##chargement des packages----
library(questionr)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.1     ✔ readr     2.1.4
## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ ggplot2   3.4.2     ✔ tibble    3.2.1
## ✔ lubridate 1.9.2     ✔ tidyr     1.3.0
## ✔ purrr     1.0.1     
## ── 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 errors
library(tableone)
library(labelled)
library(gtsummary)
library(GGally)
## Registered S3 method overwritten by 'GGally':
##   method from   
##   +.gg   ggplot2
library(readxl)
library(effects)
## Le chargement a nécessité le package : carData
## lattice theme set by effectsTheme()
## See ?effectsTheme for details.
library(survival)
library(survminer)
## Le chargement a nécessité le package : ggpubr
## 
## Attachement du package : 'survminer'
## 
## L'objet suivant est masqué depuis 'package:survival':
## 
##     myeloma
library(ggplot2)
library(dplyr)
library(knitr)
library(cowplot)
## 
## Attachement du package : 'cowplot'
## 
## L'objet suivant est masqué depuis 'package:ggpubr':
## 
##     get_legend
## 
## L'objet suivant est masqué depuis 'package:lubridate':
## 
##     stamp
##chargement des données
informations <- read_excel("informations.xlsx")
## New names:
## • `Dosage (mg/j)` -> `Dosage (mg/j)...13`
## • `Dosage (mg/j)` -> `Dosage (mg/j)...15`
##tableau descriptif patients ----
tbl_summary(
  informations, include = c("Age", "Sexe", "Maladie",
                           "Mutation", "anticancereux_prescrit","ligne.cat",
                           "comedication","n_comedication" ,"tac"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 1251
Age 68 [40 - 88]
Sexe
    F 79 (63.2%)
    M 46 (36.8%)
Maladie
    Adénocarcinome 101 (92.7%)
    Adénocarcinome, carcinome neuroendocrine non à petite cellule, non épidermoïde 1 (0.9%)
    Cancer épidermoïde 2 (1.8%)
    Carcinome non à petites cellules 2 (1.8%)
    Thymome 1 (0.9%)
    Thymome B3 1 (0.9%)
    Tumeurs neuroendocrines digestives et pulmonaires  1 (0.9%)
    Unknown 16
Mutation
    ALK 26 (21.1%)
    ALK/BRAF 1 (0.8%)
    Aucune 7 (5.7%)
    BRAF 6 (4.9%)
    EGFR 55 (44.7%)
    EGFR MET 2 (1.6%)
    EGFR TP53 PI3CA 2 (1.6%)
    HER2 1 (0.8%)
    KIF5 B-RET 1 (0.8%)
    KRAS 12 (9.8%)
    KRAS STK11 1 (0.8%)
    MET 2 (1.6%)
    RET 1 (0.8%)
    ROS 1 (0.8%)
    ROS1 5 (4.1%)
    Unknown 2
anticancereux_prescrit
    Afatinib 5 (4.0%)
    Alectinib 7 (5.6%)
    Brigatinib 9 (7.2%)
    Cabozantinib 3 (2.4%)
    Crizotinib 3 (2.4%)
    Dabrafénib Trametinib 6 (4.8%)
    Evérolimus 6 (4.8%)
    Géfitinib 1 (0.8%)
    Lenvatinib 1 (0.8%)
    Lorlatinib 14 (11.2%)
    Lorlatinib Dabrafénib 1 (0.8%)
    Mobocertinib 3 (2.4%)
    Osimertinib 48 (38.4%)
    Osimertinib Crizotinib 2 (1.6%)
    Osimertinib Tepotinib 1 (0.8%)
    Pralsetinib 1 (0.8%)
    Sotorasib 14 (11.2%)
ligne.cat
    1 7 (11.9%)
    2 17 (28.8%)
