House dust mite sublingual allergen immunotherapy tablet is safe and well-tolerated in Dutch clinical practice.

Background: Half (49%) of clinically diagnosed allergic rhinitis (AR) patients are sensitized to house dust mite (HDM). If allergen avoidance and symptomatic medication fail, allergen immunotherapy may be indicated. Objective: We investigated safety and tolerability of HDM-sublingual immunotherapy by HDM-SLIT tablets in Dutch daily clinical practice. Methods: Daily intake of 12 SQ-HDM SLIT-tablet was investigated in a prospective, multicenter, observational study (EUPAS43753). It comprised 4 consultations in 1 year. Data on safety, tolerability, treatment satisfaction, symptomatic medication, compliance, and clinical effectiveness (Control of Allergic Rhinitis and Asthma Test; CARAT) were collected. Descriptive and longitudinal regression data analysis were performed. Results: Adult patients (n = 415), mean (SD) age 36.6 (12.2) years, 61.4% female and 36% asthmatic were included. The preponderance (65.1%) experienced adverse events (AEs). These, mostly mild (67%), AEs comprised: oral allergic reactions (58.6%), respiratory (12.4%) and gastrointestinal symptoms (9.4%). Sixty (14.5%) patients stopped due to AEs and 76 (18.3%) for non-AE reasons. CARAT scores improved clinically significant by 6 points and symptomatic medication use decreased from 96.1% to 77.4%. Most patients (74.5%) tolerated the treatment and were compliant (>86.5%). The majority of patients (62.4%) and investigators (69.4%) were satisfied with treatment. Conclusions: HDM SLIT-tablet is a safe and well-tolerated AR treatment. AEs occur often but are mostly mild and decreasing during the first year. CARAT scores improved and symptomatic medication use decreased suggesting better control of AR with treatment. Compliance, tolerability, and treatment satisfaction are good. However, patient follow-up and compliance remain important points of attention when initiating treatment.

Remission definitions guiding immunosuppressive therapy in rheumatoid arthritis: which is best fitted for the purpose?

OBJECTIVE: To assess which definition of remission best predicts good radiographic outcome (GRO) and good functional outcome (GFO) in rheumatoid arthritis, focusing the updated American College of Rheumatology/European Alliance of Associations for Rheumatology criteria. MATERIAL AND METHODS: Meta-analyses of individual patient data (IPD) from randomised controlled trials (RCTs). Six definitions of remission were considered: (1) Boolean with Patient Global Assessment (PGA)≤1 (Boolean); (2) Simplified Disease Activity Index (SDAI)≤3.3; (3) Clinical Disease Activity Index (CDAI)≤2.8; (4) Boolean with PGA≤2 (Updated-Boolean); (5) Boolean with Physician Global Assessment (PhGA≤1) replacing PGA (Boolean-PhGA) and (6) Boolean excluding PGA (3VBoolean). GRO was defined as a worsening ≤0.5 units in radiographic score and GFO as a no worsening in Health Assessment Questionnaire (HAQ), that is, ∆HAQ-DI≤0.0 units. Relationships between each remission definition at 6 and/or 12 months and GRO and GFO during the second year were analysed. Pooled probabilities for each outcome for each definition and their predictive accuracy were estimated. RESULTS: IPD from eight RCTs (n=4423) were analysed. Boolean, SDAI, CDAI, Updated-Boolean, Boolean-PhGA and 3VBoolean were achieved by 24%, 27%, 28%, 32%, 33% and 43% of all patients, respectively. GRO among patients achieving remission ranged from 82.4% (3VBoolean) to 83.9% (SDAI). 3VBoolean showed the highest predictive accuracy for GRO: 51.1% versus 38.8% (Boolean) and 44.1% (Updated-Boolean). The relative risk of GFO ranged from 1.16 (Boolean) to 1.05 (3VBoolean). However, the proportion of GFO correctly predicted was highest for the 3VBoolean (50.3%) and lowest for the Boolean (43.8%). CONCLUSION: 3VBoolean definition provided the most accurate prediction of GRO and GFO, avoiding the risk of overtreatment in a substantial proportion of patients without increment in radiographic damage progression, supporting the proposal that 3VBoolean remission is preferable to guide immunosuppressive treatment. The patient's perspective, which must remain central, is best served by an additional patient-oriented target: a dual-target approach.

