Diversity Action Plans in Clinical Trials.

This Viewpoint discusses the US Food and Drug Administration's upcoming mandate on diversity actions plans for trial sponsors and the importance of developing accountability mechanisms to monitor those plans.

Testing and Treatment Interventions in Community Settings Key to Controlling a Recent Human Immunodeficiency Virus Outbreak Among People Who Inject Drugs in Glasgow: A Modeling Study.

BACKGROUND: A human immunodeficiency virus (HIV) outbreak was identified among people who inject drugs (PWID) in Glasgow in 2015, with >150 diagnoses by the end of 2019. The outbreak response involved scaling up HIV testing and improving HIV treatment initiation and retention. METHODS: We parameterized and calibrated a dynamic, deterministic model of HIV transmission among PWID in Glasgow to epidemiological data. We use this model to evaluate HIV testing and treatment interventions. We present results in terms of relative changes in HIV prevalence, incidence, and cases averted. RESULTS: If the improvements in both testing and treatment had not occurred, we predict that HIV prevalence would have reached 17.8% (95% credible interval [CrI], 14.1%-22.6%) by the beginning of 2020, compared to 5.9% (95% CrI, 4.7%-7.4%) with the improvements. If the improvements had been made on detection of the outbreak in 2015, we predict that peak incidence would have been 26.2% (95% CrI, 8.8%-49.3%) lower and 62.7% (95% CrI, 43.6%-76.6%) of the outbreak cases could have been averted. The outbreak could have been avoided if the improvements had already been in place. CONCLUSIONS: Our modeling suggests that the HIV testing and treatment interventions successfully brought the HIV outbreak in Glasgow under control by the beginning of 2020.

Client preferences for the design and delivery of injectable opioid agonist treatment services: Results from a best-worst scaling task.

BACKGROUND AND AIMS: Clinical trials support injectable opioid agonist treatment (iOAT) for individuals with opioid use disorder (OUD) for whom other pharmacological management approaches are not well-suited. However, despite substantial research indicating that person-centered care improves engagement, retention and health outcomes for individuals with OUD, structural requirements (e.g. drug policies) often dictate how iOAT must be delivered, regardless of client preferences. This study aimed to quantify clients' iOAT delivery preferences to improve client engagement and retention. DESIGN: Cross-sectional preference elicitation survey. SETTING: Metro Vancouver, British Columbia, Canada. PARTICIPANTS: 124 current and former iOAT clients. MEASUREMENTS: Participants completed a demographic questionnaire package and an interviewer-led preference elicitation survey (case 2 best-worst scaling task). Latent class analysis was used to identify distinct preference groups and explore demographic differences between preference groups. FINDINGS: Most participants (n = 100; 81%) were current iOAT clients. Latent class analysis identified two distinct groups of client preferences: (1) autonomous decision-makers (n = 73; 59%) and (2) shared decision-makers (n = 51; 41%). These groups had different preferences for how medication type and dosage were selected. Both groups prioritized access to take-home medication (i.e. carries), the ability to set their own schedule, receiving iOAT in a space they like and having other services available at iOAT clinics. Compared with shared decision-makers, fewer autonomous decision-makers identified as a cis-male/man and reported flexible preferences. CONCLUSIONS: Injectable opioid agonist treatment (iOAT) clients surveyed in Vancouver, Canada, appear to prefer greater autonomy than they currently have in choosing OAT medication type, dosage and treatment schedule.

Impact of the COVID-19 Pandemic on HIV Test Uptake Among People Who Inject Drugs in the Context of an HIV Outbreak.

Glasgow, Scotland's largest city, has been experiencing an HIV outbreak among people who inject drugs (PWID) since 2015. A key focus of the public health response has been to increase HIV testing among those at risk of infection. Our aim was to assess the impact of COVID-19 on HIV testing among PWID in Glasgow. HIV test uptake in the last 12 months was quantified among: (1) PWID recruited in six Needle Exchange Surveillance Initiative (NESI) surveys (n = 6110); linked laboratory data for (2) people prescribed opioid agonist therapy (OAT) (n = 14,527) and (3) people hospitalised for an injecting-related hospital admission (IRHA) (n = 12,621) across four time periods: pre-outbreak (2010-2014); early-outbreak (2015-2016); ongoing-outbreak (2017-2019); and COVID-19 (2020-June 21). From the pre to ongoing period, HIV testing increased: the highest among people recruited in NESI (from 28% to 56%) and on OAT (from 17% to 54%) while the lowest was among people with an IRHA (from 15% to 42%). From the ongoing to the COVID-19 period, HIV testing decreased markedly among people prescribed OAT, from 54% to 37% (aOR 0.50, 95% CI 0.48-0.53), but increased marginally among people with an IRHA from 42% to 47% (aOR 1.19, 95% CI 1.08-1.31). In conclusion, progress in increasing testing in response to the HIV outbreak has been eroded by COVID-19. Adoption of a linked data approach could be warranted in other settings to inform efforts to eliminate HIV transmission.