    3 et plus 35 (59.3%)
    Unknown 66
comedication
    Non 5 (4.0%)
    Oui 120 (96.0%)
n_comedication 6.0 [0.0 - 21.0]
tac
    IM 1 (0.8%)
    Non 78 (62.4%)
    Oui 46 (36.8%)
1 Median [Range]; n (%) 
##tableau descriptif activité pharmacie ----
tbl_summary(
  informations, include = c("consultation_initiale", "analyse_pharmaceutique",
                            "cr_analys_pharma_envoye", "delai_consult_pharma", "envoi_evaluable",
                            "oncologue_destinataire_cr","ide_destinataire_cr", "officine_destinataire_cr",
                            "med_t_destinataire_cr", "consult_toxicite"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 1251
consultation_initiale
    Non 118 (94.4%)
    Oui 7 (5.6%)
analyse_pharmaceutique
    Non 11 (8.8%)
    Oui 114 (91.2%)
cr_analys_pharma_envoye
    IM 28 (22.4%)
    Non 14 (11.2%)
    Oui 83 (66.4%)
delai_consult_pharma 3 [-58 - 725]
    Unknown 15
envoi_evaluable
    Non 12 (9.6%)
    Oui 113 (90.4%)
oncologue_destinataire_cr
    IM 38 (30.4%)
    Non 14 (11.2%)
    Oui 73 (58.4%)
ide_destinataire_cr
    IM 38 (30.4%)
    Non 25 (20.0%)
    Oui 62 (49.6%)
officine_destinataire_cr
    IM 38 (30.4%)
    Non 77 (61.6%)
    Oui 10 (8.0%)
med_t_destinataire_cr
    IM 39 (31.2%)
    Non 86 (68.8%)
consult_toxicite
    Non 60 (48.0%)
    Oui 65 (52.0%)
1 n (%); Median [Range] 
##Retours des analyses pharmaceutiques 
##chargement des données

analyse_pharma <- read_excel("analyse_pharma.xlsx")

##description des interactions globales
tbl_summary(
  analyse_pharma, include = c("interaction_retrouvee", "Proposition_STP", 'intervention_pharmacien'),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 5331
interaction_retrouvee
    Absence d'AP 13 (2.4%)
    Non 22 (4.1%)
    Oui 498 (93.4%)
Proposition_STP
    Oui 52 (100.0%)
    Unknown 481
intervention_pharmacien
    Adaptation plan de prise 160 (32.5%)
    Arrêt comédication 16 (3.2%)
    Modification posologique anticancéreux 7 (1.4%)
    Modification posologique comédication 4 (0.8%)
    Optimisation en fonction des indications 1 (0.2%)
    Substitution comédication 3 (0.6%)
    Surveillance renforcée EI 302 (61.3%)
    Unknown 40
1 n (%) 
##interactions anticancéreux sur comed
atk_comed<-filter(analyse_pharma, c(type_interaction=="Anticancéreux sur comédication"))

tbl_summary(
  atk_comed, include = c("risque_interaction", "anticancereux_concerne", "cat_atc"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 3371
risque_interaction
    Diminution efficacité comédication 203 (60.2%)
    Majoration toxicité comédication 91 (27.0%)
    Majoration toxicité ou diminution efficacité comed 41 (12.2%)
    Potentialisation d'EI 2 (0.6%)
anticancereux_concerne
    Afatinib 1 (0.3%)
    Alectinib 1 (0.3%)
    Alectinib (métabolite actif) 1 (0.3%)
    Brigatinib 26 (7.7%)
    Cabozantinib 8 (2.4%)
    Crizotinib 20 (5.9%)
