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Calculate fasting-based insulin sensitivity indices

Source: R/fasting_is.R
fasting_is.Rd

Compute 10 fasting indices from glucose (mmol/L) and insulin (pmol/L): Fasting_inv, Raynaud, HOMA_IR_inv, FIRI, QUICKI, Belfiore_basal, Ig_ratio_basal, Isi_basal, Bennett, HOMA_IR_rev_inv. Units converted internally: G0_mg = G0*18 (mg/dL), I0_u = I0/6 (muU/mL).

Usage

fasting_is(
  data,
  col_map,
  normalize = c("none", "z", "inverse", "range", "robust"),
  na_action = c("keep", "omit", "error", "warn"),
  check_extreme = FALSE,
  extreme_limit = 1000,
  extreme_action = c("cap", "NA", "error"),
  verbose = FALSE
)

Arguments

data

Data frame with required inputs.

col_map

Named list mapping required keys:

  • G0: fasting glucose (mmol/L)

  • I0: fasting insulin (pmol/L)

normalize

One of: "none","z","inverse","range","robust".

na_action

One of:

  • "keep" (retain all rows; indices become NA where inputs missing/non-finite)

  • "omit" (drop rows with any missing/non-finite required inputs)

  • "error" (abort if any required input is missing/non-finite)

  • "warn" (emit a warning for rows with missing inputs, then keep them)

check_extreme

Logical; if TRUE, scan computed indices for large magnitudes.

extreme_limit

Positive numeric threshold used when check_extreme = TRUE.

extreme_action

One of: "cap","NA","error".

verbose

Logical; if TRUE, emit progress/completion messages.

Value

Tibble with 10 columns (indices listed above).

References

Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985). “Homeostasis Model Assessment: Insulin Resistance and Beta-Cell Function from Fasting Plasma Glucose and Insulin Concentrations in Man.” Diabetologia, 28(7), 412–419. doi:10.1007/BF00280883 . ; Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ (2000). “Quantitative Insulin Sensitivity Check Index: A Simple, Accurate Method for Assessing Insulin Sensitivity in Humans.” Journal of Clinical Endocrinology & Metabolism, 85(7), 2402–2410. doi:10.1210/jcem.85.7.6661 . ; Raynaud E, Pérez-Martin A, Brun J, Benhaddad AA, Mercier J (1999). “Fasting Plasma Insulin and Insulin Resistance Indices.” Diabetes & Metabolism, 25(6), 524–532. No DOI identified in Crossref/PubMed as of 2026-03-16; see URL, https://pubmed.ncbi.nlm.nih.gov/?term=Fasting+Plasma+Insulin+and+Insulin+Resistance+Indices. ; Avignon A, Charles M, Rabasa-Lhoret R, et al. (1999). “Assessment of Insulin Sensitivity from Oral Glucose Tolerance Test in Normal Subjects and in Insulin-Resistant Patients.” International Journal of Obesity, 23(5), 512–517. doi:10.1038/sj.ijo.0800864 . ; Belfiore F, Iannello S, Volpicelli G (1998). “Insulin Sensitivity Indices Calculated from Basal and OGTT-Related Insulin and Glucose Levels.” Molecular Genetics and Metabolism, 63(2), 134–141. doi:10.1006/mgme.1997.2658 . ; Sluiter D, Erkelens DW, Reitsma WD, Doorenbos H (1976). “Glucose Tolerance and Insulin Release: A Mathematical Approach.” Diabetes, 25, 245–249. doi:10.2337/diabetes.25.4.245 . ; Hanson RL, Pratley RE, Bogardus C, Narayan KMV, Roumain J, Imperatore G, Fagot-Campagna A, Pettitt DJ, Bennett PH, Knowler WC (2000). “Evaluation of Simple Indices of Insulin Sensitivity and Insulin Secretion for Use in Epidemiologic Studies.” American Journal of Epidemiology, 151(2), 190–198. doi:10.1093/oxfordjournals.aje.a010187 . ; Anderson RL, Hamman RF, Savage PJ, Saad MF, Laws A, Kades WW, Sands RE, Cefalu WT (1995). “Exploration of Simple Measures of Insulin Resistance.” American Journal of Epidemiology, 142(7), 724–732. doi:10.1093/aje/142.7.724 . ; Suleman S, Madsen AL, Ängquist LH, Schubert M, Linneberg A, Loos RJF, Hansen T, Grarup N (2024). “Genetic Underpinnings of Fasting and Oral Glucose-stimulated Based Insulin Sensitivity Indices.” The Journal of Clinical Endocrinology & Metabolism, 109(11), 2754–2763. doi:10.1210/clinem/dgae275 .

Examples

# Minimal example (units: G0 in mmol/L, I0 in pmol/L)
df <- data.frame(G0 = c(5.2, 6.1, 4.8), I0 = c(60, 120, 80))
res <- fasting_is(df, col_map = list(G0 = "G0", I0 = "I0"))
head(res)
#> # A tibble: 3 × 10
#>   Fasting_inv Raynaud HOMA_IR_inv  FIRI QUICKI Belfiore_basal Ig_ratio_basal
#>         <dbl>   <dbl>       <dbl> <dbl>  <dbl>          <dbl>          <dbl>
#> 1       -10         4       -41.6  37.4  0.146       0.00213          -0.107
#> 2       -20         2       -97.6  87.8  0.130       0.000910         -0.182
#> 3       -13.3       3       -51.2  46.1  0.142       0.00173          -0.154
#> # ℹ 3 more variables: Isi_basal <dbl>, Bennett <dbl>, HOMA_IR_rev_inv <dbl>

# With NA handling and extreme checking
df2 <- data.frame(G0 = c(5.0, NA), I0 = c(90, 150))
fasting_is(df2, col_map = list(G0 = "G0", I0 = "I0"), na_action = "keep",
           check_extreme = TRUE, extreme_limit = 1e3, extreme_action = "cap")
#> # A tibble: 2 × 10
#>   Fasting_inv Raynaud HOMA_IR_inv  FIRI QUICKI Belfiore_basal Ig_ratio_basal
#>         <dbl>   <dbl>       <dbl> <dbl>  <dbl>          <dbl>          <dbl>
#> 1         -15    2.67         -60    54  0.139        0.00148         -0.167
#> 2         -25    1.6           NA    NA NA           NA               NA    
#> # ℹ 3 more variables: Isi_basal <dbl>, Bennett <dbl>, HOMA_IR_rev_inv <dbl>