Application of the Estimand Framework to Anesthesia Trials.

Events occurring after randomization, such as use of rescue medication, treatment discontinuation, or death, are common in randomized trials. These events can change either the existence or interpretation of the outcome of interest. However, appropriate handling of these intercurrent events is often unclear. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) E9(R1) addendum introduced the estimand framework, which aligns trial objectives with the design, conduct, statistical analysis, and interpretation of results. This article describes how the estimand framework can be used in anesthesia trials to precisely define the treatment effect to be estimated, key attributes of an estimand, common intercurrent events in anesthesia trials with strategies for handling them, and use of the estimand framework in a hypothetical anesthesia trial on postoperative delirium. When planning anesthesia trials, clearly defining the estimand is vital to ensure that what is being estimated is clearly understood, is clinically relevant, and helps answer the clinical questions of interest.

Personalising genetic counselling (POETIC) trial: Protocol for a hybrid type II effectiveness-implementation randomised clinical trial of a patient screening tool to improve patient empowerment after cancer genetic counselling.

BACKGROUND: Genetic counselling aims to identify, and address, patient needs while facilitating informed decision-making about genetic testing and promoting empowerment and adaptation to genetic information. Increasing demand for cancer genetic testing and genetic counsellor workforce capacity limitations may impact the quality of genetic counselling provided. The use of a validated genetic-specific screening tool, the Genetic Psychosocial Risk Instrument (GPRI), may facilitate patient-centred genetic counselling. The aim of this study is to assess the effectiveness and implementation of using the GPRI in improving patient outcomes after genetic counselling and testing for an inherited cancer predisposition. METHODS: The PersOnalising gEneTIc Counselling (POETIC) trial is a hybrid type 2 effectiveness-implementation trial using a randomised control trial to assess the effectiveness of the GPRI in improving patient empowerment (primary outcome), while also assessing implementation from the perspective of clinicians and the healthcare service. Patients referred for a cancer risk assessment to the conjoint clinical genetics service of two metropolitan hospitals in Victoria, Australia, who meet the eligibility criteria and consent to POETIC will be randomised to the usual care or intervention group. Those in the intervention group will complete the GPRI prior to their appointment with the screening results available for the clinicians' use during the appointment. Appointment audio recordings, clinician-reported information about the appointment, patient-reported outcome measures, and clinical data will be used to examine the effectiveness of using the GPRI. Appointment audio recordings, health economic information, and structured interviews will be used to examine the implementation of the GPRI. DISCUSSION: The POETIC trial takes a pragmatic approach by deploying the GPRI as an intervention in the routine clinical practice of a cancer-specific clinical genetics service that is staffed by a multidisciplinary team of genetics and oncology clinicians. Therefore, the effectiveness and implementation evidence generated from this real-world health service setting aims to optimise the relevance of the outcomes of this trial to the practice of genetic counselling while enhancing the operationalisation of the screening tool in routine practice. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry registration number 12621001582842p. Date of registration: 19th November 2021.

Effects of a Massive Open Online Course on osteoarthritis knowledge and pain self-efficacy in people with hip and/or knee osteoarthritis: protocol for the MOOC-OA randomised controlled trial.