    Dabrafénib 35 (10.4%)
    Evérolimus 8 (2.4%)
    Lorlatinib 46 (13.6%)
    Mobocertinib 7 (2.1%)
    Osimertinib 137 (40.7%)
    Sotorasib 45 (13.4%)
    Tramétinib 2 (0.6%)
cat_atc
    Agents acting on the renin 10 (3.0%)
    Analgesics 72 (21.4%)
    Anesthetics 4 (1.2%)
    ANTI-ACNE PREPARATIONS 2 (0.6%)
    Antianemic preparations 2 (0.6%)
    Antibacterials for systemic use 1 (0.3%)
    Antidiarrheals, intestinal antiinflammatory/antiinfective agents 6 (1.8%)
    Antiemetics and antinauseants 5 (1.5%)
    Antiepileptics 6 (1.8%)
    Antigout preparations 3 (0.9%)
    Antihistamines for systemic use 1 (0.3%)
    Antithrombotic agents 15 (4.5%)
    Beta blocking agents 14 (4.2%)
    Calcium channel blockers 14 (4.2%)
    Cardiac therapy 3 (0.9%)
    Corticosteroids for systemic use 33 (9.8%)
    Cough and cold preparations 1 (0.3%)
    Diuretics 14 (4.2%)
    DRUGS FOR ACID RELATED DISORDERS 32 (9.5%)
    Drugs for functional gastrointestinal disorders 1 (0.3%)
    Drugs for obstructive airway diseases 8 (2.4%)
    Drugs used in diabetes 1 (0.3%)
    Laxatives 7 (2.1%)
    Lipid modifying agents 29 (8.6%)
    Psychoanaleptics 14 (4.2%)
    Psycholeptics 35 (10.4%)
    Urologicals 4 (1.2%)
1 n (%) 
#sources interactions
tbl_summary(
  atk_comed, include = c("BCRP", "P-gp", "MATE1", "MRP2", "OAT3", "OATP1", 
                         "OATP1B1", "OATP1B3", "OTC2", "CYP2C8", "CYP2C9", "CYP2C19", 
                         "CYP3A", "absorption"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 3371
BCRP
    Modéré 1 (0.3%)
    Non 308 (91.4%)
    Oui 28 (8.3%)
P-gp
    Modéré 24 (7.1%)
    Non 290 (86.1%)
    Oui 23 (6.8%)
MATE1
    Non 336 (99.7%)
    Oui 1 (0.3%)
MRP2
    Non 329 (97.6%)
    Oui 8 (2.4%)
OAT3
    Non 333 (98.8%)
    Oui 4 (1.2%)
OATP1
    Non 336 (99.7%)
    Oui 1 (0.3%)
OATP1B1
    Non 335 (99.4%)
    Oui 2 (0.6%)
OATP1B3
    Non 333 (98.8%)
    Oui 4 (1.2%)
OTC2
    Non 336 (99.7%)
    Oui 1 (0.3%)
CYP2C8
    Non 336 (99.7%)
    Oui 1 (0.3%)
CYP2C9
    Faible 2 (0.6%)
    Non 332 (98.5%)
    Oui 3 (0.9%)
CYP2C19
    Faible 2 (0.6%)
    Non 335 (99.4%)
CYP3A
    Faible 135 (40.1%)
    Modéré 71 (21.1%)
    Non 83 (24.6%)
    Oui 48 (14.2%)
absorption
    Absorption 2 (0.6%)
    Non 335 (99.4%)
1 n (%) 
##interactions comed sur atk
comed_atk<-filter(analyse_pharma, c(type_interaction=="Comédication sur anticancéreux"))

tbl_summary(
  comed_atk, include = c("risque_interaction", "anticancereux_concerne", "cat_atc"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 1421
risque_interaction
    Diminution efficacité anticancéreux 34 (25.8%)
    Majoration toxicité anticancéreux 96 (72.7%)
    Potentialisation d'EI 2 (1.5%)
    Unknown 10
anticancereux_concerne
    Afatinib 8 (5.6%)
    Alectinib 1 (0.7%)
    Alectinib + mtb actif 1 (0.7%)
    Brigatinib 5 (3.5%)
    Cabozantinib 7 (4.9%)
    Crizotinib 8 (5.6%)
