Ethnic differences in response to atypical antipsychotics in patients with schizophrenia: individual patient data meta-analysis of randomised placebo-controlled registration trials submitted to the Dutch Medicines Evaluation Board

BACKGROUND

Little is known about the effect of ethnicity on the response to antipsychotic medication in patients with schizophrenia.

AIMS

To determine whether ethnicity moderates the response to antipsychotic medication in patients with schizophrenia, and whether this moderation is independent of confounders.

METHOD

We analysed 18 short-term, placebo-controlled registration trials of atypical antipsychotic medications in patients with schizophrenia (N = 3880). A two-step, random-effects, individual patient data meta-analysis was applied to establish the moderating effect of ethnicity (White versus Black) on symptom improvement according to the Brief Psychiatric Rating Scale (BPRS) and on response, defined as >30% BPRS reduction. These analyses were corrected for baseline severity, baseline negative symptoms, age and gender. A conventional meta-analysis was performed to determine the effect size of antipsychotic treatment for each ethnic group separately.

RESULTS

In the complete data-set, 61% of patients were White, 25.6% of patients were Black and 13.4% of patients were of other ethnicities. Ethnicity did not moderate the efficacy of antipsychotic treatment: pooled β-coefficient for the interaction between treatment and ethnic group was -0.582 (95% CI -2.567 to 1.412) for mean BPRS change, with an odds ratio of 0.875 (95% CI 0.510-1.499) for response. These results were not modified by confounders.

CONCLUSIONS

Atypical antipsychotic medication is equally effective in both Black and White patients with schizophrenia. In registration trials, White and Black patients were overrepresented relative to other ethnic groups, limiting the generalisability of our findings.

Comprehensive Cardiovascular Magnetic Resonance-Derived Myocardial Strain Analysis Provides Independent Prognostic Value in Acute Myocarditis

Background Late gadolinium enhancement and left ventricular (LV) ejection fraction on cardiovascular magnetic resonance (CMR) are prognostic markers, but their predictive value for incident heart failure or life-threatening arrhythmias in acute myocarditis patients is limited. CMR-derived feature tracking provides a more sensitive analysis of myocardial function and may improve risk stratification in myocarditis. In this study, the prognostic value of LV, right ventricular, and left atrial strain in acute myocarditis patients is evaluated. Methods and Results In this multicenter retrospective study, patients with CMR-proven acute myocarditis were included. The primary end point was occurrence of major adverse cardiovascular events: all-cause mortality, heart transplantation, heart failure hospitalizations, and life threatening arrhythmias. LV global longitudinal strain, global circumferential strain and global radial strain, right ventricular-global longitudinal strain and left atrial strain were measured. Unadjusted and adjusted cox proportional hazard regression analysis were performed. In total, 162 CMR-proven myocarditis patients were included (41 ± 17 years, 75% men). Mean LV ejection fraction was 51 ± 12%, and 144 (89%) patients had presence of late gadolinium enhancement. Major adverse cardiovascular events occurred in 29 (18%) patients during a follow-up of 5.5 (2.2-8.3) years. All LV strain parameters were independent predictors of outcome beyond clinical features, LV ejection fraction and late gadolinium enhancement (LV-global longitudinal strain: hazard ratio [HR] 1.07, P=0.02; LV-global circumferential strain: HR 1.15, P=0.02; LV-global radial strain: HR 0.98, P=0.03), but right ventricular or left atrial strain did not predict outcome. Conclusions CMR-derived LV strain analysis provides independent prognostic value on top of clinical parameters, LV ejection fraction and late gadolinium enhancement in acute myocarditis patients, while left atrial and right ventricular strain seem to be of less importance.

Left Atrial Strain Has Superior Prognostic Value to Ventricular Function and Delayed-Enhancement in Dilated Cardiomyopathy

BACKGROUND

The left atrium is an early sensor of left ventricular (LV) dysfunction. Still, the prognostic value of left atrial (LA) function (strain) on cardiac magnetic resonance (CMR) in dilated cardiomyopathy (DCM) remains unknown.

OBJECTIVES

The goal of this study was to evaluate the prognostic value of CMR-derived LA strain in DCM.

METHODS

Patients with DCM from the Maastricht Cardiomyopathy Registry with available CMR imaging were included. The primary endpoint was the combination of sudden or cardiac death, heart failure (HF) hospitalization, or life-threatening arrhythmias. Given the nonlinearity of continuous variables, cubic spline analysis was performed to dichotomize.

RESULTS

A total of 488 patients with DCM were included (median age: 54 [IQR: 46-62] years; 61% male). Seventy patients (14%) reached the primary endpoint (median follow-up: 6 [IQR: 4-9] years). Age, New York Heart Association (NYHA) functional class >II, presence of late gadolinium enhancement (LGE), LV ejection fraction (LVEF), LA volume index (LAVI), LV global longitudinal strain (GLS), and LA reservoir and conduit strain were univariably associated with the outcome (all P < 0.02). LA conduit strain was a stronger predictor of outcome compared with reservoir strain. LA conduit strain, NYHA functional class >II, and LGE remained associated in the multivariable model (LA conduit strain HR: 3.65 [95% CI: 2.01-6.64; P < 0.001]; NYHA functional class >II HR: 1.81 [95% CI: 1.05-3.12; P = 0.033]; and LGE HR: 2.33 [95% CI: 1.42-3.85; P < 0.001]), whereas age, N-terminal pro-B-type natriuretic peptide, LVEF, left atrial ejection fraction, LAVI, and LV GLS were not. Adding LA conduit strain to other independent predictors (NYHA functional class and LGE) significantly improved the calibration, accuracy, and reclassification of the prediction model (P < 0.05).

CONCLUSIONS

LA conduit strain on CMR is a strong independent prognostic predictor in DCM, superior to LV GLS, LVEF, and LAVI and incremental to LGE. Including LA conduit strain in DCM patient management should be considered to improve risk stratification.

Near-infrared spectroscopy predicts events in men and women: Results from the Lipid Rich Plaque study

Background

The Lipid Rich Plaque (LRP) study demonstrated that near-infrared spectroscopy imaging of non-obstructive lesions identified patients and segments at higher risk for subsequent non-culprit major adverse cardiac events (NC-MACE). Whether this is true for both men and women is not known. In this post hoc analysis of the LRP study, we sought to investigate whether the maximum 4-mm Lipid Core Burden Index (maxLCBI_4mm) was of similar predictive value in men and women for NC-MACE.

Methods

Patients with an evaluable maxLCBI_4mm were stratified on the basis of sex at birth. A Cox proportional-hazards model was used to assess the predictive value of maxLCBI_4mm on future NC-MACE at the patient and plaque levels. The primary endpoint was cumulative incidence of NC-MACE at 24 months.

Results

Among 1271 patients, 388 (30.5%) were women. Women were older and had a higher cardiovascular risk profile. Cumulative incidence of NC-MACE at 24 months was 10.3% for women and 7.6% for men (log-rank p = 0.11). When comparing maxLCBI_4mm > 400 to maxLCBI_4mm ≤ 400, the hazard ratio (HR) for future NC-MACE was not significantly different between sexes: 2.10 (95% confidence interval [CI]: 1.28–3.44; p = 0.003) for men and 2.24 (95% CI: 1.18–4.28; p = 0.014) for women (p = 0.87). At the plaque level, the HR comparing maxLCBI_4mm > 400 to maxLCBI_4mm ≤ 400 was 3.49 (95% CI: 1.60–7.60, p = 0.002) for men and 4.79 (95% CI: 2.02–11.38, p < 0.001) for women, which was not significantly different (p = 0.57).

Conclusions

The maxLCBI_4mm was of similar predictive value for NC-MACE within 24 months in men and women.

Medical Specialists' Perspectives on the Influence of Electronic Medical Record Use on the Quality of Hospital Care: Semistructured Interview Study

Background

Numerous publications show that electronic medical records (EMRs) may make an important contribution to increasing the quality of care. There are indications that particularly the medical specialist plays an important role in the use of EMRs in hospitals.

Objective

The aim of this study was to examine how, and by which aspects, the relationship between EMR use and the quality of care in hospitals is influenced according to medical specialists.

Methods

To answer this question, a qualitative study was conducted in the period of August-October 2018. Semistructured interviews of around 90 min were conducted with 11 medical specialists from 11 different Dutch hospitals. For analysis of the answers, we used a previously published taxonomy of factors that can influence the use of EMRs.

Results

The professional experience of the participating medical specialists varied between 5 and 27 years. Using the previously published taxonomy, these medical specialists considered technical barriers the most significant for EMR use. The suboptimal change processes surrounding implementation were also perceived as a major barrier. A final major problem is related to the categories “social” (their relationships with the patients and fellow care providers), “psychological” (based on their personal issues, knowledge, and perceptions), and “time” (the time required to select, implement, and learn how to use EMR systems and subsequently enter data into the system). However, the medical specialists also identified potential technical facilitators, particularly in the assured availability of information to all health care professionals involved in the care of a patient. They see promise in using EMRs for medical decision support to improve the quality of care but consider these possibilities currently lacking.

