components, are often used to diagnose and classify SAD. However, the diagnostic value of autoantibodies in the context of systemic irAEs (sirAEs) triggered by ICIs is not well understood. This review aims to evaluate the diagnostic value of conventional autoantibodies in the identification and classification of sirAEs. A comprehensive search of the literature was conducted using the PubMed database, with a focus on articles published in the past 10 years. The results of the review suggest that, although autoantibodies can be useful in the diagnosis and classification of some SAD triggered by ICIs, there is a clear predominance of seronegative irAEs. The lack of traditional autoantibodies may suggest a unique mechanism for sirAEs and increases the already complex diagnostic approach of these manifestations, requiring evaluation by multidisciplinary teams with extensive experience in immunomediated diseases. Further research is needed to fully understand the diagnostic value of autoantibodies in this context and to determine the optimal approach for their detection and interpretation.
Publisher: Oxford University Press (OUP)
Date: 15-07-2021
Publisher: Oxford University Press (OUP)
Date: 23-04-2022
DOI: 10.1093/RHEUMATOLOGY/KEAC249
Abstract: To examine the frequency of, and risk factors for, disease flare following COVID-19 vaccination in patients with systemic rheumatic disease (SRD). An international study was conducted from 2 April to 16 August 2021, using an online survey of 5619 adults with SRD for adverse events following COVID-19 vaccination, including flares of disease requiring a change in treatment. We examined risk factors identified a priori based on published associations with SRD activity and SARS-CoV-2 severity, including demographics, SRD type, comorbidities, vaccine type, cessation of immunosuppressive medications around vaccination and history of reactions to non-COVID-19 vaccines, using multivariable logistic regression. Flares requiring a change in treatment following COVID-19 vaccination were reported by 4.9% of patients. Compared with rheumatoid arthritis, certain SRD, including systemic lupus erythematosus (OR 1.51, 95% CI 1.03, 2.20), psoriatic arthritis (OR 1.95, 95% CI 1.20, 3.18) and polymyalgia rheumatica (OR 1.94, 95% CI 1.08, 2.48) were associated with higher odds of flare, while idiopathic inflammatory myopathies were associated with lower odds for flare (OR 0.54, 95% CI 0.31–0.96). The Oxford-AstraZeneca vaccine was associated with higher odds of flare relative to the Pfizer-BioNTech vaccine (OR 1.44, 95% CI 1.07, 1.95), as were a prior reaction to a non-COVID-19 vaccine (OR 2.50, 95% CI 1.76, 3.54) and female sex (OR 2.71, 95% CI 1.55, 4.72). SRD flares requiring changes in treatment following COVID-19 vaccination were uncommon in this large international study. Several potential risk factors, as well as differences by disease type, warrant further examination in prospective cohorts.
Publisher: Springer Science and Business Media LLC
Date: 06-02-2019
DOI: 10.1007/S40264-018-00794-Y
Abstract: Adverse drug reaction (ADR) detection in hospitals is heavily reliant on spontaneous reporting by clinical staff, with studies in the literature pointing to high rates of underreporting [1]. International Classification of Diseases, 10th Revision (ICD-10) codes have been used in epidemiological studies of ADRs and offer the potential for automated ADR detection systems. The aim of this study was to develop an automated ADR detection system based on ICD-10 codes, using machine-learning algorithms to improve accuracy and efficiency. For a 12-month period from December 2016 to November 2017, every inpatient episode receiving an ICD-10 code in the range Y40.0-Y59.9 (ADR code) was flagged for review as a potential ADR. Each flagged admission was assessed by an expert pharmacist and, if needed, reviewed at regular ADR committee meetings. For each report, a determination was made about ADR probability and severity. The dataset was randomly split into training and test sets. A machine-learning model using the random forest algorithm was developed on the training set to discriminate between true and false ADR reports. The model was then applied to the test set to assess accuracy using the area under the receiver operating characteristic (AUC). In the study period, 2917 Y40.0-Y59.9 codes were applied to admissions, resulting in 245 ADR reports after review. These 245 reports accounted for 44.5% of all ADR reporting in our hospital in the study period. A random forest model built on the training set was able to discriminate between true and false reports on the test set with an AUC of 0.803. Automated ADR detection using ICD-10 coding significantly improved ADR detection in the study period, with improved discrimination between true and false reports by applying a machine-learning model.