Rheumatoid arthritis patients' perspective on the use of prediction models in clinical decision-making.

OBJECTIVES: A rapidly expanding number of prediction models is being developed aiming to improve rheumatoid arthritis (RA) diagnosis and treatment. However, few are actually implemented in clinical practice. This study explores factors influencing the acceptance of prediction models in clinical decision-making by RA patients. METHODS: A qualitative study design was used with thematic analysis of semi-structured interviews. Purposive sampling was applied to capture a complete overview of influencing factors. The interview topic list was based on pilot data. RESULTS: Data saturation was reached after 12 interviews. Patients were generally positive about the use of prediction models in clinical decision-making. Six key themes were identified from the interviews. First, patients have the need for information on prediction models. Second, factors influencing trust in model-supported treatment are described. Third, patients envision the model to have a supportive role in clinical decision-making. Fourth, patients hope to personally benefit from model-supported treatment in various ways. Fifth, patients are willing to contribute time and effort to contribute to model input. And lastly, we discuss the theme on effects of the relationship with the caregiver in model-supported treatment. CONCLUSION: Within this study RA patients were generally positive about the use of prediction models in their treatment given some conditions were met and concerns addressed. The results of this study can be used during the development and implementation in RA care of prediction models in order to enhance patient acceptability.

Endoscopic ultrasonography-guided gastroenterostomy versus surgical gastrojejunostomy for palliation of malignant gastric outlet obstruction (ENDURO): study protocol for a randomized controlled trial.

BACKGROUND: Malignant gastric outlet obstruction (GOO) is a debilitating condition that frequently occurs in patients with malignancies of the distal stomach and (peri)ampullary region. The standard palliative treatment for patients with a reasonable life expectancy and adequate performance status is a laparoscopic surgical gastrojejunostomy (SGJ). Recently, endoscopic ultrasound-guided gastroenterostomy (EUS-GE) emerged as a promising alternative to the surgical approach. The present study aims to compare these treatment modalities in terms of efficacy, safety, and costs. METHODS: The ENDURO-study is a multicentre, open-label, parallel-group randomized controlled trial. In total, ninety-six patients with gastric outlet obstruction caused by an irresectable or metastasized malignancy will be 1:1 randomized to either SGJ or EUS-GE. The primary endpoint is time to tolerate at least soft solids. The co-primary endpoint is the proportion of patients with persisting or recurring symptoms of gastric outlet obstruction for which a reintervention is required. Secondary endpoints are technical and clinical success, quality of life, gastroenterostomy dysfunction, reinterventions, time to reintervention, adverse events, quality of life, time to start chemotherapy, length of hospital stay, readmissions, weight, survival, and costs. DISCUSSION: The ENDURO-study assesses whether EUS-GE, as compared to SGJ, results in a faster resumption of solid oral intake and is non-inferior regarding reinterventions for persistent or recurrent obstructive symptoms in patients with malignant GOO. This trial aims to guide future treatment strategies and to improve quality of life in a palliative setting. TRIAL REGISTRATION: International Clinical Trials Registry Platform (ICTRP): NL9592. Registered on 07 July 2021.

Clinical Validation of a Primary Antibody Deficiency Screening Algorithm for Primary Care.

