Primary temporal bone angiosarcoma: a case report.

We present a rare case of temporal bone angiosarcoma diagnosed in a 26-year-old female patient at 36 week of pregnancy. The patient was referred with a 2 months history of left otalgia and tinnitus with a tender swelling above the mastoid. Cranial imaging studies showed a 7 x 5 x 4 cm hypervascularized mass located in the left middle fossa with lysis of the temporal bone and extension to the subcutis. After the baby was delivered by caesarean section, the patient entered the oncology protocol. Selective embolization of the feeding vessels was followed by gross total surgical resection using a combined supra- and infra-tentorial approach. Pathological findings were those of a poorly differentiated, highly malignant sarcoma with a large epitheloid component and immunohistochemical evidence of endothelial differentiation (CD31, Factor VIII related antigen, CD34), consistent with an angiosarcoma with epitheloid features. No extra-cranial tumor was found after extensive staging. The patient received adjuvant radiotherapy followed by a course of chemotherapy consisting of 6 cycles of paclitaxel. At 15 months follow-up, she developed multiple distant metastasis to a left postauricular lymph node and to the lungs and ribs. The patient was given a second line chemotherapy using doxorubicine and ifosfamide. Despite an initial good response, she died with metastatic disease 26 months after diagnosis. We present a rare case of primary temporal bone angiosarcoma and report our experience with a multimode therapeutic approach combining surgery, radiotherapy and chemotherapy.Peer reviewe

Contribution of NMR spectroscopy to the differential diagnosis of a recurrent cranial mass 7 years after irradiation for a pediatric ependymoma.

CASE REPORT: We describe the case of a 5-year-old-boy who underwent surgery and focal radiotherapy for an anaplastic ependymoma of the fourth ventricle. One year later, a spinal metastasis was treated the same way. Six years later, a 16-mm lesion was found on a control MRI in the posterior fossa. To help the differential diagnosis between a relapse, a radio-induced modification, and a new tumor, magnetic resonance spectroscopy was performed. The main findings were a peak at the expected resonance frequency of reduced glutathione, a prominent peak of glutamate/glutamine compounds, a low N-acetylaspartate, and the absence of elevated choline. These findings were suggestive of a meningioma, although the latency between irradiation and development of the lesion was quite short. The diagnosis was confirmed by the pathological examination. CONCLUSION: This case exemplifies the fact that magnetic resonance spectroscopy provides useful biochemical information in such a clinical setting.Case ReportsJournal ArticleSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Impact of age at onset on symptom profiles, treatment characteristics and health-related quality of life in Parkinson’s disease

Parkinson’s disease (PD) is typically considered an age-related disease, but the age at disease onset can vary by decades between patients. Aging and aging-associated diseases can affect the movement system independently of PD, and advanced age has previously been proposed to be associated with a more severe PD phenotype with accelerated progression. In this work, we investigated how interactions between PD progression and aging affect a wide range of outcomes related to PD motor and nonmotor symptoms as well as Health Related Quality of Life (HRQoL) and treatment characteristics. This population-based cohort study is based on 1436 PD patients from southern Sweden followed longitudinally for up to approximately 7.5 years from enrollment (3470 visits covering 2285 patient years, average follow-up time 1.7 years). Higher age at onset was generally associated with faster progression of motor symptoms, with a notable exception of dyskinesia and other levodopa-associated motor fluctuations that had less severe trajectories for patients with higher age at onset. Mixed results were observed for emergence of non-motor symptoms, while higher age at onset was generally associated with worse HRQoL trajectories. Accounting for these identified age-associated differences in disease progression could positively impact patient management and drug development efforts

High risk of developing dementia in Parkinson’s disease : a Swedish registry-based study

