Single-arm trials (SATs), while not preferred, remain in use throughout the drug development cycle. They may be accepted by regulators in particular contexts (e.g., in oncology or rare diseases) when the potential effects of new treatments are very large and placebo treatment is unethical. However, in the postregulatory space, SATs are common, and perhaps even more poorly suited to address the questions of interest. In this manuscript, we review regulatory and HTA positions on SATs; challenges posed by SATs to address research questions beyond regulators, evolving statistical methods to provide context for SATs, case studies where SATs could and could not address questions of interest, and communication strategies to influence decision making and optimize study design to address evidence needs.

Background: It is challenging to select the most appropriate biologic treatment for patients with moderate-to-severe plaque psoriasis. Objective: To compare speed of onset and level of skin improvement between the interleukin (IL)-17A antagonist ixekizumab and the IL-23 p19 inhibitors guselkumab, tildrakizumab, and risankizumab in patients with moderate-to-severe plaque psoriasis. Methods: Using data from controlled clinical trials, both adjusted indirect comparisons (AICs) and matching adjusted indirect comparisons (MAICs) were performed to determine the risk difference (RD) between ixekizumab and each IL-23 p19 inhibitor for the proportion of patients with >= 75%/90%/100% improvement compared with baseline in Psoriasis Area and Severity Index (PASI 75/90/100) up to week 12. Placebo, etanercept, or ustekinumab were used as the comparator bridge. Results: In all (M)AICs, RDs generally significantly favored ixekizumab over guselkumab (placebo bridge), tildrakizumab (placebo or etanercept bridge), and risankizumab (placebo or ustekinumab bridge) from the earliest assessment time (>= week 2) to week 12 when considering PASI 75/90/100 responses. Conclusion: Ixekizumab provides a faster onset of effect and earlier clinical benefits than guselkumab, tildrakizumab, or risankizumab in patients with moderate-to-severe psoriasis, as reflected by higher levels of skin improvement than with these IL-23 p19 inhibitors up to week 12.

Abstract Background Indirect comparisons (including network meta‐analyses [NMAs]) allow us to compare benefits and risks of multiple interventions for the same clinical condition when head‐to‐head comparisons are not feasible. Objective To provide guidance to the clinical community on better understanding indirect comparison methods to help them to interpret their results by applying two quality standards to published indirect comparisons of systemic biologics for moderate to severe psoriasis. Methods A systematic literature review (SLR) of published indirect comparisons of biologics for the treatment of moderate to severe psoriasis in adults was conducted. Data extraction was performed using a predefined subset of NICE TSD7 (National Institute for Health and Care Excellence Technical Support Document 7) checklist questions and methods used to perform each analysis were descriptively compared. Methodological quality of the SLR underlying each indirect comparison was assessed using AMSTAR 2 (A MeaSurement Tool to Assess systematic Reviews version 2). Results Twenty‐two NMAs and four adjusted indirect comparisons (AICs) were identified. Although there were some similarities, for example, application of Bayesian random‐effects models, several important methodological aspects varied considerably across NMAs identified, for example, classes of drugs, number of treatments and studies included, reporting and handling of different doses, and reporting of both checks for and investigations of inconsistency. Methodological comparisons across AICs were limited by the small number. The quality of most underlying SLRs described, assessed as overall level of confidence in the results, was ‘critically low’. Conclusions Understanding that there are different methodologies employed to answer differing research questions is key to helping clinicians to interpret the indirect evidence currently available in psoriasis.