Publisher: Wiley
Date: 05-2021
DOI: 10.1111/IMJ.15309
Abstract: Community restrictions due to COVID‐19 have changed healthcare, including increased telehealth use. During the early pandemic phase, a cohort of Australian patients with inflammatory arthritis was surveyed. Self‐reported access to healthcare was maintained and physical health was more likely to be self‐rated poorly than mental health. There was a high level of support for telehealth during and after the pandemic.
Publisher: Springer Science and Business Media LLC
Date: 23-02-2020
Publisher: Springer Science and Business Media LLC
Date: 26-08-2021
Publisher: Wiley
Date: 07-2020
DOI: 10.1111/IMJ.14888
Publisher: Proceedings of the National Academy of Sciences
Date: 06-04-2022
Abstract: The emergence of SARS-CoV-2 triggering the COVID-19 pandemic ranks as arguably the greatest medical emergency of the last century. COVID-19 has highlighted health disparities both within and between countries and will leave a lasting impact on global society. Nonetheless, substantial investment in life sciences over recent decades has facilitated a rapid scientific response with innovations in viral characterization, testing, and sequencing. Perhaps most remarkably, this permitted the development of highly effective vaccines, which are being distributed globally at unprecedented speed. In contrast, drug treatments for the established disease have delivered limited benefits so far. Innovative and rapid approaches in the design and execution of large-scale clinical trials and repurposing of existing drugs have saved many lives however, many more remain at risk. In this review we describe challenges and unmet needs, discuss existing therapeutics, and address future opportunities. Consideration is given to factors that have hindered drug development in order to support planning for the next pandemic challenge and to allow rapid and cost-effective development of new therapeutics with equitable delivery.
Publisher: Elsevier BV
Date: 04-2023
Publisher: Elsevier BV
Date: 2022
Publisher: Therapeutic Guidelines Limited
Date: 03-10-2017
Publisher: Wiley
Date: 12-10-2021
Publisher: BMJ
Date: 09-2022
DOI: 10.1136/RMDOPEN-2022-002587
Abstract: We investigated prolonged COVID-19 symptom duration, defined as lasting 28 days or longer, among people with systemic autoimmune rheumatic diseases (SARDs). We analysed data from the COVID-19 Global Rheumatology Alliance Vaccine Survey (2 April 2021–15 October 2021) to identify people with SARDs reporting test-confirmed COVID-19. Participants reported COVID-19 severity and symptom duration, sociodemographics and clinical characteristics. We reported the proportion experiencing prolonged symptom duration and investigated associations with baseline characteristics using logistic regression. We identified 441 respondents with SARDs and COVID-19 (mean age 48.2 years, 83.7% female, 39.5% rheumatoid arthritis). The median COVID-19 symptom duration was 15 days (IQR 7, 25). Overall, 107 (24.2%) respondents had prolonged symptom duration (≥28 days) 42/429 (9.8%) reported symptoms lasting ≥90 days. Factors associated with higher odds of prolonged symptom duration included: hospitalisation for COVID-19 vs not hospitalised and mild acute symptoms (age-adjusted OR (aOR) 6.49, 95% CI 3.03 to 14.1), comorbidity count (aOR 1.11 per comorbidity, 95% CI 1.02 to 1.21) and osteoarthritis (aOR 2.11, 95% CI 1.01 to 4.27). COVID-19 onset in 2021 vs June 2020 or earlier was associated with lower odds of prolonged symptom duration (aOR 0.42, 95% CI 0.21 to 0.81). Most people with SARDs had complete symptom resolution by day 15 after COVID-19 onset. However, about 1 in 4 experienced COVID-19 symptom duration 28 days or longer 1 in 10 experienced symptoms 90 days or longer. Future studies are needed to investigate the possible relationships between immunomodulating medications, SARD type/flare, vaccine doses and novel viral variants with prolonged COVID-19 symptoms and other postacute sequelae of COVID-19 among people with SARDs.
