83 research outputs found

    Bayesian penalised likelihood reconstruction (Q.Clear) of 18F-fluciclovine PET for imaging of recurrent prostate cancer: semi-quantitative and clinical evaluation

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    Objective: 18F-Fluciclovine (FACBC) is an amino acid PET radiotracer approved for recurrent prostate cancer imaging. We investigate the use of Bayesian penalised likelihood (BPL) reconstruction for 18F-fluciclovine PET. Methods: 15 18F-fluciclovine scans were reconstructed using ordered subset expectation maximisation (OSEM), OSEM + point spread function (PSF) modelling and BPL using β-values 100–600. Lesion maximum standardised uptake value (SUVmax), organ SUVmean and standard deviation were measured. Deidentified reconstructions (OSEM, PSF, BPL using β200–600) from 10 cases were visually analysed by two readers who indicated their most and least preferred reconstructions, and scored overall image quality, noise level, background marrow image quality and lesion conspicuity. Results: Comparing BPL to OSEM, there were significant increments in lesion SUVmax and signal-to-background up to β400, with highest gain in β100 reconstructions (mean ΔSUVmax 3.9, p < 0.0001). Organ noise levels increased on PSF, β100 and β200 reconstructions. Across BPL reconstructions, there was incremental reduction in organ noise with increasing β, statistically significant beyond β300–500 (organ-dependent). Comparing with OSEM and PSF, lesion signal-to-noise was significantly increased in BPL reconstructions where β ≥ 300 and ≥ 200 respectively. On visual analysis, β 300 had the first and second highest scores for image quality, β500 and β600 equal highest scores for marrow image quality and least noise, PSF and β 200 had first and second highest scores for lesion conspicuity. For overall preference, one reader preferred β 300 in 9/10 cases and the other preferred β 200 in all cases. Conclusion: BPL reconstruction of 18F-fluciclovine PET images improves signal-to-noise ratio, affirmed by overall reader preferences. On balance, β300 is suggested for 18F-fluciclovine whole body PET image reconstruction using BPL. Advances in knowledge: The optimum β is different to that previously published for 18F-fluorodeoxyglucose, and has practical implications for a relatively new tracer in an environment with modern reconstruction technologies

    Lung cancer prediction by Deep Learning to identify benign lung nodules

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    INTRODUCTION: Deep Learning has been proposed as promising tool to classify malignant nodules. Our aim was to retrospectively validate our Lung Cancer Prediction Convolutional Neural Network (LCP-CNN), which was trained on US screening data, on an independent dataset of indeterminate nodules in an European multicentre trial, to rule out benign nodules maintaining a high lung cancer sensitivity. METHODS: The LCP-CNN has been trained to generate a malignancy score for each nodule using CT data from the U.S. National Lung Screening Trial (NLST), and validated on CT scans containing 2106 nodules (205 lung cancers) detected in patients from from the Early Lung Cancer Diagnosis Using Artificial Intelligence and Big Data (LUCINDA) study, recruited from three tertiary referral centers in the UK, Germany and Netherlands. We pre-defined a benign nodule rule-out test, to identify benign nodules whilst maintaining a high sensitivity, by calculating thresholds on the malignancy score that achieve at least 99 % sensitivity on the NLST data. Overall performance per validation site was evaluated using Area-Under-the-ROC-Curve analysis (AUC). RESULTS: The overall AUC across the European centers was 94.5 % (95 %CI 92.6-96.1). With a high sensitivity of 99.0 %, malignancy could be ruled out in 22.1 % of the nodules, enabling 18.5 % of the patients to avoid follow-up scans. The two false-negative results both represented small typical carcinoids. CONCLUSION: The LCP-CNN, trained on participants with lung nodules from the US NLST dataset, showed excellent performance on identification of benign lung nodules in a multi-center external dataset, ruling out malignancy with high accuracy in about one fifth of the patients with 5-15 mm nodules

