##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
data_camille <- read_excel("Y:/fp/projets études/infection a clostridium/20230312/data_camille.xlsx")
## New names:
## • `` -> `...53`
##recodage bases de données le cas échéant----
clostri<-filter(data_camille, c(eligibilite=="Oui" ))
##recodage bases de données le cas échéant----
clostri$gravite<-ifelse(clostri$score_gravite>=1, 1, 0)
clostri$complique<-ifelse(clostri$score_complication>=1, 1, 0)
clostri$r_recidive<-ifelse(clostri$score_risque_recidive>2, 1, 0)
##renommer des variables pour présentation dans les tableaux de résultats
library(labelled)
var_label(clostri$score_gravite) <- "Score de Gravité"
var_label(clostri$score_complication) <- "Score de Complication"
var_label(clostri$score_risque_recidive) <- "Score de risque de recidive"
var_label(clostri$icd_hospit) <- "Infection en cours d'hospitalisation"
var_label(clostri$premiere_icd) <- "Premiere infection"
var_label(clostri$delai_icd_hospit) <- "delai entre entrée service et infection"
##réation de variables à plusieurs catégorie selon valeurs variable continue
##tableau descriptif population globales ----
tbl_summary(
clostri, include = c("age", "sexe", "pathologie","icd_hospit","premiere_icd", "score_gravite", "score_complication", "score_risque_recidive", "traitement"),
digits=all_categorical()~ c(0,1)
)
| Characteristic |
N = 46 |
| age |
68 (56, 71) |
| sexe |
|
| F |
24 (52.2%) |
| M |
22 (47.8%) |
| pathologie |
|
| Hématologie |
29 (63.0%) |
| Oncologie |
17 (37.0%) |
| Infection en cours d'hospitalisation |
|
| Non |
10 (21.7%) |
| Oui |
36 (78.3%) |
| Premiere infection |
|
| Non |
4 (8.7%) |
| Oui |
42 (91.3%) |
| Score de Gravité |
|
| 0 |
23 (50.0%) |
| 1 |
17 (37.0%) |
| 2 |
5 (10.9%) |
| 3 |
1 (2.2%) |
| Score de Complication |
|
| 0 |
20 (43.5%) |
| 1 |
18 (39.1%) |
| 2 |
3 (6.5%) |
| 3 |
4 (8.7%) |
| 4 |
1 (2.2%) |
| Score de risque de recidive |
|
| 1 |
9 (19.6%) |
| 2 |
16 (34.8%) |
| 3 |
16 (34.8%) |
| 4 |
4 (8.7%) |
| 5 |
1 (2.2%) |
| traitement |
|
| Fidaxomicine |
10 (21.7%) |
| Métronidazole IV + Vancomycine lavement intra-rectal |
1 (2.2%) |
| Métronidazole PO |
3 (6.5%) |
| Vancomycine PO |
31 (67.4%) |
| Vancomycine PO + Métronidazole IV |
1 (2.2%) |
##Delai de déclaration de l'infection à clostridiume lorsque infection en cours de séjour---
clostri_sejour<-filter(clostri, c(icd_hospit=="Oui" ))
tbl_summary(
clostri_sejour, include = c("delai_icd_hospit"),
digits=all_categorical()~ c(0,1)
)
| Characteristic |
N = 36 |
| delai entre entrée service et infection |
9 (1, 17) |
## taux de guerison
tbl_summary(
clostri, include = c("taux_guerison"),
digits=all_categorical()~ c(0,1)
)
| Characteristic |
N = 46 |
| taux_guerison |
38 (82.6%) |
##tableau descriptif population selon critère de catégorie ----
tbl_summary(
clostri, include = c("taux_guerison"),
by="traitement",
digits=all_categorical()~ c(0,1)
)%>%
add_p()
| Characteristic |
Fidaxomicine, N = 10 |
Métronidazole IV + Vancomycine lavement intra-rectal, N = 1 |
Métronidazole PO, N = 3 |
Vancomycine PO, N = 31 |
Vancomycine PO + Métronidazole IV, N = 1 |
p-value |
| taux_guerison |
8 (80.0%) |
1 (100.0%) |
2 (66.7%) |
26 (83.9%) |
1 (100.0%) |
0.8 |
##taux de guerison selon rechute ou primo
tbl_summary(
clostri, include = c("taux_guerison"),
by="premiere_icd",
digits=all_categorical()~ c(0,1)
)%>%
add_p()
| Characteristic |
Non, N = 4 |
Oui, N = 42 |
p-value |
| taux_guerison |
4 (100.0%) |
34 (81.0%) |
>0.9 |
##taux de guérison selon score de gravité
tbl_summary(
clostri, include = c("taux_guerison"),
by="score_gravite",
digits=all_categorical()~ c(0,1)
)%>%
add_p()
| Characteristic |
0, N = 23 |
1, N = 17 |
2, N = 5 |
3, N = 1 |
p-value |
| taux_guerison |
21 (91.3%) |
13 (76.5%) |
3 (60.0%) |
1 (100.0%) |
0.3 |
##taux de guérison selon score de gravité_binaire
tbl_summary(
clostri, include = c("taux_guerison"),
by="gravite",
digits=all_categorical()~ c(0,1)
)%>%
add_p()
| Characteristic |
0, N = 23 |
1, N = 23 |
p-value |
| taux_guerison |
21 (91.3%) |
17 (73.9%) |
0.2 |
##taux de guérison selon score de risque de complication
tbl_summary(
clostri, include = c("taux_guerison"),
by="score_complication",
digits=all_categorical()~ c(0,1)
)%>%
add_p()
| Characteristic |
0, N = 20 |
1, N = 18 |
2, N = 3 |
3, N = 4 |
4, N = 1 |
p-value |
| taux_guerison |
17 (85.0%) |
15 (83.3%) |
3 (100.0%) |
3 (75.0%) |
0 (0.0%) |
0.4 |
##taux de guérison selon score de risque de complication_binaire
tbl_summary(
clostri, include = c("taux_guerison"),
by="complique",
digits=all_categorical()~ c(0,1)
)%>%
add_p()
| Characteristic |
0, N = 20 |
1, N = 26 |
p-value |
| taux_guerison |
17 (85.0%) |
21 (80.8%) |
>0.9 |
##taux de guérison selon score de risque de recidive
tbl_summary(
clostri, include = c("taux_guerison"),
by="score_risque_recidive",
digits=all_categorical()~ c(0,1)
)%>%
add_p()
| Characteristic |
1, N = 9 |
2, N = 16 |
3, N = 16 |
4, N = 4 |
5, N = 1 |
p-value |
| taux_guerison |
8 (88.9%) |
12 (75.0%) |
13 (81.2%) |
4 (100.0%) |
1 (100.0%) |
0.8 |
##taux de guérison selon score de risque de recidive_binaire
tbl_summary(
clostri, include = c("taux_guerison"),
by="r_recidive",
digits=all_categorical()~ c(0,1)
)%>%
add_p()
| Characteristic |
0, N = 25 |
1, N = 21 |
p-value |
| taux_guerison |
20 (80.0%) |
18 (85.7%) |
0.7 |
#Courbe de Kaplan Meier survie sans recidive----
km_pfr<-survfit(Surv(clostri$pfr, clostri$evtpfr)~1)
ggsurvplot(km_pfr, data = clostri,
risk.table=TRUE,
surv.scale="percent",
break.time.by=3,
surv.median.line = "hv"
)
## Warning in .add_surv_median(p, fit, type = surv.median.line, fun = fun, :
## Median survival not reached.
#Courbe de Kaplan Meier survie globale----
km_os<-survfit(Surv(clostri$os, clostri$evtos)~1)
ggsurvplot(km_os, data = clostri,
risk.table=TRUE,
surv.scale="percent",
break.time.by=3,
surv.median.line = "hv"
)
## Warning in .add_surv_median(p, fit, type = surv.median.line, fun = fun, :
## Median survival not reached.
#Courbe de Kaplan Meier de survie sans récidive selon populations selon score de gravité >1----
km_pfr_gravite<-survfit(Surv(pfr, evtpfr)~gravite, data=clostri)
ggsurvplot(km_pfr_gravite, data = clostri,
risk.table=TRUE,
surv.scale="percent",
break.time.by=3,
surv.median.line = "hv"
)
## Warning in .add_surv_median(p, fit, type = surv.median.line, fun = fun, :
## Median survival not reached.
#Courbe de Kaplan Meier de survie sans récidive selon populations selon guerison clinique à J10----
km_pfr_guerison<-survfit(Surv(pfr, evtpfr)~taux_guerison, data=clostri)
ggsurvplot(km_pfr_guerison, data = clostri,
risk.table=TRUE,
surv.scale="percent",
break.time.by=3,
surv.median.line = "hv"
)
