| Title: | Z-Score Calculator for Biomarkers: Childhood to Young Adulthood |
|---|---|
| Description: | Provides tools to compute individual percentile ranks and z-scores for clinical biomarkers in children, adolescents and young adults, based on age-, sex-, and height-specific reference data from the IDEFICS (Identification and prevention of Dietary and lifestyle-induced health EFfects In Children and infantS) study and the Biomarkers4Pediatrics collaboration. Supports the computation of a composite Metabolic Syndrome (MetS) score and associated monitoring/action levels for health monitoring. For more details see Ahrens et al. (2014) <doi:10.1038/ijo.2014.130>. |
| Authors: | Andreas Mändle [aut, cre], Timm Intemann [aut], Zülal Bekerecioglu [aut] |
| Maintainer: | Andreas Mändle <[email protected]> |
| License: | GPL-3 |
| Version: | 0.1.1 |
| Built: | 2026-09-30 14:10:18 UTC |
| Source: | https://github.com/cran/pediatric.zcalc |
Assigns monitoring or action levels based on individual percentile ranks using standard IDEFICS thresholds.
action_levels( df, sex = NULL, lvl_name = c("none", "monit", "action"), perc_level = c(0.9, 0.95), append = FALSE, filter = NULL )action_levels( df, sex = NULL, lvl_name = c("none", "monit", "action"), perc_level = c(0.9, 0.95), append = FALSE, filter = NULL )
df |
A data frame containing percentile columns such as 'waist_percentile', 'sbp_percentile', 'hdl_percentile', etc. |
sex |
Character vector. Same length as 'age', 'height', and 'values'. Accepts "f" for female or "m" for male. |
lvl_name |
Character vector of level labels. Defaults to 'c("none", "monit", "action")'. |
perc_level |
Numeric vector of two percentiles used as cutoffs. Defaults to 'c(0.9, 0.95)' for 90th and 95th percentile. |
append |
Logical. If 'TRUE', appends action level columns to 'df'. If 'FALSE', returns only the computed levels. |
filter |
Character. Optional. Limits calculation to a specific domain: '"adiposity"', '"blood_pressure"', '"blood_lipids"', '"blood_glu_insu"', or '"overall"'. |
Action levels are derived using 'cut()' on percentile values. For example, a value > 95th percentile maps to '"action"'. HDL is reversed ('1 - hdl_percentile') since low HDL values are considered unhealthy.
A list (or a modified data frame if 'append = TRUE') containing action level classifications for each domain.
df <- data.frame(waist_percentile = c(0.85, 0.96)) action_levels(df) df <- data.frame( hdl_percentile = c(0.1,0.5), homa_percentile = c(0.4,0.9), trg_percentile = c(0.6,0.5), waist_percentile = c(0.9,0.99), sbp_percentile = c(0.8,0.01) ) action_levels(df) df <- data.frame( #sex = c("m", "m"), hdl_percentile = c(0.1,0.5), homa_percentile = c(0.4,0.9), trg_percentile = c(0.6,0.5), crp_percentile = c(0.95, 0.9), waist_percentile = c(0.9,0.99), sbp_percentile = c(0.8,0.01) ) action_levels(df, sex = c("m", "m"))df <- data.frame(waist_percentile = c(0.85, 0.96)) action_levels(df) df <- data.frame( hdl_percentile = c(0.1,0.5), homa_percentile = c(0.4,0.9), trg_percentile = c(0.6,0.5), waist_percentile = c(0.9,0.99), sbp_percentile = c(0.8,0.01) ) action_levels(df) df <- data.frame( #sex = c("m", "m"), hdl_percentile = c(0.1,0.5), homa_percentile = c(0.4,0.9), trg_percentile = c(0.6,0.5), crp_percentile = c(0.95, 0.9), waist_percentile = c(0.9,0.99), sbp_percentile = c(0.8,0.01) ) action_levels(df, sex = c("m", "m"))
Computes age-, sex- and (for 'sbp' and 'dbp') height-specific percentile ranks or z-scores for clinical biomarkers using IDEFICS study reference data and Biomarkers4Pediatrics collaboration (for 'crp').
get_scores( variable = "waist", sex = c("f", "m"), age = 6:5, height = NULL, values = c(20, 21), return_values = c("percentile", "z.score") )get_scores( variable = "waist", sex = c("f", "m"), age = 6:5, height = NULL, values = c(20, 21), return_values = c("percentile", "z.score") )
variable |
Character. The variable to assess. Must be one of the supported variables ("waist", "bmi", "hdl", "sbp", "dbp", "trg", "homa", "glu", "height","insu", or "crp"). |
sex |
Character vector. Same length as 'age', 'height', and 'values'. Accepts "f" for female or "m" for male. |
age |
Numeric vector. Ages of the children/young adults in years. Must be between 1 and 22.5 for 'crp', and between 2 and 11 otherwise. |
height |
Numeric vector or NULL. Required for height-dependent models ('sbp' and 'dbp'). Defaults to NULL. |
values |
Numeric vector. Observed values of the variable to score.
