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Compute inflammatory indices (classic, eosinophil, or both)

Source: R/inflammatory_markers.R
inflammatory_markers.Rd

Panels:

  • classic: NLR, PLR, LMR, dNLR, SII, SIRI, AISI, CRP_category

  • eos: NLR, PLR, LMR, NER, SII, SIRI, PIV, CLR, CAR, PCR, mGPS, ESR (if mapped)

  • both: union of classic and eos panels

Usage

inflammatory_markers(
  data,
  col_map,
  panel = c("auto", "classic", "eos", "both"),
  na_action = c("keep", "omit", "error"),
  check_extreme = FALSE,
  extreme_action = c("warn", "cap", "error", "ignore", "NA"),
  verbose = FALSE
)

Arguments

data

data.frame or tibble

col_map

named list mapping keys to column names in data. Keys: neutrophils, lymphocytes, monocytes, platelets, WBC, CRP, albumin, eosinophils, ESR.

panel

one of c("auto","classic","eos","both"). "auto" uses presence of eosinophils key.

na_action

one of c("keep","omit","error"). Default "keep" propagates NA in outputs where inputs are missing. "omit" drops rows with any NA in required inputs. "error" aborts if required inputs contain NA.

check_extreme

logical; if TRUE, handle extremes per extreme_action

extreme_action

one of c("warn","cap","error","ignore","NA")

verbose

logical; if TRUE, prints progress messages via hm_inform

Value

tibble with selected inflammatory indices

Details

Derived markers:

  • NLR = neutrophils / lymphocytes

  • PLR = platelets / lymphocytes

  • LMR = lymphocytes / monocytes

  • dNLR = neutrophils / (WBC - neutrophils) when WBC available

  • SII = platelets * neutrophils / lymphocytes

  • SIRI = neutrophils * monocytes / lymphocytes

  • AISI = neutrophils * monocytes * platelets / lymphocytes

  • CRP_category: "low" (<1 mg/L), "moderate" (1-3 mg/L), "high" (>3 mg/L) when CRP available

  • Eosinophil-panel extras: NER = neutrophils / eosinophils; PIV = plateletsneutrophilsmonocytes/lymphocytes; CLR = CRP/lymphocytes; CAR = CRP/albumin; PCR = platelets/CRP; mGPS (CRP, albumin); ESR passthrough.

References

Zahorec R (2001). “Ratio of neutrophil to lymphocyte counts–rapid and simple parameter of systemic inflammation and stress.” Bratislavske lekarske listy, 102(1), 5–14. No DOI identified; PMID: 11723675, https://pubmed.ncbi.nlm.nih.gov/11723675/. ; Templeton AJ, others (2014). “Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis.” Journal of the National Cancer Institute, 106(6), dju124. doi:10.1093/jnci/dju124 . ; Hu B, others (2014). “Systemic Immune-Inflammation Index Predicts Prognosis of Patients after Curative Resection for Hepatocellular Carcinoma.” Clinical Cancer Research, 20(23), 6212–6222. doi:10.1158/1078-0432.CCR-14-0442 . ; Qi Q, others (2016). “A novel systemic inflammation response index (SIRI) for predicting the survival of patients with pancreatic cancer after chemotherapy.” Cancer, 122(14), 2158–2167. doi:10.1002/cncr.30057 . ; Mammadova A, Naurzvai D, others (2025). “Association of systemic immune-inflammation index and aggregate index of systemic inflammation with clinical status in stable and exacerbated COPD: A single-center retrospective study.” Medicine, 104(39), e44589. doi:10.1097/MD.0000000000044589 . ; Proctor MJ, others (2011). “An inflammation-based prognostic score (mGPS) predicts cancer survival independent of tumour site: a Glasgow Inflammation Outcome Study.” British Journal of Cancer, 104(4), 726–734. doi:10.1038/sj.bjc.6606087 . ; Pearson TA, others (2003). “Markers of inflammation and cardiovascular disease: a statement for healthcare professionals from the CDC and AHA.” Circulation, 107(3), 499–511. doi:10.1161/01.CIR.0000052939.59093.45 .

Examples

df <- data.frame(
  neutrophils = c(4, 2),
  lymphocytes = c(2, 0),
  monocytes   = c(0.5, 0.3),
  platelets   = c(200, 150),
  WBC         = c(7, 4.5),
  CRP         = c(2.5, 0.8),
  albumin     = c(40, 42),
  eosinophils = c(0.2, 0.1),
  ESR         = c(12, 15)
)
cm <- list(
  neutrophils = "neutrophils", lymphocytes = "lymphocytes", monocytes = "monocytes",
  platelets = "platelets", WBC = "WBC", CRP = "CRP", albumin = "albumin",
  eosinophils = "eosinophils", ESR = "ESR"
)
# Classic panel (no eosinophils key)
classic_cm <- cm; classic_cm$eosinophils <- NULL; classic_cm$ESR <- NULL
inflammatory_markers(df, classic_cm, panel = "classic", na_action = "keep")
#> Warning: inflammatory_markers(): zero denominators detected.
#> # A tibble: 2 × 8
#>     NLR   PLR   LMR  dNLR   SII  SIRI  AISI CRP_category
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <ord>       
#> 1     2   100     4  1.33   400     1   200 moderate    
#> 2   Inf   Inf     0  0.8    Inf   Inf   Inf low         
# Eosinophil panel
inflammatory_markers(df, cm, panel = "eos", na_action = "keep",
                     check_extreme = TRUE, extreme_action = "cap", verbose = TRUE)
#> inflammatory_markers(): preparing inputs
#> inflammatory_markers(): column map: neutrophils -> 'neutrophils', lymphocytes -> 'lymphocytes', monocytes -> 'monocytes', platelets -> 'platelets', CRP -> 'CRP'
#> Warning: inflammatory_markers(): capped out-of-range extreme input values.
#> inflammatory_markers(): results: NLR 2/2, PLR 2/2, LMR 2/2, NER 2/2, SII 2/2, SIRI 2/2, PIV 2/2, CLR 2/2, CAR 2/2, PCR 2/2, mGPS 2/2, ESR 2/2
#> # A tibble: 2 × 12
#>     NLR   PLR   LMR   NER   SII  SIRI   PIV   CLR    CAR   PCR  mGPS   ESR
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>  <dbl> <dbl> <int> <dbl>
#> 1     2   100  4        4   400   1     200  1.25 0.0625   80      0    12
#> 2     2   150  3.33     2   300   0.6    90  0.8  0.0190  188.     0    15