    Dabrafénib 11 (7.7%)
    Evérolimus 7 (4.9%)
    Lenvatinib 1 (0.7%)
    Lorlatinib 6 (4.2%)
    Mobocertinib 5 (3.5%)
    Osimertinib 61 (43.0%)
    Sotorasib 13 (9.2%)
    Tramétinib 8 (5.6%)
cat_atc
    Agents acting on the renin 14 (9.9%)
    Analgesics 2 (1.4%)
    Antibacterials for systemic use 2 (1.4%)
    Antidiarrheals, intestinal antiinflammatory/antiinfective agents 14 (9.9%)
    Antiemetics and antinauseants 1 (0.7%)
    Antiepileptics 1 (0.7%)
    Antiinflammatory and antirheumatic products 2 (1.4%)
    Antithrombotic agents 2 (1.4%)
    Antivirals for systemic use 2 (1.4%)
    Beta blocking agents 1 (0.7%)
    Calcium channel blockers 15 (10.6%)
    Cardiac therapy 3 (2.1%)
    Corticosteroids for systemic use 1 (0.7%)
    Cough and cold preparations 1 (0.7%)
    Diuretics 6 (4.2%)
    DRUGS FOR ACID RELATED DISORDERS 46 (32.4%)
    Drugs for functional gastrointestinal disorders 2 (1.4%)
    Lipid modifying agents 8 (5.6%)
    Nasal preparations 2 (1.4%)
    Other drugs for disorders of the musculo 1 (0.7%)
    Pituitary and hypothalamic hormones 1 (0.7%)
    Psychoanaleptics 8 (5.6%)
    Psycholeptics 3 (2.1%)
    TOPICAL PRODUCTS FOR JOINT AND MUSCULAR PAIN 1 (0.7%)
    VASOPROTECTIVES 3 (2.1%)
1 n (%) 
#sources interactions
tbl_summary(
  comed_atk, include = c("BCRP", "P-gp", "MATE1", "MRP2", "OAT3", "OATP1", 
                         "OATP1B1", "OATP1B3", "OTC2", "CYP2C8", "CYP2C9", "CYP2C19", 
                         "CYP3A", "absorption"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 1421
BCRP
    Modéré 1 (0.7%)
    Non 100 (70.4%)
    Oui 41 (28.9%)
P-gp
    Modéré 7 (4.9%)
    Non 99 (69.7%)
    Oui 36 (25.4%)
MATE1
    Non 135 (95.1%)
    Oui 7 (4.9%)
MRP2
    Non 141 (99.3%)
    Oui 1 (0.7%)
OAT3
    Non 142 (100.0%)
OATP1
    Non 142 (100.0%)
OATP1B1
    Non 142 (100.0%)
OATP1B3
    Non 142 (100.0%)
OTC2
    Non 142 (100.0%)
CYP2C8
    Faible 1 (0.7%)
    Non 141 (99.3%)
CYP2C9
    Modéré 1 (0.7%)
    Non 141 (99.3%)
CYP2C19
    Non 142 (100.0%)
CYP3A
    Faible 7 (4.9%)
    Modéré 9 (6.3%)
    Non 123 (86.6%)
    Oui 2 (1.4%)
    Puissant 1 (0.7%)
absorption
    Absoption HE 2 (1.4%)
    Absorption 17 (12.0%)
    Non 109 (76.8%)
    pH gastrique 14 (9.9%)
1 n (%) 
##interactions comed sur comed

comed_comed<-filter(analyse_pharma, c(type_interaction=="Comédication sur comédication"))

tbl_summary(
  comed_comed, include = c("risque_interaction", "anticancereux_concerne", "comedication_concernee"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 231
risque_interaction
    Diminution efficacité comédication 18 (78.3%)
    Majoration toxicité ou diminution efficacité comed 2 (8.7%)
    Potentialisation d'EI 3 (13.0%)
anticancereux_concerne
    Bisoprolol 1 (14.3%)
    Candésartan 1 (14.3%)
    Doxycycline 1 (14.3%)
    Escitalopram 1 (14.3%)
    Formotérol 1 (14.3%)
