Examining the clinical use of hemochromatosis genetic testing

BACKGROUND: Hereditary hemochromatosis leads to an increased lifetime risk for end-organ damage due to excess iron deposition. Guidelines recommend that genetic testing be performed in patients with clinical suspicion of iron overload accompanied by elevated serum ferritin and transferrin saturation levels. OBJECTIVE: To evaluate guideline adherence and the clinical and economic impact of HFE genetic testing. METHODS: The electronic charts of patients submitted for HFE testing in 2012 were reviewed for genetic testing results, biochemical markers of iron overload and clinical history of phlebotomy. RESULTS: A total of 664 samples were sent for testing, with clinical, biochemical and phlebotomy data available for 160 patients. A positive C282Y homozygote or C282Y/H63D compound heterozygote test result was observed in 18% of patients. Patients with an at-risk HFE genotype had significantly higher iron saturation, serum iron and hemoglobin (P\u3c0.001), without higher ferritin or liver enzyme levels. Fifty percent of patients referred for testing did not have biochemical evidence of iron overload (transferrin saturation \u3e45% and ferritin level \u3e300μg/L). Patients were four times more likely to undergo phlebotomy if they were gene test positive (RR 4.29 [95% CI 2.35 to 7.83]; P\u3c0.00001). DISCUSSION: One-half of patients referred for testing did not exhibit biochemical evidence of iron overload. Many patients with biochemical evidence of iron overload, but with negative genetic test results, did not undergo phlebotomy. A requisition to determine clinical indication for testing may reduce the use of the HFE genetic test. Finally, improvement of current genetic test characteristics would improve rationale for the test. CONCLUSION: A significant proportion of hemochromatosis genetic testing does not adhere to current guidelines and would not alter patient management

Participant characteristics and exclusion from trials: a meta-analysis of individual participant-level data from phase 3/4 industry-funded trials in chronic medical conditions

Objectives Trials often do not represent their target populations, threatening external validity. The aim was to assess whether age, sex, comorbidity count and/or race/ethnicity are associated with likelihood of screen failure (i.e., failure to be enrolled in the trial for any reason) among potential trial participants.Design Bayesian meta-analysis of individual participant-level data (IPD).SettingIndustry-funded phase 3/4 trials in chronic medical conditions. Participants were identified as “enrolled” or “screen failure” using trial IPD.Participants Data were available for 52 trials involving 72,178 screened individuals of whom 24,733 (34%) failed screening.Main outcome measures For each trial, logistic regression models were constructed to assess likelihood of screen failure in people who had been invited to screening, regressed on age (per 10-year increment), sex (male versus female), comorbidity count (per one additional comorbidity) and race/ethnicity. Trial-level analyses were combined in Bayesian hierarchical models with pooling across condition.ResultsIn age- and sex-adjusted models across all trials, neither age nor sex was associated with increased odds of screen failure, though weak associations were detected after additionally adjusting for comorbidity (age, per 10-year increment: odds ratio [OR] 1.02; 95% credibility interval [CI] 1.01 to 1.04 and male sex: OR 0.95; 95% CI 0.91 to 1.00). Comorbidity count was weakly associated with screen failure, but in an unexpected direction (OR 0.97 per additional comorbidity, 95% CI 0.94 to 1.00, adjusted for age and sex). Those who self-reported as Black were slightly more likely to fail screening (OR 1.04; 95% CI 0.99 to 1.09); an effect which persisted after adjustment for age, sex and comorbidity count (OR 1.05; 95% CI 0.98 to 1.12). The between-trial heterogeneity was generally low, but there was evidence of heterogeneity by sex across conditions (variation in odds ratios on log-scale of 0.01-0.13).Conclusions Though the conclusions are limited by uncertainty about the completeness or accuracy of data collection among non-randomised participants, we identified mostly weak associations between age, sex, comorbidity count and Black race/ethnicity and increased likelihood of screen failure. Proportionate increases in screening these underserved populations may improve representation in trials. Trial registration Relevant trials in chronic medical conditions were identified according to pre-specified criteria (PROSPERO CRD42018048202) then analysed according to availability of IPD. <br/

Predicting soil carbon loss with warming

Journal ArticleThis is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.ARISING FROM: T. W. Crowther et al. Nature 540, 104–108 (2016); doi:10.1038/nature2015

Correlations between comorbidities in trials and the community: an individual-level participant data meta-analysis