PURPOSE: The diagnostic delay of primary antibody deficiencies (PADs) is associated with increased morbidity, mortality, and healthcare costs. Therefore, a screening algorithm was previously developed for the early detection of patients at risk of PAD in primary care. We aimed to clinically validate and optimize the PAD screening algorithm by applying it to a primary care database in the Netherlands. METHODS: The algorithm was applied to a data set of 61,172 electronic health records (EHRs). Four hundred high-scoring EHRs were screened for exclusion criteria, and remaining patients were invited for serum immunoglobulin analysis and referred if clinically necessary. RESULTS: Of the 104 patients eligible for inclusion, 16 were referred by their general practitioner for suspected PAD, of whom 10 had a PAD diagnosis. In patients selected by the screening algorithm and included for laboratory analysis, prevalence of PAD was ~ 1:10 versus 1:1700-1:25,000 in the general population. To optimize efficiency of the screening process, we refitted the algorithm with the subset of high-risk patients, which improved the area under the curve-receiver operating characteristics curve value to 0.80 (95% confidence interval 0.63-0.97). We propose a two-step screening process, first applying the original algorithm to distinguish high-risk from low-risk patients, then applying the optimized algorithm to select high-risk patients for serum immunoglobulin analysis. CONCLUSION: Using the screening algorithm, we were able to identify 10 new PAD patients from a primary care population, thus reducing diagnostic delay. Future studies should address further validation in other populations and full cost-effectiveness analyses. REGISTRATION: Clinicaltrials.gov record number NCT05310604, first submitted 25 March 2022.

Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study.

Objectives: To efficiently assess the disease-modifying potential of new osteoarthritis treatments, clinical trials need progression-enriched patient populations. To assess whether the application of machine learning results in patient selection enrichment, we developed a machine learning recruitment strategy targeting progressive patients and validated it in the IMI-APPROACH knee osteoarthritis prospective study. Design: We designed a two-stage recruitment process supported by machine learning models trained to rank candidates by the likelihood of progression. First stage models used data from pre-existing cohorts to select patients for a screening visit. The second stage model used screening data to inform the final inclusion. The effectiveness of this process was evaluated using the actual 24-month progression. Results: From 3500 candidate patients, 433 with knee osteoarthritis were screened, 297 were enrolled, and 247 completed the 2-year follow-up visit. We observed progression related to pain (P, 30%), structure (S, 13%), and combined pain and structure (P â€‹+ â€‹S, 5%), and a proportion of non-progressors (N, 52%) ∼15% lower vs an unenriched population. Our model predicted these outcomes with AUC of 0.86 [95% CI, 0.81-0.90] for pain-related progression and AUC of 0.61 [95% CI, 0.52-0.70] for structure-related progression. Progressors were ranked higher than non-progressors for P â€‹+ â€‹S (median rank 65 vs 143, AUC = 0.75), P (median rank 77 vs 143, AUC = 0.71), and S patients (median rank 107 vs 143, AUC = 0.57). Conclusions: The machine learning-supported recruitment resulted in enriched selection of progressive patients. Further research is needed to improve structural progression prediction and assess this strategy in an interventional trial.

Identifying multivariate disease trajectories and potential phenotypes of early knee osteoarthritis in the CHECK cohort.

OBJECTIVE: To gain better understanding of osteoarthritis (OA) heterogeneity and its predictors for distinguishing OA phenotypes. This could provide the opportunity to tailor prevention and treatment strategies and thus improve care. DESIGN: Ten year follow-up data from CHECK (1002 early-OA subjects with first general practitioner visit for complaints ≤6 months before inclusion) was used. Data were collected on WOMAC (pain, function, stiffness), quantitative radiographic tibiofemoral (TF) OA characteristics, and semi-quantitative radiographic patellofemoral (PF) OA characteristics. Using functional data analysis, distinctive sets of trajectories were identified for WOMAC, TF and PF characteristics, based on model fit and clinical interpretation. The probabilities of knee membership to each trajectory were used in hierarchical cluster analyses to derive knee OA phenotypes. The number and composition of potential phenotypes was selected again based on model fit (silhouette score) and clinical interpretation. RESULTS: Five trajectories representing different constant levels or changing WOMAC scores were identified. For TF and PF OA, eight and six trajectories respectively were identified based on (changes in) joint space narrowing, osteophytes and sclerosis. Combining the probabilities of knees belonging to these different trajectories resulted in six clusters ('phenotypes') of knees with different degrees of functional (WOMAC) and radiographic (PF) parameters; TF parameters were found not to significantly contribute to clustering. Including baseline characteristics as well resulted in eight clusters of knees, dominated by sex, menopausal status and WOMAC scores, with only limited contribution of PF features. CONCLUSIONS: Several stable and progressive trajectories of OA symptoms and radiographic features were identified, resulting in phenotypes with relatively independent symptomatic and radiographic features. Sex and menopausal status may be especially important when phenotyping knee OA patients, while radiographic features contributed less. Possible phenotypes were identified that, after validation, could aid personalized treatments and patients selection.

