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ObjectivesIt has been suggested that diffusion tensor imaging (DTI) measures sensitive to white matter (WM) damage may predict future dementia risk not only in cerebral small vessel disease (SVD), but also in mild cognitive impairment. To determine whether DTI measures were associated with cognition cross-sectionally and predicted future dementia risk across the full range of SVD severity, we established the International OPtimising mulTImodal MRI markers for use as surrogate markers in trials of Vascular Cognitive Impairment due to cerebrAl small vesseL disease collaboration which included six cohorts.MethodsAmong the six cohorts, prospective data with dementia incidences were available for three cohorts. The associations between six different DTI measures and cognition or dementia conversion were tested. The additional contribution to prediction of other MRI markers of SVD was also determined.ResultsThe DTI measure mean diffusivity (MD) median correlated with cognition in all cohorts, demonstrating the contribution of WM damage to cognition. Adding MD median significantly improved the model fit compared to the clinical risk model alone and further increased in all single-centre SVD cohorts when adding conventional MRI measures. Baseline MD median predicted dementia conversion. In a study with severe SVD (SCANS) change in MD median also predicted dementia conversion. The area under the curve was best when employing a multimodal MRI model using both DTI measures and other MRI measures.ConclusionsOur results support a central role for WM alterations in dementia pathogenesis in all cohorts. DTI measures such as MD median may be a useful clinical risk predictor. The contribution of other MRI markers varied according to disease severity.

To re-analyse the clinical outcomes and interferon (IFN) activity data from the JOQUER trial, a phase III trial investigating hydroxychloroquine (HCQ) in patients with primary Sjögren’s syndrome (pSS), after stratifying patients into putative pathobiological subgroups utilizing the Newcastle Sjögren’s Stratification Tool (NSST) based on patient-reported symptoms of dryness, pain, fatigue, anxiety and depression. 107 patients were assigned to one of four subgroups using NSST at baseline—the high symptom burden (HSB), pain dominant with fatigue (PDF), dryness dominant with fatigue (DDF) and low symptom burden (LSB). Endpoints were re-analysed after stratification, testing for treatment differences within subgroups and adjusting for baseline differences using a repeated measures covariate model. The HSB subgroup (n = 32) showed a relative improvement in ESSPRI of 1.49 points (95% CI 0.54–2.43; p = 0.002) within 12 weeks in patients taking HCQ compared to placebo, with no further changes after 24 weeks. For the LSB subgroup (n = 14), the ESSPRI worsened in the placebo but not the HCQ arm after 12 weeks (mean difference 1.44, 95% CI 0.05–2.83, p = 0.042). Neither the HSB nor the LSB patients showed significant changes in IFN activity at 24 weeks. There were no significant differences in ESSPRI in the PDF (n = 39) and DDF (n = 22) patients taking HCQ. However, significant reductions in overall IFN score at 24 weeks were seen in both PDF (difference at 24 weeks; 6.41, 95% CI, 2.48–10.34, p = 0.002) and DDF (difference at 24 weeks; 7.23, 95% CI, 1.85–12.6, p = 0.009) without improvement in ESSPRI. Although the JOQUER trial reported no overall benefit from HCQ in pSS patients, stratification suggests that both HSB and LSB subgroups may respond to HCQ. However, these patients may benefit through mechanisms other than the reduction of IFN activities.

High-dimensional biomarkers such as genomics are increasingly being measured in randomized clinical trials. Consequently, there is a growing interest in developing methods that improve the power to detect biomarker-treatment interactions. We adapt recently proposed two-stage interaction detecting procedures in the setting of randomized clinical trials. We also propose a new stage 1 multivariate screening strategy using ridge regression to account for correlations among biomarkers. For this multivariate screening, we prove the asymptotic between-stage independence, required for family-wise error rate control, under biomarker-treatment independence. Simulation results show that in various scenarios, the ridge regression screening procedure can provide substantially greater power than the traditional one-biomarker-at-a-time screening procedure in highly correlated data. We also exemplify our approach in two real clinical trial data applications., Accepted version, to be published in Biometrics

Summary Background Multisystemic therapy is a manualised treatment programme for young people aged 11–17 years who exhibit antisocial behaviour. To our knowledge, the Systemic Therapy for At Risk Teens (START) trial is the first large-scale randomised controlled trial of multisystemic therapy in the UK. Previous findings reported to 18 months after baseline (START-I study) did not indicate superiority of multisystemic therapy compared with management as usual. Here, we report outcomes of the trial to 60 months (START-II study). Methods In this pragmatic, randomised, controlled, superiority trial, young people (aged 11–17 years) with moderate-to-severe antisocial behaviour were recruited from social services, youth offending teams, schools, child and adolescent mental health services, and voluntary services across England, UK. Participants were eligible if they had at least three severity criteria indicating past difficulties across several settings and one of five general inclusion criteria for antisocial behaviour. Eligible families were randomly assigned (1:1), using stochastic minimisation and stratifying for treatment centre, sex, age at enrolment, and age at onset of antisocial behaviour, to management as usual or 3–5 months of multisystemic therapy followed by management as usual. Research assistants and investigators were masked to treatment allocation; the participants could not be masked. For this extension study, the primary outcome was the proportion of participants with offences with convictions in each group at 60 months after randomisation. This study is registered with ISRCTN, ISRCTN77132214, and is closed to accrual. Findings Between Feb 4, 2010, and Sept 1, 2012, 1076 young people and families were assessed for eligibility and 684 were randomly assigned to management as usual (n=342) or multisystemic therapy (n=342). By 60 months' of follow-up, 188 (55%) of 342 people in the multisystemic therapy group had at least one offence with a criminal conviction, compared with 180 (53%) of 341 in the management-as-usual group (odds ratio 1·13, 95% CI 0·82–1·56; p=0·44). Interpretation The results of the 5-year follow-up show no evidence of longer-term superiority for multisystemic therapy compared with management as usual. Funding National Institute for Health Research Health Services and Delivery Research programme.

Background The Systemic Therapy for At Risk Teens (START) trial is a randomised controlled trial of multisystemic therapy (MST) compared with management as usual (MAU). The present study reports on long-term follow-up of the trial (to 60 months). Objectives The primary objective was to compare MST and MAU for the proportion of young people in each group with criminal convictions up to 60 months post baseline. Secondary outcomes included group comparisons of psychological and behavioural factors. An economic analysis was carried out to determine the cost-effectiveness of MST compared with MAU. Two qualitative studies were conducted to better understand the subjective experiences of the participants. Design Primary outcomes (collected up to 60 months) were collected using a centralised police database. Secondary outcomes were evaluated using self-report questionnaires completed by both young people and parents or carers at the 24-, 36- and 48-month follow-ups. Research assistants were blind to treatment allocation. Setting Participants were recruited from participating MST sites in nine areas of England. Secondary outcomes were typically collected within the family home. Participants A total of 684 families were recruited into the START trial and allocated randomly to a treatment group. Of these, 487 remained in the second phase of the trial. Young people were aged, on average, 13.8 years at baseline, with 63% male and 37% female. Interventions MST is a manualised programme for young people exhibiting antisocial behaviour and their families that uses principles from cognitive–behavioural and family therapy to provide an individualised approach. MAU content was not prespecified, but consisted of the standard care offered to young people who met eligibility for the trial. Main outcome measures Young people’s offending was evaluated using the Police National Computer. Secondary measures included validated self-report measures completed by both the young person and their parent or carer. The economic evaluation took a broad perspective and outcomes were assessed in terms of quality-adjusted life-years and offending. Results No significant differences were found in the proportion of offending between the groups (hazard ratio 1.03, 95% confidence interval 0.84 to 1.26; p = 0.78). No differences were found between the groups on secondary outcome measures, with a few exceptions that did not hold up consistently across the follow-up period. The economic analysis did not find evidence to support the cost-effectiveness of MST compared with MAU. Outcomes from the qualitative studies suggest that families mostly felt positive about MST, and that MST was associated with greater maturity in young men. Limitations Some intended evaluations were not possible to deliver. Selective attrition may have influenced the nature of the sample size. It is also unclear how representative the MAU services were of reality. Future research Recommendations are made for the evaluation of MST in populations with more severe behavioural problems, as well as for identifying and testing new moderators. Conclusions The results of the second phase of the START trial do not support the long-term superiority of MST to MAU, but elements of the intervention may be adapted successfully. Trial registration Current Controlled Trials ISRCTN77132214 and London South-East REC registration number 09/H1102/55. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 23. See the NIHR Journals Library website for further project information.

Funder: NIHR Cambridge Biomedical Research Centre, BACKGROUND: Composite responder endpoints feature frequently in rheumatology due to the multifaceted nature of many of these conditions. Current analysis methods used to analyse these endpoints discard much of the data used to classify patients as responders and are therefore highly inefficient, resulting in low power. We highlight a novel augmented methodology that uses more of the information available to improve the precision of reported treatment effects. Since these methods are more challenging to implement, we developed free, user-friendly software available in a web-based interface and as R packages. The software consists of two programs: one that supports the analysis of responder endpoints; the second that facilitates sample size estimation. We demonstrate the use of the software to conduct the analysis with both the augmented and standard analysis method using the MUSE study, a phase IIb trial in patients with systemic lupus erythematosus. RESULTS: The software outputs similar point estimates with smaller confidence intervals for the odds ratio, risk ratio and risk difference estimators using the augmented approach. The sample size required in each arm for a future trial using the novel approach based on the MUSE data is 50 versus 135 for the standard method, translating to a reduction in required sample size of approximately 63%. CONCLUSIONS: We encourage trialists to use the software demonstrated to implement the augmented methodology in future studies to improve efficiency.