Understanding what patients and physicians need to improve their decision-making about antenatal corticosteroids in late preterm gestation: a qualitative framework analysis.

BACKGROUND: It is unclear whether the benefits of administration of antenatal corticosteroids in late preterm gestation outweigh its harms. We sought to understand whether patients and physicians need increased support to decide whether to administer antenatal corticosteroids in late preterm gestation, and their informational needs and preferences for decision-making roles related to this intervention; we also wanted to know if creation of a decision-support tool would be useful. METHODS: We conducted individual, semistructured interviews with pregnant people, obstetricians and pediatricians in Vancouver, Canada, in 2019. Using a qualitative framework analysis method, we coded, charted and interpreted interview transcripts into categories that formed an analytical framework. RESULTS: We included 20 pregnant participants, 10 obstetricians and 10 pediatricians. We organized codes into the following categories: informational needs to decide whether to administer antenatal corticosteroids; preferences for decision-making roles regarding this treatment; the need for support to make this treatment decision; and the preferred format and content of a decision-support tool. Pregnant participants wanted to be involved in decision-making about antenatal corticosteroids in late preterm gestation. They wanted information on the medication, respiratory distress, hypoglycemia, parent-neonate bonding and long-term neurodevelopment. There was variation in physician counselling practices, and in how patients and physicians perceived the balance of treatment harms and benefits. Responses suggested a decision-support tool may be useful. Participants desired clear descriptions of risk magnitude and uncertainty. INTERPRETATION: Pregnant people and physicians would likely benefit from increased support to consider the harms and benefits of antenatal corticosteroids in late preterm gestation. Creation of a decision-support tool may be useful.

Using a patient-centred composite endpoint in a secondary analysis of the Control of Hypertension in Pregnancy Study (CHIPS) Trial.

BACKGROUND: Clinical trials commonly use multiple endpoints to measure the impact of an intervention. While this improves the comprehensiveness of outcomes, it can make trial results difficult to interpret. We examined the impact of integrating patient weights into a composite endpoint on the interpretation of Control of Hypertension in Pregnancy Study (CHIPS) Trial results. METHODS: Outcome weights were extracted from a previous patient preferences study in pregnancy hypertension (N = 183 women) which identified (i) seven outcomes most important to women (taking medication, severe hypertension, pre-eclampsia, blood transfusion, Caesarean, delivery < 34 weeks, and baby born smaller-than-expected) and (ii) three preference subgroups: (1) 'equal prioritizers', 62%; (2) 'early delivery avoiders', 23%; and (3) 'medication minimizers', 14%. Outcome weights from the preference subgroups were integrated with CHIPS data for the seven outcomes identified in the preference study. A weighted composite score was derived for each participant by multiplying the preference weight for each outcome by the binary outcome if it occurred. Analyses considered equal weights and those from the preference subgroups. The mean composite scores were compared between trial arms (t-tests). RESULTS: Composite scores were similar between trial arms with the use of equal weights or those of subgroup (1) (95% confidence intervals [CIs]: - 0.03, 0.02; p > 0.50 for each). 'Tight' control was superior when using subgroup (2) weights (95% CIs: 0.002, 0.07; p = 0.03), and 'less-tight' control was superior when using subgroup (3) weights (95% CIs: - 0.11, - 0.04; p < 0.01). CONCLUSIONS: Evidence-based recommendations for 'tight' control are consistent with most women's preferences, but for a sixth of women, 'less-tight' control is more preference consistent. Depending on patient preferences, a single trial may support different interventions. Future trials should specify component weights to improve interpretation. TRIAL REGISTRATION: ClinicalTrials.gov NCT01192412.

IMplementing Predictive Analytics towards efficient COPD Treatments (IMPACT): protocol for a stepped-wedge cluster randomized impact study.