Publisher: Therapeutic Guidelines Limited
Date: 06-04-2030
Publisher: Elsevier BV
Date: 10-2021
Publisher: Springer Science and Business Media LLC
Date: 28-04-2021
Publisher: Elsevier BV
Date: 11-2022
Publisher: Elsevier BV
Date: 2021
Publisher: Oxford University Press (OUP)
Date: 13-04-2022
Publisher: American College of Physicians
Date: 16-06-2020
DOI: 10.7326/M20-1223
Publisher: Therapeutic Guidelines Limited
Date: 02-2018
Publisher: Informa UK Limited
Date: 22-09-2020
Publisher: Wiley
Date: 29-06-2023
DOI: 10.1002/JPPR.1872
Abstract: Opioid prescribing requires careful planning to minimise the risk of serious adverse outcomes. However, documentation of discharge opioid plans for patients and their general practitioners (GPs) is inconsistent, particularly when opioids are commenced in the emergency department or after surgery. We describe an initiative to promote consistent discharge opioid plan communication by implementing an opioid management plan (OMP) in our hospital's electronic medical record. Completion of an electronic form by the prescriber generates an OMP note in the medical history, which is used by the pharmacist to provide tailored opioid patient education. The OMP also populates the discharge summary that is sent to the GP and the Australian national digital health record platform, My Health Record. Preliminary evaluation shows incorporating OMP documentation into routine workflows has assisted prescribers to consistently document the plan for supplied opioids, supporting continuity of care. Workflow optimisation is ongoing to further improve discharge summary documentation and provision of patient‐friendly written information. This study was conducted as a quality improvement project and audits conducted as part of the project were approved by Austin Health's Office for Research (Project No: LNR/18/Austin/155). Informed patient consent was not required by Austin Health.
Publisher: AME Publishing Company
Date: 04-2020
Publisher: BMJ
Date: 02-2022
DOI: 10.1136/RMDOPEN-2022-002236
Abstract: The US Food and Drug Administration (FDA) has recently added a new ‘black box warning’ on all currently approved Janus kinase (JAK) inhibitors indicated for the treatment of arthritis and other inflammatory conditions based on results from the ORAL Surveillance study of tofacitinib versus tumour necrosis factor alpha inhibitors in rheumatoid arthritis. This is a warning difficult to ignore because the data, being from a randomised controlled trial, are of high fidelity and hard to reproach. It is especially problematic because safety data for all the other JAK inhibitors will be pending for several years. So how might we proceed, without being bound by our stasis? The lack of absolute certainty seems to require a pragmatic approach to the routine care use of JAK inhibitors. The patients who were at greatest risk were older and had other risk factors for the corresponding adverse events, in keeping with effect modification. This highlights the need to focus on risk stratification when tailoring therapy. In this viewpoint, we propose a simple illustration to guide clinical decision-making. First, identify general risk factors for venous thromboembolic event (VTE), major adverse cardiac event (MACE) and cancer (age years and smoking) and whether there is a previous history of VTE, MACE or cancer. Then, evaluate risk based on the number of other risk factors for VTE and the number of other risk factors for MACE. Ultimately, ‘treat-to-target’ will in the end always be ‘treat-to-agreement’. As we have done in the past, and will do in the future, the optimal treatment strategy will have to be tailored based on in idual patient risk factors and preferences in a shared-decision process.
Publisher: BMJ
Date: 09-2021
DOI: 10.1136/RMDOPEN-2021-001814
Abstract: We describe the early experiences of adults with systemic rheumatic disease who received the COVID-19 vaccine. From 2 April to 30 April 2021, we conducted an online, international survey of adults with systemic rheumatic disease who received COVID-19 vaccination. We collected patient-reported data on clinician communication, beliefs and intent about discontinuing disease-modifying antirheumatic drugs (DMARDs) around the time of vaccination, and patient-reported adverse events after vaccination. We analysed 2860 adults with systemic rheumatic diseases who received COVID-19 vaccination (mean age 55.3 years, 86.7% female, 86.3% white). Types of COVID-19 vaccines were Pfizer-BioNTech (53.2%), Oxford/AstraZeneca (22.6%), Moderna (21.3%), Janssen/Johnson & Johnson (1.7%) and others (1.2%). The most common rheumatic disease was rheumatoid arthritis (42.3%), and 81.2% of respondents were on a DMARD. The majority (81.9%) reported communicating with clinicians about vaccination. Most (66.9%) were willing to temporarily discontinue DMARDs to improve vaccine efficacy, although many (44.3%) were concerned about rheumatic disease flares. After vaccination, the most reported patient-reported adverse events were fatigue/somnolence (33.4%), headache (27.7%), muscle/joint pains (22.8%) and fever/chills (19.9%). Rheumatic disease flares that required medication changes occurred in 4.6%. Among adults with systemic rheumatic disease who received COVID-19 vaccination, patient-reported adverse events were typical of those reported in the general population. Most patients were willing to temporarily discontinue DMARDs to improve vaccine efficacy. The relatively low frequency of rheumatic disease flare requiring medications was reassuring.