BACKGROUND: Osteoarthritis (OA) is a prevalent, chronic joint condition that commonly affects the knee and hip causing pain, impaired function, and reduced quality of life. As there is no cure, the main goal of treatment is to alleviate symptoms via ongoing self-management predominantly consisting of exercise and weight loss (if indicated). However, many people with OA do not feel adequately informed about their condition and management options to self-manage effectively. Patient education is recommended by all OA Clinical Practice Guidelines to support appropriate self-management, but little is known about the optimal delivery method and content. Massive Open Online Courses (MOOCs) are free, interactive, e-learning courses. They have been used to deliver patient education in other chronic health conditions but have not been used in OA. METHODS: A two-arm parallel-design, assessor- and participant-blinded superiority randomised controlled trial. People with persistent knee/hip pain consistent with a clinical diagnosis of knee/hip OA (n = 120) are being recruited from the Australia-wide community. Participants are randomly allocated into one of two groups i) electronic information pamphlet (control group) or ii) MOOC (experimental group). Those allocated to the control group receive access to an electronic pamphlet about OA and its recommended management, currently available from a reputable consumer organisation. Those allocated to the MOOC receive access to a 4-week 4-module interactive consumer-facing e-Learning course about OA and its recommended management. Course design was informed by behaviour theory and learning science, and consumer preferences. The two primary outcomes are OA knowledge and pain self-efficacy with a primary endpoint of 5 weeks and a secondary endpoint of 13 weeks. Secondary outcomes include measures of fear of movement, exercise self-efficacy, illness perceptions, OA management and health professional care seeking intentions, physical activity levels, and actual use of physical activity/exercise and weight loss, pain medication, and health professional care seeking to manage joint symptoms. Clinical outcomes and process measures are also collected. DISCUSSION: Findings will determine whether a comprehensive consumer-facing MOOC improves OA knowledge and confidence to self-manage joint pain compared to a currently available electronic OA information pamphlet. TRIAL REGISTRATION: Prospectively registered (Australian New Zealand Clinical Trials Registry ID: ACTRN12622001490763).

Evaluation of approaches for accommodating interactions and non-linear terms in multiple imputation of incomplete three-level data.

Three-level data structures arising from repeated measures on individuals clustered within larger units are common in health research studies. Missing data are prominent in such studies and are often handled via multiple imputation (MI). Although several MI approaches can be used to account for the three-level structure, including adaptations to single- and two-level approaches, when the substantive analysis model includes interactions or quadratic effects, these too need to be accommodated in the imputation model. In such analyses, substantive model compatible (SMC) MI has shown great promise in the context of single-level data. Although there have been recent developments in multilevel SMC MI, to date only one approach that explicitly handles incomplete three-level data is available. Alternatively, researchers can use pragmatic adaptations to single- and two-level MI approaches, or two-level SMC-MI approaches. We describe the available approaches and evaluate them via simulations in the context of three three-level random effects analysis models involving an interaction between the incomplete time-varying exposure and time, an interaction between the time-varying exposure and an incomplete time-fixed confounder, or a quadratic effect of the exposure. Results showed that all approaches considered performed well in terms of bias and precision when the target analysis involved an interaction with time, but the three-level SMC MI approach performed best when the target analysis involved an interaction between the time-varying exposure and an incomplete time-fixed confounder, or a quadratic effect of the exposure. We illustrate the methods using data from the Childhood to Adolescence Transition Study.

Alcohol availability and prevalent Chlamydia trachomatis in young Australians: a multi-level analysis.

Background Prevalence of sexually transmissible infections (STIs) has been associated with availability of alcohol. This paper investigates potential associations between prevalent cases of chlamydia in young people in Australia and the availability of alcohol within their local area, defined as postcode of residence. Methods Alcohol availability was determined at the postcode level using liquor licensing data, classified as total number of licences, number of 'take-away' licences and number of licenses by population. Participant data were drawn from a survey targeting Australians aged 16-29years in rural and regional Australia, capturing demographic details including postcode of residence, indicators of sexual behaviour including condom use and chlamydia test results. Mixed-effects logistic regression was used to examine potential associations between first, alcohol availability and chlamydia, and second, between condom use and chlamydia. Results We found little evidence of associations between alcohol availability and chlamydia in either unadjusted or adjusted models. After adjusting for alcohol availability, we observed significant associations between inconsistent condom use and chlamydia prevalence, whether alcohol availability was measured as total number (adjusted odds ratio (AOR) 2.20; 95% confidence interval (CI) 1.20, 3.70), number of take-away licenses (AOR 2.19; 95% CI1.30, 3.69) or licenses per 1000 population (AOR 2.19; 95% CI 1.30, 3.68). Conclusion Little evidence of association between alcohol availability and chlamydia at the postcode level was found. Further research is required to determine appropriate measures of 'local area' and how characteristics thereof may impact on sexual health.