Funder: AstraZeneca (GB), Background: Window-of-opportunity trials, evaluating the engagement of drugs with their biological target in the time period between diagnosis and standard-of-care treatment, can help prioritise promising new systemic treatments for later-phase clinical trials. Renal cell carcinoma (RCC), the 7th commonest solid cancer in the UK, exhibits targets for multiple new systemic anti-cancer agents including DNA damage response inhibitors, agents targeting vascular pathways and immune checkpoint inhibitors. Here we present the trial protocol for the WIndow-of-opportunity clinical trial platform for evaluation of novel treatment strategies in REnal cell cancer (WIRE). Methods: WIRE is a Phase II, multi-arm, multi-centre, non-randomised, proof-of-mechanism (single and combination investigational medicinal product [IMP]), platform trial using a Bayesian adaptive design. The Bayesian adaptive design leverages outcome information from initial participants during pre-specified interim analyses to determine and minimise the number of participants required to demonstrate efficacy or futility. Patients with biopsy-proven, surgically resectable, cT1b+, cN0���1, cM0���1 clear cell RCC and no contraindications to the IMPs are eligible to participate. Participants undergo diagnostic staging CT and renal mass biopsy followed by treatment in one of the treatment arms for at least 14 days. Initially, the trial includes five treatment arms with cediranib, cediranib + olaparib, olaparib, durvalumab and durvalumab + olaparib. Participants undergo a multiparametric MRI before and after treatment. Vascularised and de-vascularised tissue is collected at surgery. A ��� 30% increase in CD8+ T-cells on immunohistochemistry between the screening and nephrectomy is the primary endpoint for durvalumab-containing arms. Meanwhile, a reduction in tumour vascular permeability measured by Ktrans on dynamic contrast-enhanced MRI by ���30% is the primary endpoint for other arms. Secondary outcomes include adverse events and tumour size change. Exploratory outcomes include biomarkers of drug mechanism and treatment effects in blood, urine, tissue and imaging. Discussion: WIRE is the first trial using a window-of-opportunity design to demonstrate pharmacological activity of novel single and combination treatments in RCC in the pre-surgical space. It will provide rationale for prioritising promising treatments for later phase trials and support the development of new biomarkers of treatment effect with its extensive translational agenda. Trial registration: ClinicalTrials.gov: NCT03741426 / EudraCT: 2018���003056-21.

Background Adaptive designs offer great promise in improving the efficiency and patient-benefit of clinical trials. An important barrier to further increased use is a lack of understanding about which additional resources are required to conduct a high-quality adaptive clinical trial, compared to a traditional fixed design. The Costing Adaptive Trials (CAT) project investigated which additional resources may be required to support adaptive trials. Methods We conducted a mock costing exercise amongst seven Clinical Trials Units (CTUs) in the UK. Five scenarios were developed, derived from funded clinical trials, where a non-adaptive version and an adaptive version were described. Each scenario represented a different type of adaptive design. CTU staff were asked to provide the costs and staff time they estimated would be needed to support the trial, categorised into specified areas (e.g. statistics, data management, trial management). This was calculated separately for the non-adaptive and adaptive version of the trial, allowing paired comparisons. Interviews with 10 CTU staff who had completed the costing exercise were conducted by qualitative researchers to explore reasons for similarities and differences. Results Estimated resources associated with conducting an adaptive trial were always (moderately) higher than for the non-adaptive equivalent. The median increase was between 2 and 4% for all scenarios, except for sample size re-estimation which was 26.5% (as the adaptive design could lead to a lengthened study period). The highest increase was for statistical staff, with lower increases for data management and trial management staff. The percentage increase in resources varied across different CTUs. The interviews identified possible explanations for differences, including (1) experience in adaptive trials, (2) the complexity of the non-adaptive and adaptive design, and (3) the extent of non-trial specific core infrastructure funding the CTU had. Conclusions This work sheds light on additional resources required to adequately support a high-quality adaptive trial. The percentage increase in costs for supporting an adaptive trial was generally modest and should not be a barrier to adaptive designs being cost-effective to use in practice. Informed by the results of this research, guidance for investigators and funders will be developed on appropriately resourcing adaptive trials.

Background Frailty is the loss of ability to withstand a physiological stressor and is associated with multiple adverse outcomes in older people. Trials to prevent or ameliorate frailty are in their infancy. A range of different outcome measures have been proposed, but current measures require either large sample sizes, long follow-up, or do not directly measure the construct of frailty. Methods We propose a composite outcome for frailty prevention trials, comprising progression to the frail state, death, or being too unwell to continue in a trial. To determine likely event rates, we used data from the English Longitudinal Study for Ageing, collected 4 years apart. We calculated transition rates between non-frail, prefrail, frail or loss to follow up due to death or illness. We used Markov state transition models to interpolate one- and two-year transition rates and performed sample size calculations for a range of differences in transition rates using simple and composite outcomes. Results The frailty category was calculable for 4650 individuals at baseline (2226 non-frail, 1907 prefrail, 517 frail); at follow up, 1282 were non-frail, 1108 were prefrail, 318 were frail and 1936 had dropped out or were unable to complete all tests for frailty. Transition probabilities for those prefrail at baseline, measured at wave 4 were respectively 0.176, 0.286, 0.096 and 0.442 to non-frail, prefrail, frail and dead/dropped out. Interpolated transition probabilities were 0.159, 0.494, 0.113 and 0.234 at two years, and 0.108, 0.688, 0.087 and 0.117 at one year. Required sample sizes for a two-year outcome in a two-arm trial were between 1040 and 7242 for transition from prefrailty to frailty alone, 246 to 1630 for transition to the composite measure, and 76 to 354 using the composite measure with an ordinal logistic regression approach. Conclusion Use of a composite outcome for frailty trials offers reduced sample sizes and could ameliorate the effect of high loss to follow up inherent in such trials due to death and illness.

ObjectiveTo determine whether a simple small vessel disease (SVD) score, which uses information available on rapid visual assessment of clinical MRI scans, predicts risk of cognitive decline and dementia, above that provided by simple clinical measures.MethodsThree prospective longitudinal cohort studies (SCANS [St George's Cognition and Neuroimaging in Stroke], RUN DMC [Radboud University Nijmegen Diffusion Imaging and Magnetic Resonance Imaging Cohort], and the ASPS [Austrian Stroke Prevention Study]), which covered a range of SVD severity from mild and asymptomatic to severe and symptomatic, were included. In all studies, MRI was performed at baseline, cognitive tests repeated during follow-up, and progression to dementia recorded prospectively. Outcome measures were cognitive decline and onset of dementia during follow-up. We determined whether the SVD score predicted risk of cognitive decline and future dementia. We also determined whether using the score to select a group of patients with more severe disease would reduce sample sizes for clinical intervention trials.ResultsIn a pooled analysis of all 3 cohorts, the score improved prediction of dementia (area under the curve [AUC], 0.85; 95% confidence interval [CI], 0.81–0.89) compared with that from clinical risk factors alone (AUC, 0.76; 95% CI, 0.71–0.81). Predictive performance was higher in patients with more severe SVD. Power calculations showed selecting patients with a higher score reduced sample sizes required for hypothetical clinical trials by 40%–66% depending on the outcome measure used.ConclusionsA simple SVD score, easily obtainable from clinical MRI scans and therefore applicable in routine clinical practice, aided prediction of future dementia risk.

Background Adaptive designs are a wide class of methods focused on improving the power, efficiency and participant benefit of clinical trials. They do this through allowing information gathered during the trial to be used to make changes in a statistically robust manner – the changes could include which treatment arms patients are enrolled to (e.g. dropping non-promising treatment arms), the allocation ratios, the target sample size or the enrolment criteria of the trial. Generally, we are enthusiastic about adaptive designs and advocate their use in many clinical situations. However, they are not always advantageous. In some situations, they provide little efficiency advantage or are even detrimental to the quality of information provided by the trial. In our experience, factors that reduce the efficiency of adaptive designs are routinely downplayed or ignored in methodological papers, which may lead researchers into believing they are more beneficial than they actually are. Main text In this paper, we discuss situations where adaptive designs may not be as useful, including situations when the outcomes take a long time to observe, when dropping arms early may cause issues and when increased practical complexity eliminates theoretical efficiency gains. Conclusion Adaptive designs often provide notable efficiency benefits. However, it is important for investigators to be aware that they do not always provide an advantage. There should always be careful consideration of the potential benefits and disadvantages of an adaptive design.