Dementia have substantial negative impact on the affected individual, their care partners and society. Persons living with Parkinson’s disease (PwP) are also to a large extent living with dementia. The aim of this study is to estimate time to dementia in PD using data from a large quality register with access to baseline clinical and patient reported data merged with Swedish national health registries. Persons with Parkinson’s disease in the Swedish Neuro Registries/Parkinson’s Disease Swedish PD Registry (PARKreg) in Sweden were included and linked to national health registries and matched by sex and age to controls without PD. Time to dementia was analysed with Cox regression models assuming proportional hazards, with time since diagnosis as the underlying time variable. In this large prospective cohort study, PwP had approximately four times higher risk of developing dementia as compared to age and sex-matched controls, a finding which remained after adjusting for potential confounders. The present results underline the high risk of dementia in PD and further emphasize the importance of developing symptomatic and ultimately disease modifying strategies to counteract this part of the non-motor symptomatology in PD

Transdiagnostic individualized clinically-based risk calculator for the automatic detection of individuals at-risk and the prediction of psychosis : external replication in 2,430,333 US patients

The real-world impact of psychosis prevention is reliant on effective strategies for identifying individuals at risk. A transdiagnostic, individualized, clinically-based risk calculator to improve this has been developed and externally validated twice in two different UK healthcare trusts with convincing results. The prognostic performance of this risk calculator outside the UK is unknown. All individuals who accessed primary or secondary health care services belonging to the IBM® MarketScan® Commercial Database between January 2015 and December 2017, and received a first ICD-10 index diagnosis of nonorganic/nonpsychotic mental disorder, were included. According to the risk calculator, age, gender, ethnicity, age-by-gender, and ICD-10 cluster diagnosis at index date were used to predict development of any ICD-10 nonorganic psychotic disorder. Because patient-level ethnicity data were not available city-level ethnicity proportions were used as proxy. The study included 2,430,333 patients with a mean follow-up of 15.36 months and cumulative incidence of psychosis at two years of 1.43%. There were profound differences compared to the original development UK database in terms of case-mix, psychosis incidence, distribution of baseline predictors (ICD-10 cluster diagnoses), availability of patient-level ethnicity data, follow-up time and availability of specialized clinical services for at-risk individuals. Despite these important differences, the model retained accuracy significantly above chance (Harrell’s C = 0.676, 95% CI: 0.672–0.679). To date, this is the largest international external replication of an individualized prognostic model in the field of psychiatry. This risk calculator is transportable on an international scale to improve the automatic detection of individuals at risk of psychosis

Disease Progression in Multiple System Atrophy—Novel Modeling Framework and Predictive Factors

Background: Multiple system atrophy (MSA) is a rare and aggressive neurodegenerative disease that typically leads to death 6 to 10 years after symptom onset. The rapid evolution renders it crucial to understand the general disease progression and factors affecting the disease course. Objectives: The aims of this study were to develop a novel disease-progression model to estimate a population-level MSA progression trajectory and predict patient-specific continuous disease stages describing the degree of progress into the disease. Methods: The disease-progression model estimated a population-level progression trajectory of subscales of the Unified MSA Rating Scale and the Unified Parkinson's Disease Rating Scale using patients in the European MSA natural history study. The predicted disease continuum was validated via multiple analyses based on reported anchor points, and the effect of MSA subtype on the rate of disease progression was evaluated. Results: The predicted disease continuum spanned approximately 6 years, with an estimated average duration of 51 months for a patient with global disability score 0 to reach the highest level of 4. The predicted continuous disease stages were shown to be correlated with time of symptom onset and predictive of survival time. MSA motor subtype was found to significantly affect disease progression, with MSA-parkinsonian (MSA-P) type patients having an accelerated rate of progression. Conclusions: The proposed modeling framework introduces a new method of analyzing and interpreting the progression of MSA. It can provide new insights and opportunities for investigating covariate effects on the rate of progression and provide well-founded predictions of patient-level future progressions

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

Accurate prediction of progression in subjects at risk of Alzheimer's disease is crucial for enrolling the right subjects in clinical trials. However, a prospective comparison of state-of-the-art algorithms for predicting disease onset and progression is currently lacking. We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of patient-specific biomarkers. On a limited, cross-sectional subset of the data emulating clinical trials, performance of the best algorithms at predicting clinical diagnosis decreased only slightly (2 percentage points) compared to the full longitudinal dataset. The submission system remains open via the website https://tadpole.grand-challenge.org, while TADPOLE SHARE (https://tadpole-share.github.io/) collates code for submissions. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials.</jats:p