Necrotizing enterocolitis (NEC) is a severe intestinal disease of the newborn infants, associated with high morbidity and mortality. It has been reported that Bifidobacterium could protect the intestinal barrier function and reduce the risk of NEC. This study aimed to evaluate the probiotic potential of Bifidobacterium strains isolated from the chicken intestines and its effect on necrotizing enterocolitis in newborn SD rats. Out of 32 isolates, B. breve AHC3 not only exhibited excellent probiotic potential, including tolerance to artificial simulated gastric conditions, adhesion to HT-29 cells, antioxidant capacity and antibacterial activity, but also possessed reliable safety. Additionally, NEC model was established to further investigate the effect of B. breve AHC3 on necrotizing enterocolitis in newborn SD rats. It was illustrated that administration of B. breve AHC3 significantly not only reduced the incidence of NEC (from 81.25% to 34.38%) (P< 0.05), but also alleviated the severity of ileal injury (P< 0.05). Compared with NEC model, B. breve AHC3 could significantly decrease the level of proinflammatory factor TNF-α (P< 0.05) and increase the level of antiinflammatory factor IL-10 (P< 0.05) in the ileum of NEC rats. Through the intervention of B. breve AHC3, the gray value of inducible nitric oxide synthase (iNOS) in intestinal tissue of NEC rats was significantly reduced (P< 0.05). It was indicated that B. breve AHC3 exhibited prominent probiotic potential and reliable safety. In the neonatal SD rat model of NEC, B. breve AHC3 had an available protective effect on the intestinal injury of NEC, which might be related to reducing the inflammatory reaction in the ileum and inhibiting the expression of iNOS in intestinal tissue cells. B. breve AHC3 could be used as a potential treatment for human NEC.
Respiratory disease is a common cause for primary care consultations, and increasingly, patients with complex and 'high-risk' lung disease are managed in the community. Variation in the quality of community management of 'high-risk' patients may lead to sub-optimal outcomes for some. The ASSIST study (REC: 16/5C/0629) has implemented a complex intervention aimed at identifying and optimising the management of asthma and/or COPD patients in primary care, in 'at risk' patients.
Method
Patients with documented asthma and/or COPD were identified through 'Read code' searches of GP practice records. A DOSE score ≥3 defined 'at risk' COPD patients, whilst 'at risk' asthma patients were defined using a search algorithm identifying factors associated with poor control (including previous exacerbations and high bronchodilator requirements). The DOSE and asthma algorithms were run in 12 and 8 GP practices respectively. All eligible patients were invited to attend their GP practice for a specialist respiratory review.
Results
A total of 464 patients were invited, 66 responded but only 35 were enrolled onto the study due to exclusions and drop-outs. 54% were male with a mean age of 67.23 (SD: 13.07). 16 (46%) patients had asthma, 15 (43%) had COPD, 4 (11%) had asthma/COPD overlap (ACO). Mean pack year was 40.96 (SD: 30.62), 4 patients (11%) were current-smokers, whilst 7 (20%) were never-smokers. Median FEV1 was 1.43 litres (IQR 0.97–2.17) and FEV1% predicted was 61% (IQR: 41%–109%). The primary diagnosis was changed in 12 (34%) patients. Changes to inhaled medications were recommended in 18 (51%) cases (including change of device/s, and/or addition of spacers), further tests were requested in 17 (49%) cases and onward referral for specialist review was advised in 19 (54%) cases.
Conclusions
It is possible to identify high-risk patients from electronic GP record searches, although only a minority will attend, when invited, for subsequent review. Actions to improve outcomes, including diagnosis and treatment changes and onward referral, resulted for most patients. 12 month follow up data will evaluate patient reported outcomes, health care resource usage and overall cost effectiveness of the intervention.