BackgroundDespite progress that has been made in the treatment of many immune-mediated inflammatory diseases (IMIDs), there remains a need for improved treatments. Randomised controlled trials (RCTs) provide the highest form of evidence on the effectiveness of a potential new treatment regimen, but they are extremely expensive and time consuming to conduct. Consequently, much focus has been given in recent years to innovative design and analysis methods that could improve the efficiency of RCTs. In this article, we review the current use and future potential of these methods within the context of IMID trials.MethodsWe provide a review of several innovative methods that would provide utility in IMID research. These include novel study designs (adaptive trials, Sequential Multi-Assignment Randomised Trials, basket, and umbrella trials) and data analysis methodologies (augmented analyses of composite responder endpoints, using high-dimensional biomarker information to stratify patients, and emulation of RCTs from routinely collected data). IMID trials are now well-placed to embrace innovative methods. For example, well-developed statistical frameworks for adaptive trial design are ready for implementation, whilst the growing availability of historical datasets makes the use of Bayesian methods particularly applicable.To assess whether and how these innovative methods have been used in practice, we conducted a review via PubMed of clinical trials pertaining to any of 51 IMIDs that were published between 2018 and 20 in five high impact factor clinical journals.ResultsAmongst 97 articles included in the review, 19 (19.6%) used an innovative design method, but most of these were relatively straightforward examples of innovative approaches. Only two (2.1%) reported the use of evidence from routinely collected data, cohorts, or biobanks. Eight (9.2%) collected high-dimensional data.ConclusionsApplication of innovative statistical methodology to IMID trials has the potential to greatly improve efficiency, to generalise and extrapolate trial results, and to further personalise treatment strategies. Currently, such methods are infrequently utilised in practice. New research is required to ensure that IMID trials can benefit from the most suitable methods.

Hyperpolarized 13C-MRI is an emerging tool for probing tissue metabolism by measuring 13C-label exchange between intravenously injected hyperpolarized [1–13C]pyruvate and endogenous tissue lactate. Here, we demonstrate that hyperpolarized 13C-MRI can be used to detect early response to neoadjuvant therapy in breast cancer. Seven patients underwent multiparametric 1H-MRI and hyperpolarized 13C-MRI before and 7–11 days after commencing treatment. An increase in the lactate-to-pyruvate ratio of approximately 20% identified three patients who, following 5–6 cycles of treatment, showed pathological complete response. This ratio correlated with gene expression of the pyruvate transporter MCT1 and lactate dehydrogenase A (LDHA), the enzyme catalyzing label exchange between pyruvate and lactate. Analysis of approximately 2,000 breast tumors showed that overexpression of LDHA and the hypoxia marker CAIX was associated with reduced relapse-free and overall survival. Hyperpolarized 13C-MRI represents a promising method for monitoring very early treatment response in breast cancer and has demonstrated prognostic potential. Significance: Hyperpolarized carbon-13 MRI allows response assessment in patients with breast cancer after 7–11 days of neoadjuvant chemotherapy and outperformed state-of-the-art and research quantitative proton MRI techniques.

Objectives Evidence suggests that factors beyond disease activity associate with functional disability in RA. The primary study objective was to explore associations between comorbidities, sociodemographic factors and functional outcomes at five and 10 years. Methods RA patients from two UK prospective cohorts were grouped into low ( Results In total, 2701 RA patients were recruited (mean age 56.1 years, 66.9% female). A total of 1718 (63.4%) had five-year and 820 (30.4%) 10-year follow-up data. In multivariable analysis, no association was found between RDCI and HAQ ≥ 1.5 at five or 10 years. Sociodemographic factors (increased age at disease onset, female gender, minority ethnicity) were associated with higher odds of HAQ ≥ 1.5 at five and 10 years, with worse deprivation additionally associated with HAQ ≥ 1.5 at 10 years (OR 0.79, 95% CI: 0.69, 0.90). Conclusion Comorbidities at baseline have not been found to be associated with worse RA functional outcome in the long-term. On the other hand, sociodemographic factors, independently of disease measures, are associated with worse functional outcome in RA at five and 10 years, in models adjusting for comorbidity burden. Tailoring management interventions according to not only clinical disease parameters but also patient sociodemographic factors may improve long-term outcomes including functional disability.

External pilot trials of complex interventions are used to help determine if and how a confirmatory trial should be undertaken, providing estimates of parameters such as recruitment, retention, and adherence rates. The decision to progress to the confirmatory trial is typically made by comparing these estimates to pre-specified thresholds known as progression criteria, although the statistical properties of such decision rules are rarely assessed. Such assessment is complicated by several methodological challenges, including the simultaneous evaluation of multiple endpoints, complex multi-level models, small sample sizes, and uncertainty in nuisance parameters. In response to these challenges, we describe a Bayesian approach to the design and analysis of external pilot trials. We show how progression decisions can be made by minimizing the expected value of a loss function, defined over the whole parameter space to allow for preferences and trade-offs between multiple parameters to be articulated and used in the decision-making process. The assessment of preferences is kept feasible by using a piecewise constant parametrization of the loss function, the parameters of which are chosen at the design stage to lead to desirable operating characteristics. We describe a flexible, yet computationally intensive, nested Monte Carlo algorithm for estimating operating characteristics. The method is used to revisit the design of an external pilot trial of a complex intervention designed to increase the physical activity of care home residents.

Objectives The primary objective of MATIS is to determine the efficacy of ruxolitinib (RUX) or fostamatinib (FOS) compared to standard of care (SOC) with respect to reducing the proportion of hospitalised patients progressing from mild or moderate to severe COVID-19 pneumonia. Secondary objectives, at 14 and 28 days, are to: Determine the efficacy of RUX or FOS to reduce mortality Determine the efficacy of RUX or FOS to reduce the need for invasive ventilation or ECMO Determine the efficacy of RUX or FOS to reduce the need for non-invasive ventilation Determine the efficacy of RUX or FOS to reduce the proportion of participants suffering significant oxygen desaturation Determine the efficacy of RUX or FOS to reduce the need for renal replacement therapy Determine the efficacy of RUX and FOS to reduce the incidence of venous thromboembolism Determine the efficacy of RUX and FOS to reduce the severity of COVID-19 pneumonia [graded by a 9-point modified WHO Ordinal Scale* Determine the efficacy of RUX or FOS to reduce systemic inflammation Determine the efficacy of RUX or FOS to the incidence of renal impairment Determine the efficacy of RUX or FOS to reduce duration of hospital stay Evaluate the safety of RUX and FOS for treatment of COVID-19 pneumonia. Trial design A multi-arm, multi-stage (3-arm parallel-group, 2-stage) randomised controlled trial that allocates participants 1:1:1 and tests for superiority in experimental arms versus standard of care. Participants Patients will be recruited while inpatients during hospitalisation for COVID-19 in multiple centres throughout the UK including Imperial College Healthcare NHS Trust. INCLUSION: Patients age ≥ 18 years at screening Patients with mild or moderate COVID-19 pneumonia, defined as Grade 3 or 4 severity by the WHO COVID-19 Ordinal Scale Patients meeting criteria: Hospitalization AND SARS-CoV2 infection (clinically suspected or laboratory confirmed) AND Radiological change consistent with COVID-19 disease CRP ≥ 30mg/L at any time point Informed consent from patient or personal or professional representative Agreement to abstain from sexual intercourse or use contraception that is >99% effective for all participants of childbearing potential for 42 days after the last dose of study drug. For male participants, agreement to abstain from sperm donation for 42 days after the last dose of study drug. EXCLUSION: Requiring either invasive or non-invasive ventilation including CPAP or high flow nasal oxygen at any point after hospital admission but before baseline, not related to a pre-existing condition (e.g., obstructive sleep apnoea) Grade ≥ 5 severity on the modified WHO COVID-19 Ordinal Scale, i.e. SpO2 < 90% on ≥ 60% inspired oxygen by facemask at baseline; non-invasive ventilation; or invasive mechanical ventilation In the opinion of the investigator, progression to death is inevitable within the next 24 hours, irrespective of the provision of therapy Known severe allergic reactions to the investigational agents Child-Pugh B or C grade hepatic dysfunction Use of drugs within the preceding 14 days that are known to interact with any study treatment (FOS or RUX), as listed in the Summary of Product Characteristics Pregnant or breastfeeding Any medical condition or concomitant medication that in the opinion of the investigator would compromise subjects’ safety or compliance with study procedures. Any medical condition which in the opinion of the principal investigator would compromise the scientific integrity of the study Non-English speakers will be able to join the study. If participants are unable to understand verbal or written information in English, then hospital translation services will be requested at the participating site for the participant where possible. Intervention and comparator RUXOLITINIB (RUX) (14 days): An oral selective and potent inhibitor of Janus Associated Kinases (JAK1 and JAK2) and cell proliferation (Verstovek, 2010). It is approved for the treatment of disease-related splenomegaly or constitutional symptoms in myelofibrosis, polycythaemia vera and graft-versus-host-disease. RUX will be administered orally 10mg bd Day 1-7 and 5mg bd Day 8-14. FOSTAMATINIB (FOS) (14 days): An oral spleen tyrosine kinase inhibitor approved for the treatment of thrombocytopenia in adult participants with chronic immune thrombocytopenia. FOS will be administered orally 150mg bd Day 1-7 and 100mg bd Day 8-14. Please see protocol for recommended dose modifications where required. COMPARATOR (Standard of Care, SOC): experimental arms will be compared to participants receiving standard of care. It is accepted that SOC may change during a rapidly evolving pandemic. Co-enrolment to other trials and rescue therapy, either pre- or post-randomisation, is permitted and will be accounted for in the statistical analysis. Main outcomes Pairwise comparison (RUX vs SOC and FOS vs SOC) of the proportion of participants diagnosed with severe COVID-19 pneumonia within 14 days. Severe COVID-19 pneumonia is defined by a score ≥ 5 on a modified WHO COVID-19 Ordinal Scale, comprising the following indicators of disease severity: Death OR Requirement for invasive ventilation OR Requirement for non-invasive ventilation including CPAP or high flow oxygen OR O2 saturation < 90% on ≥60% inspired oxygen Randomisation Participants will be allocated to interventions using a central web-based randomisation service that generates random sequences using random permuted blocks (1:1:1), with stratification by age ( Blinding (masking) No participants or caregivers are blinded to group assignment. Clinical outcomes will be compared blind to group assignment. Numbers to be randomised (sample size) For an early informal dose examination by the Data Monitoring Committee a minimum of 30 participants will be recruited. For Stage 1 of this multi-arm multi-stage study, 171 participants will be randomised, with 57 participants in each arm. If at least one experimental intervention shows promise, then Stage 2 will recruit a further 95 participants per arm. Sample size calculations are given in the protocol. Trial Status Recruitment is ongoing and started 2nd October 2020. We anticipate completion of Stage 1 by July 2021 and Stage 2 by April 2022. The current protocol version 2.0 of 11th February 2021 is appended. Trial registration EudraCT: 2020-001750-22, 9th July 2020 ClinicalTrials.gov: NCT04581954, 9th October 2020 Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest of expediting dissemination of this material, familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Umbrella trials are an innovative trial design where different treatments are matched with subtypes of a disease, with the matching typically based on a set of biomarkers. Consequently, when patients can be positive for more than one biomarker, they may be eligible for multiple treatment arms. In practice, different approaches could be applied to allocate patients who are positive for multiple biomarkers to treatments. However, to date there has been little exploration of how these approaches compare statistically. We conduct a simulation study to compare five approaches to handling treatment allocation in the presence of multiple biomarkers - equal randomisation; randomisation with fixed probability of allocation to control; Bayesian adaptive randomisation (BAR); constrained randomisation; and hierarchy of biomarkers. We evaluate these approaches under different scenarios in the context of a hypothetical phase II biomarker-guided umbrella trial. We define the pairings representing the pre-trial expectations on efficacy as linked pairs, and the other biomarker-treatment pairings as unlinked. The hierarchy and BAR approaches have the highest power to detect a treatment-biomarker linked interaction. However, the hierarchy procedure performs poorly if the pre-specified treatment-biomarker pairings are incorrect. The BAR method allocates a higher proportion of patients who are positive for multiple biomarkers to promising treatments when an unlinked interaction is present. In most scenarios, the constrained randomisation approach best balances allocation to all treatment arms. Pre-specification of an approach to deal with treatment allocation in the presence of multiple biomarkers is important, especially when overlapping subgroups are likely.

