Embedding routine health care data in clinical trials:with great power comes great responsibility

Randomised clinical trials (RCTs) are vital for medical progress. Unfortunately, ‘traditional’ RCTs are expensive and inherently slow. Moreover, their generalisability has been questioned. There is considerable overlap in routine health care data (RHCD) and trial-specific data. Therefore, integration of RHCD in an RCT has great potential, as it would reduce the effort and costs required to collect data, thereby overcoming some of the major downsides of a traditional RCT. However, use of RHCD comes with other challenges, such as privacy issues, as well as technical and practical barriers. Here, we give a current overview of related initiatives on national cardiovascular registries (Netherlands Heart Registration, Heart4Data), showcasing the interrelationships between and the relevance of the different registries for the practicing physician. We then discuss the benefits and limitations of RHCD use in the setting of a pragmatic RCT from a cardiovascular perspective, illustrated by a case study in heart failure.</p

Embedding routine health care data in clinical trials:with great power comes great responsibility

Randomised clinical trials (RCTs) are vital for medical progress. Unfortunately, ‘traditional’ RCTs are expensive and inherently slow. Moreover, their generalisability has been questioned. There is considerable overlap in routine health care data (RHCD) and trial-specific data. Therefore, integration of RHCD in an RCT has great potential, as it would reduce the effort and costs required to collect data, thereby overcoming some of the major downsides of a traditional RCT. However, use of RHCD comes with other challenges, such as privacy issues, as well as technical and practical barriers. Here, we give a current overview of related initiatives on national cardiovascular registries (Netherlands Heart Registration, Heart4Data), showcasing the interrelationships between and the relevance of the different registries for the practicing physician. We then discuss the benefits and limitations of RHCD use in the setting of a pragmatic RCT from a cardiovascular perspective, illustrated by a case study in heart failure.</p

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET

Background: The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. // Methods: We included 286 subjects (135 controls, 108 Alzheimer’s disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. // Results: The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). // Conclusion: Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup

Is it time for Heart-Brain clinics?: A clinical survey and proposition to improve current care for cognitive problems in heart failure

BACKGROUND: Cognitive impairment is highly prevalent among patients with heart failure (HF). International guidelines on the management of HF recommend screening for cognitive impairment and tailored care for patients with cognitive impairment. However, practical guidance is lacking. In this study, we explore cardiologists' perspective on screening and care for cognitive impairment in patients with HF. We give an example of a multidisciplinary Heart-Brain care pathway that facilitates screening for cognitive impairment in patients with HF. METHODS: We distributed an online survey to cardiologists from the Dutch working groups on Geriatric Cardiology and Heart Failure. It covered questions about current clinical practice, impact of cognitive impairment on clinical decision-making, and their knowledge and skills to recognize cognitive impairment. RESULTS: Thirty-six out of 55 invited cardiologists responded. Only 3% performed structured cognitive screening, while 83% stated that not enough attention is paid to cognitive impairment. More than half of the cardiologists desired more training in recognizing cognitive impairment and three-quarters indicated that knowing about cognitive impairment would change their treatment plan. Eighty percent agreed that systematic cognitive screening would benefit their patients and 74% wished to implement a Heart-Brain clinic. Time and expertise were addressed as the major barriers to screening for cognitive impairment. CONCLUSION: Although cardiologists are aware of the clinical relevance of screening for cognitive impairment in cardiology patients, such clinical conduct is not yet commonly practiced due to lack of time and expertise. The Heart-Brain care pathway could facilitate this screening, thus improving personalized care in cardiology

Neuropsychology/computerized neuropsychological assessment

AbstractBackgroundDifferential diagnostics in dementia is challenging. To date, the basic assessment still includes imaging of the brain and cognitive testing with pen and paper. Web‐based cognitive tests however hold potential for standardized and low‐cost screening in clinical workup. How they perform when combined with imaging of the brain is unknown. We therefore evaluated the accuracy of a new web‐based cognitive battery (Muistikko [1]) detecting different types of dementia, when combined with brain MRI, and compared this to traditional cognitive testing and MRI.MethodWe included 229 subjects from two memory clinic cohorts (PredictND and VPH‐DARE), consisting of 188 controls, 29 patients with Alzheimer's dementia (AD), 7 with frontotemporal dementia (FTD) and 5 with vascular dementia (VaD) (Table 1). All patients performed a traditional cognitive test battery (consisting of MMSE, RAVLT, TMT‐A and B, Animal Fluency), web‐based cognitive testing and had MRI of the brain. Although Muistikko is composed of seven subtasks, only global cognitive score (GCS) was used as defined in [1]. From MRI, multiple imaging biomarkers were defined [2]. Disease‐state index classifier was developed from the predictors [2]. Cross‐validation was used to calculate balanced accuracy (BACC; average of sensitivities for each diagnostic group). Given the class imbalance, we also calculated prevalence corrected accuracy (PACC).ResultBACC was 66 % and PACC 64% when using the traditional cognitive test battery + MRI. Both BACC and PAC were 69 % when using the web‐based cognitive testing + MRI (Table 2). Of note, since we compare four diagnostic groups, BACC by guessing would be 25%.ConclusionThis study shows that combining web‐based cognitive tests with MRI data results in high accuracy when separating different types of dementia. The results were comparable with the standard traditional work‐up. Web‐based cognitive testing is therefore a promising tool to support the clinician in the daily challenge of differential diagnostics, especially when combined with MRI data. References: [1] Paajanen, S. et al. Detecting cognitive disorders using Muistikko web‐based cognitive test battery. Alzheimer's & Dementia 13(7):Supplement,P234‐P235,2017 [2] Bruun, M. et al. Evaluating combinations of diagnostic tests to discriminate different dementia types. Alzheimers Dement 2018 Aug17;10:509‐51

