A randomised controlled trial of an audiovisual patient information intervention in cancer clinical trials

Introduction and background Recruitment to cancer clinical trials needs to be improved, as does patient understanding about clinical trials, to enable patients to make an informed choice about whether or not to take part. The main reason that clinically eligible patients do not take part in clinical trials is because they refuse; poor understanding of the research has been associated with patient refusal. Audiovisual patient information (AVPI) has been shown to improve knowledge/understanding in various areas of practice but there is limited information about its effect in the cancer clinical trial setting, particularly in relation to recruitment rates. Understanding the research is necessary for informed consent, and it was hypothesised that if patient understanding about clinical trials was increased with AVPI, then this could result in a reduction in the number of patients refusing clinical trials, and therefore provide an ethical approach to improving recruitment. This study aimed to test the impact of an audiovisual patient information intervention on recruitment to randomised cancer clinical trials (refusal rates), patient understanding of the information given, and levels of anxiety. Reasons for patients’ decisions about trial participation were also assessed. Method An AVPI intervention was developed that aimed to address the common misconceptions associated with randomisation and clinical equipoise, as well as improve patient understanding generally of randomised cancer trials, and of other core clinical trial informational requirements, such as voluntariness. Patients were randomised to receive either AVPI in addition to the standard trial-specific written information, or the written information alone. A new questionnaire was developed to assess patient understanding (also referred to as knowledge) in the randomised trial setting and, following testing with patients and research nurses, this was shown to be reliable and valid. Patients completed self-report questionnaires to assess their understanding (new knowledge questionnaire) and anxiety (Spielberger State-Trait Anxiety Inventory), at baseline and after they had made their decision about clinical trial entry, when their perceptions of the intervention, as well as factors contributing to their decision were also determined (this tool incorporated Jenkins and Fallowfield’s (2005) questionnaire which assessed reasons for accepting and declining randomised cancer trials). Results A total of 173 patients with breast cancer (65%), colorectal cancer (32%) and lung cancer (3%) were entered into the main study. The median age was 60 (range 37-92 years). There was no difference in clinical trial recruitment rates between the two groups: 72.1% in the AVPI group and 75.9% in the standard information group. The estimated odds ratio for refusal (intervention/no intervention) was 1.19 (95% ci 0.55-2.58, p=0.661). Knowledge scores increased more in the intervention group compared to the standard group (U= 2029, p=0.0072). The change in anxiety score between the arms was also statistically significant (p=0.011) with anxiety improving in the intervention arm more than in the no-intervention arm. The estimated difference in the median anxiety change score between the groups is –4.6 (95% ci –7.0 to –2.0). Clinical trial entry was not influenced by tumour type, stage of cancer, age, educational qualifications or previous research experience, however, there was a modest association with deprivation status (p=0.046) where more affluent patients were the least likely to consent to a trial. Educational qualifications and stage of cancer were independently associated with knowledge: patients who were better educated had higher levels of knowledge about randomised trials, and patients who had limited stage of cancer had higher baseline knowledge than patients with advanced cancer. Acceptability of the intervention was high with 93% of those who watched it finding it useful, and 42% stating that it made them want to take part in the clinical trial. Personal benefit and altruism were key motivating factors for clinical trial participation, with reasons for refusal being less clear. Discussion and conclusions Although the potential for AVPI to increase clinical trial recruitment rates was highlighted in the literature, in this study, AVPI was not shown to have any effect on refusal rates to randomised cancer trials. However, by improving patient understanding prior to decision making, AVPI was shown to be a useful addition to the consent process for randomised cancer trials. AVPI addresses the fundamental ethical challenges of informed consent by improving patient understanding, and supports the ethical framework integral to Faden and Beauchamp’s (1986) theory of informed consent. The new knowledge questionnaire was shown to be a sensitive and effective instrument for measuring understanding of randomised clinical trials in the cancer setting, although it would benefit from further testing. The AVPI appears to reduce anxiety at the decision making time point and has been shown to be an acceptable medium for patients. This study confirms existing findings from studies assessing factors affecting decision making, with personal benefit and altruism being key motivating factors, and reasons for refusal being less clear. The need for further qualitative work in this area is highlighted to gain a deeper understanding of what is important to patients, in terms of why they refuse clinical trial participation. Implications for practice and further research Several implications for practice have been identified, including using AVPI as part of the standard information package for patients considering randomised cancer trials, and focussing on patient and staff education in this area. The knowledge questionnaire could be introduced to routine practice as a tool to determine patient understanding prior to decision making, allowing clinicians the opportunity to correct any misconceptions prior to consent. Further research focussing on AVPI specific to individual trials would be helpful, to determine if a more customised approach would be of benefit in terms of clinical trial recruitment. The importance of studying other aspects of the consent process such as the interaction between the clinician and the patient, in addition to more detailed exploration of the factors affecting patients’ decisions were highlighted

Recalibrating single-study effect sizes using hierarchical Bayesian models

INTRODUCTION: There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance.METHODS: We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method.RESULTS: The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = -0.27, p &lt; 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p &lt; 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. DISCUSSION: Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.</p

Adjunctive rifampicin for Staphylococcus aureus bacteraemia (ARREST): a multicentre, randomised, double-blind, placebo-controlled trial.

