International consensus statement on the diagnosis and management of phaeochromocytoma and paraganglioma in children and adolescents.
Ruth T CaseyEmile HendriksCheri DealSteven G WaguespackVerena WiegeringRedlich AntjeScott AkkerRathi PrasadFassnacht MartinRoderick John Clifton-BlighLaurence AmarStefan R BornsteinLetizia CanuEvangelia CharmandariAlexandra ChrisoulidouMaria Currás FreixesRonald de KrijgerLuisa de SanctisAntonio FojoAmol J GhiaAngela HuebnerVasilis KosmoliaptsisMichaela KuehlenMarco RaffaeliCharlotte Lussey-LepoutreStephen D MarksNaris NilubolMirko Parasiliti-CaprinoHenri H J L M TimmersAnna Lena ZietlowMercedes RobledoAnne-Paule Gimenez-RoqueploAshley B GrossmanDavid TaïebEamonn R MaherJacques W M LendersGraeme EisenhoferCamilo JimenezKarel PacakChristina PamporakiPublished in: Nature reviews. Endocrinology (2024)
Phaeochromocytomas and paragangliomas (PPGL) are rare neuroendocrine tumours that arise not only in adulthood but also in childhood and adolescence. Up to 70-80% of childhood PPGL are hereditary, accounting for a higher incidence of metastatic and/or multifocal PPGL in paediatric patients than in adult patients. Key differences in the tumour biology and management, together with rare disease incidence and therapeutic challenges in paediatric compared with adult patients, mandate close expert cross-disciplinary teamwork. Teams should ideally include adult and paediatric endocrinologists, oncologists, cardiologists, surgeons, geneticists, pathologists, radiologists, clinical psychologists and nuclear medicine physicians. Provision of an international Consensus Statement should improve care and outcomes for children and adolescents with these tumours.
Keyphrases
- intensive care unit
- emergency department
- end stage renal disease
- risk factors
- early life
- palliative care
- quality improvement
- depressive symptoms
- small cell lung cancer
- healthcare
- newly diagnosed
- primary care
- childhood cancer
- chronic kidney disease
- prognostic factors
- peritoneal dialysis
- artificial intelligence
- young adults
- machine learning
- type diabetes
- patient reported outcomes
- metabolic syndrome
- deep learning
- adipose tissue
- chronic pain
- advanced cancer