Background: Iron deficiency anaemia (IDA) is the leading cause of years lost to disability in most sub-Saharan African countries and is especially common in young children. The IHAT-GUT trial assessed the efficacy and safety of a novel nano iron supplement, which is a dietary ferritin analogue termed iron hydroxide adipate tartrate (IHAT), for the treatment of IDA in children under 3 years of age. Methods: In this single-centre, randomised, double-blind, parallel, placebo-controlled, non-inferiority study in The Gambia, children 6-35 months with IDA (7£Hb

Background Antisocial personality disorder (ASPD), although associated with very significant health and social burden, is an under-researched mental disorder for which clinically effective and cost-effective treatment methods are urgently needed. No intervention has been established for prevention or as the treatment of choice for this disorder. Mentalization-based treatment (MBT) is a psychotherapeutic treatment that has shown some promising preliminary results for reducing personality disorder symptomatology by specifically targeting the ability to recognize and understand the mental states of oneself and others, an ability that is compromised in people with ASPD. This paper describes the protocol of a multi-site RCT designed to test the effectiveness and cost-effectiveness of MBT for reducing aggression and alleviating the wider symptoms of ASPD in male offenders subject to probation supervision who fulfil diagnostic criteria for ASPD. Methods Three hundred and two participants recruited from a pool of offenders subject to statutory supervision by the National Probation Service at 13 sites across the UK will be randomized on a 1:1 basis to 12 months of probation plus MBT or standard probation as usual, with follow-up to 24 months post-randomization. The primary outcome is frequency of aggressive antisocial behaviour as assessed by the Overt Aggression Scale – Modified. Secondary outcomes include violence, offending rates, alcohol use, drug use, mental health status, quality of life, and total service use costs. Data will be gathered from police and criminal justice databases, NHS record linkage, and interviews and self-report measures administered to participants. Primary analysis will be on an intent-to-treat basis; per-protocol analysis will be undertaken as secondary analysis. The primary outcome will be analysed using hierarchical mixed-effects linear regression. Secondary outcomes will be analysed using mixed-effects linear regression, mixed-effects logistic regression, and mixed-effects Poisson models for secondary outcomes depending on whether the outcome is continuous, binary, or count data. A cost-effectiveness and cost-utility analysis will be undertaken. Discussion This definitive, national, multi-site trial is of sufficient size to evaluate MBT to inform policymakers, service commissioners, clinicians, and service users about its potential to treat offenders with ASPD and the likely impact on the population at risk. Trial registration ISRCTN 32309003. Registered on 8 April 2016.

ObjectiveTo provide guidance to researchers, funders, regulators and study delivery teams to ensure that research on COVID-19 is inclusive, particularly of groups disproportionately affected by COVID-19 and who may have been historically under-served by research.Summary of key pointsGroups who are disproportionately affected by COVID-19 include (but are not limited to) older people, people with multiple long-term conditions, people with disabilities, people from Black, Asian and Ethnic minority groups, people living with obesity, people who are socioeconomically deprived and people living in care homes. All these groups are under-served by clinical research, and there is an urgent need to rectify this if COVID-19 research is to deliver relevant evidence for these groups who are most in need. We provide a framework and checklists for addressing key issues when designing and delivering inclusive COVID-19 research, based on the National Institute for Health Research INnovations in CLinical trial design and delivery for the UnDEr-served project roadmap. Strong community engagement, codevelopment and prioritisation of research questions and interventions are essential. Under-served groups should be represented on funding panels and ethics committees, who should insist on the removal of barriers to participation. Exclusion criteria should be kept to a minimum; intervention delivery and outcome measurement should be simple, flexible and tailored to the needs of different groups, and local advice on the best way to reach and engage with under-served communities should be taken by study delivery teams. Data on characteristics that allow identification of under-served groups must be collected, analyses should include these data to enable subgroup comparisons and results should be shared with under-served groups at an early stage.ConclusionInclusive COVID-19 research is a necessity, not a luxury, if research is to benefit all the communities it seeks to serve. It requires close engagement with under-served groups and attention to aspects of study topic, design, delivery, analysis and dissemination across the research life cycle.

There is the potential for high-dimensional information about patients collected in clinical trials (such as genomic, imaging, and data from wearable technologies) to be informative for the efficacy of a new treatment in situations where only a subset of patients benefits from the treatment. The adaptive signature design (ASD) method has been proposed for developing and testing the efficacy of a treatment in a high-efficacy patient group (the sensitive group) using genetic data. The method requires selection of three tuning parameters which may be highly computationally expensive. We propose a variation to the ASD method, the cross-validated risk scores (CVRS) design method, that does not require selection of any tuning parameters. The method is based on computing a risk score for each patient and dividing them into clusters using a nonparametric clustering procedure. We assess the properties of CVRS against the originally proposed cross-validated ASD using simulation data and a real psychiatry trial. CVRS, as assessed for various sample sizes and response rates, has a substantial reduction in the computational time required. In many simulation scenarios, there is a substantial improvement in the ability to correctly identify the sensitive group and the power of the design to detect a treatment effect in the sensitive group. We illustrate the application of the CVRS method on the psychiatry trial.

INTRODUCTION: The value of antineutrophil cytoplasmic antibody (ANCA) measurements among patients with an established diagnosis of ANCA-associated vasculitis (AAV) to assess disease activity or predict relapse remains controversial, but recent evidence suggests a possible role for rituximab-treated patients. PATIENTS AND METHODS: All patients with active vasculitis and positive proteinase 3 (PR3)–ANCA who were starting a 2-year treatment course of rituximab for induction of remission at Addenbrooke’s Hospital between January 2011 and January 2016 were included in this study. Common department practice consists of 6 g of rituximab given over 2 years, concomitant corticosteroids (0.5–1.0 mg/kg) with rapid taper over 3 months, and cessation of oral maintenance immunosuppressive agents at time of first rituximab dose. Clinical and laboratory data were collected retrospectively using electronic patient records. RESULTS: Fifty-seven patients with current PR3-ANCA positivity were included in the analysis. Median follow-up was 59 months. PR3-ANCA negativity was achieved in 25 patients (44%) with a median time of 14 months. Clinical remission was achieved in 53 patients (93%) with a median time of 3 months. Among the 53 patients who achieved remission during follow-up, 24 (45%) relapsed with a median time to relapse of 36 months from remission. Both PR3-ANCA–negative status and 50% reduction in PR3-ANCA from baseline (as time-varying covariates) were significantly associated with a longer time to relapse (PR3-ANCA–negative status: hazards ratio, 0.08 [95% confidence interval, 0.01–0.63, p = 0.016]; 50% reduction in PR3-ANCA: hazards ratio, 0.25 [95% confidence interval, 0.18–0.99, p = 0.046]). CONCLUSIONS: Achieving and maintaining PR3-ANCA negativity after rituximab was associated with longer-lasting remission.

