##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
library(readxl)

informations <- read_excel("informations.xlsx")
## New names:
## • `Dosage (mg/j)` -> `Dosage (mg/j)...13`
## • `Dosage (mg/j)` -> `Dosage (mg/j)...15`
##recodage des variables et bases de données le cas échéant----



##renommer des variables pour présentation dans les tableaux de résultat



##


##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 = 1321
Age 68 [28 - 88]
Sexe
    F 81 (61.4%)
    M 51 (38.6%)
Maladie
    Adénocarcinome 126 (95.5%)
    Carcinome épidermoïde 3 (2.3%)
    Thymome 2 (1.5%)
    Tumeurs neuroendocrines digestives et pulmonaires  1 (0.8%)
Mutation
    ALK 26 (19.7%)
    ALK BRAF 1 (0.8%)
    Aucune 7 (5.3%)
    BRAF 7 (5.3%)
    EGFR 64 (48.5%)
    EGFR MET 2 (1.5%)
    HER2 1 (0.8%)
    KIF5 B-RET 1 (0.8%)
    KRAS 14 (10.6%)
    MET 2 (1.5%)
    RET 1 (0.8%)
    ROS1 6 (4.5%)
anticancereux_prescrit 0 (NA%)
    Unknown 132
ligne.cat
    1 19 (25.3%)
    2 19 (25.3%)
    3 et plus 37 (49.3%)
    Unknown 57
comedication
    Non 5 (3.8%)
    Oui 127 (96.2%)
n_comedication 6.0 [0.0 - 21.0]
tac
    IM 1 (0.8%)
    Non 83 (62.9%)
    Oui 48 (36.4%)
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 = 1321
consultation_initiale
    Non 124 (93.9%)
    Oui 8 (6.1%)
analyse_pharmaceutique
    Non 12 (9.1%)
    Oui 120 (90.9%)
cr_analys_pharma_envoye
    IM 30 (22.7%)
    Non 15 (11.4%)
    Oui 87 (65.9%)
delai_consult_pharma 4 [-10 - 725]
    Unknown 16
envoi_evaluable
    Non 13 (9.8%)
    Oui 119 (90.2%)
oncologue_destinataire_cr
    IM 40 (30.3%)
    Non 15 (11.4%)
    Oui 77 (58.3%)
ide_destinataire_cr
    IM 40 (30.3%)
    Non 26 (19.7%)
    Oui 66 (50.0%)
officine_destinataire_cr
    IM 40 (30.3%)
    Non 82 (62.1%)
    Oui 10 (7.6%)
med_t_destinataire_cr
    IM 41 (31.1%)
    Non 91 (68.9%)
consult_toxicite
    Non 65 (49.2%)
    Oui 67 (50.8%)
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 = 5661
interaction_retrouvee
    Absence d'AP 13 (2.3%)
    Non 23 (4.1%)
    Oui 530 (93.6%)
Proposition_STP
    Oui 54 (100.0%)
    Unknown 512
intervention_pharmacien
    Adaptation plan de prise 171 (32.9%)
    Arrêt comédication 16 (3.1%)
    Modification posologique anticancéreux 7 (1.3%)
    Modification posologique comédication 4 (0.8%)
    Optimisation en fonction des indications 1 (0.2%)
    Substitution comédication 3 (0.6%)
    Surveillance renforcée EI 318 (61.2%)
    Unknown 46
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 = 3591
risque_interaction
    Diminution efficacité comédication 215 (59.9%)
    Majoration toxicité comédication 99 (27.6%)
    Majoration toxicité ou diminution efficacité comed 41 (11.4%)
    Potentialisation d'EI 4 (1.1%)
anticancereux_concerne
    Afatinib 1 (0.3%)
    Alectinib 1 (0.3%)
    Alectinib (métabolite actif) 1 (0.3%)
    Brigatinib 26 (7.2%)
    Cabozantinib 8 (2.2%)
    Crizotinib 20 (5.6%)
    Dabrafénib 35 (9.7%)
