Introduction
Within the ADLB ADaM data set there is a concept of lab grading, where there is a set of criteria for particular lab tests that grade the severity or abnormality of a lab value. The grades are from 0 to 4, where grade 0 can be viewed generally as a “NORMAL” value. The higher the grade the more severe or more abnormal the lab value is. There are several sets of lab grading criteria, currently admiral has implemented NCI-CTCAEv4, NCI-CTCAEv5 and DAIDS grading criteria. In future releases admiral may look to implement further grading criteria.
The NCI-CTCAE version 4 and 5 grading criteria can be found here: https://ctep.cancer.gov/protocoldevelopment/electronic_applications/ctc.htm .
The NCI-CTCAEv4 criteria can be found under the heading Common Terminology Criteria for Adverse Events (CTCAE)v4.0
The NCI-CTCAEv5 criteria can be found under the heading Common Terminology Criteria for Adverse Events (CTCAE)v5.0
The DAIDS grading criteria can be found here: https://rsc.niaid.nih.gov/clinical-research-sites/daids-adverse-event-grading-tables .
The DAIDS criteria can be found under the heading DAIDS Table for Grading the Severity of Adult and Pediatric Adverse Events Corrected Version 2.1
Grading metadata
admiral will store a metadata data set for each set of
grading criteria in the data folder of admiral.
Currently, we have atoxgr_criteria_ctcv4()
for NCI-CTCAEv4,
atoxgr_criteria_ctcv5()
for NCI-CTCAEv5 and
atoxgr_criteria_daids()
for DAIDS. Each metadata data set
has required variables and optional variables, the optional variables
are purely for transparency, and will contain detailed information about
the grading criteria. The required variables are those used by
admiral to create the grade.
Structure of metadata set
The metadata data set has the following structure for the required variables:
Variable | Scope | Type | Example Value |
---|---|---|---|
TERM | Term describing the criteria applied to a particular lab test. | Character | “Anemia” |
DIRECTION | The direction of the abnormality of a particular lab test value | Character | “L” or “H”. |
SI_UNIT_CHECK | Unit of lab test, to check against input data if criteria is based on absolute values. | Character | “mmol/L” |
VAR_CHECK | Comma separated list of variables used in criteria, to check input data that variables exist. | Character | “AVAL, ANRLO” |
FILTER | Only required for DAIDS grading. Variable to hold code that filters the lab data based on contents of column SUBGROUP. | Character | R code that is valid within a filter function
call. |
GRADE_CRITERIA_CODE | Variable to hold code that creates grade based on defined criteria. | Character | R code that is a valid case statement within a mutate
function call. |
The metadata data set has the following structure for the optional variables:
Variable | Scope | Type | Example Value |
---|---|---|---|
SOC | System Organ Class the lab test belongs to. | Character | “Investigations” |
SUBGROUP | Only required for DAIDS grading. Description of subgroup of lab data. | Character | “> 15 years of age”. |
GRADE_1 | Grade 1 criteria for lab test, normally straight from source document. | Character | “>ULN - 3.0 x ULN”. |
GRADE_2 | Grade 2 criteria for lab test, normally straight from source document. | Character | “>3.0 - 5.0 x ULN”. |
GRADE_3 | Grade 3 criteria for lab test, normally straight from source document. | Character | “>5.0 - 20.0 x ULN”. |
GRADE_4 | Grade 4 criteria for lab test, normally straight from source document. | Character | “>20.0 x ULN”. |
DEFINITION | Definition of abnormality, normally from source document. | Character | “A finding based on laboratory test results that indicate an increase in the level of alanine aminotransferase (ALT or SGPT) in the blood specimen.”. |
COMMENT | Description of any decisions made by admiral to implement grading criteria, where grading criteria alone was ambiguous. | Character | “Take worst case and assume on anticoagulation”. |
Handling floating points when comparing numeric values
When comparing numeric values, for example
AVAL > 1.1*ANRHI
, unexpected results can occur due to
floating point issues. To solve this issue {admiral} used the
signif()
function on both side of the equation, the number
of significant digits used to compare is passed into the function
derive_var_atoxgr_dir()
via the argument
signif_dig
. Please see documentation of the function for
more details and the blog post How
admiral handles floating points for more context.