Values must be supplied in the units used by the corresponding reference
model: 'waist' and 'height' in cm; 'bmi' in kg/m^2; 'sbp' and 'dbp'
in mmHg; 'trg' and 'hdl' in mg/dL; 'glu' in mg/dL; 'insu' in
|
return_values |
Character vector. Specifies which outputs to return. Options include "percentile", "z.score". |
For triglycerides ('trg'), the original IDEFICS scoring procedure applies sex-specific percentile and z-score values at 45 mg/dL, corresponding to the lower measurement limit used in the IDEFICS study. These values are retained here to reproduce the original IDEFICS score calculation.
A named list containing the requested scores. Each element is a numeric vector of the same length as 'values'.
get_scores( variable = "crp", sex = c("f","f"), age = c(3, 12), values = c(4, 0.5) ) get_scores( variable="dbp", sex=c("f","m"), age=c(5,5), height=c(120,110), values=c(70,60) ) get_scores( variable = "trg", sex = c("f", "m"), age = c(5.8, 6.5), values = c(50, 48) # mg/dL )get_scores( variable = "crp", sex = c("f","f"), age = c(3, 12), values = c(4, 0.5) ) get_scores( variable="dbp", sex=c("f","m"), age=c(5,5), height=c(120,110), values=c(70,60) ) get_scores( variable = "trg", sex = c("f", "m"), age = c(5.8, 6.5), values = c(50, 48) # mg/dL )
Computes a composite MetS score from individual z-scores of clinical biomarkers.
MetSScore(df)MetSScore(df)
df |
A data frame containing the following columns: 'waist_z.score', 'homa_z.score', 'sbp_z.score', 'dbp_z.score', 'trg_z.score', and 'hdl_z.score'. These are expected to be numeric vectors representing z-scores. |
The MetS score is computed as:
'waist_z + homa_z + 0.5 × (sbp_z + dbp_z + trg_z - hdl_z)'
A numeric vector representing the calculated MetS score for each row in the input data.
df <- data.frame( waist_z.score = c(1.2, 0.5), homa_z.score = c(0.8, 0.6), sbp_z.score = c(0.7, 0.3), dbp_z.score = c(0.6, 0.4), trg_z.score = c(1.0, 0.9), hdl_z.score = c(-0.5, -0.2) ) MetSScore(df)df <- data.frame( waist_z.score = c(1.2, 0.5), homa_z.score = c(0.8, 0.6), sbp_z.score = c(0.7, 0.3), dbp_z.score = c(0.6, 0.4), trg_z.score = c(1.0, 0.9), hdl_z.score = c(-0.5, -0.2) ) MetSScore(df)
Applies 'get_scores()' to multiple clinical biomarkers in a data frame and optionally returns MetS and cutoff levels.
ScoreCalc( df, return_input = FALSE, return_values = c("percentile", "z.score", "MetS", "cutoff.levels") )ScoreCalc( df, return_input = FALSE, return_values = c("percentile", "z.score", "MetS", "cutoff.levels") )
df |
A data frame with columns: 'sex', 'age', 'height', and observed values for any of the supported variables: 'bmi', 'glu', 'hdl', 'height', 'homa', 'insu', 'trg', 'waist', 'sbp', 'dbp', 'crp'. Variables must be supplied using the units of the corresponding reference model:
'height' is required for the height-dependent blood-pressure models ('sbp' and 'dbp'). |
return_input |
Logical. If 'TRUE', includes original input columns in the result. Defaults to 'FALSE'. |
return_values |
Character vector. Specifies which scores to compute. Options include '"percentile"', '"z.score"', '"MetS"', and '"cutoff.levels"'. |
The function applies 'get_scores()' to each recognized variable in the input and combines the results. If '"MetS"' is requested, a Metabolic Syndrome score is computed and optionally transformed to percentile ranks/z-scores.
A data frame with score columns named as '<variable>_percentile', '<variable>_z.score', etc. Includes additional columns like 'MetS' or cutoff levels if requested.
df <- data.frame( sex = c("f", "m"), age = c(8, 15), height = c(120, 125), waist = c(55, 60), homa = c(1.2, 1.4), sbp = c(100, 105), dbp = c(65, 70), trg = c(80, 90), # mg/dL crp = c(6, 2), # mg/L hdl = c(50, 45) # mg/dL ) ScoreCalc(df, return_values = c("percentile", "cutoff.levels")) # for the 15 year old male everything except CRP is NA (outside IDEFICS age range)df <- data.frame( sex = c("f", "m"), age = c(8, 15), height = c(120, 125), waist = c(55, 60), homa = c(1.2, 1.4), sbp = c(100, 105), dbp = c(65, 70), trg = c(80, 90), # mg/dL crp = c(6, 2), # mg/L hdl = c(50, 45) # mg/dL ) ScoreCalc(df, return_values = c("percentile", "cutoff.levels")) # for the 15 year old male everything except CRP is NA (outside IDEFICS age range)