Conclusions

The 11 medical specialists shared positive experiences with EMR use when comparing it to formerly used paper records. The fact that involved health care professionals can access patient data at any time they need is considered important. However, in practice, potential quality improvement lags as long as decision support cannot be applied because of the lack of a fully coded patient record.

Direct comparison of predictive performance of PRECISE-DAPT versus PARIS versus CREDO-Kyoto: a subanalysis of the ReCre8 trial

Background

Multiple scores have been proposed to guide risk stratification after percutaneous coronary intervention. This study assessed the performance of the PRECISE-DAPT, PARIS and CREDO-Kyoto risk scores to predict post-discharge ischaemic or bleeding events.

Methods

A total of 1491 patients treated with latest-generation drug-eluting stent implantation were evaluated. Risk scores for post-discharge ischaemic or bleeding events were calculated and directly compared. Prognostic performance of both risk scores was assessed with calibration, Harrell’s c‑statistics net reclassification index and decision curve analyses.

Results

Post-discharge ischaemic events occurred in 56 patients (3.8%) and post-discharge bleeding events in 34 patients (2.3%) within the first year after the invasive procedure. C‑statistics for the PARIS ischaemic risk score was marginal (0.59, 95% confidence interval (CI) 0.51–0.68), whereas the CREDO-Kyoto ischaemic risk score was moderate (0.68, 95% CI 0.60–0.75). With regard to post-discharge bleeding events, CREDO-Kyoto displayed moderate discrimination (c-statistic 0.67, 95% CI 0.56–0.77), whereas PRECISE-DAPT (0.59, 95% CI 0.48–0.69) and PARIS (0.55, 95% CI 0.44–0.65) had a marginal discriminative capacity. Net reclassification index and decision curve analysis favoured CREDO-Kyoto-derived bleeding risk assessment.

Conclusion

In this contemporary all-comer population, PARIS and PRECISE-DAPT risk scores were not resilient to independent testing for post-discharge bleeding events. CREDO-Kyoto-derived risk stratification was associated with a moderate predictive capability for post-discharge ischaemic or bleeding events. Future studies are warranted to improve risk stratification with more focus on robustness and rigorous testing.

Electronic supplementary material

The online version of this article (10.1007/s12471-020-01486-y) contains supplementary material, which is available to authorized users.

Evidence supporting regulatory-decision making on orphan medicinal products authorisation in Europe: methodological uncertainties

BACKGROUND

To assess uncertainty in regulatory decision-making for orphan medicinal products (OMP), a summary of the current basis for approval is required; a systematic grouping of medical conditions may be useful in summarizing information and issuing recommendations for practice.

METHODS

A grouping of medical conditions with similar characteristics regarding the potential applicability of methods and designs was created using a consensus approach. The 125 dossiers for authorised OMP published between 1999 and 2014 on the EMA webpage were grouped accordingly and data was extracted from European Public Assessment Reports (EPARs) to assess the extent and robustness of the pivotal evidence supporting regulatory decisions.

RESULTS

88% (110/125) of OMP authorizations were based on clinical trials, with 35% (38/110) including replicated pivotal trials. The mean (SD) number of pivotal trials per indication was 1.4 (0.7), and the EPARs included a median of three additional non-pivotal supportive studies. 10% of OMPs (13/125) were authorised despite only negative pivotal trials. One-third of trials (53/159) did not include a control arm, one-third (50/159) did not use randomisation, half the trials (75/159) were open-label and 75% (119/159) used intermediate or surrogate variables as the main outcome. Chronic progressive conditions led by multiple system/organs, conditions with single acute episodes and progressive conditions led by one organ/system were the groups where the evidence deviated most from conventional standards. Conditions with recurrent acute episodes had the most robust datasets. The overall size of the exposed population at the time of authorisation of OMP - mean(SD) 190.5 (202.5) - was lower than that required for the qualification of clinically-relevant adverse reactions.

CONCLUSIONS

The regulatory evidence supporting OMP authorization showed substantial uncertainties, including weak protection against errors, substantial use of designs unsuited for conclusions on causality, use of intermediate variables, lack of a priorism and insufficient safety data to quantify risks of relevant magnitude. Grouping medical conditions based on clinical features and their methodological requirements may facilitate specific methodological and regulatory recommendations for the study of OMP to strengthen the evidence base.