Publisher: Wiley
Date: 20-09-2023
DOI: 10.1002/ACR.25239
Publisher: Oxford University Press (OUP)
Date: 24-03-2023
DOI: 10.1093/RAP/RKAD008
Abstract: Diagnosing septic arthritis can be challenging and frequently involves clinical assessment, laboratory investigations and synovial fluid analysis. We sought to determine the utility of synovial aspiration and intra-operative synovial fluid and tissue culture for the accurate diagnosis of septic arthritis. We carried out a retrospective review of the records of patients referred to a tertiary orthopaedic unit with possible septic arthritis between 2015 and 2019 inclusive, including clinical and laboratory data for this cohort study. Performance characteristics were determined for synovial aspiration, intra-operative synovial fluid and tissue culture in diagnosing expert review-determined true septic arthritis. Concordance between discharge diagnosis, antibiotic prescribing and true septic arthritis was determined. Of 268 patients identified with suspected septic arthritis, 143 underwent both synovial fluid aspiration and intra-operative synovial fluid and tissue biopsy culture. True septic arthritis was not differentiated significantly by laboratory parameters including serum white cell count (WCC), CRP or synovial WCC. Considering only patients with negative pre-operative synovial aspirate cultures, intra-operative s les led to diagnosis of true septic arthritis in 6 of 63 patients [number needed to treat (NNT) 10.5]. For all patients s led in theatre, positive synovial tissue biopsy was the only evidence of true septic arthritis in six (NNT 23.9). Despite insufficient microbiological evidence, 27 of the 59 patients who did not have septic arthritis received a discharge diagnosis of septic arthritis, 26 of whom were discharged with antibiotics. Intra-operative s le collection, particularly tissue biopsy, increases the likelihood of a true septic arthritis diagnosis. Such measures might help to reduce diagnostic ambiguity in clinical practice and might therefore reduce overtreatment.
Publisher: Therapeutic Guidelines Limited
Date: 22-08-2023
Publisher: Therapeutic Guidelines Limited
Date: 02-2021
Publisher: Oxford University Press (OUP)
Date: 07-09-2022
DOI: 10.1093/RHEUMATOLOGY/KEAC503
Abstract: To determine COVID-19 vaccine hesitancy rates in inflammatory arthritis patients and identify factors associated with changing vaccine hesitancy over time. This investigation was a prospective cohort study of inflammatory arthritis patients from community and public hospital outpatient rheumatology clinics enrolled in the Australian Rheumatology Association Database (ARAD). Two surveys were conducted, one immediately prior to (pre-pandemic) and another approximately 1 year after the start of the pandemic (follow-up). Coronavirus disease 2019 (COVID-19) vaccine hesitancy was measured at follow-up, and general vaccine hesitancy was inferred pre-pandemic these were used to identify factors associated with fixed and changing vaccine beliefs, including sources of information and broader beliefs about medication. Of the 594 participants who completed both surveys, 74 (12%) were COVID-19 vaccine hesitant. This was associated with pre-pandemic beliefs about medications being harmful (P & 0.001) and overused (P = 0.002), with stronger beliefs resulting in vaccine hesitancy persistent over two time points (P = 0.008, P = 0.005). For those not vaccine hesitant pre-pandemic, the development of COVID-19 vaccine hesitancy was associated with a lower likelihood of seeking out vaccine information from health-care professionals (P & 0.001). COVID-19 vaccine hesitancy was not associated with new influenza vaccine hesitancy (P = 0.138). In this study of vaccine beliefs before and during the COVID-19 pandemic, factors associated with COVID-19 vaccine hesitancy in inflammatory arthritis patients varied, depending on vaccine attitudes immediately prior to the start of the pandemic. Fixed beliefs reflected broader views about medications, while fluid beliefs were highly influenced by whether they sought out information from health-care professionals, including rheumatologists.