Sugammadex, neostigmine and postoperative pulmonary complications: an international randomised feasibility and pilot trial.

BACKGROUND: Sugammadex reduces residual neuromuscular blockade after anaesthesia, potentially preventing postoperative pulmonary complications. However, definitive evidence is lacking. We therefore conducted a feasibility and pilot trial for a large randomised controlled trial of sugammadex, neostigmine, and postoperative pulmonary complications. METHODS: Patients aged ≥40 years having elective or expedited abdominal or intrathoracic surgery were recruited in Australia and Hong Kong. Perioperative care was at the discretion of clinicians, except for the use of rocuronium and/or vecuronium for neuromuscular blockade and the randomised intervention (sugammadex or neostigmine) for reversal. Feasibility measurements included recruitment, crossover, acceptability, completeness, and workload. Trial coordinator feedback was systematically sought. Patient-reported quality of life was measured using the EQ-5D-5L score. The primary pilot outcome was the incidence of new pulmonary complications up to hospital discharge (or postoperative day 7 if still in hospital). RESULTS: Among 150 eligible patients, 120 consented to participate (recruitment rate 80%, 95% confidence interval [CI] 73 to 86%). The randomised intervention was administered without crossover to 115 of 117 patients who received reversal (98%, 95% CI 94 to 100%). The protocol was acceptable or highly acceptable to the anaesthetist in 108 of 116 cases (93%, 95% CI 87 to 97%; missing = 4). Four patients of the 120 patients were lost to follow-up at 3 months (3.3%, 95% CI 0.9 to 8.3%). Case report forms were complete at 3 months for all remaining patients. The median time to complete trial processes was 3.5 h (range 2.5-4.5 h). Trial coordinators reported no barriers to trial processes. Patients were aged 64 (standard deviation 11) years, 70 (58%) were male and 50 (42%) were female, and planned surgeries were thoracic (23 [19%]), upper abdominal (41 [34%]), and lower abdominal (56 [47%]). The primary outcome was observed in 5 (8.5%) of the 59 sugammadex patients and 5 (8.2%) of the 61 neostigmine patients (odds ratio 1.02, 95% CI 0.28 to 3.67). CONCLUSIONS: A large international randomised controlled trial of sugammadex, neostigmine and postoperative pulmonary complications in adult patients having abdominal and intrathoracic surgery, including collection of cost-effectiveness evidence for Health Technology Appraisal, is feasible. TRIAL REGISTRATION: Prospectively registered at the Australian and New Zealand Clinical Trials Registry ( ACTRN12620001313921 ) on December 7, 2020. www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380645&isReview=true .

Multiple imputation methods for handling missing values in longitudinal studies with sampling weights: Comparison of methods implemented in Stata.

Many analyses of longitudinal cohorts require incorporating sampling weights to account for unequal sampling probabilities of participants, as well as the use of multiple imputation (MI) for dealing with missing data. However, there is no guidance on how MI and sampling weights should be implemented together. We simulated a target population based on the Australian Bureau of Statistics Estimated Resident Population and drew 1000 random samples dependent on three design variables to mimic the Longitudinal Study of Australian Children. The target analysis was the weighted prevalence of overweight/obesity over childhood. We evaluated the performance of several MI approaches available in Stata, based on multivariate normal imputation (MVNI), fully conditional specification (FCS) and twofold FCS: a weighted imputation model, imputing missing data separately for each quintile sampling weight grouping, including the design stratum indicator in the imputation model, and using sampling weights as a covariate in the imputation model. Approaches based on available cases and inverse probability weighting (IPW), with time-varying weights, were also compared. We observed severe issues of convergence with FCS and twofold FCS. All MVNI-based approaches performed similarly, producing minimal bias and nominal coverage, except for when imputation was conducted separately for each quintile sampling weight group. IPW performed equally as well as MVNI-based approaches in terms of bias, however, was less precise. In similar longitudinal studies, we recommend using MVNI with the design stratum as a covariate in the imputation model. If this is unknown, including the sampling weight as a covariate is an appropriate alternative.