    Association of Serum Ustekinumab Levels With Clinical Response in Psoriasis

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    Importance: High-cost biologic therapies have transformed the management of immune-mediated inflammatory diseases. To optimize outcomes and reduce costs, dose adjustment informed by measurement of circulating drug levels has been shown to be effective in various settings. However, limited evidence exists for this approach with the interleukin 12 and interleukin 23 inhibitor ustekinumab. Objective: To evaluate clinical utility of therapeutic drug monitoring for ustekinumab in patients with psoriasis. Design, Setting, and Participants: A prospective observational cohort of 491 adults with psoriasis was recruited to the multicenter Biomarkers of Systemic Treatment Outcomes in Psoriasis study within the British Association of Dermatologists Biologic and Immunomodulators Register from June 2009 to December 2017; samples from some patients were taken between 2009 and 2011 as part of a pilot study with the same inclusion criteria. Exposure: Serum ustekinumab level measured at any point during the dosing cycle using an enzyme-linked immunosorbent assay. Main Outcomes and Measures@ Disease activity measured using the Psoriasis Area and Severity Index (PASI) score. Treatment response outcomes were PASI75 (75% reduction in PASI score from baseline [primary outcome]), PASI90 (90% reduction of PASI score from baseline), and absolute PASI score of 1.5 or less. Results: A total of 491 patients (171 women and 320 men; mean [SD] age, 45.7 [12.8] years) had 1 or more serum samples (total, 853 samples obtained 0-56 weeks from start of treatment) and 1 or more PASI scores within the first year of treatment. Antidrug antibodies were detected in only 17 of 490 patients (3.5%). Early measured drug levels (1-12 weeks after starting treatment) were associated with PASI75 response 6 months after starting treatment (odds ratio, 1.38; 95% CI, 1.11-1.71) when adjusted for baseline PASI score, age, and ustekinumab dose. However, this finding was not consistent across the other PASI outcomes (PASI90 and PASI score of ≤1.5). Conclusions and Relevance: This real-world study provides evidence that measurement of early serum ustekinumab levels could be useful to direct the treatment strategy for psoriasis. Adequate drug exposure early in the treatment cycle may be particularly important in determining clinical outcome

    Defining the therapeutic range for adalimumab and predicting response in psoriasis: a multicenter prospective observational cohort study

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    Biologics have transformed management of inflammatory diseases. To optimize outcomes and reduce costs, dose adjustment informed by circulating drug levels has been proposed. We aimed to determine the real-world clinical utility of therapeutic drug monitoring in psoriasis. Within a multicenter (n=60) prospective observational cohort, 544 psoriasis patients were included who were on adalimumab monotherapy, with at least one serum sample and PASI (Psoriasis Area and Severity Index) score available within the first year. We present models giving individualized probabilities of response for any given drug level: a minimally effective drug level of 3.2 μg/ml discriminates responders (PASI75: 75% improvement in baseline PASI) from non-responders and gives an estimated PASI75 probability of 65% (95% CI 60-71%). At 7ug/ml, PASI75 probability is 81% (95% CI 76-86%); beyond 7ug/ml, the drug level/response curve plateaus. Crucially, drug levels are predictive of response 6 months later, whether sampled early or at steady state. We confirm serum drug level to be the most important factor determining treatment response, highlighting the need to take drug levels into account when searching for biomarkers of response. This real-world study with pragmatic drug level sampling provides evidence to support the proactive measurement of adalimumab levels in psoriasis to direct treatment strategy, and is relevant to other inflammatory diseases

    Risk mitigating behaviours in people with inflammatory skin and joint disease during the COVID-19 pandemic differ by treatment type:a cross-sectional patient survey

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    BACKGROUND: Registry data suggest that people with immune-mediated inflammatory diseases (IMIDs) receiving targeted systemic therapies have fewer adverse coronavirus disease 2019 (COVID-19) outcomes compared with patients receiving no systemic treatments. OBJECTIVES: We used international patient survey data to explore the hypothesis that greater risk-mitigating behaviour in those receiving targeted therapies may account, at least in part, for this observation. METHODS: Online surveys were completed by individuals with psoriasis (globally) or rheumatic and musculoskeletal diseases (RMDs) (UK only) between 4 May and 7 September 2020. We used multiple logistic regression to assess the association between treatment type and risk-mitigating behaviour, adjusting for clinical and demographic characteristics. We characterized international variation in a mixed-effects model. RESULTS: Of 3720 participants (2869 psoriasis, 851 RMDs) from 74 countries, 2262 (60·8%) reported the most stringent risk-mitigating behaviour (classified here under the umbrella term 'shielding'). A greater proportion of those receiving targeted therapies (biologics and Janus Kinase inhibitors) reported shielding compared with those receiving no systemic therapy [adjusted odds ratio (OR) 1·63, 95% confidence interval (CI) 1·35-1·97]. The association between targeted therapy and shielding was preserved when standard systemic therapy was used as the reference group (OR 1·39, 95% CI 1·23-1·56). Shielding was associated with established risk factors for severe COVID-19 [male sex (OR 1·14, 95% CI 1·05-1·24), obesity (OR 1·37, 95% CI 1·23-1·54), comorbidity burden (OR 1·43, 95% CI 1·15-1·78)], a primary indication of RMDs (OR 1·37, 95% CI 1·27-1·48) and a positive anxiety or depression screen (OR 1·57, 95% CI 1·36-1·80). Modest differences in the proportion shielding were observed across nations. CONCLUSIONS: Greater risk-mitigating behaviour among people with IMIDs receiving targeted therapies may contribute to the reported lower risk of adverse COVID-19 outcomes. The behaviour variation across treatment groups, IMIDs and nations reinforces the need for clear evidence-based patient communication on risk-mitigation strategies and may help inform updated public health guidelines as the pandemic continues

    Efficacy of the Enquiring About Tolerance (EAT) study among infants at high risk of developing food allergy.