Publisher: Elsevier BV
Date: 02-2022
DOI: 10.1016/J.SEMARTHRIT.2022.152110
Abstract: Immune checkpoint inhibitors (ICI), increasingly used cancer therapeutics, can cause off-target inflammatory effects called immune-related adverse events (irAEs), including ICI-induced inflammatory arthritis (ICI-induced IA) and polymyalgia rheumatica (ICI-induced PMR). There are no validated classification criteria or outcome measures for these conditions, and adaptation of treatment recommendations from corresponding rheumatic diseases may not be appropriate. We summarized clinical descriptors of ICI-induced IA and ICI-induced PMR and aggregated domains used for these conditions in order to inform the development of a core set of outcome domains. As the initial step of the core domain set generation process, we systemically searched Medline (Pubmed), EMBASE, Cochrane, and CINHL through March 2021 to identify all studies that provide both clinical descriptions and domains relevant to ICI-induced IA and ICI-induced PMR. Domains were mapped to core areas, such as pathophysiological manifestations, life impact, resource use, and longevity/survival, as suggested by the OMERACT 2.1 Filter. We identified 69 publications, over a third of which utilized non-specific diagnoses of "arthritis," "arthralgia," and/or "PMR". Other publications provided the number, the distribution and/or names of specific joints affected, while others labeled the irAE as the corresponding rheumatic disease, such as rheumatoid arthritis or spondyloarthritis. Most distinct domains mapped to the pathophysiology/manifestations core area (24 domains), such as signs/symptoms (13 domains), labs (6 domains), and imaging (5 domains), with harm domains of adverse effects from irAE treatment and fear of irAE treatment decreasing ICI efficacy. Forty-three publications also referenced irAE treatment and 35 subsequent response, as well as 32 tumor response. There is considerable heterogeneity in the domains used to clinically characterize ICI-induced IA and ICI-induced PMR. There were several domains mapped to the pathophysiologic manifestations core area, although several publications highlighted domains evenly distributed among the other core areas of life impact, longevity/survival and resource use.
Publisher: Springer Science and Business Media LLC
Date: 25-07-2023
Publisher: Springer Science and Business Media LLC
Date: 17-10-2022
DOI: 10.1186/S41927-022-00290-Y
Abstract: There is scant research about laboratory monitoring in people taking conventional synthetic disease-modifying anti-rheumatic drugs (csDMARDs) for rheumatic disease. Our objective was to conduct a scoping study to assess the range of current attitudes and the variation in practice of laboratory monitoring of csDMARDs by rheumatologists and trainees. Australian and overseas rheumatologists or trainees were invited through newsletter, Twitter and personal e-mail, to complete an anonymous online survey between 1 February and 22 March 2021. Questions focused on laboratory tests requested by csDMARD prescribed, frequency attern of monitoring, influence of additional factors and combination therapy, actions in response to abnormal tests, and attitudes to monitoring frequencies. Results were presented descriptively and analysed using linear and logistic regression. There were 221 valid responses. Most respondents were from Australia (n = 53, 35%) followed by the US (n = 39, 26%), with a slight preponderance of women (n = 84, 56%), ≥ 11 years in rheumatology practice (n = 83, 56%) and in mostly public practice (n = 79, 53%). Respondents had a wide variation in the frequency and scheduling of tests. In general, respondents reported increasing monitoring frequency if patients had numerous comorbidities or if both methotrexate and leflunomide were being taken concurrently. There was a wide variety of responses to abnormal monitoring results and 27 (40%) considered that in general, monitoring tests are performed too frequently. The results demonstrated a wide variation in the frequency of testing, factors that should influence this, and what responses to abnormal test results are appropriate, indicates a likely lack of evidence and the need to define the risks, benefits and costs of different csDMARD monitoring regimens.
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 12-2021
Publisher: Wiley
Date: 26-10-2022
DOI: 10.1002/ART.42296
Abstract: Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing field of academic research and commercial applications across medicine. Deep learning could have particular relevance to rheumatology if correctly utilized. The greatest benefits of deep learning methods are seen with unstructured data frequently found in rheumatology, such as images and text, where traditional machine learning methods have struggled to unlock the trove of information held within these data formats. The basis for this success comes from the ability of deep learning to learn the structure of the underlying data. It is no surprise that the first areas of medicine that have started to experience impact from deep learning heavily rely on interpreting visual data, such as triaging radiology workflows and computer‐assisted colonoscopy. Applications in rheumatology are beginning to emerge, with recent successes in areas as erse as detecting joint erosions on plain radiography, predicting future rheumatoid arthritis disease activity, and identifying halo sign on temporal artery ultrasound. Given the important role deep learning methods are likely to play in the future of rheumatology, it is imperative that rheumatologists understand the methods and assumptions that underlie the deep learning algorithms in widespread use today, their limitations and the landscape of deep learning research that will inform algorithm development, and clinical decision support tools of the future. The best applications of deep learning in rheumatology must be informed by the clinical experience of rheumatologists, so that algorithms can be developed to tackle the most relevant clinical problems.