OBJECTIVES:This study aimed to elicit preferences for psoriasis treatment features and to test for preference heterogeneity across groups of respondents.MATERIALS AND METHODS:A discrete-choice experiment was employed to elicit preferences of patients with plaque psoriasis in multiple countries. The survey instrument included a series of choice questions between three hypothetical treatments, each characterized by varying levels of six attributes (namely, lesion reduction, risk of impairing side effects, time to reach results, mode and frequency of administration, itching reduction, and side effects). Random parameters logit was used to model the data. Results were compared across a total of 18 subgroup sets.RESULTS:The data analysis from 1,123 respondents showed that, on average, respondents receive more utility gain from higher levels of lesion reduction and lower risks of impairing side effects than changes in other attributes included in the study. Systematic differences were detected for 13 sets; the most pronounced differences were observed based on disease severity, nail psoriasis, biologic experience, and quality-of-life scores.CONCLUSION:These many sources of preference heterogeneity identified by our analysis suggest that to improve patient satisfaction and, probably, adherence and persistence, clinicians should discuss options with patients when prescribing their treatment.

Background Network meta-analysis (NMA) and indirect comparisons combine aggregate data (AgD) from multiple studies on treatments of interest but may give biased estimates if study populations differ. Population adjustment methods such as multilevel network meta-regression (ML-NMR) aim to reduce bias by adjusting for differences in study populations using individual patient data (IPD) from 1 or more studies under the conditional constancy assumption. A shared effect modifier assumption may also be necessary for identifiability. This article aims to demonstrate how the assumptions made by ML-NMR can be assessed in practice to obtain reliable treatment effect estimates in a target population. Methods We apply ML-NMR to a network of evidence on treatments for plaque psoriasis with a mix of IPD and AgD trials reporting ordered categorical outcomes. Relative treatment effects are estimated for each trial population and for 3 external target populations represented by a registry and 2 cohort studies. We examine residual heterogeneity and inconsistency and relax the shared effect modifier assumption for each covariate in turn. Results Estimated population-average treatment effects were similar across study populations, as differences in the distributions of effect modifiers were small. Better fit was achieved with ML-NMR than with NMA, and uncertainty was reduced by explaining within- and between-study variation. We found little evidence that the conditional constancy or shared effect modifier assumptions were invalid. Conclusions ML-NMR extends the NMA framework and addresses issues with previous population adjustment approaches. It coherently synthesizes evidence from IPD and AgD studies in networks of any size while avoiding aggregation bias and noncollapsibility bias, allows for key assumptions to be assessed or relaxed, and can produce estimates relevant to a target population for decision-making. Highlights Multilevel network meta-regression (ML-NMR) extends the network meta-analysis framework to synthesize evidence from networks of studies providing individual patient data or aggregate data while adjusting for differences in effect modifiers between studies (population adjustment). We apply ML-NMR to a network of treatments for plaque psoriasis with ordered categorical outcomes. We demonstrate for the first time how ML-NMR allows key assumptions to be assessed. We check for violations of conditional constancy of relative effects (such as unobserved effect modifiers) through residual heterogeneity and inconsistency and the shared effect modifier assumption by relaxing this for each covariate in turn. Crucially for decision making, population-adjusted treatment effects can be produced in any relevant target population. We produce population-average estimates for 3 external target populations, represented by the PsoBest registry and the PROSPECT and Chiricozzi 2019 cohort studies.

BACKGROUND:Scientific guidelines have been developed to update and harmonize exercise based cardiac rehabilitation (ebCR) in German speaking countries. Key recommendations for ebCR indications have recently been published in part 1 of this journal. The present part 2 updates the evidence with respect to contents and delivery of ebCR in clinical practice, focusing on exercise training (ET), psychological interventions (PI), patient education (PE). In addition, special patients' groups and new developments, such as telemedical (Tele) or home-based ebCR, are discussed as well.METHODS:Generation of evidence and search of literature have been described in part 1.RESULTS:Well documented evidence confirms the prognostic significance of ET in patients with coronary artery disease. Positive clinical effects of ET are described in patients with congestive heart failure, heart valve surgery or intervention, adults with congenital heart disease, and peripheral arterial disease. Specific recommendations for risk stratification and adequate exercise prescription for continuous-, interval-, and strength training are given in detail. PI when added to ebCR did not show significant positive effects in general. There was a positive trend towards reduction in depressive symptoms for "distress management" and "lifestyle changes". PE is able to increase patients' knowledge and motivation, as well as behavior changes, regarding physical activity, dietary habits, and smoking cessation. The evidence for distinct ebCR programs in special patients' groups is less clear. Studies on Tele-CR predominantly included low-risk patients. Hence, it is questionable, whether clinical results derived from studies in conventional ebCR may be transferred to Tele-CR.CONCLUSIONS:ET is the cornerstone of ebCR. Additional PI should be included, adjusted to the needs of the individual patient. PE is able to promote patients self-management, empowerment, and motivation. Diversity-sensitive structures should be established to interact with the needs of special patient groups and gender issues. Tele-CR should be further investigated as a valuable tool to implement ebCR more widely and effectively.