    Insuline 1 (14.3%)
    Tramadol 1 (14.3%)
    Unknown 16
comedication_concernee
    Amiodarone 1 (4.3%)
    Bétaxolol 1 (4.3%)
    Calcium 1 (4.3%)
    CARBOLEVURE 1 (4.3%)
    Diosmectite 7 (30.4%)
    FERO-GRAD VITAMINE C 1 (4.3%)
    GAVISCON 6 (26.1%)
    Octreotide 2 (8.7%)
    Racécadotril 1 (4.3%)
    Siméticone 1 (4.3%)
    Zopiclone, bromazépam, hydroxyzine, alprazolam 1 (4.3%)
1 n (%) 
#sources interactions
tbl_summary(
  comed_comed, include = c("BCRP", "P-gp", "MATE1", "MRP2", "OAT3", "OATP1", 
                         "OATP1B1", "OATP1B3", "OTC2", "CYP2C8", "CYP2C9", "CYP2C19", 
                         "CYP3A", "absorption"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 231
BCRP
    Non 23 (100.0%)
P-gp
    Non 23 (100.0%)
MATE1
    Non 23 (100.0%)
MRP2
    Non 23 (100.0%)
OAT3
    Non 23 (100.0%)
OATP1
    Non 23 (100.0%)
OATP1B1
    Non 23 (100.0%)
OATP1B3
    Non 23 (100.0%)
OTC2
    Non 23 (100.0%)
CYP2C8
    Non 23 (100.0%)
CYP2C9
    Non 23 (100.0%)
CYP2C19
    Non 23 (100.0%)
CYP3A
    Non 22 (95.7%)
    Oui 1 (4.3%)
absorption
    Absorption 17 (73.9%)
    Non 6 (26.1%)
1 n (%) 
##interactions atk sur atk

atk_atk<-filter(analyse_pharma, c(type_interaction=="Anticancéreux sur anticancéreux"))

tbl_summary(
  atk_atk, include = c("risque_interaction", "anticancereux_concerne", "comedication_concernee"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 51
risque_interaction
    Diminution efficacité anticancéreux 2 (40.0%)
    Majoration toxicité anticancéreux 3 (60.0%)
anticancereux_concerne
    Crizotinib 1 (20.0%)
    Osimertinib 2 (40.0%)
    Tépotinib 1 (20.0%)
    Tramétinib 1 (20.0%)
comedication_concernee
    Crizotinib 1 (20.0%)
    Dabrafénib 1 (20.0%)
    Osimertinib 2 (40.0%)
    Tépotinib 1 (20.0%)
1 n (%) 
#sources interactions
tbl_summary(
  atk_atk, include = c("BCRP", "P-gp", "MATE1", "MRP2", "OAT3", "OATP1", 
                           "OATP1B1", "OATP1B3", "OTC2", "CYP2C8", "CYP2C9", "CYP2C19", 
                           "CYP3A", "absorption"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 51
BCRP
    Non 5 (100.0%)
P-gp
    Non 2 (40.0%)
    Oui 3 (60.0%)
MATE1
    Non 5 (100.0%)
MRP2
    Non 5 (100.0%)
OAT3
    Non 5 (100.0%)
OATP1
    Non 5 (100.0%)
OATP1B1
    Non 5 (100.0%)
OATP1B3
    Non 5 (100.0%)
OTC2
    Non 5 (100.0%)
CYP2C8
    Non 5 (100.0%)
CYP2C9
    Non 5 (100.0%)
CYP2C19
    Non 5 (100.0%)
CYP3A
    Faible 1 (20.0%)
    Non 2 (40.0%)
    Oui 2 (40.0%)
absorption
    Non 5 (100.0%)
1 n (%) 
#Analyse des interactions avec TAC

##chargement des données 

analyse_tac <- read_excel("analyse_tac.xlsx")

###descriptif 
tbl_summary(
  analyse_tac, include = c("type_traitement","intervention_pharmacien","nom"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  digits=all_categorical()~ c(0,1)
)
Characteristic N = 2351
type_traitement
    Alimentation 10 (4.3%)
