Skip to contents

Changelog

Source: NEWS.md

HealthMarkers 0.1.4

CRAN release: 2026-06-17

Formula & unit audit

This release follows a systematic, script-by-script audit of every marker-calculation function in the package, checking each formula and its unit handling against the original publication. The supporting/utility scripts were also confirmed to apply no hidden unit conversions (column inference maps names only; the global pre-computation helper keeps variables in their canonical units). The fixes below correct genuine formula/unit bugs; the great majority of functions were verified correct and unchanged.

Bug fixes — insulin sensitivity indices

  • fasting_is() — HOMA_IR_inv. HOMA-IR (Matthews et al. 1985) is defined with glucose in mmol/L (divisor 22.5). The previous code applied the mg/dL conversion (*18) while keeping the 22.5 divisor, yielding values 18x too large. Now uses raw mmol/L glucose. HOMA_IR_rev_inv (mg/dL convention, /405) already produced the correct value and is unchanged; the two columns are now equal, as intended.

  • fasting_is() — FIRI. The Fasting Insulin Resistance Index (Duncan et al. 1995) is defined with glucose in mmol/L (divisor 25). Now uses raw mmol/L glucose instead of the mg/dL-converted value (previously 18x too large).

  • fasting_is() — QUICKI. Now uses log10 (as defined by Katz et al.

    1. instead of natural log. Glucose (mg/dL) and insulin (muU/mL) units were already correct.

  • ogtt_is() — Cederholm_index. Cederholm & Wibell (1990) is defined with glucose in mmol/L; the formula’s *180 term is itself the mmol/L->mg conversion. The previous code pre-converted glucose to mg/dL (*18), causing a double conversion and a non-linear distortion of the index. Now uses raw mmol/L glucose. Gutt_index (defined in mg/dL, no *180 term) is unchanged and correct.

Bug fixes — other markers

  • glycemic_markers() — SPISE and METS_IR. Both indices are defined for inputs in mg/dL (SPISE: Paulmichl 2016; METS-IR: Bello-Gaytan 2018) and carry validated cut-offs in those units. The previous code fed raw mmol/L values, giving systematically wrong (non-constant) results. Now converts HDL-c (*38.67), TG (*88.57) and glucose (*18) to mg/dL internally. TyG_index was already correct.

  • liver_fat_markers() — NAFLD_LFS. The NAFLD Liver Fat Score (Kotronen et al. 2009) codes type-2 diabetes as yes = 2 / no = 0, so the diabetic contribution is 0.45 * 2 = 0.90. The previous code used a 0/1 indicator, giving half the intended contribution for people with diabetes. Fixed.

  • renal_markers() — eGFR_combined. The combined creatinine–cystatin C CKD-EPI equation (Inker et al. 2012) uses its own creatinine alpha (-0.207 male / -0.248 female) and its own female (x0.969) and Black (x1.08) multipliers. The previous code reused the creatinine-only alpha (-0.411 / -0.329) and incorrect multipliers (1.008, 1.145). All three corrected. eGFR_cr (2009) and eGFR_cys (2012) were already correct.

  • ckd_stage() — KDIGO_risk. Two cells of the KDIGO 2012 risk heatmap were mis-mapped: G1/G2 + A3 now returns High (was “Moderate”), and G3a + A3 now returns Very High (was “High”). GFR and albuminuria stage cut-offs were already correct.

  • kidney_failure_risk() — KFRE. The 4-variable Kidney Failure Risk Equation (Tangri et al. 2011) was reimplemented correctly. The previous linear predictor used log-transformed age and eGFR (the equation uses age/10 and eGFR/5 linearly), the wrong sign on age, no covariate centring, an incorrect sex coefficient, and baseline-survival constants matching no published calibration. Now uses the non-North-American calibration: PI = -0.2201*(age/10 - 7.036) + 0.2467*(male - 0.5642) - 0.5567*(eGFR/5 - 7.222) + 0.4510*(ln(ACR_mmol) - 5.137), S0(2y) = 0.9832, S0(5y) = 0.9365. UACR continues to be supplied in mg/g and is converted internally to mg/mmol (/8.84).