INTRODUCTION:Ixekizumab, a high-affinity monoclonal antibody that selectively targets interleukin-17A, is an approved treatment for plaque psoriasis. This study aimed to use animated visualizations as a tool to simplify complex data from ixekizumab clinical trials.METHODS:Animated visualizations were developed to show outcomes from ixekizumab clinical trials and a Bayesian network meta-analysis of 11 approved biologics. The visualizations simultaneously highlighted both aggregate scores and the individual progression of patients over the course of treatment.RESULTS:The animations provided key messages and information from the complex data in efficient and scientific ways that were also visually pleasing and simple to understand. The animations highlighted (1) rapid reduction in disease severity from baseline; (2) sustained efficacy of ixekizumab in the treatment of skin and nail psoriasis; (3) side-by-side comparisons of treatment efficacy and clinical improvement across trials; (4) simultaneous visual presentation of individual results with summary response over time; and (5) indirect comparison of relative treatment effects with other biologics based on Bayesian network meta-analysis.CONCLUSION:The rapid and sustained efficacy of ixekizumab in the treatment of psoriasis was demonstrated using multiple dynamic visualizations with different clinical endpoints. Animated visualizations provided a simpler and more comprehensive understanding of complex data than conventional static figures.

Background: Although cardiovascular rehabilitation (CR) is well accepted in general, CR-attendance and delivery still considerably vary between the European countries. Moreover, clinical and prognostic effects of CR are not well established for a variety of cardiovascular diseases. Methods: The guidelines address all aspects of CR including indications, contents and delivery. By processing the guidelines, every step was externally supervised and moderated by independent members of the "Association of the Scientific Medical Societies in Germany" (AWMF). Four meta-analyses were performed to evaluate the prognostic effect of CR after acute coronary syndrome (ACS), after coronary bypass grafting (CABG), in patients with severe chronic systolic heart failure (HFrEF), and to define the effect of psychological interventions during CR. All other indications for CR-delivery were based on a predefined semi-structured literature search and recommendations were established by a formal consenting process including all medical societies involved in guideline generation. Results: Multidisciplinary CR is associated with a significant reduction in all-cause mortality in patients after ACS and after CABG, whereas HFrEF-patients (left ventricular ejection fraction <40%) especially benefit in terms of exercise capacity and health-related quality of life. Patients with other cardiovascular diseases also benefit from CR-participation, but the scientific evidence is less clear. There is increasing evidence that the beneficial effect of CR strongly depends on "treatment intensity" including medical supervision, treatment of cardiovascular risk factors, information and education, and a minimum of individually adapted exercise volume. Additional psychologic interventions should be performed on the basis of individual needs. Conclusions: These guidelines reinforce the substantial benefit of CR in specific clinical indications, but also describe remaining deficits in CR-delivery in clinical practice as well as in CR-science with respect to methodology and presentation.