Background Participants in clinical research studies often do not reflect the populations for which healthcare interventions are needed or will be used. Enhancing representation of under-served groups in clinical research is important to ensure that research findings are widely applicable. We describe a multicomponent workstream project to improve representation of under-served groups in clinical trials. Methods The project comprised three main strands: (1) a targeted scoping review of literature to identify previous work characterising under-served groups and barriers to inclusion, (2) surveys of professional stakeholders and participant representative groups involved in research delivery to refine these initial findings and identify examples of innovation and good practice and (3) a series of workshops bringing together key stakeholders from funding, design, delivery and participant groups to reach consensus on definitions, barriers and a strategic roadmap for future work. The work was commissioned by the UK National Institute for Health Research Clinical Research Network. Output from these strands was integrated by a steering committee to generate a series of goals, workstream plans and a strategic roadmap for future development work in this area. Results ‘Under-served groups’ was identified and agreed by the stakeholder group as the preferred term. Three-quarters of stakeholders felt that a clear definition of under-served groups did not currently exist; definition was challenging and context-specific, but exemplar groups (e.g. those with language barriers or mental illness) were identified as under-served. Barriers to successful inclusion of under-served groups could be clustered into communication between research teams and participant groups; how trials are designed and delivered, differing agendas of research teams and participant groups; and lack of trust in the research process. Four key goals for future work were identified: building long-term relationships with under-served groups, developing training resources to improve design and delivery of trials for under-served groups, developing infrastructure and systems to support this work and working with funders, regulators and other stakeholders to remove barriers to inclusion. Conclusions The work of the INCLUDE group over the next 12 months will build on these findings by generating resources customised for different under-served groups to improve the representativeness of trial populations.

Background Clinical trials and other studies commonly assess the effectiveness of an intervention through the use of responder-based endpoints. These classify patients based on whether they meet a number of criteria which often involve continuous variables categorised as being above or below a threshold. The proportion of patients who are responders is estimated and, where relevant, compared between groups. An alternative method called the augmented binary method keeps the definition of the endpoint the same but utilises information contained within the continuous component to increase the power considerably (equivalent to increasing the sample size by > 30%). In this article we summarise the method and investigate the variety of clinical conditions that use endpoints to which it could be applied. Methods We reviewed a database of core outcome sets (COSs) that covered physiological and mortality trial endpoints recommended for collection in clinical trials of different disorders. We identified responder-based endpoints where the augmented binary method would be useful for increasing power. Results Out of the 287 COSs reviewed, we identified 67 new clinical areas where endpoints were used that would be more efficiently analysed using the augmented binary method. Clinical areas that had particularly high numbers were rheumatology (11 clinical disorders identified), non-solid tumour oncology (10 identified), neurology (9 identified) and cardiovascular (8 identified). Conclusions The augmented binary method can potentially provide large benefits in a vast array of clinical areas. Further methodological development is needed to account for some types of endpoints.

IntroductionDiabetes affects more than 425 million people worldwide with a lifetime risk of diabetic foot ulcer (DFU) of up to 25%. Management includes wound debridement, wound dressings, offloading, treatment of infection and ischaemia, optimising glycaemic control; use of advanced adjuvant therapies is limited by high cost and lack of robust evidence.Methods and analysisA multicentre, seamless phase II/III, open, parallel group, multi-arm multi-stage randomised controlled trial in patients with a hard-to-heal DFU, with blinded outcome assessment. A maximum of 447 participants will be randomised (245 participants in phase II and 202 participants in phase III). The phase II primary objective will determine the efficacy of treatment strategies including hydrosurgical debridement ± decellularised dermal allograft, or the combination with negative pressure wound therapy, as an adjunct to treatment as usual (TAU), compared with TAU alone, with patients randomised in a 1:1:1:2 allocation. The outcome is achieving at least 50% reduction in index ulcer area at 4 weeks post randomisation.The phase III primary objective will determine whether one treatment strategy, continued from phase II, reduces time to healing of the index ulcer compared with TAU alone, with participants randomised in a 1:1 allocation. Secondary objectives will compare healing status of the index ulcer, infection rate, reulceration, quality of life, cost-effectiveness and incidence of adverse events over 52 weeks post randomisation. Phase II and phase III primary endpoint analysis will be conducted using a mixed-effects logistic regression model and Cox proportional hazards regression, respectively. A within-trial economic evaluation will be undertaken; the primary economic analysis will be a cost-utility analysis presenting ICERs for each treatment strategy in rank order of effectiveness, with effects expressed as quality-adjusted life years.The trial has predefined progression criteria for the selection of one treatment strategy into phase III based on efficacy, safety and costs at 4 weeks.Ethics and disseminationEthics approval has been granted by the National Research Ethics Service (NRES) Committee Yorkshire and The Humber - Bradford Leeds Research Ethics Committee; approved 26 April 2017; (REC reference: 17/YH/0055). There is planned publication of a monograph in National Institute for Health Research journals and main trial results and associated papers in high-impact peer-reviewed journals.Trial registration numberISRCTN64926597; registered on 6 June 2017

Summary Background Adolescent antisocial behaviour is a major health and social problem. Studies in the USA have shown that multisystemic therapy reduces such behaviour and the number of criminal offences committed by this group. However, findings outside the USA are equivocal. We aimed to assess the effectiveness and cost-effectiveness of multisystemic therapy versus management as usual in the treatment of adolescent antisocial behaviour. Methods We did an 18 month, multisite, pragmatic, randomised controlled, superiority trial in England. Eligible participants aged 11–17 years with moderate-to-severe antisocial behaviour had at least three severity criteria indicating past difficulties across several settings and one of five general inclusion criteria for antisocial behaviour. We randomly assigned families (1:1) using stochastic minimisation, stratifying for treatment centre, sex, age at enrolment to study, and age at onset of antisocial behaviour, to receive either management as usual or 3–5 months of multisystemic therapy followed by management as usual. Research assistants and investigators were masked to treatment allocation; the participants could not be masked. The primary outcome was out-of-home placement at 18 months. The primary analysis included all randomised participants for whom data were available. This trial is registered, number ISRCTN77132214. Follow-up of the trial is still ongoing. Findings Between Feb 4, 2010, and Sept 1, 2012, 1076 families were referred to nine multi-agency panels, 684 of whom were assigned to management as usual (n=342) or multisystemic therapy followed by management as usual (n=342). At 18 months, the proportion of participants in out-of-home placement was not significantly different between the groups (13% [43/340] in the multisystemic therapy group vs 11% [36/335] in the management-as-usual group; odds ratio 1·25, 95% CI 0·77–2·05; p=0·37). Interpretation The findings do not support that multisystemic therapy should be used over management as usual as the intervention of choice for adolescents with moderate-to-severe antisocial behaviour. Funding Department for Children, Schools and Families, Department of Health.

In many phase II trials in solid tumours, patients are assessed using endpoints based on the Response Evaluation Criteria in Solid Tumours (RECIST) scale. Often, analyses are based on the response rate. This is the proportion of patients who have an observed tumour shrinkage above a predefined level and no new tumour lesions. The augmented binary method has been proposed to improve the precision of the estimator of the response rate. The method involves modelling the tumour shrinkage to avoid dichotomising it. However, in many trials the best observed response is used as the primary outcome. In such trials, patients are followed until progression, and their best observed RECIST outcome is used as the primary endpoint. In this paper, we propose a method that extends the augmented binary method so that it can be used when the outcome is best observed response. We show through simulated data and data from a real phase II cancer trial that this method improves power in both single‐arm and randomised trials. The average gain in power compared to the traditional analysis is equivalent to approximately a 35% increase in sample size. A modified version of the method is proposed to reduce the computational effort required. We show this modified method maintains much of the efficiency advantages.

Background Multi-arm designs provide an effective means of evaluating several treatments within the same clinical trial. Given the large number of treatments now available for testing in many disease areas, it has been argued that their utilisation should increase. However, for any given clinical trial there are numerous possible multi-arm designs that could be used, and choosing between them can be a difficult task. This task is complicated further by a lack of available easy-to-use software for designing multi-arm trials. Results To aid the wider implementation of multi-arm clinical trial designs, we have developed a web application for sample size calculation when using a variety of popular multiple comparison corrections. Furthermore, the application supports sample size calculation to control several varieties of power, as well as the determination of optimised arm-wise allocation ratios. It is built using the Shiny package in the R programming language, is free to access on any device with an internet browser, and requires no programming knowledge to use. It incorporates a variety of features to make it easier to use, including help boxes and warning messages. Using design parameters motivated by a recently completed phase II oncology trial, we demonstrate that the application can effectively determine and evaluate complex multi-arm trial designs. Conclusions The application provides the core information required by statisticians and clinicians to review the operating characteristics of a chosen multi-arm clinical trial design. The range of designs supported by the application is broader than other currently available software solutions. Its primary limitation, particularly from a regulatory agency point of view, is its lack of validation. However, we present an approach to efficiently confirming its results via simulation.