Concomitant prednisone may alleviate methotrexate side-effects in rheumatoid arthritis patients.

OBJECTIVES: To evaluate whether addition of low-moderate dose prednisone to methotrexate (MTX) treatment can alleviate common MTX side-effects in rheumatoid arthritis (RA) patients. METHODS: We performed a post-hoc analysis of the CAMERA-II trial which randomized (1:1) 236 early DMARD and prednisone naive RA patients to treatment with MTX + prednisone 10 mg daily, or MTX monotherapy during two years. MTX dose was increased using a treat-to-target approach. We used Generalized Estimating Equations to model the occurrence of common MTX side-effects and of any adverse event over time, controlling for disease activity and MTX dose over time and other possible predictors of adverse events. To assess whether a possible effect was prednisone-specific, we performed the same analysis in the U-ACT-EARLY trial, in which the addition of tocilizumab (TCZ) to MTX was compared to MTX monotherapy in a comparable setting. RESULTS: MTX side-effects were reported at 5.9% of visits in the prednisone-MTX group, compared to 11.2% in the MTX monotherapy group. After controlling for MTX dose and disease activity over time, treatment duration, age, sex, and baseline transaminase levels, addition of prednisone significantly decreased the occurrence of MTX side-effects (OR: 0.54, CI: 0.38-0.77, p = 0.001). Specifically, the occurrence of nausea (OR 0.46, CI: 0.26-0.83, p = 0.009)) and elevated ALT/AST (OR 0.29, CI: 0.17-0.49, p < 0.001) was decreased. There was a trend towards fewer overall adverse events in the prednisone-MTX arm (OR: 0.89, CI: 0.72-1.11, p = 0.30). No difference in MTX side-effects was found between TCZ-MTX and MTX monotherapy in U-ACT-EARLY (OR 1.05, CI: 0.61-1.80, p = 0.87). CONCLUSION: Addition of 10 mg prednisone daily to MTX treatment in RA patients may ameliorate MTX side-effects, specifically nausea and elevated ALT/AST.

Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency.

BACKGROUND: Primary antibody deficiencies (PAD) are characterized by a heterogeneous clinical presentation and low prevalence, contributing to a median diagnostic delay of 3-10 years. This increases the risk of morbidity and mortality from undiagnosed PAD, which may be prevented with adequate therapy. To reduce the diagnostic delay of PAD, we developed a screening algorithm using primary care electronic health record (EHR) data to identify patients at risk of PAD. This screening algorithm can be used as an aid to notify general practitioners when further laboratory evaluation of immunoglobulins should be considered, thereby facilitating a timely diagnosis of PAD. METHODS: Candidate components for the algorithm were based on a broad range of presenting signs and symptoms of PAD that are available in primary care EHRs. The decision on inclusion and weight of the components in the algorithm was based on the prevalence of these components among PAD patients and control groups, as well as clinical rationale. RESULTS: We analyzed the primary care EHRs of 30 PAD patients, 26 primary care immunodeficiency patients and 58,223 control patients. The median diagnostic delay of PAD patients was 9.5 years. Several candidate components showed a clear difference in prevalence between PAD patients and controls, most notably the mean number of antibiotic prescriptions in the 4 years prior to diagnosis (5.14 vs. 0.48). The final algorithm included antibiotic prescriptions, diagnostic codes for respiratory tract and other infections, gastro-intestinal complaints, auto-immune symptoms, malignancies and lymphoproliferative symptoms, as well as laboratory values and visits to the general practitioner. CONCLUSIONS: In this study, we developed a screening algorithm based on a broad range of presenting signs and symptoms of PAD, which is suitable to implement in primary care. It has the potential to considerably reduce diagnostic delay in PAD, and will be validated in a prospective study. Trial registration The consecutive prospective study is registered at clinicaltrials.gov under NCT05310604.

