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  • Title: The 6-minute walk test is a good predictor of cardiorespiratory fitness in childhood cancer survivors when access to comprehensive testing is limited.
    Author: Mizrahi D, Fardell JE, Cohn RJ, Partin RE, Howell CR, Hudson MM, Robison LL, Ness KK, McBride J, Field P, Wakefield CE, Simar D.
    Journal: Int J Cancer; 2020 Aug 01; 147(3):847-855. PubMed ID: 31800093.
    Abstract:
    Cardiovascular disease is up to 10 times more likely among childhood cancer survivors compared to siblings. Low cardiorespiratory fitness is a modifiable risk-factor for cardiovascular diseases. Yet, cardiorespiratory fitness is not routinely screened in pediatric oncology, and healthy VO2max cut-points are unavailable. We aimed to predict cardiorespiratory fitness by developing a simple algorithm and establish cut-points identifying survivors' cardiovascular fitness health-risk zones. We recruited 262 childhood cancer survivors (8-18 years old, ≥1-year posttreatment). Participants completed gold-standard cardiorespiratory fitness assessment (Cardiopulmonary Exercise Test [CPET; VO2max ]) and 6-minute walk test (6MWT). Associations with VO2max were included in a linear regression algorithm to predict VO2max , which was then cross-validated. We used Bland-Altman's limits of agreement and Receiver Operating Characteristic curves using FITNESSGRAM's "Healthy Fitness Zones" to identify cut-points for adequate cardiorespiratory fitness. A total of 199 participants (aged 13.7 ± 2.7 years, 8.5 ± 3.5 years posttreatment) were included. We found a strong positive correlation between VO2max and 6MWT distance (r = 0.61, r2 = 0.37, p < 0.001). Our regression algorithm included 6MWT distance, waist-to-height ratio, age and sex to predict VO2max (r = 0.79, r2 = 0.62, p < 0.001). Forty percentages of predicted VO2max values were within ±3 ml/kg/min of measured VO2max . The cut-point for FITNESSGRAM's "health-risk" fitness zone was 39.8 ml/kg/min (males: AUC = 0.88), and 33.5 ml/kg/min (females: AUC = 0.82). We present an algorithm to reasonably predict cardiorespiratory fitness for childhood cancer survivors, using inexpensive measures. This algorithm has useful clinical application, particularly when CPET is unavailable. Our algorithm has the potential to assist clinicians to identify survivors below the cut-points with increased cardiovascular disease-risk, to monitor and refer for tailored interventions with exercise specialists.
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