Background: People with comorbidities are under-represented in randomised controlled trials, and it is unknown whether patterns of comorbidity are similar in trials and the community. Methods: Individual-level participant data were obtained for 83 clinical trials (54,688 participants) for 16 index conditions from two trial repositories: Yale University Open Data Access (YODA) and the Centre for Global Clinical Research Data (Vivli). Community data (860,177 individuals) were extracted from the Secure Anonymised Information Linkage (SAIL) databank for the same index conditions. Comorbidities were defined using concomitant medications. For each index condition, we estimated correlations between comorbidities separately in trials and community data. For the six commonest comorbidities we estimated all pairwise correlations using Bayesian multivariate probit models, conditioning on age and sex. Correlation estimates from trials with the same index condition were combined into a single estimate. We then compared the trial and community estimates for each index condition. Results: Despite a higher prevalence of comorbidities in the community than in trials, the correlations between comorbidities were mostly similar in both settings. On comparing correlations between the community and trials, 21% of correlations were stronger in the community, 10% were stronger in the trials and 68% were similar in both. In the community, 5% of correlations were negative, 21% were null, 56% were weakly positive and 18% were strongly positive. Equivalent results for the trials were 11%, 33%, 45% and 10% respectively. Conclusions: Comorbidity correlations are generally similar in both the trials and community, providing some evidence for the reporting of comorbidity-specific findings from clinical trials

Participant characteristics and exclusion from trials: a meta-analysis of individual participant-level data from phase 3/4 industry-funded trials in chronic medical conditions

Objectives: To assess whether age, sex, comorbidity count, and race and ethnic group are associated with the likelihood of trial participants not being enrolled in a trial for any reason (ie, screen failure). Design: Bayesian meta-analysis of individual participant level data. Setting: Industry funded phase 3/4 trials of chronic medical conditions. Participants: Participants were identified using individual participant level data to be in either the enrolled group or screen failure group. Data were available for 52 trials involving 72 178 screened individuals of whom 24 733 (34%) were excluded from the trial at the screening stage. Main outcome measures: For each trial, logistic regression models were constructed to assess likelihood of screen failure in people who had been invited to screening, and were regressed on age (per 10 year increment), sex (male v female), comorbidity count (per one additional comorbidity), and race or ethnic group. Trial level analyses were combined in Bayesian hierarchical models with pooling across condition. Results: In age and sex adjusted models across all trials, neither age nor sex was associated with increased odds of screen failure, although weak associations were detected after additionally adjusting for comorbidity (odds ratio of age, per 10 year increment was 1.02 (95% credibility interval 1.01 to 1.04) and male sex (0.95 (0.91 to 1.00)). Comorbidity count was weakly associated with screen failure, but in an unexpected direction (0.97 per additional comorbidity (0.94 to 1.00), adjusted for age and sex). People who self-reported as black seemed to be slightly more likely to fail screening than people reporting as white (1.04 (0.99 to 1.09)); a weak effect that seemed to persist after adjustment for age, sex, and comorbidity count (1.05 (0.98 to 1.12)). The between-trial heterogeneity was generally low, evidence of heterogeneity by sex was noted across conditions (variation in odds ratios on log scale of 0.01-0.13). Conclusions: Although the conclusions are limited by uncertainty about the completeness or accuracy of data collection among participants who were not randomised, we identified mostly weak associations with an increased likelihood of screen failure for age, sex, comorbidity count, and black race or ethnic group. Proportionate increases in screening these underserved populations may improve representation in trials. Trial registration number: PROSPERO CRD42018048202

Participant characteristics and exclusion from trials: a meta-analysis of individual participant-level data from phase 3/4 industry-funded trials in chronic medical conditions