Embedding routine health care data in clinical trials: with great power comes great responsibility

Randomised clinical trials (RCTs) are vital for medical progress. Unfortunately, 'traditional' RCTs are expensive and inherently slow. Moreover, their generalisability has been questioned. There is considerable overlap in routine health care data (RHCD) and trial-specific data. Therefore, integration of RHCD in an RCT has great potential, as it would reduce the effort and costs required to collect data, thereby overcoming some of the major downsides of a traditional RCT. However, use of RHCD comes with other challenges, such as privacy issues, as well as technical and practical barriers. Here, we give a current overview of related initiatives on national cardiovascular registries (Netherlands Heart Registration, Heart4Data), showcasing the interrelationships between and the relevance of the different registries for the practicing physician. We then discuss the benefits and limitations of RHCD use in the setting of a pragmatic RCT from a cardiovascular perspective, illustrated by a case study in heart failure

Pseudo-Healthy Image Synthesis for White Matter Lesion Segmentation

White matter hyperintensities (WMH) seen on FLAIR images are established as a key indicator of Vascular Dementia (VD) and other pathologies.We propose a novel modality transformation technique to generate a subject-specific pathology-free synthetic FLAIR image from a T1 -weighted image. WMH are then accurately segmented by comparing this synthesized FLAIR image to the actually acquired FLAIR image. We term this method Pseudo-Healthy Image Synthesis (PHI-Syn). The method is evaluated on data from 42 stroke patients where we compare its performance to two commonly used methods from the Lesion Segmentation Toolbox. We show that the proposed method achieves superior performance for a number of metrics. Finally, we show that the features extracted from the WMH segmentations can be used to predict a Fazekas lesion score that supports the identification of VD in a dataset of 468 dementia patients. In this application the automatically calculated features perform comparably to clinically derived Fazekas scores

Reviews of individual patient data (IPD) are useful for geriatrics: an overview of available IPD reviews

To determine how many individual patient data (IPD) reviews that included older people were available in MEDLINE and whether the effectiveness of treatments differed between older and younger individuals. Overview of IPD reviews. A MEDLINE search was conducted for IPD reviews of randomized controlled trials published before July 2012. IPD reviews that presented a regression model that included age as a factor or a subgroup analysis of individuals aged 70 and older or in which all participants were aged 70 and older. Whether the IPD reviews reported similar conclusions for the younger and older populations was evaluated. Twenty-six IPD reviews with a subgroup of older individuals and eight reviews with only older individuals were included (median N = 3,351). The most important reason for choosing an IPD review was the ability to perform a subgroup analysis in the older population. Fourteen IPD reviews suggested that older people should receive different treatments from younger people because of differences in effectiveness, six of which indicated that the investigated treatment(s) should be avoided in older adults. IPD review is a valuable approach for generating evidence in older adults. Treatment effects frequently differed between older and younger individuals. Still, IPD results should be applied to older adults cautiously, because they are often excluded from primary trials. The collaborative sharing of raw data should be promoted to improve evidence-based decisions for this grou

Sex-Specific Associations of Diabetes With Brain Structure and Function in a Geriatric Population

Introduction: Globally, women with dementia have a higher disease burden than men with dementia. In addition, women with diabetes especially are at higher risk for cognitive impairment and dementia compared to men with diabetes. Differences in the influence of diabetes on the cerebral vasculature and brain structure may contribute to these sex-specific differences. We examined sex-specific patterns in the relationship between diabetes and brain structure, as well as diabetes and cognitive function. Methods: In total, 893 patients [age 79 ± 6.6 years, 446 (50%) women] from the Amsterdam Ageing Cohort with available data on brain structures (assessed by an MRI or CT scan) and cognitive function were included. All patients underwent a thorough standardized clinical and neuropsychological assessment (including tests on memory, executive functioning, processing speed, language). Brain structure abnormalities were quantified using visual scales. Results: Cross-sectional multivariable regression analyses showed that diabetes was associated with increased incidence of cerebral lacunes and brain atrophy in women (OR 2.18 (1.00–4.72) but not in men. Furthermore, diabetes was associated with decreased executive function, processing speed and language in women [B −0.07 (0.00–0.13), −0.06 (0.02–0.10) and −0.07 (0.01–0.12) resp.] but not in men. Conclusions: Diabetes is related to increased risk of having lacunes, brain atrophy and impaired cognitive function in women but not in men. Further research is required to understand the time trajectory leading up to these changes and to understand the mechanisms behind them in order to improve preventive health care for both sexes