Group comparison by treatment group
compareGroups::createTable(compareGroups(Group~., data=SG_raw, subset=!Group=="HC"))
##
## --------Summary descriptives table by 'Group'---------
##
## ___________________________________________________
## PBO_ESC CBX_ESC p.overall
## N=25 N=30
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## Sex: 0.739
## 1 8 (32.0%) 12 (40.0%)
## 2 17 (68.0%) 18 (60.0%)
## BMI 32.2 (5.80) 31.2 (7.13) 0.595
## Age 46.6 (12.5) 39.4 (11.4) 0.033
## PLT_BL 246 (75.9) 225 (48.8) 0.250
## MONO_BL 0.52 (0.23) 0.49 (0.16) 0.581
## NEUT_BL 4.15 (1.50) 3.82 (1.34) 0.418
## LYMPH_BL 1.96 (0.63) 2.02 (0.61) 0.732
## PLT_WK8 222 (64.5) 224 (46.3) 0.891
## MONO_WK8 0.52 (0.23) 0.48 (0.19) 0.472
## NEUT_WK8 4.31 (2.17) 3.84 (1.60) 0.394
## LYMPH_WK8 1.98 (0.67) 2.09 (0.81) 0.595
## HAMD21_BL 23.4 (6.24) 25.0 (6.08) 0.411
## HAMA_BL 21.9 (7.72) 21.9 (7.40) 0.996
## HAMD21_WK8 15.0 (7.41) 9.19 (6.33) 0.007
## HAMA_WK8 13.8 (8.03) 10.1 (6.78) 0.098
## SII_BL 541 (257) 457 (222) 0.234
## SII_WK8 497 (263) 440 (189) 0.391
## Remission: 0.004
## Non-remitter 19 (95.0%) 14 (51.9%)
## Remitter 1 (5.00%) 13 (48.1%)
## Response: 0.040
## Non-responder 12 (60.0%) 7 (25.9%)
## Responder 8 (40.0%) 20 (74.1%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Group comparison by tx response
createTable(compareGroups(Response~., data=SG_raw, subset=!Group=="HC"))
##
## --------Summary descriptives table by 'Response'---------
##
## ____________________________________________________
## Non-responder Responder p.overall
## N=19 N=28
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## Group: 0.040
## PBO_ESC 12 (63.2%) 8 (28.6%)
## CBX_ESC 7 (36.8%) 20 (71.4%)
## Sex: 0.271
## 1 10 (52.6%) 9 (32.1%)
## 2 9 (47.4%) 19 (67.9%)
## BMI 32.2 (6.81) 31.6 (6.84) 0.751
## Age 45.9 (12.4) 39.9 (11.8) 0.101
## PLT_BL 227 (69.9) 232 (48.9) 0.791
## MONO_BL 0.56 (0.21) 0.47 (0.16) 0.125
## NEUT_BL 4.04 (1.17) 3.88 (1.49) 0.707
## LYMPH_BL 1.98 (0.63) 1.99 (0.65) 0.952
## PLT_WK8 202 (63.9) 232 (49.6) 0.105
## MONO_WK8 0.58 (0.24) 0.47 (0.18) 0.131
## NEUT_WK8 4.74 (2.34) 3.73 (1.37) 0.130
## LYMPH_WK8 2.06 (0.72) 1.99 (0.77) 0.754
## HAMD21_BL 22.5 (5.65) 25.6 (6.21) 0.084
## HAMA_BL 20.6 (7.31) 22.8 (7.68) 0.331
## HAMD21_WK8 18.3 (6.31) 7.18 (3.67) <0.001
## HAMA_WK8 16.6 (7.62) 8.34 (5.36) <0.001
## SII_BL 486 (236) 482 (232) 0.950
## SII_WK8 482 (258) 467 (201) 0.847
## Remission: 0.001
## Non-remitter 19 (100%) 14 (50.0%)
## Remitter 0 (0.00%) 14 (50.0%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Group comparison by tx remission
createTable(compareGroups(Remission~., data=SG_raw, subset=!Group=="HC"))
##
## --------Summary descriptives table by 'Remission'---------
##
## ____________________________________________________
## Non-remitter Remitter p.overall
## N=33 N=14
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## Group: 0.004
## PBO_ESC 19 (57.6%) 1 (7.14%)
## CBX_ESC 14 (42.4%) 13 (92.9%)
## Sex: 0.451
## 1 15 (45.5%) 4 (28.6%)
## 2 18 (54.5%) 10 (71.4%)
## BMI 32.5 (5.97) 30.3 (8.37) 0.370
## Age 42.9 (12.8) 41.0 (11.4) 0.623
## PLT_BL 228 (61.1) 235 (49.3) 0.688
## MONO_BL 0.51 (0.19) 0.50 (0.19) 0.881
## NEUT_BL 3.93 (1.23) 3.97 (1.71) 0.950
## LYMPH_BL 1.99 (0.65) 1.96 (0.60) 0.868
## PLT_WK8 217 (60.4) 230 (48.1) 0.430
## MONO_WK8 0.53 (0.22) 0.45 (0.18) 0.194
## NEUT_WK8 4.35 (2.05) 3.56 (1.07) 0.102
## LYMPH_WK8 2.10 (0.79) 1.83 (0.64) 0.228
## HAMD21_BL 25.3 (6.49) 22.1 (4.62) 0.064
## HAMA_BL 23.0 (7.77) 19.2 (6.40) 0.089
## HAMD21_WK8 14.8 (6.35) 4.21 (2.46) <0.001
## HAMA_WK8 14.1 (7.06) 5.89 (4.99) <0.001
## SII_BL 470 (214) 518 (277) 0.596
## SII_WK8 459 (216) 502 (235) 0.565
## Response: 0.001
## Non-responder 19 (57.6%) 0 (0.00%)
## Responder 14 (42.4%) 14 (100%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Univariate correlations
list_vars<-SG_raw %>% dplyr::select(-Sex, -Remission, -Response) %>% names()
heatmap_df<-SG_raw %>% dplyr::select(all_of(list_vars))
heatmap_df_pts<-heatmap_df %>% filter(!heatmap_df$Group=="HC") %>% select(-Group)
heatmap_df_pts<- as.data.frame(mutate_all(heatmap_df_pts, function(x) as.numeric(as.character(x))))
dim(heatmap_df_pts)
## [1] 57 16
# heatmap_df_remitter<-heatmap_df %>% filter(!heatmap_df$Group=="HC") %>% filter(HAMD21_WK8<=7) %>% select(-Group)
# heatmap_df_nonremitter<-heatmap_df %>% filter(!heatmap_df$Group=="HC") %>% filter(HAMD21_WK8>7) %>% select(-Group)
corr <- round(cor(heatmap_df_pts, use="complete.obs"), 2)
ggcorrplot(corr, hc.order = FALSE, type = "lower",
lab = TRUE, lab_size=2, insig="blank", tl.cex=10, title = "Pearson Correlation Matrix (TRBDD cohort)")
Modelling HAMD21_WK8 by SII_BL
SII_model<-lm(HAMD21_WK8~Sex+Age+BMI+Group+HAMD21_BL+SII_BL, data=SG_raw)
sjPlot::tab_model(SII_model)
|
|
HAMD 21 WK 8
|
|
Predictors
|
Estimates
|
CI
|
p
|
|
(Intercept)
|
1.80
|
-14.77 – 18.37
|
0.827
|
|
Sex [2]
|
-4.64
|
-9.16 – -0.11
|
0.045
|
|
Age
|
0.11
|
-0.07 – 0.29
|
0.235
|
|
BMI
|
0.09
|
-0.26 – 0.43
|
0.613
|
|
Group [CBX ESC]
|
-5.76
|
-10.40 – -1.11
|
0.017
|
|
HAMD21 BL
|
0.30
|
-0.05 – 0.65
|
0.092
|
|
SII BL
|
0.00
|
-0.01 – 0.01
|
0.549
|
|
Observations
|
43
|
|
R2 / R2 adjusted
|
0.327 / 0.215
|
SII_model<-lm(HAMD21_WK8~Group+HAMD21_BL+SII_BL, data=SG_raw)
sjPlot::tab_model(SII_model)
|
|
HAMD 21 WK 8
|
|
Predictors
|
Estimates
|
CI
|
p
|
|
(Intercept)
|
9.78
|
-1.17 – 20.73
|
0.079
|
|
Group [CBX ESC]
|
-6.71
|
-11.18 – -2.25
|
0.004
|
|
HAMD21 BL
|
0.27
|
-0.08 – 0.62
|
0.132
|
|
SII BL
|
-0.00
|
-0.01 – 0.01
|
0.807
|
|
Observations
|
43
|
|
R2 / R2 adjusted
|
0.219 / 0.159
|
Modelling HAMD21_WK8 by SII_BL*Age
SII_model<-lm(HAMD21_WK8~Group+HAMD21_BL+SII_BL*Age, data=SG_raw)
# plot(SII_model, which=c(2,6))
sjPlot::tab_model(SII_model)
|
|
HAMD 21 WK 8
|
|
Predictors
|
Estimates
|
CI
|
p
|
|
(Intercept)
|
28.20
|
9.10 – 47.31
|
0.005
|
|
Group [CBX ESC]
|
-5.05
|
-9.33 – -0.77
|
0.022
|
|
HAMD21 BL
|
0.06
|
-0.27 – 0.40
|
0.696
|
|
SII BL
|
-0.04
|
-0.07 – -0.01
|
0.004
|
|
Age
|
-0.35
|
-0.68 – -0.02
|
0.036
|
|
SII BL * Age
|
0.00
|
0.00 – 0.00
|
0.002
|
|
Observations
|
43
|
|
R2 / R2 adjusted
|
0.415 / 0.336
|
interactions::interact_plot(SII_model, pred = SII_BL, modx = Age, jitter=0.1, plot.points = TRUE, main.title = "The effect of SII (baseline) on post-tx depression depends on age")
Take home message: low depressive severity (post-treatment) is predicted by PBO arm, and lower SII (baseline) amongst pts with higher age
Modelling HAMD21_WK8 by cell-count/age interaction
test<-lm(HAMD21_WK8~ BMI + NEUT_BL*Age + PLT_BL + LYMPH_BL , data=SG_raw)
sjPlot::tab_model(test)
|
|
HAMD 21 WK 8
|
|
Predictors
|
Estimates
|
CI
|
p
|
|
(Intercept)
|
27.19
|
3.34 – 51.05
|
0.027
|
|
BMI
|
0.24
|
-0.10 – 0.58
|
0.159
|
|
NEUT BL
|
-7.16
|
-11.77 – -2.56
|
0.003
|
|
Age
|
-0.65
|
-1.14 – -0.16
|
0.011
|
|
PLT BL
|
-0.01
|
-0.05 – 0.02
|
0.510
|
|
LYMPH BL
|
0.85
|
-2.47 – 4.18
|
0.605
|
|
NEUT BL * Age
|
0.21
|
0.10 – 0.32
|
0.001
|
|
Observations
|
43
|
|
R2 / R2 adjusted
|
0.376 / 0.272
|