# Load required libraries
library(tidyverse)── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.2.1 ✔ readr 2.2.0
✔ forcats 1.0.1 ✔ stringr 1.6.0
✔ ggplot2 4.0.3 ✔ tibble 3.3.1
✔ lubridate 1.9.5 ✔ tidyr 1.3.2
✔ purrr 1.2.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(knitr)
library(kableExtra)
Attaching package: 'kableExtra'
The following object is masked from 'package:dplyr':
group_rowslibrary(gt)
# Table 1: WHO Classification of Mastocytosis
who_classification <- tibble(
Category = c("Cutaneous mastocytosis",
"Maculopapular CM (MPCM)",
"Diffuse CM",
"Mastocytoma of skin",
"Systemic mastocytosis",
"Non-advanced SM",
"Advanced SM",
"Mast cell sarcoma"),
Subtypes = c("—",
"Polymorphic/Monomorphic forms",
"—",
"—",
"—",
"Bone marrow mastocytosis, Indolent SM, Smouldering SM",
"SM-AHN, Aggressive SM, Mast cell leukaemia",
"—"),
`Prevalence (%)` = c(0.01, 0.01, 0.0001, 0.02, 0.005, 0.002, 0.001, "<0.0001"),
`KIT D816V (%)` = c("—", "20-80", "<10", "Unknown", "—", "80-95", "70-95", "<5")
)
# Table 2: Diagnostic Criteria for SM
sm_criteria <- tibble(
Type = c("Major criterion",
rep("Minor criteria", 4)),
Criteria = c("Multifocal packed aggregates of mast cells (>15 cells per aggregate) in bone marrow and/or extracutaneous organ",
">25% of mast cells are atypical (type I or II) in bone marrow smears",
"KIT-activating point mutation detected in bone marrow or extracutaneous organ",
"Mast cells express CD2 and/or CD25 and/or CD30",
"Baseline serum tryptase >20 ng/ml")
)
# Table 3: Mediator-Related Symptoms
mediator_symptoms <- tibble(
System = c("Skin", "Cardiovascular", "Gastrointestinal",
"Bone", "Constitutional", "Neurological"),
Symptoms = c("Flushing, itching, urticaria",
"Tachycardia, hypotension, syncope",
"Diarrhea, nausea, vomiting, cramping, GERD",
"Osteopenia, osteoporosis, musculoskeletal pain",
"Fatigue, night sweats, anaphylaxis",
"Brain fog, depression, headache"),
Mediators = c("Histamine, PGD2, cysLTs",
"Histamine, PAF",
"Histamine, PGD2",
"RANKL, cytokines",
"TNF, IL-6, VEGF",
"Various")
)
# Table 4: SM Variants and Prognosis
sm_variants <- tibble(
Variant = c("Bone marrow mastocytosis",
"Indolent SM",
"Smouldering SM",
"Aggressive SM",
"Acute MCL",
"Chronic MCL"),
`B-findings` = c("0", "0-1", "2-3", "0-3", "0-3", "0-3"),
`C-findings` = c("0", "0", "0", "≥1", "≥1", "0"),
`Mast cells in BM (%)` = c("<5", "<5", "<5", "<5", "≥20", "≥20"),
Prognosis = c("Excellent", "Excellent", "Intermediate", "Poor", "Very poor", "Poor")
)
# Table 5: Treatment Options
treatment_options <- tibble(
`Disease Stage` = c("Non-advanced SM",
"Non-advanced SM",
"Non-advanced SM",
"Advanced SM",
"Advanced SM"),
`Treatment Type` = c("Trigger avoidance",
"Anti-mediator therapy",
"Osteoporosis management",
"KIT inhibitors",
"Chemotherapy/HSCT"),
`Specific Treatments` = c("Avoid heat, friction, alcohol, NSAIDs",
"H1/H2 blockers, cromolyn, montelukast",
"Bisphosphonates, vitamin D, calcium",
"Midostaurin, avapritinib",
"Cladribine, interferon-α, HSCT"),
`Key Points` = c("Patient-specific triggers",
"Symptom control",
"Prevent fractures",
"Target KIT D816V mutation",
"For resistant disease")
)
# Table 6: KIT Mutations in Mastocytosis
kit_mutations <- tibble(
`Mutation Type` = c("D816V", "D816A/F/H/I/Y", "Del419", "ITD502-503",
"K509I", "F522C", "V560G"),
`Location` = c("Kinase domain", "Kinase domain", "Extracellular",
"Juxtamembrane", "Extracellular", "Transmembrane",
"Juxtamembrane"),
`Frequency` = c(">80% in SM", "Rare", "10-20% in pediatric CM",
"3-5%", "<3%", "<3%", "<3%"),
`TKI Sensitivity` = c("Resistant to imatinib",
"Variable",
"May respond to imatinib",
"May respond to imatinib",
"Unknown",
"May respond to imatinib",
"May respond to imatinib")
)
