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External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis. | LitMetric

AI Article Synopsis

  • The study aimed to assess the effectiveness of a UK-based prediction model for estimating fat-free mass in children and adolescents across 19 countries outside the UK.
  • Involving 5,693 participants aged 4 to 15, the model exhibited strong predictive performance, with R values over 75% in all countries and good calibration of predicted versus actual fat-free mass.
  • The researchers found minimal variation in model performance based on gender, age, ethnicity, or national income, and they adjusted the model for different countries to enhance accuracy for future use.

Article Abstract

Objective: To evaluate the performance of a UK based prediction model for estimating fat-free mass (and indirectly fat mass) in children and adolescents in non-UK settings.

Design: Individual participant data meta-analysis.

Setting: 19 countries.

Participants: 5693 children and adolescents (49.7% boys) aged 4 to 15 years with complete data on the predictors included in the UK based model (weight, height, age, sex, and ethnicity) and on the independently assessed outcome measure (fat-free mass determined by deuterium dilution assessment).

Main Outcome Measures: The outcome of the UK based prediction model was natural log transformed fat-free mass (lnFFM). Predictive performance statistics of R, calibration slope, calibration-in-the-large, and root mean square error were assessed in each of the 19 countries and then pooled through random effects meta-analysis. Calibration plots were also derived for each country, including flexible calibration curves.

Results: The model showed good predictive ability in non-UK populations of children and adolescents, providing R values of >75% in all countries and >90% in 11 of the 19 countries, and with good calibration (ie, agreement) of observed and predicted values. Root mean square error values (on fat-free mass scale) were <4 kg in 17 of the 19 settings. Pooled values (95% confidence intervals) of R, calibration slope, and calibration-in-the-large were 88.7% (85.9% to 91.4%), 0.98 (0.97 to 1.00), and 0.01 (-0.02 to 0.04), respectively. Heterogeneity was evident in the R and calibration-in-the-large values across settings, but not in the calibration slope. Model performance did not vary markedly between boys and girls, age, ethnicity, and national income groups. To further improve the accuracy of the predictions, the model equation was recalibrated for the intercept in each setting so that country specific equations are available for future use.

Conclusion: The UK based prediction model, which is based on readily available measures, provides predictions of childhood fat-free mass, and hence fat mass, in a range of non-UK settings that explain a large proportion of the variability in observed fat-free mass, and exhibit good calibration performance, especially after recalibration of the intercept for each population. The model demonstrates good generalisability in both low-middle income and high income populations of healthy children and adolescents aged 4-15 years.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490487PMC
http://dx.doi.org/10.1136/bmj-2022-071185DOI Listing

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