Machine-learning predicted and actual 2-year structural progression in the IMI-APPROACH cohort.

In the Innovative Medicine's Initiative Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) knee osteoarthritis (OA) study, machine learning models were trained to predict the probability of structural progression (s-score), predefined as >0.3 mm/year joint space width (JSW) decrease and used as inclusion criterion. The current objective was to evaluate predicted and observed structural progression over 2 years according to different radiographic and magnetic resonance imaging (MRI)-based structural parameters. Radiographs and MRI scans were acquired at baseline and 2-year follow-up. Radiographic (JSW, subchondral bone density, osteophytes), MRI quantitative (cartilage thickness), and MRI semiquantitative [SQ; cartilage damage, bone marrow lesions (BMLs), osteophytes] measurements were obtained. The number of progressors was calculated based on a change exceeding the smallest detectable change (SDC) for quantitative measures or a full SQ-score increase in any feature. Prediction of structural progression based on baseline s-scores and Kellgren-Lawrence (KL) grades was analyzed using logistic regression. Among 237 participants, around 1 in 6 participants was a structural progressor based on the predefined JSW-threshold. The highest progression rate was seen for radiographic bone density (39%), MRI cartilage thickness (38%), and radiographic osteophyte size (35%). Baseline s-scores could only predict JSW progression parameters (most P>0.05), while KL grades could predict progression of most MRI-based and radiographic parameters (P<0.05). In conclusion, between 1/6 and 1/3 of participants showed structural progression during 2-year follow-up. KL scores were observed to outperform the machine-learning-based s-scores as progression predictor. The large amount of data collected, and the wide range of disease stage, can be used for further development of more sensitive and successful (whole joint) prediction models. Trial Registration: Clinicaltrials.gov number NCT03883568.

Co-sensitization between legumes is frequently seen, but variable and not always clinically relevant.

Background: Food allergy to peanut and soybean, both legumes, is highly prevalent. The consumption of other legumes and legume protein isolates, some of which may be considered novel foods, is increasing. This may lead to an increase in sensitization and allergy and may pose a risk for legume-allergic (e.g. peanut and soybean) patients due to cross-reactivity. Objective: This study investigated the frequency of co-sensitization and co-allergy between legumes and the role of different protein families. Methods: Six legume-allergic patient groups were included: peanut (n = 30), soybean (n = 30), lupine (n = 30), green pea (n = 30), lentil (n = 17), bean (n = 9). IgE binding to total extracts, protein fractions (7S/11S globulin, 2S albumin, albumin), and 16 individual proteins from 10 legumes (black lentil, blue lupine, chickpea, faba bean, green lentil, pea, peanut, soybean, white bean, and white lupine) was measured by line blot. Results: Co-sensitization varied from 36.7% to 100%. Mono-sensitization was only found in soybean (16.7%), peanut (10%), and green pea-allergic (3.3%) patients. A high frequency of co-sensitization between the 7S/11S globulin fractions of all 10 legumes and individual 7S and 11S globulins was observed. In peanut and soybean-allergic patients, co-allergies for other legumes were uncommon (≤16,7%), while in green pea, lupine, lentil, and bean-allergic patients co-allergy for peanut (64.7%-77.8%) or soybean (50%-64.7%) was frequently seen. Conclusion: Co-sensitization between legumes was high, but generally not clinically relevant. Co-allergy to other legumes was not often seen in peanut- and soybean allergic patients. The 7S and 11S globulins were likely responsible for the observed co-sensitization.