Creating the lab grade
Mapping ADLB VAD to the TERM variable in the {admiral}
metadata data set
library(admiral)
library(pharmaversesdtm)
library(dplyr, warn.conflicts = FALSE)
library(stringr)
library(tibble)
data("lb")
adsl <- admiral_adsl
lb <- convert_blanks_to_na(lb)
Each company needs to map their lab test to a term that
describes the criteria being applied. The list of terms defined in the
admiral metadata to implement NCI-CTCAEv4 is below:
Likewise, the list of terms defined in the
admiral metadata to implement NCI-CTCAEv5 is below:
(Terms identical to NCI-CTCAEv4, except Hyperglycemia
,
Hyperglycemia (Fasting)
and Hypophosphatemia
)
which are not present in NCI-CTCAEv5.
Finally, the list of terms defined in the admiral
metadata to implement DAIDS is below:
Using CDISC data these lab tests can be mapped to the correct
terms, firstly create PARAMCD
, PARAM
,
AVAL
, ANRLO
and ANRHI
, also some
lab grading criteria require BASE
and PCHG
, so
these would also need to be created before running
derive_var_atoxgr_dir()
function.
# Look-up tables ----
# Assign PARAMCD, PARAM, and PARAMN
param_lookup <- tibble::tribble(
~LBTESTCD, ~PARAMCD, ~PARAM, ~PARAMN,
"ALB", "ALB", "Albumin (g/L)", 1,
"ALP", "ALKPH", "Alkaline Phosphatase (U/L)", 2,
"ALT", "ALT", "Alanine Aminotransferase (U/L)", 3,
"ANISO", "ANISO", "Anisocytes", 4,
"AST", "AST", "Aspartate Aminotransferase (U/L)", 5,
"BASO", "BASO", "Basophils (10^9/L)", 6,
"BASOLE", "BASOLE", "Basophils/Leukocytes (FRACTION)", 7,
"BILI", "BILI", "Bilirubin (umol/L)", 8,
"BUN", "BUN", "Blood Urea Nitrogen (mmol/L)", 9,
"CA", "CA", "Calcium (mmol/L)", 10,
"CHOL", "CHOLES", "Cholesterol (mmol/L)", 11,
"CK", "CK", "Creatinine Kinase (U/L)", 12,
"CL", "CL", "Chloride (mmol/L)", 13,
"COLOR", "COLOR", "Color", 14,
"CREAT", "CREAT", "Creatinine (umol/L)", 15,
"EOS", "EOS", "Eosinophils (10^9/L)", 16,
"EOSLE", "EOSLE", "Eosinophils/Leukocytes (FRACTION)", 17,
"GGT", "GGT", "Gamma Glutamyl Transferase (U/L)", 18,
"GLUC", "GLUC", "Glucose (mmol/L)", 19,
"HBA1C", "HBA1C", "Hemoglobin A1C (1)", 20,
"HCT", "HCT", "Hematocrit (1)", 21,
"HGB", "HGB", "Hemoglobin (mmol/L)", 22,
"K", "POTAS", "Potassium (mmol/L)", 23,
"KETONES", "KETON", "Ketones", 24,
"LYM", "LYMPH", "Lymphocytes (10^9/L)", 25,
"LYMLE", "LYMPHLE", "Lymphocytes/Leukocytes (FRACTION)", 26,
"MACROCY", "MACROC", "Macrocytes", 27,
"MCH", "MCH", "Ery. Mean Corpuscular Hemoglobin (fmol(Fe))", 28,
"MCHC", "MCHC", "Ery. Mean Corpuscular HGB Concentration (mmol/L)", 29,
"MCV", "MCV", "Ery. Mean Corpuscular Volume (f/L)", 30,
"MICROCY", "MICROC", "Microcytes", 31,
"MONO", "MONO", "Monocytes (10^9/L)", 32,
"MONOLE", "MONOLE", "Monocytes/Leukocytes (FRACTION)", 33,
"PH", "PH", "pH", 34,
"PHOS", "PHOS", "Phosphate (mmol/L)", 35,
"PLAT", "PLAT", "Platelet (10^9/L)", 36,
"POIKILO", "POIKIL", "Poikilocytes", 37,
"POLYCHR", "POLYCH", "Polychromasia", 38,
"PROT", "PROT", "Protein (g/L)", 39,
"RBC", "RBC", "Erythrocytes (TI/L)", 40,
"SODIUM", "SODIUM", "Sodium (mmol/L)", 41,
"SPGRAV", "SPGRAV", "Specific Gravity", 42,
"TSH", "TSH", "Thyrotropin (mU/L)", 43,
"URATE", "URATE", "Urate (umol/L)", 44,
"UROBIL", "UROBIL", "Urobilinogen", 45,
"VITB12", "VITB12", "Vitamin B12 (pmol/L)", 46,
"WBC", "WBC", "Leukocytes (10^9/L)", 47
)
adlb <- lb %>%
## Add PARAMCD PARAM and PARAMN - from LOOK-UP table
derive_vars_merged_lookup(
dataset_add = param_lookup,
new_vars = exprs(PARAMCD, PARAM, PARAMN),
by_vars = exprs(LBTESTCD)
) %>%
## Calculate PARCAT1 AVAL AVALC ANRLO ANRHI
## Dummy the values for BASE
mutate(
PARCAT1 = LBCAT,
AVAL = LBSTRESN,
AVALC = ifelse(
is.na(LBSTRESN) | as.character(LBSTRESN) != LBSTRESC,
LBSTRESC,
NA
),
ANRLO = LBSTNRLO,
ANRHI = LBSTNRHI,
BASE = AVAL - 10
)
#> All `LBTESTCD` are mapped.
Another look-up table is used to add on ATOXDSCL
and
ATOXDSCH
using PARAMCD
. ATOXDSCL
holds the terms for grading low lab values, and ATOXDSCH
holds the terms for grading high lab values. The names of these
variables can be user-defined. ATOXDSCL
and
ATOXDSCH
are the link from ADLB data to the
admiral metadata that holds the grading criteria.
# Assign ATOXDSCL and ATOXDSCH to hold lab grading terms
# ATOXDSCL and ATOXDSCH hold terms defined by NCI-CTCAEv4.
grade_lookup <- tibble::tribble(
~PARAMCD, ~ATOXDSCL, ~ATOXDSCH,
"ALB", "Hypoalbuminemia", NA_character_,
"ALKPH", NA_character_, "Alkaline phosphatase increased",
"ALT", NA_character_, "Alanine aminotransferase increased",
"AST", NA_character_, "Aspartate aminotransferase increased",
"BILI", NA_character_, "Blood bilirubin increased",
"CA", "Hypocalcemia", "Hypercalcemia",
"CHOLES", NA_character_, "Cholesterol high",
"CK", NA_character_, "CPK increased",
"CREAT", NA_character_, "Creatinine increased",
"GGT", NA_character_, "GGT increased",
"GLUC", "Hypoglycemia", "Hyperglycemia",
"HGB", "Anemia", "Hemoglobin increased",
"POTAS", "Hypokalemia", "Hyperkalemia",
"LYMPH", "CD4 lymphocytes decreased", NA_character_,
"PHOS", "Hypophosphatemia", NA_character_,
"PLAT", "Platelet count decreased", NA_character_,
"SODIUM", "Hyponatremia", "Hypernatremia",
"WBC", "White blood cell decreased", "Leukocytosis",
)
adlb <- adlb %>%
derive_vars_merged(
dataset_add = grade_lookup,
by_vars = exprs(PARAMCD),
)
It is now straightforward to create the grade, for low lab values the
grade will be held in ATOXGRL
and for high lab values the
grade will be held in ATOXGRH
.
Note: for NCICTCAEv5 grading, you would update
meta_criteria
parameter to
atoxgr_criteria_ctcv5
and for DAIDS grading you would
update meta_criteria
parameter to
atoxgr_criteria_daids
adlb <- adlb %>%
derive_var_atoxgr_dir(
new_var = ATOXGRL,
tox_description_var = ATOXDSCL,
meta_criteria = atoxgr_criteria_ctcv4,
criteria_direction = "L",
get_unit_expr = extract_unit(PARAM)
) %>%
derive_var_atoxgr_dir(
new_var = ATOXGRH,
tox_description_var = ATOXDSCH,
meta_criteria = atoxgr_criteria_ctcv4,
criteria_direction = "H",
get_unit_expr = extract_unit(PARAM)
)
Note: admiral does not grade ‘Anemia’ or ‘Hemoglobin
Increased’ because the metadata is based on the SI unit of ‘g/L’,
however the CDISC data has SI unit of ‘mmol/L’. Please see
SI_UNIT_CHECK
variable in admiral metadata
atoxgr_criteria_ctcv4()
or
atoxgr_criteria_ctcv5()
or
atoxgr_criteria_daids()
, the metadata is in the data folder
of admiral.
admiral also gives the option to combine
ATOXGRL
and ATOXGRH
into one variable, namely
ATOXGR
. Grades held in ATOXGRL
will be given a
negative value in ATOXGR
to distinguish between low and
high values.
adlb <- adlb %>%
derive_var_atoxgr()
NCI-CTCAEV4 implementation
Terms graded
Grading is implemented for those lab tests where a lab value is included in the grading definition, admiral does NOT try to read any other data to determine the grade, and only the ADLB VAD is used. The following CTCAE v4.0 SOC values were identified for grading, these are “Investigations”, “Metabolism and nutrition disorders” and “Blood and lymphatic system disorders”.
From these SOC values the following terms criteria is implemented in admiral
From SOC = “Investigations” there are 21 CTCAE v4.0 Terms:
- Activated partial thromboplastin time prolonged
- Alanine aminotransferase increased
- Alkaline phosphatase increased
- Aspartate aminotransferase increased
- Blood bilirubin increased
- CD4 lymphocytes decreased
- Cholesterol high
- CPK increased
- Creatinine increased
- Fibrinogen decreased
- GGT increased
- Haptoglobin decreased
- Hemoglobin increased
- INR increased
- Lipase increased
- Lymphocyte count decreased
- Lymphocyte count increased
- Neutrophil count decreased
- Platelet count decreased
- Serum amylase increased
- White blood cell decreased
From the SOC = “Metabolism and nutrition disorders” there are 14 CTCAE v4.0 Terms:
- Hypercalcemia
- Hyperglycemia
- Hyperkalemia
- Hypermagnesemia
- Hypernatremia
- Hypertriglyceridemia
- Hyperuricemia
- Hypoalbuminemia
- Hypocalcemia
- Hypoglycemia
- Hypokalemia
- Hypomagnesemia
- Hyponatremia
- Hypophosphatemia
From the SOC = “Blood and lymphatic system disorders” there are 2 CTCAE v4.0 Terms:
- Anemia
- Leukocytosis
Updates made to TERM
For terms “Hypocalcemia” and “Hypercalcemia” the criteria is provided
for Calcium and Ionized Calcium, therefore admiral
created a row for each in the metadata, this is noted in the COMMENT
variable of the metadata:
Similarly, there is criteria applicable to Fasting Glucose as well as non-Fasting Glucose for “Hyperglycemia” so again this was split into 2 rows, and noted in the COMMENT variable. Note “Hypoglycemia” does not require to be split into 2 rows:
Assumptions made when grading
For term “INR Increased” there is the following criteria:
admiral assumed worst case and used both parts of the
criteria for grading, so comparing lab value against ULN and also BASE.