    Evérolimus 8 (2.2%)
    Lorlatinib 46 (12.8%)
    Mobocertinib 9 (2.5%)
    Osimertinib 157 (43.7%)
    Sotorasib 45 (12.5%)
    Tramétinib 2 (0.6%)
cat_atc
    Agents acting on the renin 10 (2.8%)
    Analgesics 76 (21.2%)
    Anesthetics 4 (1.1%)
    ANTI-ACNE PREPARATIONS 2 (0.6%)
    Antianemic preparations 2 (0.6%)
    Antibacterials for systemic use 1 (0.3%)
    Antidiarrheals, intestinal antiinflammatory/antiinfective agents 6 (1.7%)
    Antiemetics and antinauseants 5 (1.4%)
    Antiepileptics 6 (1.7%)
    Antigout preparations 3 (0.8%)
    Antihistamines for systemic use 1 (0.3%)
    Antithrombotic agents 15 (4.2%)
    Beta blocking agents 15 (4.2%)
    Calcium channel blockers 15 (4.2%)
    Cardiac therapy 5 (1.4%)
    Corticosteroids for systemic use 36 (10.0%)
    Cough and cold preparations 1 (0.3%)
    Diuretics 15 (4.2%)
    DRUGS FOR ACID RELATED DISORDERS 34 (9.5%)
    Drugs for functional gastrointestinal disorders 1 (0.3%)
    Drugs for obstructive airway diseases 9 (2.5%)
    Drugs used in diabetes 1 (0.3%)
    Endocrine therapy 1 (0.3%)
    Laxatives 7 (1.9%)
    Lipid modifying agents 32 (8.9%)
    Psychoanaleptics 15 (4.2%)
    Psycholeptics 36 (10.0%)
    Urologicals 5 (1.4%)
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 = 3591
BCRP
    Modéré 1 (0.3%)
    Non 326 (90.8%)
    Oui 32 (8.9%)
P-gp
    Modéré 24 (6.7%)
    Non 312 (86.9%)
    Oui 23 (6.4%)
MATE1
    Non 358 (99.7%)
    Oui 1 (0.3%)
MRP2
    Non 351 (97.8%)
    Oui 8 (2.2%)
OAT3
    Non 355 (98.9%)
    Oui 4 (1.1%)
OATP1
    Non 358 (99.7%)
    Oui 1 (0.3%)
OATP1B1
    Non 357 (99.4%)
    Oui 2 (0.6%)
OATP1B3
    Non 355 (98.9%)
    Oui 4 (1.1%)
OTC2
    Non 358 (99.7%)
    Oui 1 (0.3%)
CYP2C8
    Non 358 (99.7%)
    Oui 1 (0.3%)
CYP2C9
    Faible 2 (0.6%)
    Non 354 (98.6%)
    Oui 3 (0.8%)
CYP2C19
    Faible 2 (0.6%)
    Non 357 (99.4%)
CYP3A
    Faible 149 (41.5%)
    Modéré 71 (19.8%)
    Non 89 (24.8%)
    Oui 50 (13.9%)
absorption
    Absorption 2 (0.6%)
    Non 357 (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 = 1511
risque_interaction
    Diminution efficacité anticancéreux 35 (24.8%)
    Majoration toxicité anticancéreux 102 (72.3%)
    Potentialisation d'EI 4 (2.8%)
    Unknown 10
anticancereux_concerne
    Afatinib 8 (5.3%)
    Alectinib 1 (0.7%)
    Alectinib + mtb actif 1 (0.7%)
    Brigatinib 5 (3.3%)
    Cabozantinib 7 (4.6%)
    Crizotinib 8 (5.3%)
    Dabrafénib 11 (7.3%)
    Evérolimus 7 (4.6%)
    Lenvatinib 1 (0.7%)
    Lorlatinib 6 (4.0%)
    Mobocertinib 6 (4.0%)
    Osimertinib 69 (45.7%)
    Sotorasib 13 (8.6%)
    Tramétinib 8 (5.3%)
cat_atc
    Agents acting on the renin 14 (9.3%)
    Analgesics 2 (1.3%)
    Antibacterials for systemic use 2 (1.3%)
    Antidiarrheals, intestinal antiinflammatory/antiinfective agents 14 (9.3%)
    Antiemetics and antinauseants 1 (0.7%)
    Antiepileptics 1 (0.7%)
    Antiinflammatory and antirheumatic products 2 (1.3%)