Publisher: Elsevier BV
Date: 12-2018
DOI: 10.1016/J.EJCA.2018.09.027
Abstract: Rheumatic immune-related adverse events (irAEs) occur in approximately 10-20% of anti-programmed death 1 (anti-PD1)-treated cancer patients. There are limited data on the natural history, optimal treatment and long-term oncological outcomes of patients with rheumatic irAEs. The objective of the study was to describe the spectrum and natural history of rheumatic irAEs and the potential impact of rheumatic irAEs and immunomodulators on anti-PD1 tumour efficacy. Cancer patients with pre-existing rheumatic disease before anti-PD1 therapy or de novo rheumatic irAEs on anti-PD1 therapy were retrospectively reviewed across three sites. Patient demographics, treatment history, anti-PD1 irAEs, and anti-PD1 responses were evaluated. Relationships between the development or pre-existence of rheumatic irAE, use of immunomodulatory agents and outcomes were evaluated. This multicenter case series describes 36 cancer patients who had rheumatic disease before anti-PD1 therapy (n = 12) or developed de novo rheumatic irAEs (n = 24). Thirty-four of the 36 patients sustained rheumatic irAEs (median time to rheumatic irAE: 14.5 weeks), including 24 de novo (18 inflammatory arthritis, three myositis, two polymyalgia rheumatica, one fasciitis) and 10 flares in 12 patients with pre-existing rheumatic disease. Corticosteroids were used in 30 of 36 patients (median duration: 10 months), and disease-modifying antirheumatic drugs were used in 14 of 36 patients (median duration: 5.5 months). The objective response rate to anti-PD1 therapy was 69% (n = 25/36) overall and 81% (n = 21/26) in the melanoma subgroup. Rheumatic irAEs are often chronic and require prolonged immunomodulatory therapy. Prospective studies are required to define optimal management of rheumatic irAEs that maintain long-term anticancer outcomes.
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 04-2019
Publisher: Elsevier BV
Date: 12-2020
Publisher: Therapeutic Guidelines Limited
Date: 06-2017
Publisher: Elsevier BV
Date: 06-2201
Publisher: Therapeutic Guidelines Limited
Date: 17-06-2020
Publisher: Elsevier BV
Date: 07-2023
Publisher: The Journal of Rheumatology
Date: 09-2022
Abstract: The use of colchicine has been associated with varying degrees of myelosuppression. Despite expanded use in cardiovascular and inflammatory conditions, there remains clinician concern because of potential myelosuppressive side effects. A systematic review was conducted to explore the reported myelosuppressive events of colchicine. A systematic review was conducted using the MeSH terms ("colchicine") AND ("myelosuppression," "bone*," "marrow," "suppression," "aplasia," "leukopenia/leucopenia," "lymphopenia," "neutropenia") on September 1, 2020, and was updated on November 30, 2021. The search was conducted in PubMed, ScienceDirect, Scopus, Embase, and Cochrane Library. The search included references published from 1978 to 2020 and was limited to English-language observational studies (ie, case reports, case series, case control studies, and cohort studies) or trial data. In total, 3233 articles were screened, with 30 studies of 47 patients with myelosuppression from colchicine identified. Most patients with myelosuppression had comorbidities, including renal impairment (21/47, 44.7%). Out of 47 patients, 15 (31.9%) and 13 (27.7%) were reported to be concurrently taking cytochrome P450 3A4 (CYP3A4) inhibitors and P-glycoprotein (P-gp) efflux transporter inhibitors, respectively. Patients with renal impairment accounted for the majority of overall patients taking these CYP3A4 and P-gp inhibitors (8/15, 53.3%, and 8/13, 61.5%, respectively). Out of 21 patients with renal impairment, 13 had worsening cytopenia during colchicine use. The presentations ranged from moderate anemia (grade 2) to severe thrombocytopenia, neutropenia, and leukopenia (grade 4). Colchicine has few reports of myelosuppression. The majority of patients with myelosuppression had preexisting renal impairment or concomitant CYP3A4 or P-gp inhibitor use. Caution should be taken in this subset of patients with increased monitoring.
No related grants have been discovered for David Liew.