Phase II clinical trials of experimental treatments play an essential role in drug development. Historically, trials were conducted sequentially, starting from a phase I trial in which dose and safety are evaluated advancing to phase II, looking for some sign of efficacy on a short-term end-point such as tumour shrinkage to screen out inefficacious experimental agents, and to large-scale randomised phase III trials evaluating properly the efficacy of a new treatment on objective clinical end-points. To expedite this process, phase II trials historically used single-arm designs to treat patients with experimental therapies only [1]. However, the overall success rate of drug development programs in oncology from the start of phase I to registration has been estimated recently to be only 3.4%, much lower compared with that of other diseases [2]. Part of this low success rate has been argued to be due to suboptimal use of randomised trial designs in the phase II space.

BackgroundIn hospitalised patients with exacerbation of Chronic Obstructive Pulmonary Disease, European and British guidelines endorse oxygen target saturations of 88%–92%, with adjustment to 94%–98% if carbon dioxide levels are normal. We assessed the impact of admission oxygen saturation level and baseline carbon dioxide on inpatient mortality.MethodsPatients were identified from the prospective Dyspnoea, Eosinopenia, Consolidation, Acidaemia and Atrial Fibrillation (DECAF) derivation study (December 2008–June 2010) and the mixed methods DECAF validation study (January 2012 to May 2014). In six UK hospitals, of 2645 patients with COPD exacerbation, 1027 patients were in receipt of supplemental oxygen at admission. All had a clinical history of COPD and obstructive spirometry. These patients were subdivided into the following groups: admission oxygen saturations of 87% or less, 88%–92%, 93%–96% or 97%–100%. Inpatient mortality was calculated for each group and expressed as ORs. The DECAF score and National Early Warning Score 2 (excluding oxygen saturation) were used in binary logistic regression to adjust for baseline risk.ResultsIn patients with COPD receiving supplemental oxygen, oxygen saturations above 92% were associated with higher mortality and an adverse dose–response. Compared with the 88%–92% group, the adjusted risk of death (OR) in the 93%–96% and 97%–100% groups was 1.98 (95% CI 1.09 to 3.60, p=0.025) and 2.97 (95% CI 1.58 to 5.58, p=0.001). In the subgroup with normocapnia, the mortality signal remained significant in both the 93%–96% and 97%–100% groups.ConclusionsInpatient mortality was lowest in those with oxygen saturations of 88%–92%. Even modest elevations in oxygen saturations above this range (93%–96%) were associated with an increased risk of death. A similar mortality trend was seen in both patients with hypercapnia and normocapnia. This shows that the practice of setting different target saturations based on carbon dioxide levels is not justified. Treating all patients with COPD with target saturations of 88%–92% will simplify prescribing and should improve outcome.Trial registration numberUKCRN ID 14214.

Background: The development of a nurse-led approach to managing epilepsy in adults with an intellectual disability offers the potential of improved outcomes and lower costs of care. We undertook a cluster randomised trial to assess the impact on costs and outcomes of the provision of intellectual disability nurses working to a designated epilepsy nurse competency framework. Here, we report the impact of the intervention on costs. Method: Across the UK, 8 sites randomly allocated to the intervention recruited 184 participants, 9 sites allocated to treatment as usual recruited 128 participants. Cost and outcome data were collected mainly by telephone interview at baseline and after six months. Total costs at six months were compared from the perspective of health & social services, and society, with adjustments for pre-specified participant and cluster characteristics at baseline including costs. Missing data was imputed using Multiple Imputation. Uncertainty was quantified by bootstrapping. Results: The intervention was associated with lower per participant costs from a health & social services perspective of -£357 (2014/15 GBP) (95% CI -£986, £294) and from a societal perspective of -£631 (95% CI -£1,473, £181). Results were not sensitive to the exclusion of accommodation costs. Conclusions: Our findings suggest that the competency framework is unlikely to increase the cost of caring for people with epilepsy and intellectual disability and may reduce costs., This paper presents independent research commissioned by the National Institute for Health Research (NIHR) under its Health Technology Assessment Programme (Grant 10/104/16 PI Dr H Ring). During the time that this research was carried out, H Ring also received support from the NIHR Collaboration for Leadership in Applied Health Research and Care (CLAHRC) East of England at Cambridgeshire and Peterborough NHS Foundation Trust.

ObjectiveClear information is essential to properly determine preference in medical intervention. In neovascular age-related macular degeneration, patients need to understand the balance of risk and benefit of anti-vascular endothelial growth factor (VEGF) treatment. This balance is altered by the number of injections administered.MethodsNatural frequencies, displayed as pictographically as icon arrays, are used to show material outcomes from the MARINA and HARBOR (12 months) trials. We also calculated the number needed to treat (NNT) and number needed to harm (NNH).ResultsMARINA 24-month data show the absolute risk reduction is 37% and the NNT is 3; meaning for one patient to benefit three need to be treated.12 months’ HARBOR data show that compared with as-needed treatment, scheduled monthly injection treatment increases the number of patients achieving a better visual outcome. The number of patients suffering harm is also increased by the additional injections.ConclusionDisplaying MARINA and HARBOR trial data as natural frequencies, with numbers needed to treat and harm, communicates complimentary information on the positive and negative aspects of anti-VEGF treatment.

Potential predictive biomarkers are often measured on a continuous scale, but in practice, a threshold value to divide the patient population into biomarker 'positive' and 'negative' is desirable. Early phase clinical trials are increasingly using biomarkers for patient selection, but at this stage, it is likely that little will be known about the relationship between the biomarker and the treatment outcome. We describe a single-arm trial design with adaptive enrichment, which can increase power to demonstrate efficacy within a patient subpopulation, the parameters of which are also estimated. Our design enables us to learn about the biomarker and optimally adjust the threshold during the study, using a combination of generalised linear modelling and Bayesian prediction. At the final analysis, a binomial exact test is carried out, allowing the hypothesis that 'no population subset exists in which the novel treatment has a desirable response rate' to be tested. Through extensive simulations, we are able to show increased power over fixed threshold methods in many situations without increasing the type-I error rate. We also show that estimates of the threshold, which defines the population subset, are unbiased and often more precise than those from fixed threshold studies. We provide an example of the method applied (retrospectively) to publically available data from a study of the use of tamoxifen after mastectomy by the German Breast Study Group, where progesterone receptor is the biomarker of interest. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Objective. In clinical trials of RA, it is common to assess effectiveness using end points based upon dichotomized continuous measures of disease activity, which classify patients as responders or non-responders. Although dichotomization generally loses statistical power, there are good clinical reasons to use these end points; for example, to allow for patients receiving rescue therapy to be assigned as non-responders. We adopt a statistical technique called the augmented binary method to make better use of the information provided by these continuous measures and account for how close patients were to being responders. Methods. We adapted the augmented binary method for use in RA clinical trials. We used a previously published randomized controlled trial (Oral SyK Inhibition in Rheumatoid Arthritis-1) to assess its performance in comparison to a standard method treating patients purely as responders or non-responders. The power and error rate were investigated by sampling from this study. Results. The augmented binary method reached similar conclusions to standard analysis methods but was able to estimate the difference in response rates to a higher degree of precision. Results suggested that CI widths for ACR responder end points could be reduced by at least 15%, which could equate to reducing the sample size of a study by 29% to achieve the same statistical power. For other end points, the gain was even higher. Type I error rates were not inflated. Conclusion. The augmented binary method shows considerable promise for RA trials, making more efficient use of patient data whilst still reporting outcomes in terms of recognized response end points.