In health technology assessment (HTA), beside network meta-analysis (NMA), indirect comparisons (IC) have become an important tool used to provide evidence between two treatments when no head-to-head data are available. Researchers may use the adjusted indirect comparison based on the Bucher method (AIC) or the matching-adjusted indirect comparison (MAIC). While the Bucher method may provide biased results when included trials differ in baseline characteristics that influence the treatment outcome (treatment effect modifier), this issue may be addressed by applying the MAIC method if individual patient data (IPD) for at least one part of the AIC is available. Here, IPD is reweighted to match baseline characteristics and/or treatment effect modifiers of published data. However, the MAIC method does not provide a solution for situations when several common comparators are available. In these situations, assuming that the indirect comparison via the different common comparators is homogeneous, we propose merging these results by using meta-analysis methodology to provide a single, potentially more precise, treatment effect estimate. This paper introduces the method to combine several MAIC networks using classic meta-analysis techniques, it discusses the advantages and limitations of this approach, as well as demonstrates a practical application to combine several (M)AIC networks using data from Phase III psoriasis randomized control trials (RCT).

Standard network meta-analysis (NMA) and indirect comparisons combine aggregate data from multiple studies on treatments of interest, assuming that any effect modifiers are balanced across populations. Population adjustment methods relax this assumption using individual patient data from one or more studies. However, current matching-adjusted indirect comparison and simulated treatment comparison methods are limited to pairwise indirect comparisons and cannot predict into a specified target population. Existing meta-regression approaches incur aggregation bias. We propose a new method extending the standard NMA framework. An individual level regression model is defined, and aggregate data are fitted by integrating over the covariate distribution to form the likelihood. Motivated by the complexity of the closed form integration, we propose a general numerical approach using quasi-Monte-Carlo integration. Covariate correlation structures are accounted for by using copulas. Crucially for decision making, comparisons may be provided in any target population with a given covariate distribution. We illustrate the method with a network of plaque psoriasis treatments. Estimated population-average treatment effects are similar across study populations, as differences in the distributions of effect modifiers are small. A better fit is achieved than a random effects NMA, uncertainty is substantially reduced by explaining within- and between-study variation, and estimates are more interpretable.

It is challenging to select the most appropriate biologic treatment for patients with moderate-to-severe plaque psoriasis.To compare speed of onset and level of skin improvement between the interleukin (IL)-17A antagonist ixekizumab and the IL-23 p19 inhibitors guselkumab, tildrakizumab, and risankizumab in patients with moderate-to-severe plaque psoriasis.Using data from controlled clinical trials, both adjusted indirect comparisons (AICs) and matching adjusted indirect comparisons (MAICs) were performed to determine the risk difference (RD) between ixekizumab and each IL-23 p19 inhibitor for the proportion of patients with ≥75%/90%/100% improvement compared with baseline in Psoriasis Area and Severity Index (PASI 75/90/100) up to week 12. Placebo, etanercept, or ustekinumab were used as the comparator bridge.In all (M)AICs, RDs generally significantly favored ixekizumab over guselkumab (placebo bridge), tildrakizumab (placebo or etanercept bridge), and risankizumab (placebo or ustekinumab bridge) from the earliest assessment time (≥ week 2) to week 12 when considering PASI 75/90/100 responses.Ixekizumab provides a faster onset of effect and earlier clinical benefits than guselkumab, tildrakizumab, or risankizumab in patients with moderate-to-severe psoriasis, as reflected by higher levels of skin improvement than with these IL-23 p19 inhibitors up to week 12.

Background Either a random-parameters logit (RPL) or latent class (LC) model can be used to model or explain preference heterogeneity in discrete-choice experiment (DCE) data. The former assumes continuous distribution of preferences across the sample, while the latter assumes a discrete distribution. This study compared RPL and LC models to explore preference heterogeneity when analyzing patient preferences for psoriasis treatments. Methods Using DCE data collected from respondents with moderate-to-severe plaque psoriasis, we calculated and compared preference weights derived from RPL and LC models. We then compared how RPL and LC explain preference heterogeneity by exploring differences across subgroups defined by observed characteristics (i.e., country, age, gender, marital status, and psoriasis severity). Results While RPL and LC models resulted in the same mean preference weights, different preference-heterogeneity patterns emerged from the two approaches. In both models, country of residence and self-reported disease severity could be linked to systematic differences in preferences. The RPL also identified gender and marital status, but not age, as sources of heterogeneity; the LC membership probability model indicated that age was a significant factor, but not gender or marital status. Conclusions Using data from a psoriasis patient survey to compare two widely used methods for exploring heterogeneity identified differences in results between stated-preferences: subgroup analysis in the RPL model and inclusion of subgroup characteristics in the class membership probability function of the LC model. Researchers should model data using the most adaptable approach to address the initial study question.