    Apithérapie 4 (1.7%)
    Aromathérapie 9 (3.8%)
    Aucun 83 (35.5%)
    Complément alimentaire 84 (35.9%)
    Dispositif médical 1 (0.4%)
    Elixir 1 (0.4%)
    Gemmothérapie 1 (0.4%)
    Homéopathie 37 (15.8%)
    Mycothérapie 2 (0.9%)
    Phytothérapie 2 (0.9%)
    Unknown 1
intervention_pharmacien
    Absence d'interaction 1 (0.9%)
    Contre-indiquée si porteur de PAC 1 (0.9%)
    Déconseillée 76 (71.0%)
    Déconseillée en gélule 1 (0.9%)
    Ok 24 (22.4%)
    Prise à 2h de distance 4 (3.7%)
    Unknown 128
nom
    100% FPP (extrait fermenté de papaye) de IMMUNE’AGE 1 (0.7%)
    ACEROLA C-max 1 (0.7%)
    Aceticum acidum 15CH 1 (0.7%)
    Ail de LA ROYALE 1 (0.7%)
    ALVITYL 1 (0.7%)
    ALVITYL Vitalité 1 (0.7%)
    ANACAPS 1 (0.7%)
    Apis 15CH 1 (0.7%)
    Apis mellifica 8DH, Aurum muriaticum natronatum 7DH, Avena Sativa 4DH, Hypericum Perforatum 4DH, Ignatia amara 5DH, Phosphoricum acidum 5DH 1 (0.7%)
    Aragonite D1 50%, calcarea carb D4 25%, quercus D3 1 (0.7%)
    Argile par voie orale 2 (1.3%)
    Armoise 1 (0.7%)
    Artémisia Annua de HERBAL D-TOX 1 (0.7%)
    ARTERIA 1 (0.7%)
    Ashwagandha 1 (0.7%)
    BERBERIS RADIX D3, CARDUS MARIANUS D2, CHELIDONIUM RADIX D3, COLCHICUM D2, CURCUMA D2, SULFUR D8, TARAXACUM STANNO CULTUM D3 1 (0.7%)
    BERROCA 2 (1.3%)
    BIBHITAKI FRUIT 1 (0.7%)
    BION Vitalité 1 (0.7%)
    BIOTIC P7 1 (0.7%)
    BIOTICS 3B-G (vitamine B) 1 (0.7%)
    Bovista gigantea 5CH 1 (0.7%)
    BROMELAINE 1 (0.7%)
    Charbon végétal activé 1 (0.7%)
    Chelidonium D1, Curcuma D1, Taraxacum stanno cultum D3 1 (0.7%)
    China 9CH 1 (0.7%)
    Chlorella + Spiruline de Biotona 1 (0.7%)
    Chlorure de magnésium et vitamine B6 2 (1.3%)
    CHRYSANTELLUM 1 (0.7%)
    Compléments alimentaires 1 (0.7%)
    CORIOLUS VERSICOLOR EXTRAKT 1 (0.7%)
    Corrosol 1 (0.7%)
    Cuprum metallicum 9CH 1 (0.7%)
    Curcuma + poivre noir de LA ROYALE 1 (0.7%)
    D-Mulsion FORTE (vitamine D) de BIOTICS RESEARCH 1 (0.7%)
    D3 PROTECT (vitamine D3)  1 (0.7%)
    Desmodium 2 (1.3%)
    Dilution 5, 7 et 9CH 1 (0.7%)
    Epices, thés, infusions, graines… 1 (0.7%)
    EPS desmodium 1 (0.7%)
    EPS rhodiole et mélisse 1 (0.7%)
    ERGY D (Vit D) 2 (1.3%)
    ERGYMAG (Mg + zn) 1 (0.7%)
    ERGYMAG (Mg + Zn) 1 (0.7%)
    ERGYSIL (ortie, silicium, sélénium) 1 (0.7%)
    Ferments lactiques des laboratoire Dieti Natura 1 (0.7%)
    Ferrum metallicum 7 CH  1 (0.7%)
    Ferrum sid D10, Phosphorus D8, Silicea D12 W788 60cc dilution 1 (0.7%)
    Fleurs de Bach 1 (0.7%)
    FLEXOFYTOL (curcuma) 1 (0.7%)
    Floracare XL (bifidobactéries et des lactobacilles) de BIOTICS RESEARCH 1 (0.7%)
    Gelée royale 1 (0.7%)
    Glutathion 1 (0.7%)
    Glutathion Liposomé + de HOD 1 (0.7%)
    Graine de plantain 1 (0.7%)
    HAIR VOLUME 1 (0.7%)
    Huile essentielle de ravintsara 1 (0.7%)
    Huile essentielle de Romarin à verbénone 1 (0.7%)
