Neuroendocrine tumours (NET) are clinically challenging due to their unpredictable behaviour. Nomograms, grading and staging systems are predictive tools with multiple roles in clinical practice, including patient prognostication. The NET nomogram allocates scores for various clinicopathological parameters, calculating percentage estimates for 5- and 10-year disease-specific survival of patients with small bowel (SB) NET. We evaluated the clinical utility of three prognostic systems in 70 SB NET patients: the NET nomogram, the World Health Organisation (WHO)/European Neuroendocrine Tumour Society (ENETS) grading system and the American Joint Commission on Cancer (AJCC)/Union Internationale Contre le Cancer (UICC) TNM staging method. Using Kaplan–Meier methodology, neither the WHO/ENETS grade (P = 0.6) nor the AJCC/UICC stage (P = 0.276) systems demonstrated significant differences in patient survival in the cohort. The NET nomogram was well calibrated to our data set, displaying favourable prediction accuracy. Harrel’s C-index for the nomogram (a measure of predictive power) was 0.65, suggesting good prediction ability. On Kaplan–Meier analyses, there were significant differences in patient survival when stratified into nomogram score-based risk groups: low-, medium- and high-risk tumours were associated with median estimated survivals of 156, 129 and 112 months, respectively (P = 0.031). Our data suggest that a multivariable analysis-based NET nomogram may be clinically useful for patient survival prediction. This study identifies the limitations of the NET nomogram and the imperfections of other currently used single or binary parameter methodologies for assessing neuroendocrine disease prognosis. The future addition of other variables to the NET nomogram will likely amplify the accuracy of this personalised tool.
Ashley K Clift, Omar Faiz, Robert Goldin, John Martin, Harpreet Wasan, Marc-Olaf Liedke, Erik Schloericke, Anna Malczewska, Guido Rindi, Mark Kidd, Irvin M Modlin and Andrea Frilling
Anna Malczewska, Magdalena Witkowska, Karolina Makulik, Agnes Bocian, Agata Walter, Joanna Pilch-Kowalczyk, Wojciech Zajęcki, Lisa Bodei, Kjell Oberg and Beata Kos-Kudła
Current monoanalyte biomarkers are ineffective in gastroenteropancreatic neuroendocrine tumors (GEP-NETs). NETest, a novel multianalyte signature, provides molecular information relevant to disease biology.
Independently validate NETest to diagnose GEP-NETs and identify progression in a tertiary referral center.
Materials and methods
Cohorts are 67 pancreatic NETs (PNETs), 44 small intestine NETs (SINETs) and 63 controls. Well-differentiated (WD) PNETs, n = 62, SINETs, all (n = 44). Disease extent assessment at blood draw: anatomical (n = 110) CT (n = 106), MRI (n = 7) and/or functional 68Ga-SSA-PET/CT (n = 69) or 18F-FDG-PET/CT (n = 8). Image-positive disease (IPD) was defined as either CT/MRI or 68Ga-SSA-PET/CT/18F-FDG-PET/CT-positive. Both CT/MRI and 68Ga-SSA-PET/CT negative diagnosis in WD-NETs was considered image-negative disease (IND). NETest (normal: 20): PCR (spotted plates). Data: mean ± SD.
NETest was significantly increased in NETs (n = 111; 26 ± 21) vs controls (8 ± 4, p < 0.0001). Seventy-five (42 PNET, 33 SINET) were image positive. Eleven (8 PNET, 3 SINET; all WD) were IND. In IPD, NETest was significantly higher (36 ± 22) vs IND (8 ± 7, P < 0.0001). NETest accuracy, sensitivity and specificity are 97, 99 and 95%, respectively
Concordance with imaging
NETest was 92% (101/110) concordant with anatomical imaging, 94% (65/69) with 68Ga-SSA-PET/CT and 96% (65/68) dual modality (CT/MRI and 68Ga-SSA-PET/CT). In 70 CT/MRI positive, NETest was elevated in all (37 ± 22). In 40 CT/MRI negative, NETest was normal (11 ± 10) in 31. In 56 68Ga-SSA-PET/CT positive, NETest was elevated (36 ± 22) in 55. In 13 68Ga-SSA-PET/CT negative, NETest was normal (9 ± 8) in ten.
NETest was significantly higher in progressive (61 ± 26; n = 11) vs stable disease (29 ± 14; n = 64; P < 0.0001) (RECIST 1.1).
NETest is an effective diagnostic for PNETs and SINETs. Elevated NETest is as effective as imaging in diagnosis and accurately identifies progression.