    Antithrombotic agents 2 (1.3%)
    Antivirals for systemic use 2 (1.3%)
    Beta blocking agents 1 (0.7%)
    Calcium channel blockers 16 (10.6%)
    Cardiac therapy 6 (4.0%)
    Corticosteroids for systemic use 1 (0.7%)
    Cough and cold preparations 1 (0.7%)
    Diuretics 7 (4.6%)
    DRUGS FOR ACID RELATED DISORDERS 48 (31.8%)
    Drugs for functional gastrointestinal disorders 2 (1.3%)
    Endocrine therapy 1 (0.7%)
    Lipid modifying agents 9 (6.0%)
    Nasal preparations 2 (1.3%)
    Other drugs for disorders of the musculo 1 (0.7%)
    Pituitary and hypothalamic hormones 1 (0.7%)
    Psychoanaleptics 8 (5.3%)
    Psycholeptics 3 (2.0%)
    TOPICAL PRODUCTS FOR JOINT AND MUSCULAR PAIN 1 (0.7%)
    VASOPROTECTIVES 3 (2.0%)
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 = 1511
BCRP
    Modéré 1 (0.7%)
    Non 104 (68.9%)
    Oui 46 (30.5%)
P-gp
    Modéré 9 (6.0%)
    Non 104 (68.9%)
    Oui 38 (25.2%)
MATE1
    Non 144 (95.4%)
    Oui 7 (4.6%)
MRP2
    Non 150 (99.3%)
    Oui 1 (0.7%)
OAT3
    Non 151 (100.0%)
OATP1
    Non 151 (100.0%)
OATP1B1
    Non 151 (100.0%)
OATP1B3
    Non 151 (100.0%)
OTC2
    Non 151 (100.0%)
CYP2C8
    Faible 1 (0.7%)
    Non 150 (99.3%)
CYP2C9
    Modéré 1 (0.7%)
    Non 150 (99.3%)
CYP2C19
    Non 151 (100.0%)
CYP3A
    Faible 7 (4.6%)
    Modéré 10 (6.6%)
    Non 130 (86.1%)
    Oui 3 (2.0%)
    Puissant 1 (0.7%)
absorption
    Absoption HE 2 (1.3%)
    Absorption 17 (11.3%)
    Non 117 (77.5%)
    Oui 1 (0.7%)
    pH gastrique 14 (9.3%)
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 = 241
risque_interaction
    Diminution efficacité comédication 19 (79.2%)
    Majoration toxicité ou diminution efficacité comed 2 (8.3%)
    Potentialisation d'EI 3 (12.5%)
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 17
comedication_concernee
    Amiodarone 1 (4.2%)
    Bétaxolol 1 (4.2%)
    Calcium 1 (4.2%)
    CARBOLEVURE 1 (4.2%)
    Diosmectite 7 (29.2%)
    FERO-GRAD VITAMINE C 1 (4.2%)
    GAVISCON 7 (29.2%)
    Octreotide 2 (8.3%)
    Racécadotril 1 (4.2%)
    Siméticone 1 (4.2%)
    Zopiclone, bromazépam, hydroxyzine, alprazolam 1 (4.2%)
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 = 241
BCRP
    Non 24 (100.0%)
P-gp
    Non 24 (100.0%)
MATE1
    Non 24 (100.0%)
MRP2
    Non 24 (100.0%)
OAT3
    Non 24 (100.0%)
OATP1
    Non 24 (100.0%)
OATP1B1
    Non 24 (100.0%)
OATP1B3
    Non 24 (100.0%)
OTC2
    Non 24 (100.0%)
CYP2C8
    Non 24 (100.0%)
CYP2C9
    Non 24 (100.0%)
CYP2C19
    Non 24 (100.0%)
CYP3A
    Non 23 (95.8%)
    Oui 1 (4.2%)
absorption
    Absorption 17 (70.8%)
    Non 6 (25.0%)
    Oui 1 (4.2%)
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 = 2471
type_traitement
    Alimentation 11 (4.5%)
    Apithérapie 4 (1.6%)
    Aromathérapie 9 (3.6%)
    Aucun 88 (35.6%)
    Complément alimentaire 91 (36.8%)
    Dispositif médical 1 (0.4%)
    Elixir 1 (0.4%)
    Gemmothérapie 1 (0.4%)