    Huile essentielle de Tea tree 1 (0.7%)
    Huile essentielle de thym 1 (0.7%)
    Huile végétale de millepertuis 2 (1.3%)
    Huile végétale de rose musquée 1 (0.7%)
    Huille essentielle d'helichryse 1 (0.7%)
    Huille essentielle de lavandin 1 (0.7%)
    IMMUN ACTIFS 1 (0.7%)
    Influenzinum 15CH 1 (0.7%)
    INTENZYME FORTE 1 (0.7%)
    KIDNEY CLEANSE 1 (0.7%)
    KLARELINE 1 (0.7%)
    Lachesis 9CH, phosphorus 9CH, nux vomica 9CH 1 (0.7%)
    LACTIBIANE REFERENCE 1 (0.7%)
    LENODIAR  1 (0.7%)
    Levure de riz rouge, oméga 3 et CoQ10 1 (0.7%)
    Lithothamne de LA ROYALE 1 (0.7%)
    Lycopodium clavatum 15CH 1 (0.7%)
    Lycopodium clavatum D10 1 (0.7%)
    Macérat de gui de LA ROYALE 1 (0.7%)
    MAGN ACTIFS 2 (1.3%)
    Maitake 1 (0.7%)
    Medulo D8 1 (0.7%)
    Mélisse en gélules ou tisanes 1 (0.7%)
    MENO ACTIFS 1 (0.7%)
    Miel, propolis 1 (0.7%)
    Natrum muriaticum 15 CH 1 (0.7%)
    Natrum sulfuricum 15CH 1 (0.7%)
    Nux vomica 9CH 1 (0.7%)
    Oméga 3 1 (0.7%)
    OMEGA 3 de Solgar 1 (0.7%)
    OMEGABIANE DHA 1 (0.7%)
    OPTIFLOR 1 (0.7%)
    Phosphorus 30CH 1 (0.7%)
    Plumbum mellitum D12 30g Trit 1 (0.7%)
    Pollen de fleurs 1 (0.7%)
    Pollen en pelotes Bio Miel Besacier 1 (0.7%)
    PROCARTIL (glucosamine, chondrotoïne, manganèse, cuivre) 1 (0.7%)
    PROPOMAX (propolis verte et brune bio, bioflavonoides et artepilline c) 1 (0.7%)
    Prostate 8DH 2 (1.3%)
    Psyllium 1 (0.7%)
    RENFORSTIM 1 (0.7%)
    Ribes nigrum 1DH 1 (0.7%)
    Ruscus aculeatus 4DH 1 (0.7%)
    Selenium ACE Optimum 50+ 1 (0.7%)
    SEREMAG (magnésium, taurine et vitamine B6) 1 (0.7%)
    Serum de Yersin 9 CH 1 (0.7%)
    Sève de bouleau 1DH 1 (0.7%)
    STRESS’O (rhadiola, choline, lavande vrai) de PHYSIOSENS 1 (0.7%)
    Sulfate de magnésium 1 (0.7%)
    Sulfurum 7CH 1 (0.7%)
    Teinture mère de Calendula 2 (1.3%)
    Teinture mère de Dionaea Muscipula 1 (0.7%)
    Teinture mère GINKGO BILOBA 1 (0.7%)
    TEMPORAL (Levure de riz rouge, policaosanol, CoQ10) 1 (0.7%)
    Thé au citron ou orange-canelle 1 (0.7%)
    Thymuline 4CH 1 (0.7%)
    THYROSTIM (L-thyroxine, vit C, vit D, zinc…) de Copmed 1 (0.7%)
    Tisane 1 (0.7%)
    Tisane d’olivier et d’hibiscus 1 (0.7%)
    Tisane de thym et sauge 2 (1.3%)
    Tisane verveine 1 (0.7%)
    Tuberculinum 15CH 1 (0.7%)
    UNIBIANE HCA (garcinia) 1 (0.7%)
    UNIBIANE R-α lipoïque 1 (0.7%)
    Vitamine B12 1 (0.7%)
    Vitamine C 2 (1.3%)
    VITAMINE C 1000 mg 1 (0.7%)
    Vitamine C liposomale de Biocyte  1 (0.7%)
    Vitamine C liposomale de LA ROYALE 1 (0.7%)
    Vitamine D 1 (0.7%)
    VITAMINE D3 1 (0.7%)
    Vitamine d3 + k2 de Sunday Naturel 1 (0.7%)
    VITAMINE D3 2000UI 1 (0.7%)
    VITAMINE D3 800UI de Sante verte 1 (0.7%)
    Vitamine K2 1 (0.7%)
    VITAMINE K2 1 (0.7%)
    Weleda c692 1 (0.7%)
    Weleda c720 1 (0.7%)
    Zinc 3 (2.0%)