When misfolded proteins accumulate in the endoplasmic reticulum (ER), the cell is said to experience ER stress. This triggers an unfolded protein response (UPR) to restore the balance between misfolded proteins and ER chaperones such as BiP. UPR signalling is required for the growth of many solid cancers. In chronic ER stress, factors including CHOP have been shown to mediate cell death. Colorectal adenocarcinoma arises due to progressive changes within pre-malignant lesions. Our aim was to test the hypothesis that the expression of BiP and CHOP correlates with the progression of those pre-malignant lesions. Eighty-one patients with colon neoplasms treated at Rouen University Hospital between January 1, 2003 and January 1, 2013 were randomly selected. The expression of BiP and CHOP was estimated by immunohistochemical staining of a tissue microarray generated from colon cores: normal tissue, low-grade and high-grade adenoma, invasive colon adenocarcinoma and lymph node metastasis of colon adenocarcinoma. In parallel, nine cases comprising areas from normal epithelium to dyplasia to invasive carcinoma and included in the TMA were analysed on whole sections. As colon epithelium shows increasing evidence of pre-malignant and then malignant changes, BiP expression significantly increases (p for trend

Background\ud \ud Adequate reporting of adaptive designs (ADs) maximises their potential benefits in the conduct of clinical trials. Transparent reporting can help address some obstacles and concerns relating to the use of ADs. Currently, there are deficiencies in the reporting of AD trials. To overcome this, we have developed a consensus-driven extension to the CONSORT statement for randomised trials using an AD. This paper describes the processes and methods used to develop this extension rather than detailed explanation of the guideline.\ud \ud \ud Methods\ud \ud We developed the guideline in seven overlapping stages:1)\ud \ud Building on prior research to inform the need for a guideline;\ud \ud \ud \ud 2)\ud \ud A scoping literature review to inform future stages;\ud \ud \ud \ud 3)\ud \ud Drafting the first checklist version involving an External Expert Panel;\ud \ud \ud \ud 4)\ud \ud A two-round Delphi process involving international, multidisciplinary, and cross-sector key stakeholders;\ud \ud \ud \ud 5)\ud \ud A consensus meeting to advise which reporting items to retain through voting, and to discuss the structure of what to include in the supporting explanation and elaboration (E&E) document;\ud \ud \ud \ud 6)\ud \ud Refining and finalising the checklist; and\ud \ud \ud \ud 7)\ud \ud Writing-up and dissemination of the E&E document.\ud \ud \ud \ud \ud The CONSORT Executive Group oversaw the entire development process.\ud \ud \ud Results\ud \ud Delphi survey response rates were 94/143 (66%), 114/156 (73%), and 79/143 (55%) in rounds 1, 2, and across both rounds, respectively. Twenty-seven delegates from Europe, the USA, and Asia attended the consensus meeting. The main checklist has seven new and nine modified items and six unchanged items with expanded E&E text to clarify further considerations for ADs. The abstract checklist has one new and one modified item together with an unchanged item with expanded E&E text. The E&E document will describe the scope of the guideline, the definition of an AD, and some types of ADs and trial adaptations and explain each reporting item in detail including case studies.\ud \ud \ud Conclusions\ud \ud We hope that making the development processes, methods, and all supporting information that aided decision-making transparent will enhance the acceptability and quick uptake of the guideline. This will also help other groups when developing similar CONSORT extensions. The guideline is applicable to all randomised trials with an AD and contains minimum reporting requirements.

Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits. In order to encourage its wide dissemination this article is freely accessible on the BMJ and Trials journal websites.“To maximise the benefit to society, you need to not just do research but do it well” Douglas G Altman

It is often of interest to explore how dose affects the toxicity and efficacy properties of a novel treatment. In oncology, efficacy is often assessed through response, which is defined by a patient having no new tumour lesions and their tumour size shrinking by 30%. Usually response and toxicity are analysed as binary outcomes in early phase trials. Methods have been proposed to improve the efficiency of analysing response by utilising the continuous tumour size information instead of dichotomising it. However, these methods do not allow for toxicity or for different doses. Motivated by a phase II trial testing multiple doses of a treatment against placebo, we propose a latent variable model that can estimate the probability of response and no toxicity (or other related outcomes) for different doses. We assess the confidence interval coverage and efficiency properties of the method, compared to methods that do not use the continuous tumour size, in a simulation study and the real study. The coverage is close to nominal when model assumptions are met, although can be below nominal when the model is misspecified. Compared to methods that treat response as binary, the method has confidence intervals with 30–50% narrower widths. The method adds considerable efficiency but care must be taken that the model assumptions are reasonable.

This cross-sectional study assesses the prevalence of multiplicity and whether appropriate multiplicity adjustments were performed among cardiovascular randomized clinical trials published in 6 medical journals with a high impact factor., Key Points Questions What is the prevalence of multiplicity among cardiovascular randomized clinical trials published in 6 medical journals with a high impact factor, and how frequently are multiplicity adjustments made in these trials? Findings In this cross-sectional study, data were collected from the past issues of 6 journals with high impact factors published between August 1, 2015, and July 31, 2018. Of 511 cardiovascular randomized clinical trials included in this analysis, 300 had some form of multiplicity; of these 300, only 85 adjusted for multiplicity. Meaning Among contemporary cardiovascular randomized clinical trials, it appears that multiplicity adjustments are infrequently reported., Importance Multiple analyses in a clinical trial can increase the probability of inaccurately concluding that there is a statistically significant treatment effect. However, to date, it is unknown how many randomized clinical trials (RCTs) perform adjustments for multiple comparisons, the lack of which could lead to erroneous findings. Objectives To assess the prevalence of multiplicity and whether appropriate multiplicity adjustments were performed among cardiovascular RCTs published in 6 medical journals with a high impact factor. Design, Setting, and Participants In this cross-sectional study, cardiovascular RCTs were selected from all over the world, characterized as North America, Western Europe, multiregional, and rest of the world. Data were collected from past issues of 3 cardiovascular journals (Circulation, European Heart Journal, and Journal of the American College of Cardiology) and 3 general medicine journals (JAMA, The Lancet, and The New England Journal of Medicine) with high impact factors published between August 1, 2015, and July 31, 2018. Supplements and trial protocols of each of the included RCTs were also searched for multiplicity. Data were analyzed December 20 to 27, 2018. Exposures Data from the selected RCTs were extracted and verified independently by 2 researchers using a structured data instrument. In case of disagreement, a third reviewer helped to achieve consensus. An RCT was considered to have multiple treatment groups if it had more than 2 arms; multiple outcomes were defined as having more than 1 primary outcome, and multiple analyses were defined as analysis of the same outcome variable in multiple ways. Multiplicity was examined only for the analysis of the primary end point. Main Outcomes and Measures Outcomes of interest were percentages of primary analyses that performed multiplicity adjustment of primary end points. Results Of 511 cardiovascular RCTs included in this analysis, 300 (58.7%) had some form of multiplicity; of these 300, only 85 (28.3%) adjusted for multiplicity. Intervention type and funding source had no statistically significant association with the reporting of multiplicity risk adjustment. Trials that assessed mortality vs nonmortality outcomes were more likely to contain a multiplicity risk in their primary analysis (66.3% [177 of 267] vs 50.4% [123 of 244]; P

BACKGROUND: Many recent Stroke trials fail to show a beneficial effect of the intervention late in the development. Currently a large number of new treatment options are being developed. Multi-arm multi-stage (MAMS) designs offer one potential strategy to avoid lengthy studies of treatments without beneficial effects while at the same time allowing evaluation of several novel treatments. In this paper we provide a review of what MAMS designs are and argue that they are of particular value for Stroke trials. We illustrate this benefit through a case study based on previous published trials of endovascular treatment for acute ischemic stroke. We show in this case study that MAMS trials provide additional power for the same sample size compared to alternative trial designs. This level of additional power depends on the recruitment length of the trial, with most efficiency gained when recruitment is relatively slow. We conclude with a discussion of additional considerations required when starting a MAMS trial. CONCLUSION: MAMS trial designs are potentially very useful for stroke trials due to their improved statistical power compared to the traditional approach., This work was supported in part by grants the National Institute for Health Research (NIHR-SRF-2015-08-001, TJ), the Medical Research Council (SLAH/210 JW).

Background Youth in general and college life in particular are characterized by new educational, vocational, and interpersonal challenges, opportunities, and substantial stress. It is estimated that 30–50% of university students meet criteria for some mental disorder, especially depression, in any given year. The university has traditionally provided many channels to promote students’ mental health, but until now only a minority have sought such help, possibly owing to lack of time and/or to stigma related to mental illness. Smartphone-delivered cognitive behavioral therapy (CBT) shows promise for its accessibility and effectiveness. However, its most effective components and for whom it is more (or less) effective are not known. Methods/design Based on the multiphase optimization strategy framework, this study is a parallel-group, multicenter, open, fully factorial trial examining five smartphone-delivered CBT components (self-monitoring, cognitive restructuring, behavioral activation, assertion training, and problem solving) among university students with elevated distress, defined as scoring 5 or more on the Patient Health Questionnaire-9 (PHQ-9). The primary outcome is change in PHQ-9 scores from baseline to week 8. We will estimate specific efficacy of the five components and their interactions through the mixed-effects repeated-measures analysis and propose the most effective and efficacious combinations of components. Effect modification by selected baseline characteristics will be examined in exploratory analyses. Discussion The highly efficient experimental design will allow identification of the most effective components and the most efficient combinations thereof among the five components of smartphone CBT for university students. Pragmatically, the findings will help make the most efficacious CBT package accessible to a large number of distressed university students at reduced cost; theoretically, they will shed light on the underlying mechanisms of CBT and help further advance CBT for depression. Trial registration UMIN, CTR-000031307 . Registered on February 14, 2018.

Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial’s course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented. We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. This tutorial paper provides guidance on key aspects of adaptive designs that are relevant to clinical triallists. We explain the basic rationale behind adaptive designs, clarify ambiguous terminology and summarise the utility and pitfalls of adaptive designs. We discuss practical aspects around funding, ethical approval, treatment supply and communication with stakeholders and trial participants. Our focus, however, is on the interpretation and reporting of results from adaptive design trials, which we consider vital for anyone involved in medical research. We emphasise the general principles of transparency and reproducibility and suggest how best to put them into practice.