  • obesity_indices() — BRI. The Body Roundness Index (Thomas et al. 2013) eccentricity ratio is WC / (pi * height); the previous code used WC / (2*pi * height) (half the correct value), which produced near-zero or negative BRI for normal adults. Fixed.

Documentation clarifications

  • atherogenic_indices() and cvd_marker_aip() — AIP units. The Atherogenic Index of Plasma log10(TG/HDL) is not scale-invariant (TG and HDL-c convert to mg/dL with different factors), and its published risk strata assume mmol/L. Documentation and the atherogenic_indices() example were corrected to mmol/L, with an explicit note that mg/dL inputs shift AIP by about +0.36. Formulas are unchanged.

Internal

  • obesity_indices() — dplyr deprecation. Replaced the unit-normalization dplyr::case_when() calls with scalar conversion factors. weight_unit and height_unit are scalar arguments, so the previous size-1 LHS / vector RHS pattern triggered a deprecation warning under dplyr >= 1.2.0. Behaviour is unchanged.

Metadata

  • Bumped Version to 0.1.4.

HealthMarkers 0.1.3

Bug fixes and CRAN checks

  • CRAN / Fedora r-devel-linux-x86_64-fedora-gcc ERROR fix.
    test-frailty_index.R test 1 (“frailty_index errors without di installed”) failed on Fedora because the di namespace is already resident in memory for the whole test session, so requireNamespace("di") always returns TRUE regardless of withr::with_libpaths() or mocking base::requireNamespace. Fixed by mocking .need_pkg_di() directly in the HealthMarkers namespace via testthat::local_mocked_bindings(.package = "HealthMarkers"). This is reliable on all platforms regardless of whether di is installed or loaded.

  • Metadata — Bumped Version to 0.1.3 and updated CRAN-SUBMISSION and cran-comments.md to reflect the resubmission.

HealthMarkers 0.1.2

CRAN release: 2026-05-19

New features

  • hm_normalize() — post-computation normalisation helper (new function). Apply z-score, rank-based inverse-normal transform (Rankit), min-max, or robust median/MAD scaling to any marker output data frame. Use cols to target specific columns and skip_cols to protect covariates (e.g. age, BMI) from being rescaled. This covers domain functions whose internal normalize argument currently has no effect (glycemic_markers(), lipid_markers(), renal_markers(), etc.). See ?hm_normalize.

  • Multi-biobank column inference (major). The internal synonym dictionary (.hm_default_col_patterns_exact()) now recognises column-naming conventions from 15+ major cohort studies and biobanks for all primary analytes:

    • UK Biobank — _0_0 / _1_0 field naming (e.g. glucose_0_0, creatinine_0_0, vitamin_d_0_0); standing_height, 25OHD.
    • NHANES — LBXS, LBDS, BPX, URX prefix variables (e.g. LBXGLU, LBXSCH, BPXSY1, URXUMA).
    • Danish national registers / EHR (LABKA/OPEN) — NPU codes (NPU01994 for creatinine, NPU01567 for cholesterol, NPU03609 for haemoglobin, etc.) and Danish clinical labels (kreatinin, kolesterol, blodsukker, leukocytter, trombocytter, d_vitamin).
    • HUNT Study and Tromsø Study (Norway) — Norwegian-language terms (blodsukkerfasting, systolisk_blodtrykk, triglyserider, karbamid, kjonn, midjeomkrets).
    • SCAPIS / TwinGene (Sweden) — Swedish-language terms (glukos, urinsyra, leukocyter, trombocyter, kön, längd, vikt).
    • FinnGen / THL Biobank (Finland) — Finnish-language terms (glukoosi, kolesteroli, kreatiniini, hemoglobiini, sukupuoli, virtsahappo, leukosyytit, ferritiini, D_vitamiini).
    • Estonian Biobank (EstBB) — Estonian terms (glukoos, kolesterool, kreatiniin, hemoglobiin, naatrium, kaalium, vanus, sugu).
    • LifeLines Cohort / Rotterdam Study (Netherlands) — Dutch terms (nuchtere_glucose, totaal_cholesterol, urinezuur, ureum, leukocyten, hemoglobine, vitamine_D, tailleomtrek).
    • Generation Scotland (GS:SFHS) — SBP_mean, DBP_mean, genetic_sex, ethnic_group.
    • All of Us / OMOP CDM — LOINC codes in LOINC_XXXX_X format for all major analytes (e.g. LOINC_2345_7 for fasting glucose, LOINC_2160_0 for creatinine, LOINC_718_7 for haemoglobin).
    • NAKO / KORA (Germany) — German-language terms (Cholesterin, Triglyzeride, Harnsäure, Harnstoff, Leukozyten, Thrombozyten).