    Homéopathie 37 (15.0%)
    Mycothérapie 2 (0.8%)
    Phytothérapie 2 (0.8%)
intervention_pharmacien
    Absence d'interaction 1 (0.9%)
    Contre-indiquée si porteur de PAC 1 (0.9%)
    Déconseillée 83 (72.2%)
    Déconseillée en gélule 1 (0.9%)
    Ok 24 (20.9%)
    Prise à 2h de distance 5 (4.3%)
    Unknown 132
nom
    100% FPP (extrait fermenté de papaye) de IMMUNE’AGE 1 (0.6%)
    ACEROLA C-max 1 (0.6%)
    Aceticum acidum 15CH 1 (0.6%)
    Ail de LA ROYALE 1 (0.6%)
    ALVITYL 1 (0.6%)
    ALVITYL Vitalité 1 (0.6%)
    ANACAPS 1 (0.6%)
    Apis 15CH 1 (0.6%)
    Apis mellifica 8DH, Aurum muriaticum natronatum 7DH, Avena Sativa 4DH, Hypericum Perforatum 4DH, Ignatia amara 5DH, Phosphoricum acidum 5DH 1 (0.6%)
    Aragonite D1 50%, calcarea carb D4 25%, quercus D3 1 (0.6%)
    Argile par voie orale 2 (1.3%)
    Armoise 1 (0.6%)
    Artémisia Annua de HERBAL D-TOX 1 (0.6%)
    ARTERIA 1 (0.6%)
    Ashwagandha 1 (0.6%)
    BERBERIS RADIX D3, CARDUS MARIANUS D2, CHELIDONIUM RADIX D3, COLCHICUM D2, CURCUMA D2, SULFUR D8, TARAXACUM STANNO CULTUM D3 1 (0.6%)
    BERROCA 2 (1.3%)
    BIBHITAKI FRUIT 1 (0.6%)
    BION Vitalité 1 (0.6%)
    BIOTIC P7 1 (0.6%)
    BIOTICS 3B-G (vitamine B) 1 (0.6%)
    Bovista gigantea 5CH 1 (0.6%)
    BROMELAINE 1 (0.6%)
    Charbon végétal activé 1 (0.6%)
    Chelidonium D1, Curcuma D1, Taraxacum stanno cultum D3 1 (0.6%)
    China 9CH 1 (0.6%)
    Chlorella + Spiruline de Biotona 1 (0.6%)
    Chlorure de magnésium et vitamine B6 2 (1.3%)
    CHRYSANTELLUM 1 (0.6%)
    Compléments alimentaires 1 (0.6%)
    CORIOLUS VERSICOLOR EXTRAKT 1 (0.6%)
    Corrosol 1 (0.6%)
    Cuprum metallicum 9CH 1 (0.6%)
    Curcuma + poivre noir de LA ROYALE 1 (0.6%)
    D-Mulsion FORTE (vitamine D) de BIOTICS RESEARCH 1 (0.6%)
    D3 PROTECT (vitamine D3)  1 (0.6%)
    Desmodium 2 (1.3%)
    Dilution 5, 7 et 9CH 1 (0.6%)
    Epices, thés, infusions, graines… 1 (0.6%)
    EPS desmodium 1 (0.6%)
    EPS rhodiole et mélisse 1 (0.6%)
    ERGY D (Vit D) 2 (1.3%)
    ERGYMAG (Mg + zn) 1 (0.6%)
    ERGYMAG (Mg + Zn) 1 (0.6%)
    ERGYSIL (ortie, silicium, sélénium) 1 (0.6%)
    Ferments lactiques des laboratoire Dieti Natura 1 (0.6%)
    Ferrum metallicum 7 CH  1 (0.6%)
    Ferrum sid D10, Phosphorus D8, Silicea D12 W788 60cc dilution 1 (0.6%)
    Fleurs de Bach 1 (0.6%)
    FLEXOFYTOL (curcuma) 1 (0.6%)
    Floracare XL (bifidobactéries et des lactobacilles) de BIOTICS RESEARCH 1 (0.6%)
    Gelée royale 1 (0.6%)
    Glutathion 1 (0.6%)
    Glutathion Liposomé + de HOD 1 (0.6%)
    Graine de plantain 1 (0.6%)
    HAIR VOLUME 1 (0.6%)
    Huile essentielle de ravintsara 1 (0.6%)
    Huile essentielle de Romarin à verbénone 1 (0.6%)
    Huile essentielle de Tea tree 1 (0.6%)
    Huile essentielle de thym 1 (0.6%)
    Huile végétale de millepertuis 2 (1.3%)
    Huile végétale de rose musquée 1 (0.6%)
    Huille essentielle d'helichryse 1 (0.6%)
    Huille essentielle de lavandin 1 (0.6%)
    IMMUN ACTIFS 1 (0.6%)
    Imussentiel fort 1 (0.6%)
    Influenzinum 15CH 1 (0.6%)
    INTENZYME FORTE 1 (0.6%)
    KIDNEY CLEANSE 1 (0.6%)
    KLARELINE 1 (0.6%)
    Lachesis 9CH, phosphorus 9CH, nux vomica 9CH 1 (0.6%)
    LACTIBIANE REFERENCE 1 (0.6%)
    LENODIAR  1 (0.6%)
    Levure de riz rouge, oméga 3 et CoQ10 1 (0.6%)
    Lithothamne de LA ROYALE 1 (0.6%)
    Lycopodium clavatum 15CH 1 (0.6%)
    Lycopodium clavatum D10 1 (0.6%)
    Macérat de gui de LA ROYALE 1 (0.6%)
    MAGN ACTIFS 2 (1.3%)
    Maitake 1 (0.6%)
    Medulo D8 1 (0.6%)
    Mélisse en gélules ou tisanes 1 (0.6%)
    MENO ACTIFS 1 (0.6%)
    Miel, propolis 1 (0.6%)
    Natrum muriaticum 15 CH 1 (0.6%)
    Natrum sulfuricum 15CH 1 (0.6%)
    Nux vomica 9CH 1 (0.6%)
    Oméga 3 1 (0.6%)
    OMEGA 3 de Solgar 1 (0.6%)
    OMEGABIANE DHA 1 (0.6%)
    OPTIFLOR 1 (0.6%)
    Phosphorus 30CH 1 (0.6%)
    Physiomance D-nat 1 (0.6%)
    Physiomance magnesium b6+ 1 (0.6%)
    Physiomance sélénium+ 1 (0.6%)
    Physiomance zinc 1 (0.6%)
    Physiomance Ubiquinol 3 1 (0.6%)
    Plumbum mellitum D12 30g Trit 1 (0.6%)
    Pollen de fleurs 1 (0.6%)
    Pollen en pelotes Bio Miel Besacier 1 (0.6%)
    PROCARTIL (glucosamine, chondrotoïne, manganèse, cuivre) 1 (0.6%)
    PROPOMAX (propolis verte et brune bio, bioflavonoides et artepilline c) 1 (0.6%)
    Prostate 8DH 2 (1.3%)
    Psyllium 1 (0.6%)
    RENFORSTIM 1 (0.6%)
    Ribes nigrum 1DH 1 (0.6%)
    Ruscus aculeatus 4DH 1 (0.6%)
    Selenium ACE Optimum 50+ 1 (0.6%)
    SEREMAG (magnésium, taurine et vitamine B6) 1 (0.6%)
    Serum de Yersin 9 CH 1 (0.6%)
    Sève de bouleau 1DH 1 (0.6%)
    STRESS’O (rhadiola, choline, lavande vrai) de PHYSIOSENS 1 (0.6%)
    Sulfate de magnésium 1 (0.6%)
    Sulfurum 7CH 1 (0.6%)
    Teinture mère de Calendula 2 (1.3%)
    Teinture mère de Dionaea Muscipula 1 (0.6%)
    Teinture mère GINKGO BILOBA 1 (0.6%)
    TEMPORAL (Levure de riz rouge, policaosanol, CoQ10) 1 (0.6%)
    Teoliance hpi 60 1 (0.6%)
    Thé au citron ou orange-canelle 1 (0.6%)
    Thé noir 1 (0.6%)
    Thymuline 4CH 1 (0.6%)
    THYROSTIM (L-thyroxine, vit C, vit D, zinc…) de Copmed 1 (0.6%)
    Tisane 1 (0.6%)
    Tisane d’olivier et d’hibiscus 1 (0.6%)
    Tisane de thym et sauge 2 (1.3%)
    Tisane verveine 1 (0.6%)
    Tuberculinum 15CH 1 (0.6%)
    UNIBIANE HCA (garcinia) 1 (0.6%)
    UNIBIANE R-α lipoïque 1 (0.6%)
    Vitamine B12 1 (0.6%)
    Vitamine C 2 (1.3%)
    VITAMINE C 1000 mg 1 (0.6%)
    Vitamine C liposomale de Biocyte  1 (0.6%)
    Vitamine C liposomale de LA ROYALE 1 (0.6%)
    Vitamine D 1 (0.6%)
    VITAMINE D3 1 (0.6%)
    Vitamine d3 + k2 de Sunday Naturel 1 (0.6%)
    VITAMINE D3 2000UI 1 (0.6%)
    VITAMINE D3 800UI de Sante verte 1 (0.6%)
    Vitamine K2 1 (0.6%)
    VITAMINE K2 1 (0.6%)
    Weleda c692 1 (0.6%)
    Weleda c720 1 (0.6%)
    Zinc 3 (1.9%)
    Zinc (amino chelate) 1 (0.6%)
    Unknown 88
1 n (%)