BSPED2019 ORAL COMMUNICATIONS Oral Communications 4 (9 abstracts)
1Centre for Endocrinology, William Harvey Research Institute, Queen Mary University of London, London, UK; 2Genetics and Genomic Medicine Programme UCL Great Ormond Street Institute of Child Health, London, UK; 3Postgraduate Institute of Medical Education and Research, Chandigarh, India; 4Sant Joan De Deu Children´s Hospital, Barcelona, Spain; 5Unit of Pathology, ASST Santi Paolo e Carlo, Milan, Italy; 6Department of Health Sciences, Università degli Studi di Milano, Milan, Italy; 7Cellular Pathology, Salford Royal Foundation Trust, Salford, UK; 8Neuroradiology Department, Barts Health NHS Trust, London, UK; 9Department of Endocrinology, University Hospital Centre Zagreb, Zagreb, Croatia; 10Greater Manchester Neuroscience Centre, Salford Royal Foundation Trust, Salford, UK; 11MRC Centre for Reproductive Health, Queens Medical Research Institute, Edinburgh, UK; 12Department of Paediatrics & Paediatric Endocrinology, Hospital Infantil Universitario Niño Jesús, Instituto de Investigación La Princesa, Universidad Autónoma de Madrid, Madrid, Spain; 13Neurosurgery Department, Instituto de Neurocirugia Asenjo, Santiago, Chile; 14Neurosurgery Department, Hospital Clinic of Barcelona, Barcelona, Spain; 15Endocrinology Department Vall dHebron University Hospital, Barcelona, Spain; 16Growth and Development Research Unit, Vall dHebron Research Institute (VHIR), Center for Biomedical Research on Rare Diseases (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain; 1713IIB-Sant Pau and Department of Endocrinology/Medicine, Hospital Sant Pau, UAB, and Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBER-ER, Unidad 747), ISCIII, Barcelona, Spain; 18Department of Paediatric Endocrinology, Kings College Hospital NHS Foundation Trust, London, UK; 19Department of Neurosurgery, Kings College Hospital NHS Foundation Trust, London, UK; 20Chair of EANS young neurosurgeons committee Servicio de Neurocirugía Hospital Universitario Donostia, San Sebastian, Spain; 21University of Medicine and Pharmacy Grigore T. Popa, Iasi, Romania; 22Cancer Intelligence Department, Cancer Research UK, London, UK; 23William Harvey Research Institute, Queen Mary University of London, London, UK; 24Department of Paediatric Endocrinology, Barts Health NHS Trust-Royal London Hospital, London, UK
Introduction: Craniopharyngiomas (CPs) are histologically benign tumours but are clinically associated with significant morbidity and mortality. Recurrence of CPs is known to influence mortality, but apart from the extent of surgical resection, no clinical characteristics have been shown to predict recurrence. Complete resection is difficult due to their infiltrative behaviour and unacceptable morbidity. Thus, predictors of risk of recurrence are needed.
Aim: To establish a multinational cohort of patients with CP and employ their clinical parameters to design a clinical tool that can predict the risk of CP recurrence.
Methods: 225 patients from 15 centres (8 countries) participated in our mixed prospective and retrospective observational cohort study. Tumour subtyping was performed by three histopathologists. Brain MRI (n=172) was scored for tumour size and hypothalamic invasion by a single neuroradiologist. A broad range of clinical data was collected. Statistical analyses were performed in R (2-sided, P<0.05 assumed significant); the primary outcome for prediction was time-to-first-recurrence.
Results: Median age at presentation was 19.7 years (IQR 10.647.3) and 89% were adamantinomatous. Fifty-six percent had a recurrence with a median time-to-first-recurrence of 23 months (IQR 944). A multivariate Cox model was performed using age, gender and clinical parameters before surgery (diagnosis decade; symptom duration; tumour subtype, size, consistency and location; hypothalamic invasion; endocrinopathies) and after surgery (transsphenoidal/craniotomy, complete/incomplete, radiotherapy) as risk predictors of time-to-recurrence. A risk-score was computed as the linear predictor of the fitted multivariate Cox model. 5th, 20th and 99th centiles of the risk-score were used to categorise the patients into low, medium or high risk respectively. KaplanMeier curves showed a clear separation in recurrence-free-survival between the three risk groups (P<0.0001). A cut-off value of 0.948 was selected for a 92% sensitivity at one-year follow-up (95%CI:8498%), and corresponding specificity of 35% (95%CI:2742%). KaplanMeier curves also showed that radiotherapy resulted in significantly longer recurrence-free-survival (P<0.006).
Conclusion: This is the first study that uses a large clinical dataset to design a model to predict risk of CP recurrence, combining several clinical characteristics. This model will facilitate identification of other risk factors and following external validation, can be used in clinical practice to improve clinical care.