Background: DISCOVER 1 and 2 are phase-3 trials of guselkumab (GUS, a monoclonal antibody that specifically binds the p19-subunit of IL-23) in patients with psoriatic arthritis (PsA). In both trials, treatment with GUS led to significantly more improvement than placebo (PBO) in the primary endpoint (ACR20) as well as in other measures of arthritis and psoriasis at week (W) 24. 1,2 Objectives: To evaluate the effect of GUS on fatigue in DISC 1 & 2 using the patient reported outcome (PRO) FACIT-Fatigue, which has demonstrated content validity and strong psychometric properties in clinical trials. 3 Methods: DISC 1 & 2 enrolled patients with active PsA, despite nonbiologic DMARDS and/or NSAIDS, who were mostly biologic naïve except for ~30% of patients in DISC 1 who had received 1-2 TNFi. Patients were randomized (1:1:1) in a blinded fashion to subcutaneous GUS 100 mg at W0 and W4 then every (q) 8W, to GUS 100 mg q4W, or to matching PBO. Concomitant treatment with select non-biologic DMARDS, oral corticosteroids, and NSAIDs was allowed. The FACIT-Fatigue is a 13-item PRO instrument assessing fatigue and its impact on daily activities and function over the past seven days, with a total score ranging from 0 to 52, higher score denoting less fatigue. A change of ≥4 points is identified as clinically meaningful. 3 Change from baseline in FACIT-Fatigue was analyzed using MMRM (Figure). Independence of treatment effect on FACIT-Fatigue from effect on ACR20 was assessed using Mediation Analysis 4 (Table) to estimate the natural direct effect (NDE) and natural indirect effect (NIE) mediated by ACR20 response. Results: At baseline in DISC 1 & 2, the mean FACIT-fatigue scores (SD) were 30.4 (10.4) and 29.7 (9.7), respectively, indicating moderate to severe fatigue. In both DISCOVER 1 & 2 trials, treatment with GUS led to improvements in FACIT-Fatigue scores compared with PBO as early as W8 (Figure). 54%-63% of GUS patients compared with 35%-46% of PBO patients achieved clinically meaningful improvement (≥4 points) in FACIT-Fatigue (P≤0.003). Mediation analysis revealed that the independent treatment effects on fatigue after adjustment for ACR20 response (Natural Direct Effect [NDE], Table) were 12-36% in the q8W GUS dosing group and 69% -70% in the q4W GUS group. Conclusion: In 2 phase-3 trials, treatment with GUS of patients with active PsA led to significant improvements compared to PBO in fatigue, including substantial effects on FACIT-Fatigue that were independent of the effects on ACR 20, especially for the q4W dosing group. References: [1]Deodhar et al. ACR 2019. Abstract #807. Arthr Rheumatol. 2019;71 S10: 1386 [2]Mease et al. ACR 2019. Abstract # L13. Arthr Rheumatol. 2019;71 S10:5247 [3]Cella et al. Journal of Patient-Reported Outcomes. 2019;3:30 [4]Valeri et al. Psychologic Meth. 2013;18:137 Table. Mediation Analysis of the Effect of ACR 20 Response on Change from Baseline in FACIT-Fatigue Score at Week 24 Effect GUS 100 mg q8W vs. PBO Estimate (95% CI) GUS 100 mg q4W vs. PBO Estimate (95% CI) DISCOVER 1 NDE 0.36 (-1.7, 2.4) 2.60 (0.6, 4.5)* NIE 2.75 (1.4, 4.3)* 1.20 (0.3, 2.3)* Total Effect 3.12 (1.0, 5.2)* 3.79 (1.9, 5.4)* Proportion Independent 11.7% 68.5% Proportion Mediated 88.3% 31.5% DISCOVER 2 NDE 1.44 (-0.1, 3.0) 2.49 (1.0, 4.1)* NIE 2.53 (1.6, 3.6)* 1.09 (0.4, 1.9)* Total Effect 3.97 (2.4, 5.5)* 3.58 (2.1, 5.0)* Proportion Independent 36.3% 69.7% Proportion Mediated 63.7% 30.3% *P vs placebo<0.02 NDE=Natural Direct Effect (effect on FACIT-F beyond effect on ACR20), NIE=Natural Indirect Effect (effect on FACIT-F mediated by ACR20) Mediation analysis 4 used linear and logistics regression models with Bootstrapping method Acknowledgments: None Disclosure of Interests: Philip Helliwell: None declared, Proton Rahman Grant/research support from: Janssen and Novartis, Consultant of: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer., Speakers bureau: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, Atul Deodhar Grant/research support from: AbbVie, Eli Lilly, GSK, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Bei Zhou Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Xiwu Lin Employee of: Janssen Research & Development, LLC, Chenglong Han Employee of: Janssen Research & Development, LLC, Philip J Mease Grant/research support from: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – grant/research support, Consultant of: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – consultant, Speakers bureau: Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB – speakers bureau