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    BACKGROUND: The Enquiring About Tolerance (EAT) study was a randomized trial of the early introduction of allergenic solids into the infant diet from 3 months of age. The intervention effect did not reach statistical significance in the intention-to-treat analysis of the primary outcome. OBJECTIVE: We sought to determine whether infants at high risk of developing a food allergy benefited from early introduction. METHODS: A secondary intention-to-treat analysis was performed of 3 groups: nonwhite infants; infants with visible eczema at enrollment, with severity determined by SCORAD; and infants with enrollment food sensitization (specific IgE ≥0.1 kU/L). RESULTS: Among infants with sensitization to 1 or more foods at enrollment (≥0.1 kU/L), early introduction group (EIG) infants developed significantly less food allergy to 1 or more foods than standard introduction group (SIG) infants (SIG, 34.2%; EIG, 19.2%; P = .03), and among infants with sensitization to egg at enrollment, EIG infants developed less egg allergy (SIG, 48.6%; EIG, 20.0%; P = .01). Similarly, among infants with moderate SCORAD (15-<40) at enrollment, EIG infants developed significantly less food allergy to 1 or more foods (SIG, 46.7%; EIG, 22.6%; P = .048) and less egg allergy (SIG, 43.3%; EIG, 16.1%; P = .02). CONCLUSION: Early introduction was effective in preventing the development of food allergy in specific groups of infants at high risk of developing food allergy: those sensitized to egg or to any food at enrollment and those with eczema of increasing severity at enrollment. This efficacy occurred despite low adherence to the early introduction regimen. This has significant implications for the new national infant feeding recommendations that are emerging around the world

    Nonadherence to systemic immune-modifying therapy in people with psoriasis during the COVID-19 pandemic : Findings from a global cross-sectional survey

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    Nonadherence to immune-modifying therapy is a complex behaviour which, before the COVID-19 pandemic, was shown to be associated with mental health disorders in people with immune-mediated diseases. The COVID-19 pandemic has led to a rise in the global prevalence of anxiety and depression, and limited data exist on the association between mental health and nonadherence to immune-modifying therapy during the pandemic. To assess the extent of and reasons underlying nonadherence to systemic immune-modifying therapy during the COVID-19 pandemic in individuals with psoriasis, and the association between mental health and nonadherence. Online self-report surveys (PsoProtectMe), including validated screens for anxiety and depression, were completed globally during the first year of the pandemic. We assessed the association between anxiety or depression and nonadherence to systemic immune-modifying therapy using binomial logistic regression, adjusting for potential cofounders (age, sex, ethnicity, comorbidity) and country of residence. Of 3980 participants from 77 countries, 1611 (40.5%) were prescribed a systemic immune-modifying therapy. Of these, 408 (25.3%) reported nonadherence during the pandemic, most commonly due to concerns about their immunity. In the unadjusted model, a positive anxiety screen was associated with nonadherence to systemic immune-modifying therapy [odds ratio (OR) 1.37, 95% confidence interval (CI) 1.07-1.76]. Specifically, anxiety was associated with nonadherence to targeted therapy (OR 1.41, 95% CI 1.01-1.96) but not standard systemic therapy (OR 1.16, 95% CI 0.81-1.67). In the adjusted model, although the directions of the effects remained, anxiety was not significantly associated with nonadherence to overall systemic (OR 1.20, 95% CI 0.92-1.56) or targeted (OR 1.33, 95% CI 0.94-1.89) immune-modifying therapy. A positive depression screen was not strongly associated with nonadherence to systemic immune-modifying therapy in the unadjusted (OR 1.22, 95% CI 0.94-1.57) or adjusted models (OR 1.14, 95% CI 0.87-1.49). These data indicate substantial nonadherence to immune-modifying therapy in people with psoriasis during the pandemic, with attenuation of the association with mental health after adjusting for confounders. Future research in larger populations should further explore pandemic-specific drivers of treatment nonadherence. Clear communication of the reassuring findings from population-based research regarding immune-modifying therapy-associated adverse COVID-19 risks to people with psoriasis is essential, to optimize adherence and disease outcomes
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