Abstract
Acute lymphobastic leukemia (ALL) is the most common childhood malignancy and accounts for 80% of all leukemia cases in children. Currently, long-term survival rates have been achieved along with better care committed to children with cancer, but late adverse effects have also increased markedly. Endocrine problems, such as growth impairment and obesity, are considered the most common sequelae after leukemia successful treatment, even though the pathogenesis of obesity remains to be established. As long as obesity is an important adverse effect of leukemia treatment and the association between insulin resistance, metabolic syndrome and cardiovascular risk is well-known, our goal is to determine cardiovascular risk features in young adult survivors of childhood ALL and the association between body fat distribution, carotid intima-media thickness, insulin resistance, dyslipidemia, familial contribution and biological markers secreted by adipocytes. We intend to study 20 young adult survivors of childhood ALL, maximum age 25 yr and out of treatment (chemotherapy with or without radiotherapy) for at least 2 yr. The patients must have normal gonadal, thyroid and adrenal function. Patients will be compared with a control group with no previous history of oncologic diseases and paired by age, sex and body mass index. The following parameters will be analyzed: chronologic age, sex, age at diagnosis, age at end of ALL therapy, type of treatment employed (chemotherapy only or combined with cranial radiotherapy), family history of obesity, hypertension, diabetes and/or cardiovascular disease, weight, height, body mass index, blood pressure, waist and hip circumferences. Body composition will be measured by Dual-Energy X-Ray Absorptiometry (DEXA), abdominal body fat deposits will be evaluated by Computerized Tomography (CT) scan and carotid intima-media thickness measurements will be performed by ultrasound (US) scans. The following profile will be measured: FT4, TSH-US, LH, FSH, serum estradiol or total testosterone, ACTH, hemogram, urea, creatinin, uric acid, AST and ALT. Patients with normal initial evaluation will be considered for a second measurement: glycosylated hemoglobin, fasting glucose, insulin (to calculate glucose/insulin ratio, HOMA and QUICK indexes), total cholesterol, its fractions, triglycerides, IGF-I, IGFBP-3, leptin, adiponectin, resistin, visfatin, MCP-1, TNF-alfa;, IL-6, free fatty acids, A1 apolipoprotein, B apolipoprotein and C reactive protein. Data files will be organized in electronic plans (SPSS version 11.0). Descriptive data analysis including mean, median and standard deviation score calculations will be performed when possible (quantitative variables). Wilcoxon test will compare patients and controls and Spearman correlation will be used to compare two separate variables. Simple linear regression test will determine the association between cardiovascular risk (central obesity + insulin resistance with or without dislipidemia with or without family history) and other variables. 5% is chosen as the level of significance. (AU)
Scientific publications
(4)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
SIVIERO-MIACHON, ADRIANA APARECIDA;
SPINOLA-CASTRO, ANGELA MARIA;
DE MARTINO LEE, MARIA LUCIA;
CALIXTO, ANTONIO RAMOS;
GELONEZE, BRUNO;
LAZARETTI-CASTRO, MARISE;
GUERRA-JUNIOR, GIL.
Visfatin is a positive predictor of bone mineral density in young survivors of acute lymphocytic leukemia.
JOURNAL OF BONE AND MINERAL METABOLISM,
v. 35,
n. 1,
p. 73-82,
JAN 2017.
Web of Science Citations: 2.
SIVIERO-MIACHON, ADRIANA APARECIDA;
SPINOLA-CASTRO, ANGELA MARIA;
DE MARTINO LEE, MARIA LUCIA;
DE CASTRO MONTEIRO, CARLOS MANOEL;
DE CAMARGO CARVALHO, ANTONIO CARLOS;
CALIXTO, ANTONIO RAMOS;
GELONEZE, BRUNO;
GUERRA-JUNIOR, GIL.
Subcutaneous adipose tissue plays a beneficial effect on subclinical atherosclerosis in young survivors of acute lymphocytic leukemia.
VASCULAR HEALTH AND RISK MANAGEMENT,
v. 11,
p. 479-488,
2015.
Web of Science Citations: 4.