  • Added hm_col_report() — an interactive column-mapping diagnostic. Call hm_col_report(your_data) before running any computation to see a formatted table of which internal keys were matched to columns in your data and how (exact synonym, case-insensitive, substring, or fuzzy), plus a ready-to-paste col_map template for any unmatched keys.
    The function uses a five-layer matching pipeline and returns the matched mappings invisibly so the result can be passed directly as col_map to any HealthMarkers function.

  • Auto-derivation of computed inputs. .hm_global_precompute() now automatically derives 18+ secondary columns before marker computation begins, so functions that require (e.g.) eGFR, UACR, WHR, LDL_c, or waist no longer fail silently when only the raw inputs are present. Affected keys include eGFR (from creatinine/age/sex via CKD-EPI), WHR (from waist and hip), UACR (from u_albumin / u_creatinine), LDL_c (Friedewald from TC/HDL_c/TG), MAP, PP, BMI (from height/weight), and more.

  • Expanded the internal synonym dictionary (R/utils_infer-cols.R) for all variable groups, additionally incorporating:

    • Inter99 / ADDITION real phenotype dataset labels
    • Common literature spellings (TryG, TAG, TRIG, triacylglycerol; SGPT/GPT/ALAT; hsCRP/hs_CRP)
    • Longitudinal follow-up suffixes (_0, _1, _3, _5)
    • NMR metabolomics (urine) panel, ECG markers, lifestyle covariates, and cytokine multiplex proteins.

Bug fixes

  • adiposity_sds(): fixed fn_name lookup bug that caused incorrect error messages when validation failed on non-standard column names.

Internal

HealthMarkers 0.1.1

New features

  • Added liver_fat_markers() for hepatic steatosis and fibrosis index calculation.
  • Added nfl_marker() for plasma neurofilament light chain (NfL) z-score computation.
  • Added impute_missing() for within-row imputation of missing biomarker values.

Bug fixes and improvements

  • pulmo_markers(): fixed column-inference logic for spirometry z-score inputs.
  • All marker functions: standardised verbose progress messages to emit at the “debug” level when verbose = FALSE, so that getOption("healthmarkers.verbose") controls visibility consistently across every function.
  • Computing-phase messages are now unconditionally emitted at “debug” level (independent of the per-call verbose argument) in bone_markers(), ckd_stage(), and corrected_calcium().
  • all_health_markers(): column inference is now keyed to the requested groups, falls back to regex-based infer_cols() when exact matches fail, and reports per-group status (including missing optional packages) in verbose summaries.
  • Cardiovascular risk wrappers: cvd_risk_qrisk3() now prefers the correctly named ethnicity column (typo tolerated for backward compatibility), and optional dependency errors now report the missing package name consistently.
  • Shared validation: lipid marker helpers now route through hm_validate_inputs() so duplicate/empty mappings are caught uniformly.

Internal

  • Package gains a _pkgdown.yml that lists all 46 vignettes in the articles index for the pkgdown site.