ObjectivesThe healing process of tendons after surgical treatment of tendon ruptures mainly depends on the perfusion of the tendon and its surrounding tissue. Dynamic contrast‐enhanced ultrasound (DCE‐US) and dynamic contrast‐enhanced MRI (DCE‐MRI) can provide additional information about the local microperfusion. In this pilot study, the feasibility of these techniques to assess the vascularization during tendon regeneration was evaluated.MethodsBetween 2013 and 2015, 23 patients with surgical treatment of traumatic rupture of quadriceps, patellar, and Achilles tendons were involved. All patients received clinical follow‐up examinations at 6, 12, and at least 52 weeks postoperatively. Dynamic contrast‐enhanced US and DCE‐MRI examinations were performed 6 and 12 weeks postoperatively. Dynamic contrast‐enhanced US perfusion was quantified by the parameters peak enhancement, wash‐in area under the curve, rise time, and initial area under the curve. Correlations between these parameters were examined via the Spearman rank correlation. The clinical and functional outcomes were assessed via the Lysholm Knee Score and Knee and Osteoarthritis Outcome Score at 12 and 52 weeks postoperatively.ResultsFourteen patients with quadriceps (n = 8), patellar (n = 4) and Achilles (n = 2) tendon ruptures with complete follow‐up were available. The microperfusion could be successful assessed. We could detect a strong correlation of DCE‐US (peak enhancement) parameters with DCE‐MRI (initial area under the curve) parameters after 6 and 12 weeks.ConclusionsIn this pilot study, DCE‐US was able to visualize the microperfusion of healing tendons with a strong correlation with DCE‐MRI. Our initial results are in favor of DCE‐US as a potential quantitative imaging tool for evaluating the vascularization in tendon regeneration as a complementary method.

Objective: In moderate to severe plaque psoriasis (PsO), treatment decisions are becoming increasingly complex as the number of systemic therapeutic options and associated clinical studies grows. Head-to-head comparisons are not feasible for all therapies, so indirect comparison (IC) methodology is important to inform about the relative efficacy/safety of different drugs. We discuss potential implications of published ICs in PsO for clinical decision-making.

Background To assess long-term results of implants (XiVE/Frialit-2 Synchro) in a private periodontal practice according to survival and success rates (biological and technical complications) and to detect possible influencing factors, retrospectively. Methods Implant placement of at least one implant took place 10 years ±6 months before clinical and radiographic re-examination. Incidence of implant loss as main and incidence of mucositis/ peri-implantitis as secondary outcome were detected. Also, patient-related and implant-related influencing factors were determined by regression analyses. Results 100 patients (59.0% female) with 242 implants were included into analysis. Survival rate was 94.0% (XiVE: 97.7%; Frialit-2-Synchro: 66.7%). Mucositis was found in 77.6% of all patients, moderate/severe peri-implantitis in 16.3%. In logistic regression analyses statistically significant influencing factors for implant loss was implant type ( p < 0.001), for mucositis a wider implant diameter ( p = 0.0438) and a high modified Plaque Index ( p = 0.0253), for peri-implantits number of implants per patient ( p = 0.0075) and a wider implant diameter ( p = 0.0079). Technical complications were found in 47 implants (19.4%). Conclusions XiVE implants showed a high survival rate over a 10-year follow-up, on the other hand Frialit-2 Synchro implants had worse survival rates. Success rates regarding biological complications are in line with other implant systems.

