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Obesity Does Not Affect the Recurrence Free Survival Rates in Children Less Than 20 Years of Age in Acute Promyelocytic Leukemia (APL)

Ji Heon (Paul) Lee, Alfred W. Rademaker, Bayard L. Powell, Susan Geyer, Richard A. Larson, John Gregory, Nobuko Hijiya and James H. Feusner

Abstract

Introduction Emerging data are demonstrating that obesity continues to be an epidemic among the pediatric population. A number of studies in children and adults reported that obesity at diagnosis affects survival in some cancers. Some reports show that obesity is an independent prognostic factor in patients in APL.1,2 The impact of obesity and outcome has never been studied in pediatric patients with APL.

Methods Patient data were collected and analyzed from APL patients treated on the North American Leukemia Intergroup C9710 study led by the Cancer and Leukemia Group B (Alliance), with participation by the Children’s Oncology Group (COG). Only patients with BMI data were included in these analyses (n=529) across all age groups. Children and adolescents (<20 years old) were divided into weight categories as follows: underweight, less than the 5th percentile; normal weight, from the 5th percentile to less than the 85th percentile; overweight, from the 85th percentile to less than 95th percentile; and obese, equal or greater than the 95th percentile (Center for Disease Control and Prevention; http://apps.nccd.cdc.gov/dnpabmi/). BMI for patients ≥20 years old were divided into weight categories: underweight, normal weight, overweight, obese, using the following cutpoints: underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5-25 kg/m2), overweight (BMI 25-29.9 kg/m2), and obese (BMI ≥ 30 kg/m2). Body weight categories were defined according to age- and sex-specific BMI percentiles. Both univariate and multivariate analysis were calculated using other factors such as age, gender, ethnicity and WBC at diagnosis (high risk if WBC ≥10,000). Recurrence-free survival (RFS) and overall survival (OS) were analyzed using Kaplan and Meier methods, and Log-rank tests used to assess prognostic impact of factors on survival distributions; p-values <0.05 were considered statistically significant.

Results In this group of 529 patients, 428 were ≥20 years old (y.o.) vs. 101 who were < 20 y.o. Within the < 20 y.o. group, the majority had normal weight (44.6%) based on BMI while the majority of the ≥20 y.o. group were obese (50.2%). A high percentage of those < 20 y.o. were also obese (33.7%). Median follow-up times for the <20 y.o. vs. >20 y.o. groups were 62.0 months (range, 1-149.8 months) vs. 96.7 months (range, 0.03 – 156.3 months), respectively. When compared to all other weight groups, OS and RFS did not significantly differ between obesity and other weight groups in patients < 20 y.o. (5-year OS rates: 64% vs 57%, p=0.94; and 5-year RFS rates: 83% vs 79%; p=0.60). However, in patients ≥20 years of age, RFS was worse in obese patients versus other weight groups (67% vs 77%, p = 0.026) as was OS (76% vs 85%, p = 0.023). Furthermore, we investigated therapy-related toxicities in the same weight groups. None of the toxicities (hematologic, infection, metabolic, pain, pulmonary) were significantly related to weight group (obese vs non-obese) for either age group (<20 years or >20 years).

Discussion This is the first study to report obesity in relation to clinical outcomes or toxicity in children and adolescents with APL <20 years of age. Here, obesity did not confer poorer RFS or OS in this younger age group. In contrast, this study confirms a previous Alliance study showing that increased BMI in adult patients (>18 years) with APL is associated with worse RFS and OS.2 It is not clear why BMI and obesity do not have prognostic influence on clinical outcomes in patients less than 20 years of age. Possible theories include confounding factors in adults such as poor compliance by race or socioeconomic status in obese patients, whereas close monitoring by parents may play a role for pediatric patients in this setting. Future studies would need to be dedicated to address these theories.

1. Breccia M, Mazzarella L, Bagnardi V, et al. Blood. 2012;119(1):49-54.

2. Castillo JJ, Mulkey F, Geyer S, et al. Blood. 2013;122(21):832.

Disclosures Rademaker: NIH Grant Review: Honoraria; AACR Faculty: Honoraria; Georgetown Univeristy Advisor: Honoraria. Hijiya: Sanofi: Consultancy; Jazz Pharma: Consultancy; Pfizer: Consultancy; Sigma Tau: Consultancy.

  • * Asterisk with author names denotes non-ASH members.