BackgroundPeople with an intellectual (learning) disability (ID) and epilepsy have an increased seizure frequency, higher frequencies of multiple antiepileptic drug (AED) use and side effects, higher treatment costs, higher mortality rates and more behavioural problems than the rest of the population with epilepsy. The introduction of nurse-led care may lead to improvements in outcome for those with an ID and epilepsy; however, this has not been tested in a definitive clinical trial.ObjectiveTo determine whether or not ID nurses, using a competency framework developed to optimise nurse management of epilepsy in people with an ID, can cost-effectively improve clinical and quality-of-life outcomes in the management of epilepsy compared with treatment as usual.DesignCluster-randomised two-arm trial.SettingCommunity-based secondary care delivered by members of community ID teams.ParticipantsParticipants were adults aged 18–65 years with an ID and epilepsy under the care of a community ID team and had had at least one seizure in the 6 months before the trial.InterventionsThe experimental intervention was the Learning Disability Epilepsy Specialist Nurse Competency Framework. This provides guidelines describing a structure and goals to support the delivery of epilepsy care and management by ID-trained nurses.Main outcome measuresThe primary outcome was the seizure severity scale from the Epilepsy and Learning Disabilities Quality of Life questionnaire. Measures of mood, behaviour, AED side effects and carer strain were also collected. A cost–utility analysis was undertaken along with a qualitative examination of carers’ views of participants’ epilepsy management.ResultsIn total, 312 individuals were recruited into the study from 17 research clusters. Using an intention-to-treat analysis controlling for baseline individual-level and cluster-level variables there was no significant difference in seizure severity score between the two arms. Altogether, 238 complete cases were included in the non-imputed primary analysis. Analyses of the secondary outcomes revealed no significant differences between arms. A planned subgroup analysis identified a significant interaction between treatment arm and level of ID. There was a suggestion in those with mild to moderate ID that the competency framework may be associated with a small reduction in concerns over seizure severity (standard error 2.005, 95% confidence interval –0.554 to 7.307;p = 0.092). However, neither subgroup showed a significant intervention effect individually. Family members’ perceptions of nurses’ management depended on the professional status of the nurses, regardless of trial arm. Economic analysis suggested that the competency framework intervention was likely to be cost-effective, primarily because of a reduction in the costs of supporting participants compared with treatment as usual.LimitationsThe intervention could not be delivered blinded. Treatment as usual varied widely between the research sites.ConclusionsOverall, for adults with an ID and epilepsy, the framework conferred no clinical benefit compared with usual treatment. The economic analysis suggested that there may be a role for the framework in enhancing the cost-effectiveness of support for people with epilepsy and an ID. Future research could explore the specific value of the competency framework for those with a mild to moderate ID and the potential for greater long-term benefits arising from the continuing professional development element of the framework.Trial registrationCurrent Controlled Trials ISRCTN96895428.FundingThis trial was funded by the NIHR Health Technology Assessment programme and will be published in full inHealth Technology Assessment; Vol. 22, No. 10. See the NIHR Journals Library website for further project information.

Background/Aims: The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Methods: Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. Results: We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial’s type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. Conclusion: The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into stepped-wedge cluster randomised trials according to the needs of the particular trial.

Objective To prospectively investigate the longitudinal effect of ejaculatory abstinence on MRI-measured seminal vesicle (SV) volume and whole-prostate ADC over consecutive days. Methods 15 healthy male volunteers (mean 35.9 years, range 27–53) underwent 3-T MRI at baseline and 1, 2 and 3 days post-ejaculation. Prostate and SV volumes were derived by volume segmentation and whole-gland apparent diffusion coefficient (ADC) values calculated. A mixed-effects linear regression compared ADC values and prostate/seminal vesicle volumes in each volunteer between studies in a pairwise manner. Results All subjects completed the four MRIs. Mean prostate volume was 22.45 cm3 (range 13.04–31.21 cm3), with no change between the four studies (p = 0.89–0.99). 13/15 subjects showed SV volume reduction from baseline to day 1, with group-mean decreasing from 6.45 to 4.80 cm3 (−25.6%, p

Background Peanut allergy causes severe and fatal reactions. Current food allergen labeling does not address these risks adequately against the burden of restricting food choice for allergic patients because of limited data on thresholds of reactivity and the influence of everyday factors. Objective We estimated peanut threshold doses for a United Kingdom population with peanut allergy and examined the effect of sleep deprivation and exercise. Methods In a crossover study, after blind challenge, participants with peanut allergy underwent 3 open peanut challenges in random order: with exercise after each dose, with sleep deprivation preceding challenge, and with no intervention. Primary outcome was the threshold dose triggering symptoms (in milligrams of protein). Primary analysis estimated the difference between the nonintervention challenge and each intervention in log threshold (as percentage change). Dose distributions were modeled, deriving eliciting doses in the population with peanut allergy. Results Baseline challenges were performed in 126 participants, 100 were randomized, and 81 (mean age, 25 years) completed at least 1 further challenge. The mean threshold was 214 mg (SD, 330 mg) for nonintervention challenges, and this was reduced by 45% (95% CI, 21% to 61%; P = .001) and 45% (95% CI, 22% to 62%; P = .001) for exercise and sleep deprivation, respectively. Mean estimated eliciting doses for 1% of the population were 1.5 mg (95% CI, 0.8-2.5 mg) during nonintervention challenge (n = 81), 0.5 mg (95% CI, 0.2-0.8 mg) after sleep, and 0.3 mg (95% CI, 0.1-0.6 mg) after exercise. Conclusion: Exercise and sleep deprivation each significantly reduce the threshold of reactivity in patients with peanut allergy, putting them at greater risk of a reaction. Adjusting reference doses using these data will improve allergen risk management and labeling to optimize protection of consumers with peanut allergy.

BACKGROUND: High grade serous ovarian carcinoma (HGSOC) is characterized by ubiquitous TP53 mutation and has the highest genomic complexity of all epithelial neoplasms. Sensitivity to PARP inhibitor therapy is strongly associated with homologous recombination deficiency (HRD). Genomic biomarkers of HRD such as genome-wide loss of heterozygosity (LOH) scores predict HRD and response to rucaparib. We hypothesized that functional testing of response during PARP inhibitor treatment using changes in circulating tumour DNA (ctDNA) could improve prediction of patient outcome. We tested whether the change in ctDNA TP53 mutant allele fraction (MAF) after one cycle of rucaparib treatment was predictive of progression free survival (PFS) and response in patients from the phase 2 ARIEL2 trial in women with platinum-sensitive recurrent high grade ovarian cancer (NCT01891344). METHODS: We analyzed serial plasma samples (n = 636) from 142 HGSOC patients during screening, on day 1 of each treatment cycle, and at the end of rucaparib treatment. Targeted amplicon deep sequencing (TADS) of TP53 was performed on DNA extracted from plasma (median depth 6916×). Somatic TP53 mutation and loss of heterozygosity score (LOH) were available from archival and biopsy specimens. Statistical analyses were pre-specified and ctDNA analysis was carried out blinded to visit and response data. TP53 MAF changes after one cycle of treatment were compared with PFS and best overall response assessed by RECIST v1.1 and GCIG CA-125 criteria. Optimal cut points for ctDNA response were determined using a cross-validation analysis. In cases with >1 TP53 mutation, response assessment was performed using the mutation with highest MAF. RESULTS: We detected TP53 mutations in plasma from 134 patients; all cases were concordant between tumour and plasma except for one patient (present in plasma but not tumour). In 18 patients (13%), 2 or more TP53 mutations were detected in ctDNA. The median TP53 MAF prior to cycle 1 was 2.6% (IQR 0.3–8.6). Reduction of >70% of TP53 MAF in ctDNA between cycle 1 and 2 was significantly predictive of improved PFS (n = 97; HR = 0.53, 95% CI 0.34-0.85, p = 0.008, median 273 vs 158 days, sensitivity 76%, specificity 62%) and best overall response (n = 97; OR = 7.04, 95% CI 2.69–21.06, p < 0.001). Combining ctDNA and LOH scores did not improve prediction of response. CONCLUSIONS Response measured by >70% fall in TP53 ctDNA between pre-cycle 1 and pre-cycle 2 of rucaparib therapy was significantly associated with best overall response and improved PFS. Similar findings were observed in a retrospective study of recurrent HGSOC treated with standard of care chemotherapy. The pathological or genomic factors causing multiple TP53 mutations in ctDNA are unknown. The association between early fall in ctDNA and validated RECIST and CA-125 response markers provides strong evidence that ctDNA may have utility for detecting early response to targeted therapy. Further analyses in randomized studies should be performed to confirm that ctDNA response has strong predictive value. Citation Format: Anna Piskorz, David Robertson, Kevin K. Lin, James Morris, Elaina Mann, Amit Oza, Robert L. Coleman, David M. O'Malley, Michael Friedlander, Janiel M. Cragun, Ling Ma, Heidi Giordano, Iain A. McNeish, Elizabeth Swisher, James Wason, James D. Brenton. CTDNA RESPONSE TO THE PARP INHIBITOR RUCAPARIB PREDICTS PROGRESSION-FREE SURVIVAL AND BEST OVERALL RESPONSE ON THE ARIEL2 TRIAL [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr GMM-048.