INTRODUCTION: Personalized disease management informed by quantitative risk prediction has the potential to improve patient care and outcomes. The integration of risk prediction into clinical workflow should be informed by the experiences and preferences of stakeholders, and the impact of such integration should be evaluated in prospective comparative studies. The objectives of the IMplementing Predictive Analytics towards efficient chronic obstructive pulmonary disease (COPD) treatments (IMPACT) study are to integrate an exacerbation risk prediction tool into routine care and to determine its impact on prescription appropriateness (primary outcome), medication adherence, quality of life, exacerbation rates, and sex and gender disparities in COPD care (secondary outcomes). METHODS: IMPACT will be conducted in two phases. Phase 1 will include the systematic and user-centered development of two decision support tools: (1) a decision tool for pulmonologists called the ACCEPT decision intervention (ADI), which combines risk prediction from the previously developed Acute COPD Exacerbation Prediction Tool with treatment algorithms recommended by the Canadian Thoracic Society's COPD pharmacotherapy guidelines, and (2) an information pamphlet for COPD patients (patient tool), tailored to their prescribed medication, clinical needs, and lung function. In phase 2, we will conduct a stepped-wedge cluster randomized controlled trial in two outpatient respiratory clinics to evaluate the impact of the decision support tools on quality of care and patient outcomes. Clusters will be practicing pulmonologists (n ≥ 24), who will progressively switch to the intervention over 18 months. At the end of the study, a qualitative process evaluation will be carried out to determine the barriers and enablers of uptake of the tools. DISCUSSION: The IMPACT study coincides with a planned harmonization of electronic health record systems across tertiary care centers in British Columbia, Canada. The harmonization of these systems combined with IMPACT's implementation-oriented design and partnership with stakeholders will facilitate integration of the tools into routine care, if the results of the proposed study reveal positive association with improvement in the process and outcomes of clinical care. The process evaluation at the end of the trial will inform subsequent design iterations before largescale implementation. TRIAL REGISTRATION: NCT05309356.

Measuring the preferences of injectable opioid agonist treatment (iOAT) clients: Development of a person-centered scale (best-worst scaling).

BACKGROUND: Injectable opioid agonist treatment (iOAT) is effective for opioid use disorder (OUD), yet little is known about client preferences for accessing iOAT (e.g., with diacetylmorphine, hydromorphone, buprenorphine, fentanyl, etc.). Best-worst scaling (BWS) is a preference elicitation method from health economics that has never been applied to addiction care broadly, or iOAT specifically. We describe the stages of developing a BWS scale that assesses iOAT clients' treatment delivery preferences to inform program planning and maximize healthcare efficiency. METHODS: We underwent several steps to reveal the relevant attributes/levels and design the scale structure. An initial list of potential attributes and levels was established from a literature review and prior qualitative data. Then, we conducted semi-structured interviews and focus groups with clients (n=21) on their iOAT preferences to confirm the attributes and prioritize/include new ones. Next, we conducted semi-structured interviews and focus groups with iOAT experts and stakeholders to receive their input on the draft list of attributes and levels. A BWS profile case design was piloted with iOAT clients (n=18) from different sites during a think aloud interview. After several rounds of revisions, the final version was tested by iOAT clients (n=2) before the scale was launched. RESULTS: We developed a person-centered scale that assesses current and former iOAT clients' most and least wanted aspects of iOAT delivery. The final version yielded 7 unique attributes: choice of medication, choice of dose, convenience, location & space, scheduling & routines, staff & training, and types of services offered. CONCLUSION: This scale can help expand iOAT programs in a way that is person-centered, rapid, and affordable. The methodology is a guide for other regions with similar populations who aim to develop strong quantitative methodologies that prioritize client collaboration.

Feasibility of Testing Client Preferences for Accessing Injectable Opioid Agonist Treatment (iOAT): A Pilot Study.

Purpose: Injectable opioid agonist treatment (iOAT) is an effective treatment for opioid use disorder (OUD). To our knowledge, no research has systematically studied client preferences for accessing iOAT. Incorporating preferences could help meet the heterogenous needs of clients and make addiction care more person-centred. This paper presents a pilot study of a best-worst scaling (BWS) preference elicitation survey that aimed to assess if the survey was feasible and accessible for our population and to test that the survey could gather sound data that would suit our planned analyses. Patients and Methods: Current and former iOAT clients (n = 18) completed a BWS survey supported by an interviewer using a think-aloud approach. The survey was administered on PowerPoint, and responses and contextual field notes were recorded manually. Think-aloud audio was recorded on Audacity. Results: Clients' feedback fell into five categories: framing of the task, accessibility, conceptualization of attributes and levels, formatting, and behaviour predicting questions. Survey repetitiveness was the most consistent feedback. The data simulation showed that 100 responses should provide an adequate sample size. Conclusion: This pilot demonstrates the type of analysis that can be done with BWS in our population, suggests that such analysis is feasible, and highlights the importance of the interviewer and participant working side-by-side throughout the task.