ECEESPE2025 Poster Presentations MTEabolism, Nutrition and Obesity (125 abstracts)
Single point insulin sensitivity estimator (SPISE) for cardiovascular risk assessment in pediatric central nervous system cancer survivors (PCNSCSs): a practical approach for early detection
Giacomo Tantari 1 , Amanda Casirati 1 , Gianluca Piccolo 2 , Marco Del Monte 3 , Alessandro Suppa 3 , Annalisa Gallizia 4 , Marta Panciroli 3 , Mohamad Maghnie 3 , Giuseppe d’Annunzio 1 & Natascia Di Iorgi 3
1Pediatric Clinic and Endocrinology Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy; 2Neuroncology Unit, IRCCS Istituto G. Gaslini, Genoa, Italy; 3DINOGMI (Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health), University of Genoa, Genoa, Italy; 4Pulmonary Disease and Respiratory Endoscopic Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy
JOINT3120
Background: The long-term cancer survivors has increased, but the effects of therapies require attention. PCNSCSs are at risk for insulin resistance (IR) and cardiovascular (CV) complications. IR can be detected by a simple and reproducible method called SPISE.
Methods: We assessed SPISE in 57 PCNSCSs (27 males), median age 12 years (5-18), followed for at least two years post-treatment. Diagnoses included astrocytic (37%), embryonal (23%), sellar (14%), ependymal (14%), and germ cell (12%) tumors. Treatment involved radiotherapy (88% of patients, 37% craniospinal), chemotherapy (75%), and surgery (74%). We analyzed body mass index (BMI), waist/height ratio (WHtR), laboratory exams, and DXA. BMI > 1 SDS defined overweight (40% of patients), BMI > 2 SDS obesity (12%), WHtR ≥ 0.5 CV risk. SPISE was calculated as: 600 × HDL cholesterol^0.185/triglycerides^0.2 × BMI^1.338, fat/lean mass (FLR) by DXA.
Results: A WHtR ≥ 0.5 was found in 53% of PCNSCSs. Patients with WHtR ≥ 0.5 had higher BMI SDS values (1.33 [0.83; 2.02] vs. -0.04 [-0.71; 0.5], p < 0.001) and lower SPISE values (6.98 [5.15-8.50] vs. 10.60 [8.75-11.28], p < 0.001). SPISE was associated with WHtR ≥ 0.5 (Or = 0.626, 95% CI [0.462-0.848], P = 0.003), with an AUC of 0.81 (p < 0.001) for predicting WHtR ≥ 0.5. The optimal SPISE cut-off was 8.63 (sensitivity = 78%, specificity = 79%). PCNSCSs with SPISE ≤ 8.63 (51%) had higher FLR values (0.77 [0.57; 0.93] vs. 0.58 [0.36; 0.72], P = 0.002) and higher WHtR (0.52 [0.49; 0.57] vs. 0.47 [0.42; 0.49], p <. 001). Those with WHtR ≥ 0.5 had higher FLR values (0.86 [0.63; 0.94] vs. 0.54 [0.36; 0.74], P = 0.001), with FLR associated with WHtR ≥ 0.5 (Or = 61.9, 95% CI [4.73-811.0], P = 0.002). ROC curve analysis identified FLR > 0.86 as a threshold for altered body composition (AUC = 0.77, P = 0.001, sensitivity = 53%, specificity = 93%). SPISE was associated with FLR > 0.86 (Or = 0.56, 95% CI [0.42-0.75], p < 0.001), and its AUC for predicting FLR > 0.86 was 0.82 (p < 0.001).
Conclusions: SPISE association with higher WHtR and FLR, indicates its valuable and non-invasive tool for identifying CV risk. SPISE requires few universally available laboratory data, and could be a useful tool for longitudinal studies in PCNSCSs. Furthermore, it may help to optimize resource allocation by prioritizing DXA for patients with low SPISE and high WHtR.
Volume 110
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Endocrine Abstracts
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