Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease from the parkinsonian syndrome group. PSP is characterised by the association of a non-doparesponsive parkinsonian syndrome with axial signs. The latter predominantly manifest as a psycho-motor slowness, an apathy and frontal executive deficits. Swallowing impairments may additionally provoke life-threatening situations. Today the treatment is mostly symptomatic as no cure is available. Given the limited treatment options and its clinical characteristics, PSP deeply impact on the patients' quality of life (QoL) as well as on their caregivers'. Nevertheless a limited number of studies have focused on these aspects. A better understaning of the factors determining both patient and cargiver QoL may help optimising their care. the principal objective of this study is to identify the determinants of PSP patients' QoL. The secondary objectives are : i) to identify the determinants (medical, behavioural, socio-economic, environmental …) of PSP patients' caregivers' QoL and burden ; ii) to validate in French language the QoL scale specific for PSP available in English (PSP-QoL). This is a multidisciplinary transversal study. 2 subject groups will be included : i) PSP patients ; ii) caregiver of PSP patients (designated by the patient as being the person closest to them), Data collected : i) from the patient : socio-demographic, social and professionnal environment, clinical (disease duration and severity, neuropsychological evaluation), therapeutic, mood, anxiety, coping, body image, QoL ; ii) from the caregiver: socio-demographic, social and professionnal environment, connection with the patient, data relative to their own health, mood, anxiety, coping, QoL, burden. Progress : patient information, designation of a caregiver, consent collection, collection of data Statistical analysis : To address the principal objective 'patient' QoL scores will be confronted to the other collected variables (Student's t-test, correlation coefficient). The results will be adjusted to the confounding factors using multivariate analyses.