What is the best target in a treat-to-target strategy in rheumatoid arthritis? Results from a systematic review and meta-regression analysis.

OBJECTIVES: A treat-to-target (T2T) strategy has been shown to be superior to usual care in rheumatoid arthritis (RA), but the optimal target remains unknown. Targets are based on a disease activity measure (eg, Disease Activity Score-28 (DAS28), Simplified Disease Activity Indices/Clinical Disease Activity Indices (SDAI/CDAI), and a cut-off such as remission or low disease activity (LDA). Our aim was to compare the effect of different targets on clinical and radiographic outcomes. METHODS: Cochrane, Embase and (pre)MEDLINE databases were searched (1 June 2022) for randomised controlled trials and cohort studies after 2003 that applied T2T in RA patients for ≥12 months. Data were extracted from individual T2T study arms; risk of bias was assessed with the Cochrane Collaboration tool. Using meta-regression, we evaluated the effect of the target used on clinical and radiographic outcomes, correcting for heterogeneity between and within studies. RESULTS: 115 treatment arms were used in the meta-regression analyses. Aiming for SDAI/CDAI-LDA was statistically superior to targeting DAS-LDA regarding DAS-remission and SDAI/CDAI/Boolean-remission outcomes over 1-3 years. Aiming for SDAI/CDAI-LDA was also significantly superior to DAS-remission regarding both SDAI/CDAI/Boolean-remission (over 1-3 years) and mean SDAI/CDAI (over 1 year). Targeting DAS-remission rather than DAS-LDA only improved the percentage of patients in DAS-remission, and only statistically significantly after 2-3 years of T2T. No differences were observed in Health Assessment Questionnaire and radiographic progression. CONCLUSIONS: Targeting SDAI/CDAI-LDA, and to a lesser extent DAS-remission, may be superior to targeting DAS-LDA regarding several clinical outcomes. However, due to the risk of residual confounding and the lack of data on (over)treatment and safety, future studies should aim to directly and comprehensively compare targets. PROSPERO REGISTRATION NUMBER: CRD42021249015.

Points to consider for cost-effective use of biological and targeted synthetic DMARDs in inflammatory rheumatic diseases: results from an umbrella review and international Delphi study.

OBJECTIVES: To develop evidence-based points to consider for cost-effective use of biological and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) in the treatment of inflammatory rheumatic diseases, specifically rheumatoid arthritis, psoriatic arthritis and axial spondyloarthritis. METHODS: Following EULAR procedures, an international task force was formed, consisting of 13 experts in rheumatology, epidemiology and pharmacology from seven European countries. Twelve strategies for cost-effective use of b/tsDMARDs were identified through individual and group discussion. For each strategy, PubMed and Embase were systematically searched for relevant English-language systematic reviews and, for six strategies, additionally for randomised controlled trials (RCTs). Thirty systematic reviews and 21 RCTs were included. Based on the evidence, a set of overarching principles and points to consider was formulated by the task force using a Delphi procedure. Level of evidence (1a-5) and grade (A-D) were determined for each point to consider. Individual voting on the level of agreement (LoA; between 0 (completely disagree) and 10 (completely agree)) was performed anonymously. RESULTS: The task force agreed on five overarching principles. For 10 of 12 strategies, the evidence was sufficient to formulate one or more points to consider, leading to 20 in total, regarding response prediction, drug formulary use, biosimilars, loading doses, low-dose initial therapy, concomitant conventional synthetic DMARD use, route of administration, medication adherence, disease activity-guided dose optimisation and non-medical drug switching. Ten points to consider (50%) were supported by level 1 or 2 evidence. The mean LoA (SD) varied between 7.9 (1.2) and 9.8 (0.4). CONCLUSION: These points to consider can be used in rheumatology practices and complement inflammatory rheumatic disease treatment guidelines to incorporate cost-effectiveness in b/tsDMARD treatment.

Prognostication of progressive pulmonary fibrosis in connective tissue disease-associated interstitial lung diseases: A cohort study.

Background: Connective tissue diseases-associated interstitial lung disease (CTD-ILD) is a heterogeneous condition that impairs quality of life and is associated with premature death. Progressive pulmonary fibrosis (PPF) has been identified as an important risk factor for poor prognosis. However, different criteria for PPF are used in clinical studies, which may complicate comparison between trials and translation of study findings into clinical practice. Methods: This is a retrospective single center study in patients with CTD-ILD. The prognostic relevance of PPF definitions, including INBUILD, ATS/ERS/JRS/ALAT 2022, and simplified progressive fibrosing (simplified PF) criteria, were examined in this cohort and validated in the other reported Dutch CTD-ILD cohort. Results: A total of 230 patients with CTD-ILD were included and the median follow-up period was six (3-9) years. Mortality risk was independently associated with age (adjusted HR 1.07, p < 0.001), smoking history (adjusted HR 1.90, p = 0.045), extent of fibrosis on high-resolution computed tomography (HRCT) at baseline (adjusted HR 1.05, p = 0.018) and baseline DLCO (adjusted HR 0.97, p = 0.013). Patients with regular pulmonary function tests in the first 2 years (adjusted HR 0.42, p = 0.002) had a better survival. The prognostic relevance for survival was similar between the three PPF criteria in the two cohorts. Conclusion: Higher age, smoking, increased extent of fibrosis and low baseline DLCO were associated with poor prognosis, while regular pulmonary function evaluation was associated with better survival. The INBUILD, ATS/ERS/JRS/ALAT 2022, and simplified PF criteria revealed similar prognostication.

Healthcare Costs and Health-Related Quality of Life in Older Multimorbid Patients After Hospitalization.

Objectives: We identified factors associated with healthcare costs and health-related quality of life (HRQoL) of multimorbid older adults with polypharmacy. Methods: Using data from the OPERAM (OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid older people) trial, we described the magnitude and composition of healthcare costs, and time trends of HRQoL, during 1-year after an acute-care hospitalization. We performed a cluster analysis to identify groups with different cost and HRQoL trends. Using multilevel models, we also identified factors associated with costs and HRQoL. Results: Two months after hospitalization monthly mean costs peaked (CHF 7'124) and HRQoL was highest (0.67). They both decreased thereafter. Age, falls, and comorbidities were associated with higher 1-year costs. Being female and housebound were negatively associated with HRQoL, while moderate alcohol consumption had a positive association. Being independent in daily activities was associated with lower costs and higher HRQoL. Conclusion: Although only some identified potential influences on costs and HRQoL are modifiable, our observations support the importance of prevention before health deterioration in older people with multimorbid illness and associated polypharmacy.

Exploring the differences between radiographic joint space width and MRI cartilage thickness changes using data from the IMI-APPROACH cohort.