Objectives: To assess whether age, sex, comorbidity count, and race and ethnic group are associated with the likelihood of trial participants not being enrolled in a trial for any reason (ie, screen failure). Design: Bayesian meta-analysis of individual participant level data. Setting: Industry funded phase 3/4 trials of chronic medical conditions. Participants: Participants were identified using individual participant level data to be in either the enrolled group or screen failure group. Data were available for 52 trials involving 72 178 screened individuals of whom 24 733 (34%) were excluded from the trial at the screening stage. Main outcome measures: For each trial, logistic regression models were constructed to assess likelihood of screen failure in people who had been invited to screening, and were regressed on age (per 10 year increment), sex (male v female), comorbidity count (per one additional comorbidity), and race or ethnic group. Trial level analyses were combined in Bayesian hierarchical models with pooling across condition. Results: In age and sex adjusted models across all trials, neither age nor sex was associated with increased odds of screen failure, although weak associations were detected after additionally adjusting for comorbidity (odds ratio of age, per 10 year increment was 1.02 (95% credibility interval 1.01 to 1.04) and male sex (0.95 (0.91 to 1.00)). Comorbidity count was weakly associated with screen failure, but in an unexpected direction (0.97 per additional comorbidity (0.94 to 1.00), adjusted for age and sex). People who self-reported as black seemed to be slightly more likely to fail screening than people reporting as white (1.04 (0.99 to 1.09)); a weak effect that seemed to persist after adjustment for age, sex, and comorbidity count (1.05 (0.98 to 1.12)). The between-trial heterogeneity was generally low, evidence of heterogeneity by sex was noted across conditions (variation in odds ratios on log scale of 0.01-0.13). Conclusions: Although the conclusions are limited by uncertainty about the completeness or accuracy of data collection among participants who were not randomised, we identified mostly weak associations with an increased likelihood of screen failure for age, sex, comorbidity count, and black race or ethnic group. Proportionate increases in screening these underserved populations may improve representation in trials. Trial registration number: PROSPERO CRD42018048202

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

The international WAO/EAACI guideline for the management of hereditary angioedema – the 2017 revision and update

Abstract Hereditary Angioedema (HAE) is a rare and disabling disease. Early diagnosis and appropriate therapy are essential. This update and revision of the global guideline for HAE provides up-to-date consensus recommendations for the management of HAE. In the development of this update and revision of the guideline, an international expert panel reviewed the existing evidence and developed 20 recommendations that were discussed, finalized and consented during the guideline consensus conference in June 2016 in Vienna. The final version of this update and revision of the guideline incorporates the contributions of a board of expert reviewers and the endorsing societies. The goal of this guideline update and revision is to provide clinicians and their patients with guidance that will assist them in making rational decisions in the management of HAE with deficient C1-inhibitor (type 1) and HAE with dysfunctional C1-inhibitor (type 2). The key clinical questions covered by these recommendations are: 1) How should HAE-1/2 be defined and classified?, 2) How should HAE-1/2 be diagnosed?, 3) Should HAE-1/2 patients receive prophylactic and/or on-demand treatment and what treatment options should be used?, 4) Should HAE-1/2 management be different for special HAE-1/2 patient groups such as pregnant/lactating women or children?, and 5) Should HAE-1/2 management incorporate self-administration of therapies and patient support measures? This article is co-published with permission in Allergy and the World Allergy Organization Journal

The modulating effect of education on semantic interference during healthy aging

Aging has traditionally been related to impairments in name retrieval. These impairments have usually been explained by a phonological transmission deficit hypothesis or by an inhibitory deficit hypothesis. This decline can, however, be modulated by the educational level of the sample. This study analyzed the possible role of these approaches in explaining both object and face naming impairments during aging. Older adults with low and high educational level and young adults with high educational level were asked to repeatedly name objects or famous people using the semantic-blocking paradigm. We compared naming when exemplars were presented in a semantically homogeneous or in a semantically heterogeneous context. Results revealed significantly slower rates of both face and object naming in the homogeneous context (i.e., semantic interference), with a stronger effect for face naming. Interestingly, the group of older adults with a lower educational level showed an increased semantic interference effect during face naming. These findings suggest the joint work of the two mechanisms proposed to explain age-related naming difficulties, i.e., the inhibitory deficit and the transmission deficit hypothesis. Therefore, the stronger vulnerability to semantic interference in the lower educated older adult sample would possibly point to a failure in the inhibitory mechanisms in charge of interference resolution, as proposed by the inhibitory deficit hypothesis. In addition, the fact that this interference effect was mainly restricted to face naming and not to object naming would be consistent with the increased age-related difficulties during proper name retrieval, as suggested by the transmission deficit hypothesis.This research was supported by grants PSI2013-46033-P to A.M., PSI2015-65502-C2-1-P to M.T.B., PCIN-2015-165-C02-01 to D.P., PSI2017-89324-C2-1-P to DP from the Spanish Ministry of Economy and Competitiveness (http://www.mineco.gob.es/)