Statistical analysis of Goal Attainment Scaling endpoints in randomised trials

Goal Attainment Scaling is an assessment instrument to evaluate interventions on the basis of individual, patient-specific goals. The attainment of these goals is mapped in a pre-specified way to attainment levels on an ordinal scale, which is common to all goals. This approach is patient-centred and allows one to integrate the outcomes of patients with very heterogeneous symptoms. The latter is of particular importance in clinical trials in rare diseases because it enables larger sample sizes by including a broader patient population. In this paper, we focus on the statistical analysis of Goal Attainment Scaling outcomes for the comparison of two treatments in randomised clinical trials. Building on a general statistical model, we investigate the properties of different hypothesis testing approaches. Additionally, we propose a latent variable approach to generate Goal Attainment Scaling data in a simulation study, to assess the impact of model parameters such as the number of goals per patient and their correlation, the choice of discretisation thresholds and the type of design (parallel group or cross-over). Based on our findings, we give recommendations for the design of clinical trials with a Goal Attainment Scaling endpoint. Furthermore, we discuss an application of Goal Attainment Scaling in a clinical trial in mastocytosis.

Multimodal, automated detection of nocturnal motor seizures at home: Is a reliable seizure detector feasible?

Objective

Automated seizure detection and alarming could improve quality of life and potentially prevent sudden, unexpected death in patients with severe epilepsy. As currently available systems focus on tonic–clonic seizures, we want to detect a broader range of seizure types, including tonic, hypermotor, and clusters of seizures.

Methods

In this multicenter, prospective cohort study, the nonelectroencephalographic (non‐EEG) signals heart rate and accelerometry were measured during the night in patients undergoing a diagnostic video‐EEG examination. Based on clinical video‐EEG data, seizures were classified and categorized as clinically urgent or not. Seizures included for analysis were tonic, tonic–clonic, hypermotor, and clusters of short myoclonic/tonic seizures. Features reflecting physiological changes in heart rate and movement were extracted. Detection algorithms were developed based on stepwise fulfillment of conditions during increases in either feature. A training set was used for development of algorithms, and an independent test set was used for assessing performance.

Results

Ninety‐five patients were included, but due to sensor failures, data from only 43 (of whom 23 patients had 86 seizures, representing 402 h of data) could be used for analysis. The algorithms yield acceptable sensitivities, especially for clinically urgent seizures (sensitivity = 71–87%), but produce high false alarm rates (2.3–5.7 per night, positive predictive value = 25–43%). There was a large variation in the number of false alarms per patient.

Significance

It seems feasible to develop a detector with high sensitivity, but false alarm rates are too high for use in clinical practice. For further optimization, personalization of algorithms may be necessary.

Directions for new developments on statistical design and analysis of small population group trials

Background

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions.

Method

Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible.

Results

The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations.

Conclusion

The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients’ perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.

[A proactive approach to risks: from responding tot leading]

OBJECTIVE

To give an overview of instruments for early detection of quality and safety risks for integrated risk management in hospitals.

DESIGN

Systematic literature review and qualitative research.

METHOD

A review of literature in three databases (PubMed, CINAHL and Embase) was conducted to establish which instruments are known from academic literature. Articles were selected if the effectiveness and feasibility of the instrument for risk management had been evaluated. We also examined the references of the articles found, and searched for grey literature. Moreover, 19 experts from healthcare and other sectors were interviewed in order to verify which instruments are used in practice and to study the factors influencing implementation in hospitals.

RESULTS

We found more than 60 instruments which we divided into 12 categories. Interviewees reported that a combination of instruments is required in order to assess all of the quality and safety risks, the main elements being: (a) the patient as source; (b) brainstorming sessions and consultation in networks, i.e. verbal exchange of risks between departments and organisations; (c) insight into the performance of individual healthcare professionals and teams; and (d) site visits. For instruments to work as effectively as possible, a culture is essential in which care providers recognise and discuss risks. There is also a need for a management system including all hospital risks, allowing an integrated, efficient approach to risk.

CONCLUSION

There are several instruments for early detection of quality and safety risks for integrated risk management in hospitals. The predictive value of the instruments requires further investigation.

[Cohort multiple randomized controlled trial: a solution for the evaluation of multiple interventions]

The standard randomized controlled trial (RCT) does not appear to be the most suitable design for the fast and efficient simultaneous evaluation of multiple interventions for the same condition. The cohort multiple randomized controlled trial (cmRCT) design offers the opportunity to perform randomized trials for multiple interventions simultaneously and is a promising alternative for the classic RCT. The basis of the cmRCT is an observational cohort of patients with the same condition. The patients will generally undergo standard treatment. The patient characteristics are captured at baseline and outcome measures are captured at fixed points of time. Eligible patients within the observational cohort are identified for each new intervention, some of whom will be randomly selected and offered the new intervention. The other eligible patients will not be approached and will undergo the standard treatment. The same process can be simultaneously repeated for other interventions. Advantages include the ability to facilitate multiple simultaneous randomized evaluations, the improved comparability between trials and the patient-centered informed consent procedure.