OBJECTIVE: Longitudinal weight-bearing radiographic joint space width (JSW) and non-weight-bearing MRI-based cartilage thickness changes often show weak correlations. The current objective was to investigate these correlations, and to explore the influence of different factors that could contribute to longitudinal differences between the two methods. METHODS: The current study included 178 participants with medial osteoarthritis (OA) out of the 297 knee OA participants enrolled in the IMI-APPROACH cohort. Changes over 2 years in medial JSW (ΔJSWmed), minimum JSW (ΔJSWmin), and medial femorotibial cartilage thickness (ΔMFTC) were assessed using linear regression, using measurements from radiographs and MRI acquired at baseline, 6 months, and 1 and 2 years. Pearson R correlations were calculated. The influence of cartilage quality (T2 mapping), meniscal extrusion (MOAKS scoring), potential pain-induced unloading (difference in knee-specific pain scores), and increased loading (BMI) on the correlations was analyzed by dividing participants in groups based on each factor separately, and comparing correlations (slope and strength) between groups using linear regression models. RESULT: Correlations between ΔMFTC and ΔJSWmed and ΔJSWmin were statistically significant (p < 0.004) but weak (R < 0.35). Correlations were significantly different between groups based on cartilage quality and on meniscal extrusion: only patients with the lowest T2 values and with meniscal extrusion showed significant moderate correlations. Pain-induced unloading or BMI-induced loading did not influence correlations. CONCLUSIONS: While the amount of loading does not seem to make a difference, weight-bearing radiographic JSW changes are a better reflection of non-weight-bearing MRI cartilage thickness changes in knees with higher quality cartilage and with meniscal extrusion.

Immunosuppressive Therapies in Ear, Nose, and Throat Involvement in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: Results From a Multicenter Retrospective Cohort Study.

OBJECTIVE: The aim of this study was to evaluate the response of ear, nose, and throat (ENT) symptoms to different immunosuppressive therapies in patients with antineutrophil cytoplasmic antibody-associated vasculitis (AAV). METHODS: In this cohort study, patients with AAV treated between January 2010 and April 2020 at 2 Dutch hospitals were included. Clinical, histological, and laboratory data were collected retrospectively. ENT involvement was defined as follows: (1) ≥ 1 ENT symptom according to the Birmingham Vasculitis Activity Score (version 3; BVAS3), and/or (2) presence of saddle nose deformity. Associations between therapy and ENT activity were assessed using logistic regression analysis. RESULTS: A total of 320 patients with AAV were included, of whom 209 (65.3%) had ENT involvement at some point throughout the disease course. In these 209 patients, median age at disease onset was 52.0 years (IQR 40.0-62.0) and 45.5% were male. Median BVAS3 was 12.0 (IQR 6.0-18.0) at diagnosis. Despite immunosuppressive therapy, 50% (n = 77) of the patients had ENT symptoms at relapse and 29.1% (n = 59) had ENT activity at their last visit. No statistically significant difference in ENT activity at last visit was observed between patients treated with oral or intravenous cyclophosphamide (CYC, n = 137) compared to rituximab (RTX, n = 55; adjusted odds ratio 0.59, 95% CI 0.33-1.06; P = 0.08). Lower age at disease onset and female sex were independently associated with ENT activity at last follow-up. CONCLUSION: In this cohort, CYC and RTX therapy had similar therapeutic effects on ENT symptoms in AAV. Persistent ENT activity is a common feature despite immunosuppressive therapy.

A meta-analysis on the role older adults with cancer favour in treatment decision making.

INTRODUCTION: In the complex setting of oncological treatment decision making, balancing professional guidance while respecting patient involvement can be a challenge. We set out to assess the role adults with cancer favour in treatment decision making (TDM), including differences across age groups and change over time. MATERIALS AND METHODS: A systematic search was performed in MEDLINE and Embase, for studies on role preference of (older) adults with cancer in oncological treatment decision making. A meta-analysis was conducted based on Control Preference Scale (CPS) data, a questionnaire on patient role preference in TDM. RESULTS: This meta-analysis includes 33 studies reporting CPS data comprising 17,197 adults with cancer. Mean age was 60.6 years old for studies that specified age (24 studies, 6155 patients). During the last decade, patients' role preference shifted towards significantly more active involvement in TDM (p = 0.006). No age-dependent subgroup differences have been identified; both younger and older adults, defined as, respectively, below and above 65 years old, favour active involvement in treatment decision making. DISCUSSION: Over time, adults with cancer have shifted towards more active role preference in treatment decision making. In current cancer care, a large majority prefers taking an active role, irrespective of age.