BACKGROUND: Staphylococcus aureus bacteraemia is a common cause of severe community-acquired and hospital-acquired infection worldwide. We tested the hypothesis that adjunctive rifampicin would reduce bacteriologically confirmed treatment failure or disease recurrence, or death, by enhancing early S aureus killing, sterilising infected foci and blood faster, and reducing risks of dissemination and metastatic infection. METHODS: In this multicentre, randomised, double-blind, placebo-controlled trial, adults (≥18 years) with S aureus bacteraemia who had received ≤96 h of active antibiotic therapy were recruited from 29 UK hospitals. Patients were randomly assigned (1:1) via a computer-generated sequential randomisation list to receive 2 weeks of adjunctive rifampicin (600 mg or 900 mg per day according to weight, oral or intravenous) versus identical placebo, together with standard antibiotic therapy. Randomisation was stratified by centre. Patients, investigators, and those caring for the patients were masked to group allocation. The primary outcome was time to bacteriologically confirmed treatment failure or disease recurrence, or death (all-cause), from randomisation to 12 weeks, adjudicated by an independent review committee masked to the treatment. Analysis was intention to treat. This trial was registered, number ISRCTN37666216, and is closed to new participants. FINDINGS: Between Dec 10, 2012, and Oct 25, 2016, 758 eligible participants were randomly assigned: 370 to rifampicin and 388 to placebo. 485 (64%) participants had community-acquired S aureus infections, and 132 (17%) had nosocomial S aureus infections. 47 (6%) had meticillin-resistant infections. 301 (40%) participants had an initial deep infection focus. Standard antibiotics were given for 29 (IQR 18-45) days; 619 (82%) participants received flucloxacillin. By week 12, 62 (17%) of participants who received rifampicin versus 71 (18%) who received placebo experienced treatment failure or disease recurrence, or died (absolute risk difference -1·4%, 95% CI -7·0 to 4·3; hazard ratio 0·96, 0·68-1·35, p=0·81). From randomisation to 12 weeks, no evidence of differences in serious (p=0·17) or grade 3-4 (p=0·36) adverse events were observed; however, 63 (17%) participants in the rifampicin group versus 39 (10%) in the placebo group had antibiotic or trial drug-modifying adverse events (p=0·004), and 24 (6%) versus six (2%) had drug interactions (p=0·0005). INTERPRETATION: Adjunctive rifampicin provided no overall benefit over standard antibiotic therapy in adults with S aureus bacteraemia. FUNDING: UK National Institute for Health Research Health Technology Assessment

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects

Objective: Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes. Method: Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings. Results: Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects. Conclusions: The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine

Time to Switch to Second-line Antiretroviral Therapy in Children With Human Immunodeficiency Virus in Europe and Thailand.

Background: Data on durability of first-line antiretroviral therapy (ART) in children with human immunodeficiency virus (HIV) are limited. We assessed time to switch to second-line therapy in 16 European countries and Thailand. Methods: Children aged <18 years initiating combination ART (≥2 nucleoside reverse transcriptase inhibitors [NRTIs] plus nonnucleoside reverse transcriptase inhibitor [NNRTI] or boosted protease inhibitor [PI]) were included. Switch to second-line was defined as (i) change across drug class (PI to NNRTI or vice versa) or within PI class plus change of ≥1 NRTI; (ii) change from single to dual PI; or (iii) addition of a new drug class. Cumulative incidence of switch was calculated with death and loss to follow-up as competing risks. Results: Of 3668 children included, median age at ART initiation was 6.1 (interquartile range (IQR), 1.7-10.5) years. Initial regimens were 32% PI based, 34% nevirapine (NVP) based, and 33% efavirenz based. Median duration of follow-up was 5.4 (IQR, 2.9-8.3) years. Cumulative incidence of switch at 5 years was 21% (95% confidence interval, 20%-23%), with significant regional variations. Median time to switch was 30 (IQR, 16-58) months; two-thirds of switches were related to treatment failure. In multivariable analysis, older age, severe immunosuppression and higher viral load (VL) at ART start, and NVP-based initial regimens were associated with increased risk of switch. Conclusions: One in 5 children switched to a second-line regimen by 5 years of ART, with two-thirds failure related. Advanced HIV, older age, and NVP-based regimens were associated with increased risk of switch

Binding of adenosine receptor ligands to brain of adenosine receptor knock-out mice: evidence that CGS 21680 binds to A 1 receptors in hippocampus

The adenosine receptor agonist 2-[ p-(2-carboxyethyl)phenylethylamino]-5'- N-ethylcarboxamidoadenosine (CGS 21680) is generally considered to be a selective adenosine A 2A receptor ligand. However, the compound has previously been shown to exhibit binding characteristics that are not compatible with adenosine A 2A receptor binding, at least in brain regions other than the striatum. We have examined binding of [ 3H]CGS 21680 and of antagonist radioligands with high selectivity for adenosine A 1 or A 2A receptors to hippocampus and striatum of mice lacking either adenosine A 1 (A1R (-/-)) or A 2A (A2AR (-/-)) receptors. Both receptor autoradiography and membrane binding techniques were used for this purpose and gave similar results. There were no significant changes in the binding of the A 1 receptor antagonist [ 3H]DPCPX in mice lacking A 2A receptors, or in the binding of the A 2A receptor antagonists [ 3H]SCH 58261 and [ 3H]ZM 241385 in mice lacking A 1 receptors. Furthermore, [ 3H]CGS 21680 binding in striatum was abolished in the A2AR (-/-), and essentially unaffected in striatum from mice lacking A 1 receptors. In hippocampus, however, binding of [ 3H]CGS 21680 remained in the A2AR (-/-), whereas binding was virtually abolished in the A1R (-/-). There were no adaptive alterations in A 2A receptor expression in this region in A1R (-/-) mice. Thus, most of the [ 3H]CGS 21680 binding in hippocampus is dependent on the presence of adenosine A 1 receptors, but not on A 2A receptors, indicating a novel binding site or novel binding mode