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The Application of Fat-Free Mass Index for Survival Prediction in Cancer Patients With Normal and High Body Mass Index.

ABSTRACT: Background: Fat-free mass (FFM) depletion can be masked by a stable body weight or weight gain in the presence of a normal or high body mass index (BMI). This study investigated the prognostic value of low fat-free mass index (FFMI) in cancer patients with normal or high BMI. Methods: This multicenter retrospective cohort study included 1,602 cancer patients with normal/high BMI. The association of FFMI with patients' overall survival (OS) was analyzed by the Kaplan-Meier method and a Cox model. Results: In this analysis, there were 974 (60.8%) females and 628 (39.2%) males. Low FFMI was associated with worse OS when compared with those patients with normal FFMI. After multivariate adjustment, low FFMI was demonstrated to be an independent unfavorable prognostic factor (HR: 1.69; 95% CI: 1.28, 2.23; P < 0.001) in cancer patients with normal/high BMI. For specific tumor type, low FFMI was found to be associated with worse prognosis in patients with lung cancer, breast cancer and upper gastrointestinal cancer. In subgroup analysis, the association of low FFMI with worse survival was significantly modified by weight loss (P for interaction = 0.012), and those patients with concurrent low FFMI and weight loss showed the worst prognosis (HR: 3.53; 95% CI: 2.04, 6.11; P < 0.001). Conclusion: Low FFMI was associated with worse prognosis in cancer patients with normal/high BMI. This study highlights the usefulness of FFMI for prognostic estimation in these patients.

SUBMITTER: Zhang X

PROVIDER: S-EPMC8371389 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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The Application of Fat-Free Mass Index for Survival Prediction in Cancer Patients With Normal and High Body Mass Index.

Zhang Xi X Zhang Qi Q Feng Li-Jin LJ Zhang Kang-Ping KP Tang Meng M Song Meng-Meng MM Ruan Guo-Tian GT Zhang Xiao-Wei XW Li Wei W Zhou Fu-Xiang FX Cong Ming-Hua MH Shi Han-Ping HP

Frontiers in nutrition 20210804

<b>Background:</b> Fat-free mass (FFM) depletion can be masked by a stable body weight or weight gain in the presence of a normal or high body mass index (BMI). This study investigated the prognostic value of low fat-free mass index (FFMI) in cancer patients with normal or high BMI. <b>Methods:</b> This multicenter retrospective cohort study included 1,602 cancer patients with normal/high BMI. The association of FFMI with patients' overall survival (OS) was analyzed by the Kaplan-Meier method an ...[more]

PMID: 34422885

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Project description:BackgroundAccurate obesity classification is important so that appropriate intervention can be instituted to modify metabolic risk factors. Commonly utilized body mass index (BMI) and percentage body fat (PBF) are influenced by lean mass whereas fat mass index (FMI) measures only body fat. This study compares the prevalence of obesity and metabolic risk factors with FMI, BMI and PBF using DXA (dual-energy x-ray absorptiometry).Methods489 women randomly recruited from the electoral roll were stratified into 4 age groups; 40-49, 50-59, 60-69 and 70-79 years from 2000 to 2001. Clinical data and DXA body composition were obtained. Statistical analyses were performed using Medcalc v15 (Ostend, Belgium) with significance level at p = 0.05 (two-tailed).ResultsThere was higher prevalence of obesity using PBF compared to BMI and FMI (p<0.001). This difference was greater from age 50-59 (p<0.05) which may be explained by age-related lean mass loss. PBF over-classified obesity in over 35% of normal and 95% of overweight categories compared to FMI and BMI. BMI has a sensitivity of 78.9% and specificity of 98.3% for obesity using FMI as the standard. BMI under-classified obesity in the overweight category by 14.9% compared to FMI. There was no difference in diabetes, dyslipidemia, hypertension and metabolic syndrome prevalence within the BMI-obesity and FMI-obesity categories (p>0.05).ConclusionPBF classified more obesity than BMI and FMI because of its low pre-determined threshold. The greater difference with PBF compared to BMI and FMI from the 50-59 decade onwards can be attributed to age-related lean mass loss. BMI had the lowest sensitivity for obesity diagnosis. BMI under-classified obesity in the overweight category compared to FMI due to its inability to differentiate lean mass. However, there was no significant difference in the prevalence of metabolic risk factors between BMI and FMI-obesity categories indicating that fat location may influence metabolic dysregulation.

Project description:ImportanceBody mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents.ObjectiveTo compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents.Design, setting, and participantsCross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016.Main outcomes and measuresDual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight.ResultsParticipants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2?=?0.64 vs 0.38 in boys and R2?=?0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P?<?.001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P?=?.62).Conclusions and relevanceThe tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.

Project description:Background/objectivesWe aimed to investigate the association of waist circumference (WC) with body composition among individuals with a normal body mass index (BMI) to distinguish muscle and fat mass, as both affect health differently.Subjects/methodsWe analyzed dual-energy X-ray absorptiometry data (derived from the Korean National Health and Nutrition Survey, which includes information on fat and lean mass) of 7,493 adults with a normal BMI. Subjects were categorized into four groups of increasing WC. The fourth group was defined as being centrally obese. Each number of subjects are as follows: 1,870, 695, 231, and 39 among men and 3,054, 1,100, 406, and 98 among women. We conducted a sex-stratified linear regression analysis of body composition according to WC group after adjustments for covariates.ResultsWe observed a positive association of body fat with increasing WC in both men and women (all P for trend: < 0.001). The adjusted mean values for percent body fat with 95% confidence intervals (CIs) according to the four WC groups in ascending order were 17.8 (17.5-18.3), 21.0 (20.6-21.5), 22.1 (21.5-22.8), and 25.1 (24.2-26.1) in men and 29.7 (29.4-30.0), 32.0 (31.6-32.3), 32.9 (32.4-33.4), and 34.7 (33.2-36.1) in women. However, there was an inverted J-shaped association between muscle mass and WC. The fourth group had a higher percent body fat and lower muscle mass than other groups. The adjusted mean values for appendicular skeletal muscle mass index (kg/m2) with 95% CIs according to the four WC groups in ascending order were 7.55 (7.51-7.59), 7.62 (7.56-7.68), 7.65 (7.56-7.74), and 7.22 (7.04-7.41) in men and 5.83 (5.80-5.85), 5.96 (5.92-6.00), 6.03 (5.96-6.10), and 5.88 (5.73-6.03).ConclusionsThere was a positive association between body fat and WC among individuals with normal BMI; conversely there was an inverted J-shaped association between lean body mass and WC. Our findings support the WC measurement should be included in obesity evaluations for adults with a normal BMI.

Dataset Information

The Application of Fat-Free Mass Index for Survival Prediction in Cancer Patients With Normal and High Body Mass Index.

Publications

The Application of Fat-Free Mass Index for Survival Prediction in Cancer Patients With Normal and High Body Mass Index.

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