    Zinc (amino chelate) 1 (0.7%)
    Unknown 84
1 n (%) 
#Consultations de toxicités

ct_classes <- read_excel("ct_classes.xlsx")

tbl_summary(
  ct_classes, include = c("tox_digestive","tox_cutanee", "tox_muqueuse",
                          "tox_cardiovasc", "tox_ophtalmo",
                          "tox_pulmonaire", "tox_generale", 
                          "tox_hemato", "tox_musculo_squeletique", 
                          "tox_uro_nephro", "tox_hepatique", 
                          "tox_neuro", "tox_psy", "tox_bio"),
  statistic = all_continuous() ~ "{median} [{min} - {max}]",
  by="medicament",
  digits=all_categorical()~ c(0,1)
)
Characteristic Afatinib, N = 51 Alectinib, N = 51 Brigatinib, N = 71 Cabozantinib, N = 21 Crizotinib, N = 21 Dabrafénib/Trametinib, N = 21 Evérolimus, N = 51 Lenvatinib, N = 11 Lorlatinib, N = 61 Mobocertinib, N = 21 Osimertinib, N = 261 Osimertinib/Crizotinib, N = 11 Sotorasib, N = 51
tox_digestive 5 (100.0%) 3 (60.0%) 0 (0.0%) 1 (50.0%) 2 (100.0%) 1 (50.0%) 2 (40.0%) 1 (100.0%) 2 (33.3%) 2 (100.0%) 17 (65.4%) 1 (100.0%) 4 (80.0%)
tox_cutanee 4 (80.0%) 2 (40.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (50.0%) 1 (20.0%) 0 (0.0%) 1 (16.7%) 2 (100.0%) 16 (61.5%) 0 (0.0%) 3 (60.0%)
tox_muqueuse 4 (80.0%) 1 (20.0%) 0 (0.0%) 1 (50.0%) 0 (0.0%) 1 (50.0%) 0 (0.0%) 0 (0.0%) 1 (16.7%) 1 (50.0%) 8 (30.8%) 0 (0.0%) 0 (0.0%)
tox_cardiovasc 0 (0.0%) 3 (60.0%) 1 (14.3%) 2 (100.0%) 1 (50.0%) 1 (50.0%) 2 (40.0%) 1 (100.0%) 2 (33.3%) 0 (0.0%) 2 (7.7%) 0 (0.0%) 0 (0.0%)
tox_ophtalmo 2 (40.0%) 1 (20.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (50.0%) 2 (7.7%) 0 (0.0%) 0 (0.0%)
tox_pulmonaire 0 (0.0%) 3 (60.0%) 3 (42.9%) 0 (0.0%) 0 (0.0%) 1 (50.0%) 0 (0.0%) 0 (0.0%) 1 (16.7%) 0 (0.0%) 3 (11.5%) 0 (0.0%) 2 (40.0%)
tox_generale 3 (60.0%) 1 (20.0%) 2 (28.6%) 1 (50.0%) 1 (50.0%) 0 (0.0%) 3 (60.0%) 0 (0.0%) 1 (16.7%) 2 (100.0%) 9 (34.6%) 0 (0.0%) 3 (60.0%)
tox_hemato 1 (20.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 4 (15.4%) 0 (0.0%) 1 (20.0%)
tox_musculo_squeletique 2 (40.0%) 4 (80.0%) 2 (28.6%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (100.0%) 3 (50.0%) 0 (0.0%) 7 (26.9%) 0 (0.0%) 3 (60.0%)
tox_uro_nephro 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (20.0%) 1 (100.0%) 0 (0.0%) 0 (0.0%) 1 (3.8%) 0 (0.0%) 1 (20.0%)
tox_hepatique 0 (0.0%) 0 (0.0%) 2 (28.6%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (16.7%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%)
tox_neuro 2 (40.0%) 0 (0.0%) 3 (42.9%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (11.5%) 0 (0.0%) 3 (60.0%)
tox_psy 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (50.0%) 0 (0.0%) 1 (20.0%) 0 (0.0%) 2 (33.3%) 1 (50.0%) 0 (0.0%) 0 (0.0%) 1 (20.0%)
tox_bio 0 (0.0%) 3 (60.0%) 2 (28.6%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (20.0%) 0 (0.0%) 1 (16.7%) 0 (0.0%) 1 (3.8%) 0 (0.0%) 0 (0.0%)
1 n (%)