# Table 7: Prognostic Scoring Systems
prognostic_scores <- tibble(
System = c("MAPS", "REMA", "MARS", "GPSM"),
`Applicable to` = c("Indolent/Smouldering SM",
"Indolent SM only",
"Advanced SM only",
"All SM variants"),
`Key Parameters` = c("Age ≥60, platelets <150, ALP >ULN, mutations",
"Mutations with VAF ≥1%",
"S/A/R mutations",
"Age, Hb, ALP, tryptase"),
`Risk Categories` = c("Very low to very high (5 levels)",
"Very low to high (4 levels)",
"Low/high (2 levels)",
"Low/intermediate/high (3 levels)")
)
# Create formatted tables using gt
who_table <- who_classification %>%
gt() %>%
tab_header(
title = "WHO Classification of Mastocytosis",
subtitle = "Prevalence and KIT D816V mutation frequency"
) %>%
tab_style(
style = cell_fill(color = "lightblue"),
locations = cells_body(columns = Category, rows = c(1, 5, 8))
) %>%
fmt_percent(columns = `Prevalence (%)`, decimals = 3, scale_values = FALSE)
criteria_table <- sm_criteria %>%
gt() %>%
tab_header(title = "Diagnostic Criteria for Systemic Mastocytosis") %>%
tab_style(
style = cell_text(weight = "bold"),
locations = cells_body(columns = Type, rows = 1)
)
symptoms_table <- mediator_symptoms %>%
gt() %>%
tab_header(
title = "Mediator-Related Symptoms in Mastocytosis",
subtitle = "Organized by organ system"
) %>%
tab_style(
style = cell_fill(color = "#f0f0f0"),
locations = cells_body(rows = c(1, 3, 5))
)
variants_table <- sm_variants %>%
gt() %>%
tab_header(title = "SM Variants: Clinical Features and Prognosis") %>%
tab_style(
style = cell_fill(color = scales::alpha("red", 0.3)),
locations = cells_body(
columns = Prognosis,
rows = Prognosis %in% c("Poor", "Very poor")
)
)
treatment_table <- treatment_options %>%
gt() %>%
tab_header(title = "Treatment Strategies for Mastocytosis") %>%
tab_row_group(
label = "Advanced Disease",
rows = 4:5
) %>%
tab_row_group(
label = "Non-advanced Disease",
rows = 1:3
)
mutations_table <- kit_mutations %>%
gt() %>%
tab_header(
title = "KIT Mutations in Mastocytosis",
subtitle = "Location, frequency, and therapeutic implications"
) %>%
tab_style(
style = cell_fill(color = "yellow", alpha = 0.3),
locations = cells_body(
columns = `Mutation Type`,
rows = 1
)
) %>%
tab_footnote(
footnote = "Most common mutation in systemic mastocytosis",
locations = cells_body(columns = `Mutation Type`, rows = 1)
)
scores_table <- prognostic_scores %>%
gt() %>%
tab_header(title = "Prognostic Scoring Systems in Mastocytosis") %>%
cols_width(
System ~ px(100),
`Applicable to` ~ px(200),
`Key Parameters` ~ px(300),
`Risk Categories` ~ px(250)
)
# Display tables
who_table| WHO Classification of Mastocytosis | |||
| Prevalence and KIT D816V mutation frequency | |||
| Category | Subtypes | Prevalence (%) | KIT D816V (%) |
|---|---|---|---|
| Cutaneous mastocytosis | — | 0.01 | — |
| Maculopapular CM (MPCM) | Polymorphic/Monomorphic forms | 0.01 | 20-80 |
| Diffuse CM | — | 1e-04 | <10 |
| Mastocytoma of skin | — | 0.02 | Unknown |
| Systemic mastocytosis | — | 0.005 | — |
| Non-advanced SM | Bone marrow mastocytosis, Indolent SM, Smouldering SM | 0.002 | 80-95 |
| Advanced SM | SM-AHN, Aggressive SM, Mast cell leukaemia | 0.001 | 70-95 |
| Mast cell sarcoma | — | <0.0001 | <5 |
criteria_table| Diagnostic Criteria for Systemic Mastocytosis | |
| Type | Criteria |
|---|---|
| Major criterion | Multifocal packed aggregates of mast cells (>15 cells per aggregate) in bone marrow and/or extracutaneous organ |
| Minor criteria | >25% of mast cells are atypical (type I or II) in bone marrow smears |
| Minor criteria | KIT-activating point mutation detected in bone marrow or extracutaneous organ |
| Minor criteria | Mast cells express CD2 and/or CD25 and/or CD30 |
| Minor criteria | Baseline serum tryptase >20 ng/ml |