The decision made was put in the COMMENT
field.
For TERM “Hyperuricemia”, the criteria for Grade 1 and Grade 3 is the
same with respect to the lab value, so worse case is assumed as grade 3.
The decision made was put in the COMMENT
field.
A similar approach was taken for TERM “Hypokalemia” where Grade 1 and
Grade 2 criteria is the same with respect to the lab value, so worse
case is assumed as grade 2. The decision made was put in the
COMMENT
field.
NCI-CTCAEV5 implementation
Terms graded
Grading is implemented for those lab tests where a lab value is included in the grading definition, admiral does NOT try to read any other data to determine the grade, and only the ADLB VAD is used. The following CTCAE v5.0 SOC values were identified for grading, these are “Investigations”, “Metabolism and nutrition disorders” and “Blood and lymphatic system disorders”.
From these SOC values the following terms criteria is implemented in admiral
From SOC = “Investigations” there are 21 CTCAE v5.0 Terms:
- Activated partial thromboplastin time prolonged
- Alanine aminotransferase increased
- Alkaline phosphatase increased
- Aspartate aminotransferase increased
- Blood bilirubin increased
- CD4 lymphocytes decreased
- Cholesterol high
- CPK increased
- Creatinine increased
- Fibrinogen decreased
- GGT increased
- Haptoglobin decreased
- Hemoglobin increased
- INR increased
- Lipase increased
- Lymphocyte count decreased
- Lymphocyte count increased
- Neutrophil count decreased
- Platelet count decreased
- Serum amylase increased
- White blood cell decreased
Note: These are the same terms identified for NCI-CTCAEv4.
From the SOC = “Metabolism and nutrition disorders” there are 12 CTCAE v4.0 Terms:
- Hypercalcemia
- Hyperkalemia
- Hypermagnesemia
- Hypernatremia
- Hypertriglyceridemia
- Hyperuricemia
- Hypoalbuminemia
- Hypocalcemia
- Hypoglycemia
- Hypokalemia
- Hypomagnesemia
- Hyponatremia
Note: These are the same terms identified for NCI-CTCAEv4, except “Hypophosphatemia” and “Hyperglycemia” which are not in NCICTCAEv5 grading criteria.
From the SOC = “Blood and lymphatic system disorders” there are 2 CTCAE v4.0 Terms:
- Anemia
- Leukocytosis
Note: These are the same terms identified for NCI-CTCAEv4.
Updates made to TERM
For terms “Hypocalcemia” and “Hypercalcemia” the criteria is provided
for Calcium and Ionized Calcium, therefore admiral
created a row for each in the metadata, this is noted in the COMMENT
variable of the metadata:
Assumptions made when grading
For terms “Alanine aminotransferase increased”, “Alkaline phosphatase
increased”, “Aspartate aminotransferase increased”, “Blood bilirubin
increased” and “GGT increased” the criteria is dependent on the Baseline
Value BASE
being normal or abnormal. For BASE
to be abnormal we compare it with the Upper Limit of Normal (ULN)
ANRHI
, i.e. BASE > ANRHI
. This means if
BASE
is abnormal then the grade is always zero for the
baseline observation.
For term “INR Increased” there is the following criteria:
admiral assumed worst case and used both parts of the
criteria for grading, so comparing lab value against ULN and also BASE.
The decision made was put in the COMMENT
field.
Similarly, for terms “Lipase Increased” and “Serum amylase
increased” there is the following criteria:
admiral assumed worst case and implemented highest
grade possible. The decision made was put in the COMMENT
field.
For TERM “Hyperuricemia”, the criteria for Grade 1 and Grade 3 is the
same with respect to the lab value, so worse case is assumed as grade 3.
The decision made was put in the COMMENT
field.
A similar approach was taken for TERM “Hypokalemia” and
“Hyponatremia”. For “Hypokalemia”, where Grade 1 and Grade 2 criteria is
the same with respect to the lab value, then worse case is assumed as
grade 2. For “Hyponatremia”, where Grade 2 and Grade 2 criteria is the
same with respect to the lab value, then worse case is assumed as grade
3. The decision made was put in the COMMENT
field.