Background: DISCOVER 1 & 2 are phase-3 trials of guselkumab (GUS, an IL-23 inhibitor) in patients with psoriatic arthritis (PsA). In both trials, treatment with GUS led to significantly more improvement than placebo (PBO) in the primary endpoint (American College of Rheumatology 20% improvement criteria [ACR20]) and in other measures of arthritis and psoriasis at week (w) 24, 1,2 and these improvements were maintained through 1 year of active treatment. 3,4 Objectives: To evaluate the effect of GUS on fatigue in DISCOVER 1 & 2 using the patient reported outcome (PRO) FACIT-Fatigue, which has demonstrated content validity and strong psychometric properties in clinical trials. 5 Methods: DISCOVER 1 & 2 enrolled patients with active PsA, despite non-biologic DMARDS or NSAIDS, who were biologic naïve except ~30% of patients in DISCOVER 1 who had received 1-2 TNFi. Patients were randomized (1:1:1) in a blinded fashion to subcutaneous GUS 100 mg at w0, w4, then every (q) 8w; GUS 100 mg q4w; or matching PBO. At w24, PBO patients were switched to GUS q4w. Concomitant treatment with select non-biologic DMARDS, oral corticosteroids, and NSAIDs was allowed. The FACIT-Fatigue is a 13-item PRO assessing fatigue and its impact on daily activities and function over the past 7 days, total score ranging from 0 to 52, higher score denoting less fatigue. A change of ≥4 points is considered clinically meaningful. 5 The change from baseline in FACIT-Fatigue presented below is based on observed data. Mediation analysis 6 was applied to the treatment effect of GUS on FACIT-Fatigue to estimate the natural direct and indirect effects, after adjusting for ACR20 response (Table 1). Results: At baseline in DISCOVER 1 & 2, the mean FACIT-fatigue scores (SD) were 30.4 (10.4) and 29.7 (9.7), respectively, indicating that patients with PsA experienced fatigue worse than the general population. At w24 in the DISCOVER trials, treatment with GUS led to significant improvements in FACIT-Fatigue scores compared with PBO, as early as w16 in DISCOVER 1 and w8 in DISCOVER 2. Improvements in fatigue were similar between GUS q4w and q8w doses, and the improvements at w24 were maintained through w52 (Figure 1). After a switch to GUS q4w at w24, PBO patients achieved FACIT-Fatigue scores that were comparable to those of GUS patients (Figure 1). 54%-63% of GUS patients compared with 35%-46% of PBO patients achieved clinically meaningful improvement (≥4 points) in FACIT-Fatigue at w24 (P≤0.003). At w52, 61%-70% of both GUS and PBO to GUS groups reached this improvement. As evaluated by mediation analysis at w24, GUS had independent positive treatment effects on fatigue (12%-36% in the q8w GUS dosing group and 69%-70% in the q4w GUS group) after adjustment for ACR20 response (Table 1). Conclusion: In 2 phase-3 trials, GUS treatment improved fatigue when compared to PBO during PBO-controlled periods and maintained improvements through 1 year of active treatment. Substantial proportions of those effects were independent of the effects on ACR20, especially for the q4W dosing group. References: [1]Deodhar et al. Lancet 2020;395:1115 [2]Mease et al. Lancet 2020;395:1126 [3]Ritchlin et al. EULAR20 . SAT0397 [4]McInnes et al. EULAR20 . SAT0402 [5]Cella et al. J Patient-Reported Outcomes 2019;3:30 [6]Valeri et al. Psychologic Meth 2013;18:137 Table 1. Mediation Analysis: Guselkumab Has Direct Effects and Indirect Effects (Mediated through ACR20) on Fatigue in PsA Effect GUS 100 mg q8w vs. PBO (95% CI ) GUS 100 mg q4w vs. PBO (95% CI ) DISCOVER-1 Total Effect 3.1 (1.0, 5.2) (p<0.02) 3.8 (1.9, 5.4) (p<0.02) % Direct Effect 11.7% 68.5% % Indirect effect mediated by ACR20 88.3% 31.5% DISCOVER-2 Total Effect 4.0 (2.4, 5.5) (p<0.02) 3.6 (2.1, 5.0) (p<0.02) % Direct Effect 36.3% 69.7% % Indirect effect mediated by ACR20 63.7% 30.3% ACR, American College of Rheumatology; CI, confidence interval; GUS, guselkumab; PBO, placebo; PsA, psoriatic arthritis; q4W, every 4 weeks; q8W, every 8 weeks Disclosure of Interests: Proton Rahman Speakers bureau: Received speakers fees from Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, Grant/research support from: Received grant/research support from Janssen and Novartis, consultation fees from Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer, Philip Helliwell Consultant of: Consultation fees paid to charity (AbbVie, Amgen, Pfizer, UCB) or himself (Celgene, Galapagos), Grant/research support from: Received grants/research support paid to charity (AbbVie, Janssen, Novartis), Atul Deodhar Speakers bureau: Received speakers fees from AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Consultant of: Received consultation fees from AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Grant/research support from: Received grant/research support from AbbVie, Eli Lilly, GSK, Novartis, Pfizer, UCB, Alexa Kollmeier Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Bei Zhou Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Xiwu Lin Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Chenglong Han Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Philip J Mease Speakers bureau: Received speakers fees from Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB, Consultant of: Received consultation fees from Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB, Grant/research support from: Received grant/research support from Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB.
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