symptoms_table| Mediator-Related Symptoms in Mastocytosis | ||
| Organized by organ system | ||
| System | Symptoms | Mediators |
|---|---|---|
| Skin | Flushing, itching, urticaria | Histamine, PGD2, cysLTs |
| Cardiovascular | Tachycardia, hypotension, syncope | Histamine, PAF |
| Gastrointestinal | Diarrhea, nausea, vomiting, cramping, GERD | Histamine, PGD2 |
| Bone | Osteopenia, osteoporosis, musculoskeletal pain | RANKL, cytokines |
| Constitutional | Fatigue, night sweats, anaphylaxis | TNF, IL-6, VEGF |
| Neurological | Brain fog, depression, headache | Various |
variants_table| SM Variants: Clinical Features and Prognosis | ||||
| Variant | B-findings | C-findings | Mast cells in BM (%) | Prognosis |
|---|---|---|---|---|
| Bone marrow mastocytosis | 0 | 0 | <5 | Excellent |
| Indolent SM | 0-1 | 0 | <5 | Excellent |
| Smouldering SM | 2-3 | 0 | <5 | Intermediate |
| Aggressive SM | 0-3 | ≥1 | <5 | Poor |
| Acute MCL | 0-3 | ≥1 | ≥20 | Very poor |
| Chronic MCL | 0-3 | 0 | ≥20 | Poor |
treatment_table| Treatment Strategies for Mastocytosis | |||
| Disease Stage | Treatment Type | Specific Treatments | Key Points |
|---|---|---|---|
| Non-advanced Disease | |||
| Non-advanced SM | Trigger avoidance | Avoid heat, friction, alcohol, NSAIDs | Patient-specific triggers |
| Non-advanced SM | Anti-mediator therapy | H1/H2 blockers, cromolyn, montelukast | Symptom control |
| Non-advanced SM | Osteoporosis management | Bisphosphonates, vitamin D, calcium | Prevent fractures |
| Advanced Disease | |||
| Advanced SM | KIT inhibitors | Midostaurin, avapritinib | Target KIT D816V mutation |
| Advanced SM | Chemotherapy/HSCT | Cladribine, interferon-α, HSCT | For resistant disease |
mutations_table| KIT Mutations in Mastocytosis | |||
| Location, frequency, and therapeutic implications | |||
| Mutation Type | Location | Frequency | TKI Sensitivity |
|---|---|---|---|
| D816V1 | Kinase domain | >80% in SM | Resistant to imatinib |
| D816A/F/H/I/Y | Kinase domain | Rare | Variable |
| Del419 | Extracellular | 10-20% in pediatric CM | May respond to imatinib |
| ITD502-503 | Juxtamembrane | 3-5% | May respond to imatinib |
| K509I | Extracellular | <3% | Unknown |
| F522C | Transmembrane | <3% | May respond to imatinib |
| V560G | Juxtamembrane | <3% | May respond to imatinib |
| 1 Most common mutation in systemic mastocytosis | |||
scores_table| Prognostic Scoring Systems in Mastocytosis | |||
| System | Applicable to | Key Parameters | Risk Categories |
|---|---|---|---|
| MAPS | Indolent/Smouldering SM | Age ≥60, platelets <150, ALP >ULN, mutations | Very low to very high (5 levels) |
| REMA | Indolent SM only | Mutations with VAF ≥1% | Very low to high (4 levels) |
| MARS | Advanced SM only | S/A/R mutations | Low/high (2 levels) |
| GPSM | All SM variants | Age, Hb, ALP, tryptase | Low/intermediate/high (3 levels) |
# Create a summary statistics table
summary_stats <- tibble(
Parameter = c("Annual incidence",
"Prevalence",
"Median age at diagnosis",
"Male:Female ratio",
"Anaphylaxis lifetime prevalence",
"Osteoporosis prevalence",
"5-year mortality (advanced SM)"),
Value = c("1-10 per 100,000",
"1-3 per 10,000",
"~50 years",
"~1:1",
"30-40% in SM",
"~30% in SM",
"~50%")
)
summary_table <- summary_stats %>%
gt() %>%
tab_header(title = "Key Epidemiological Data") %>%
tab_style(
style = cell_fill(color = "#e8f4fd"),
locations = cells_body()
)
summary_table| Key Epidemiological Data | |
| Parameter | Value |
|---|---|
| Annual incidence | 1-10 per 100,000 |
| Prevalence | 1-3 per 10,000 |
| Median age at diagnosis | ~50 years |
| Male:Female ratio | ~1:1 |
| Anaphylaxis lifetime prevalence | 30-40% in SM |
| Osteoporosis prevalence | ~30% in SM |
| 5-year mortality (advanced SM) | ~50% |