DAIDS implementation
Terms graded
Grading is implemented for those lab tests where a lab value is included in the grading definition, admiral does NOT try to read any other data to determine the grade, and only the ADLB VAD is used. The following DAIDS SOC values were identified for grading, these are “Chemistries” and “Hematology”.
From these SOC values the following terms criteria is implemented in admiral
From SOC = “Chemistries” there are 31 DAIDS Terms:
- Acidosis
- Albumin, Low
- Alkaline Phosphatase, High
- Alkalosis
- ALT, High
- Amylase, High
- AST, High
- Bicarbonate, Low
- Direct Bilirubin, High
- Total Bilirubin, High
- Calcium, High
- Calcium (Ionized), High
- Calcium, Low
- Calcium (Ionized), Low
- Creatine Kinase, High
- Creatinine, High
- Glucose Fasting, High
- Glucose Nonfasting, High
- Glucose, Low
- Lactate, High
- Lipase, High
- Cholesterol, Fasting, High
- LDL, Fasting, High
- Triglycerides, Fasting, High
- Magnesium, Low
- Phosphate, Low
- Potassium, High
- Potassium, Low
- Sodium, High
- Sodium, Low
- Uric Acid, High
Note: {admiral} does not grade for TERM = “Total Bilirubin, High” when AGE <= 28 days, these criteria are in Appendix of DAIDS Table for Grading the Severity of Adult and Pediatric Adverse Events Corrected Version 2.1.
From the SOC = “Hematology” there are 11 DAIDS Terms:
- Absolute CD4+ Count, Low
- Absolute Lymphocyte Count, Low
- Absolute Neutrophil Count (ANC), Low
- Fibrinogen Decreased
- Hemoglobin, Low
- INR, High
- Methemoglobin
- PTT, High
- Platelets, Decreased
- PT, High
- WBC, Decreased
Terms with age or sex dependent grading criteria
Some terms defined in DAIDS have age or sex dependent grading
criteria, {admiral} handles this in variable FILTER
in the
metadata. We use {admiral} function compute_duration
to
calculate age, see TERM = “Cholesterol, Fasting, High”:
Note: All possible values must be covered for each TERM defined, for TERM = “Absolute Lymphocyte Count, Low” and “Absolute CD4+ Count, Low” there is only grading criteria defined for age > 5 years. Therefore, we add another row with age <= 5 years and set grade to missing. Similarly, for TERM = “LDL, Fasting, High” there is only grading criteria defined for age > 2 years. Therefore, we add another row with age <= 2 years and set grade to missing.
Assumptions made when grading
For terms “INR, High”, “PT, High” and “PTT, High”, the criteria is based on subjects “not on anticoagulation therapy”, this is captured in COMMENT field.
Similarly, for terms “Absolute CD4+ Count, Low” and “Absolute Lymphocyte Count, Low”, the criteria is based on subjects “not HIV infected”, this is captured in COMMENT field.
For term “Acidosis”, “Alkalosis” and “Direct Bilirubin, High (> 28 days of age)”, {admiral} grades as high as possible, so assumes worst case and subject has “life-threatening consequences”. This is captured in COMMENT field.
Similarly, for term “Lactate, High”, {admiral} only grade 1 and
2, and there is the following criteria:
admiral assumed worst case and assume “without
acidosis”. The decision made was put in the COMMENT
field.
For TERM “Direct Bilirubin, High (<= 28 days of age)” and “Uric Acid, High” the criteria is not given in SI unit. The conversion to SI unit is in the comment field.
Conclusion
With NCI-CTCAEv4, NCI-CTCAEv5 and DAIDS grading now implemented, {admiral} may look to implement other industry standard grading criteria. Providing tools for users to easily interact with the metadata to update criteria, based on their companies needs will also be looked at. Ideally, users should be able to create their own metadata for company specific grading schemes.