Targeted biologic agents have improved the outlook for patients with moderate-to-severe psoriasis, enabling greater disease control (1). In parallel, raised expectations for treatment outcomes have contributed to an increased recognition of the importance of onset and duration of treatment response and the impact of treatment on quality of life (QoL) (1, 2). Recently, the IXORA-S phase 3 b, multicenter, randomized, controlled study (NCT02561806) in moderate-to-severe psoriasis showed that the interleukin (IL)-17A monoclonal antibody ixekizumab was superior to the IL-12/23 monoclonal antibody ustekinumab on Psoriasis Area and Severity Index (PASI) 75, 90 and 100 endpoints over 52weeks (3). In this post-hoc analysis of IXORA-S, we assessed and compared onset and duration of clinical (PASI) response of ixekizumab and ustekinumab. Onset of response was calculated as the median number of days for each individual to first show response during follow-up. We applied a Kaplan–Meier analysis to estimate mean duration of response. Clinical response parameters were the improvement in disease severity, measured as 75%, 90% or 100% improvement in PASI scores; and the impact of skin symptoms on patients’ QoL assessed as a 0/1 response in the Dermatology Life Quality Index (DLQI). Treatment responses were calculated for all four response criteria and plotted over 52weeks among patients receiving ixekizumab versus ustekinumab. Onset and duration of response were calculated for both treatments. Patient-level data between visits were estimated using Bezier interpolation as the best-fit method. Ixekizumab was superior to ustekinumab in all endpoints evaluated. The median time to onset was significantly more rapid and the mean duration of response significantly longer in the ixekizumab group for all defined response criteria (p< .001; Table 1, Figure 1). Median time to onset of PASI90 response was 49 days with ixekizumab versus 75 days with ustekinumab; duration of response was 173 versus 92 days for ixekizumab and ustekinumab, respectively. Median time to onset of a DLQI score of 0/1 was 29 days with ixekizumab versus 85 days with ustekinumab; this QoL response was sustained for 158 versus 101 days. In addition, fewer non-responders were seen with ixekizumab versus ustekinumab for all response criteria (Table 1). Kaplan–Meier analysis is new to this area of dermatology but widely used in oncology to evaluate time-to-event outcomes. In this setting, curves plot the fraction of patients alive over time and can be used to estimate mean survival rates and therefore identify treatment-related survival benefits (4). Limitations of our study include handling of data between visits and the assumption that duration of response data were normally distributed. In summary, this post-hoc analysis of a head-to-head comparison of ixekizumab and ustekinumab showed that ixekizumab led to faster and more sustained control of psoriasis symptoms and their negative impact on QoL. This analysis aligns with the initial IXORA-S results and emphasizes the

Background: Adjusted indirect comparisons (anchored via a common comparator) are an integral part of health technology assessment. These methods are challenged when differences between studies exist, including inclusion/exclusion criteria, outcome definitions, patient characteristics, as well as ensuring the choice of a common comparator. Objectives: Matching-adjusted indirect comparison (MAIC) can address these challenges, but the appropriate application of MAICs is uncertain. Examples include whether to match between individual-level data and aggregate-level data studies separately for treatment arms or to combine the arms, which matching algorithm should be used, and whether to include the control treatment outcome and/or covariates present in individual-level data. Results: Results from seven matching approaches applied to a continuous outcome in six simulated scenarios demonstrated that when no effect modifiers were present, the matching methods were equivalent to the unmatched Bucher approach. When effect modifiers were present, matching methods (regardless of approach) outperformed the Bucher method. Matching on arms separately produced more precise estimates compared with matching on total moments, and for certain scenarios, matching including the control treatment outcome did not produce the expected effect size. The entropy balancing approach was used to determine whether there were any notable advantages over the method proposed by Signorovitch et al. When unmeasured effect modifiers were present, no approach was able to estimate the true treatment effect. Conclusions: Compared with the Bucher approach (no matching), the MAICs examined demonstrated more accurate estimates, but further research is required to understand these methods across an array of situations. Copyright (c) 2019, ISPOR-The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc.