RECIST 1.1 scoring at first follow-up scan does not stratify overall survival in the PACTO trial
Last updated: 2025-03-27
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RECIST 1.1 scoring at first follow-up scan does not stratify overall survival in the PACTO trial. Overall survival probability is shown for each of the response categories for RECIST 1.1 score at the first follow-up at 8-weeks on the left, and for best overall response by RECIST 1.1 on the right.
library(ggpubr)
library(here)
library(readxl)
library(survival)
library(survminer)
library(tidyverse)clean_data <- read_excel(here("data/supplementary_tables.xlsx"),
sheet = "Table S4", range = "A2:S42")
delfi_pred <- read_excel(here("data/supplementary_tables.xlsx"),
sheet = "Table S5", range = "A2:N207")clean_data <- clean_data %>%
filter(`RECIST at FU 1` != "Not Evaluable")
delfi_pred <- delfi_pred %>%
filter(Timepoint == "Endpoint")
DELFI_complete <- delfi_pred %>%
inner_join(clean_data, by = "Patient") %>%
mutate(across("Deceased", str_replace, "Yes", "1"),
across("Deceased", str_replace, "No", "0")) %>%
mutate(`OS (days)` = as.numeric(`OS (days)`),
`PFS (days)` = as.numeric(`PFS (days)`),
`Deceased` = as.numeric(Deceased),
`FU1` = as.character(`RECIST at FU 1`),
`BOR` = as.character(`BOR RECIST 1.1`))Warning: There was 1 warning in `mutate()`.
ℹ In argument: `across("Deceased", str_replace, "Yes", "1")`.
Caused by warning:
! The `...` argument of `across()` is deprecated as of dplyr 1.1.0.
Supply arguments directly to `.fns` through an anonymous function instead.
# Previously
across(a:b, mean, na.rm = TRUE)
# Now
across(a:b, \(x) mean(x, na.rm = TRUE))p <- vector("list", 2)
fit <- survfit(Surv(`OS (days)`, Deceased) ~ FU1, data = DELFI_complete)
p[[1]] <- fit %>%
ggsurvplot(pval = TRUE, risk.table = TRUE, risk.table.col = "strata",
surv.median.line = "hv",
#title = "Overall survival based on RECIST Follow up",
ylab = "Overall survival probability",
xlab = "Time in Days",
ggtheme = theme_classic2(base_size = 11),
legend = c(.9, .75),
legend.title = element_blank(),
legend.labs = c("PR", "PD", "SD"),
pval.size = 3, pval.coord = c(400, .25))Warning in geom_segment(aes(x = 0, y = max(y2), xend = max(x1), yend = max(y2)), : All aesthetics have length 1, but the data has 3 rows.
ℹ Please consider using `annotate()` or provide this layer with data containing
a single row.p[[1]]$plot <- p[[1]]$plot +
annotate("text", x = 800, y = 0.95,
label = "RECIST 1.1 assessment\n(8 weeks)",
size = 3, hjust = 0)
fit <- survfit(Surv(`OS (days)`, Deceased) ~ BOR, data = DELFI_complete)
p[[2]] <- fit %>%
ggsurvplot(pval = TRUE, risk.table = TRUE, risk.table.col = "strata",
surv.median.line = "hv",
#title = "Overall survival based on BOR",
xlab = "Time in Days",
ylab = "Overall survival probability",
ggtheme = theme_classic2(base_size = 11),
legend = c(.9, .75),
legend.title = element_blank(),
legend.labs = c("PR", "PD", "SD"),
pval.size = 3, pval.coord = c(750, .25))Warning in geom_segment(aes(x = 0, y = max(y2), xend = max(x1), yend = max(y2)), : All aesthetics have length 1, but the data has 3 rows.
ℹ Please consider using `annotate()` or provide this layer with data containing
a single row.p[[2]]$plot <- p[[2]]$plot +
annotate("text", x = 800, y = 0.95,
label = "Best overall response\nRECIST 1.1 assessment",
size = 3, hjust = 0)
arrange_ggsurvplots(p, nrow = 1)Warning in geom_segment(aes(x = 0, y = max(y2), xend = max(x1), yend = max(y2)), : All aesthetics have length 1, but the data has 3 rows.
ℹ Please consider using `annotate()` or provide this layer with data containing
a single row.Warning in geom_segment(aes(x = 0, y = max(y2), xend = max(x1), yend = max(y2)), : All aesthetics have length 1, but the data has 3 rows.
ℹ Please consider using `annotate()` or provide this layer with data containing
a single row.
All aesthetics have length 1, but the data has 3 rows.
ℹ Please consider using `annotate()` or provide this layer with data containing
a single row.
All aesthetics have length 1, but the data has 3 rows.
ℹ Please consider using `annotate()` or provide this layer with data containing
a single row.
All aesthetics have length 1, but the data has 3 rows.
ℹ Please consider using `annotate()` or provide this layer with data containing
a single row.
All aesthetics have length 1, but the data has 3 rows.
ℹ Please consider using `annotate()` or provide this layer with data containing
a single row.
coxFU1 <- coxph(Surv(`OS (days)`, Deceased) ~ FU1, data = DELFI_complete)
summary(coxFU1)Call:
coxph(formula = Surv(`OS (days)`, Deceased) ~ FU1, data = DELFI_complete)
n= 31, number of events= 31
coef exp(coef) se(coef) z Pr(>|z|)
FU1Progressive Disease 2.19189 8.95213 1.27898 1.714 0.0866 .
FU1Stable Disease -0.06534 0.93675 0.61883 -0.106 0.9159
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
exp(coef) exp(-coef) lower .95 upper .95
FU1Progressive Disease 8.9521 0.1117 0.7299 109.80
FU1Stable Disease 0.9367 1.0675 0.2785 3.15
Concordance= 0.531 (se = 0.041 )
Likelihood ratio test= 2.49 on 2 df, p=0.3
Wald test = 3.81 on 2 df, p=0.1
Score (logrank) test = 5.7 on 2 df, p=0.06coxBOR <- coxph(Surv(`OS (days)`, Deceased) ~ BOR, data = DELFI_complete)
summary(coxBOR)Call:
coxph(formula = Surv(`OS (days)`, Deceased) ~ BOR, data = DELFI_complete)
n= 31, number of events= 31
coef exp(coef) se(coef) z Pr(>|z|)
BORProgressive Disease 2.4553 11.6501 0.9455 2.597 0.00941 **
BORStable Disease 0.2208 1.2471 0.3831 0.576 0.56432
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
exp(coef) exp(-coef) lower .95 upper .95
BORProgressive Disease 11.650 0.08584 1.8259 74.332
BORStable Disease 1.247 0.80185 0.5886 2.642
Concordance= 0.623 (se = 0.051 )
Likelihood ratio test= 5.16 on 2 df, p=0.08
Wald test = 6.74 on 2 df, p=0.03
Score (logrank) test = 10.22 on 2 df, p=0.006
sessionInfo()R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS 15.3.1
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/New_York
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] lubridate_1.9.4 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4
[5] purrr_1.0.4 readr_2.1.5 tidyr_1.3.1 tibble_3.2.1
[9] tidyverse_2.0.0 survminer_0.5.0 survival_3.8-3 readxl_1.4.5
[13] here_1.0.1 ggpubr_0.6.0 ggplot2_3.5.1 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] tidyselect_1.2.1 farver_2.1.2 fastmap_1.2.0 promises_1.3.2
[5] digest_0.6.37 timechange_0.3.0 lifecycle_1.0.4 processx_3.8.6
[9] magrittr_2.0.3 compiler_4.4.1 rlang_1.1.5 sass_0.4.9
[13] tools_4.4.1 yaml_2.3.10 data.table_1.17.0 knitr_1.49
[17] ggsignif_0.6.4 labeling_0.4.3 xml2_1.3.7 abind_1.4-8
[21] withr_3.0.2 grid_4.4.1 git2r_0.35.0 xtable_1.8-4
[25] colorspace_2.1-1 scales_1.3.0 cli_3.6.4 rmarkdown_2.29
[29] generics_0.1.3 rstudioapi_0.17.1 km.ci_0.5-6 httr_1.4.7
[33] tzdb_0.4.0 commonmark_1.9.2 cachem_1.1.0 splines_4.4.1
[37] cellranger_1.1.0 survMisc_0.5.6 vctrs_0.6.5 Matrix_1.7-3
[41] jsonlite_1.9.1 carData_3.0-5 car_3.1-3 callr_3.7.6
[45] hms_1.1.3 rstatix_0.7.2 Formula_1.2-5 jquerylib_0.1.4
[49] rematch_2.0.0 glue_1.8.0 ps_1.9.0 ggtext_0.1.2
[53] stringi_1.8.4 gtable_0.3.6 later_1.4.1 munsell_0.5.1
[57] pillar_1.10.1 htmltools_0.5.8.1 R6_2.6.1 KMsurv_0.1-5
[61] rprojroot_2.0.4 evaluate_1.0.3 lattice_0.22-6 markdown_1.13
[65] backports_1.5.0 gridtext_0.1.5 broom_1.0.7 httpuv_1.6.15
[69] bslib_0.9.0 Rcpp_1.0.14 gridExtra_2.3 whisker_0.4.1
[73] xfun_0.51 fs_1.6.5 zoo_1.8-13 getPass_0.2-4
[77] pkgconfig_2.0.3