Economic burden and health-related quality of life in tenosynovial giant-cell tumour patients in Europe: an observational disease registry

Background Tenosynovial Giant-Cell Tumour (TGCT) is a benign clonal neoplastic proliferation arising from the synovium, causing a variety of symptoms and often requiring repetitive surgery. This study aims to define the economic burden-from a societal perspective-associated with TGCT patients and their health-related quality of life (HRQOL) in six European countries. Methods This article analyses data from a multinational, multicentre, prospective observational registry, the TGCT Observational Platform Project (TOPP), involving hospitals and tertiary sarcoma centres from six European countries (Austria, France, Germany, Italy, the Netherlands, and Spain). It includes information on TGCT patients' health-related quality of life and healthcare and non-healthcare resources used at baseline (the 12-month period prior to the patients entering the registry) and after 12 months of follow-up. Results 146 TGCT patients enrolled for the study, of which 137 fulfilled the inclusion criteria. Their mean age was 44.5 years, and 62% were female. The annual average total costs associated with TGCT were euro4866 at baseline and euro5160 at the 12-month follow-up visit. The annual average healthcare costs associated with TGCT were euro4620 at baseline, of which 67% and 18% corresponded to surgery and medical visits, respectively. At the 12-month follow-up, the mean healthcare costs amounted to euro5094, with surgery representing 70% of total costs. Loss of productivity represented, on average, 5% of the total cost at baseline and 1.3% at follow-up. The most-affected HRQOL dimensions, measured with the EQ-5D-5L instrument, were pain or discomfort, mobility, and the performance of usual activities, both at baseline and at the follow-up visit. Regarding HRQOL, patients declared a mean index score of 0.75 at baseline and 0.76 at the 12-month follow-up. Conclusion The results suggest that TGCT places a heavy burden on its sufferers, which increases after one year of follow-up, mainly due to the healthcare resources required-in particular, surgical procedures. As a result, this condition has a high economic impact on healthcare budgets, while the HRQOL of TGCT patients substantially deteriorates over time.Orthopaedics, Trauma Surgery and Rehabilitatio

The diffuse-type tenosynovial giant cell tumor (dt-TGCT) patient journey: a prospective multicenter study

Background: Tenosynovial giant cell tumor (TGCT) is a rare, locally aggressive neoplasm arising from the synovium of joints, bursae, and tendon sheaths affecting small and large joints. It represents a wide spectrum ranging from minimally symptomatic to massively debilitating. Most findings to date are mainly from small, retrospective case series, and thus the morbidity and actual impact of this rare disease remain to be elucidated. This study prospectively explores the management of TGCT in tertiary sarcoma centers.Methods: The TGCT Observational Platform Project registry was a multinational, multicenter, prospective observational study involving 12 tertiary sarcoma centers in 7 European countries, and 2 US sites. This study enrolled for 2 years all consecutive >= 18 years old patients, with histologically diagnosed primary or recurrent cases of diffuse-type TGCT. Patient demographic and clinical characteristics were collected at baseline and every 6 months for 24 months. Quality of life questionnaires (PROMIS-PF and EQ-5D) were also administered at the same time-points. Here we report baseline patient characteristics.Results: 166 patients were enrolled between November 2016 and March 2019. Baseline characteristics were: mean age 44 years (mean age at disease onset: 39 years), 139/166 (83.7%) had prior treatment, 71/166 patients (42.8%) had >= 1 recurrence after treatment of their primary tumor, 76/136 (55.9%) visited a medical specialist >= 5 times, 66/116 (56.9%) missed work in the 24 months prior to baseline, and 17/166 (11.6%) changed employment status or retired prematurely due to disease burden. Prior treatment consisted of surgery (i.e., arthroscopic, open synovectomy) (128/166; 77.1%) and systemic treatments (52/166; 31.3%) with imatinib (19/52; 36.5%) or pexidartinib (27/52; 51.9%). Treatment strategies at baseline visits consisted mainly of watchful waiting (81/166; 48.8%), surgery (41/166; 24.7%), or targeted systemic therapy (37/166; 22.3%). Patients indicated for treatment reported more impairment compared to patients indicated for watchful waiting: worst stiffness NRS 5.16/3.44, worst pain NRS 6.13/5.03, PROMIS-PF 39.48/43.85, and EQ-5D VAS 66.54/71.85.Conclusion: This study confirms that diffuse-type TGCT can highly impact quality of life. A prospective observational registry in rare disease is feasible and can be a tool to collect curated-population reflective data in orphan diseases.Experimentele farmacotherapi

Function estimation with locally adaptive dynamic models

We present a nonparametric Bayesian method for fitting unsmooth functions which is based on a locally adaptive hierarchical extension of standard dynamic or state space models. The main idea is to introduce locally varying variances in the states equations and to add a further smoothness prior for this variance function. Estimation is fully Bayesian and carried out by recent MCMC techniques. The whole approach can be understood as an alternative to other nonparametric function estimators, such as local regression with local bandwidth or smoothing parameter selection. Performance is illustrated with simulated data, including unsmooth examples constructed for wavelet shrinkage, and by an application to CP6 scales data. (orig.)SIGLEAvailable from TIB Hannover: RR 6137(135) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Function estimation with locally adaptive dynamic models

We present a nonparametric Bayesian method for fitting unsmooth functions which is based on a locally adaptive hierarchical extension of standard dynamic or state space models. The main idea is to introduce locally varying variances in the states equations and to add a further smoothness prior for this variance function. Estimation is fully Bayesian and carried out by recent MCMC techniques. The whole approach can be understood as an alternative to other nonparametric function estimators, such as local regression with local bandwidth or smoothing parameter selection. Performance is illustrated with simulated data, including unsmooth examples constructed for wavelet shrinkage, and by an application to CP6 scales data. (orig.)SIGLEAvailable from TIB Hannover: RR 6137(135) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman