prostate %>%
mutate(aa = factor(aa, levels = c(0,1),
labels = c("White", "African-American"))) %>%
mutate(fam_hx = factor(fam_hx, levels = c(0,1),
labels = c("No Family History", "FHx of Prostate Cancer"))) ->
prostate_factors
prostate %>%
select(age, p_vol, preop_psa, aa, fam_hx) %>%
group_by(aa, fam_hx) %>%
summarize(across(age:preop_psa, ~ mean(.x, na.rm = TRUE)))
## `summarise()` has regrouped the output.
## ℹ Summaries were computed grouped by aa and fam_hx.
## ℹ Output is grouped by aa.
## ℹ Use `summarise(.groups = "drop_last")` to silence this message.
## ℹ Use `summarise(.by = c(aa, fam_hx))` for per-operation grouping
## (`?dplyr::dplyr_by`) instead.
## # A tibble: 4 × 5
## # Groups: aa [2]
## aa fam_hx age p_vol preop_psa
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0 0 61.8 56.9 8.06
## 2 0 1 59.5 57.3 7.22
## 3 1 0 60.7 54.3 9.90
## 4 1 1 60.1 51.4 8.71
Mean preoperative PSA levels were highest among African-American patients without a family history of prostate cancer (9.90 ng/mL), followed by African-American patients with a positive family history (8.70 ng/mL). White patients demonstrated lower mean preoperative PSA levels, both in those without a family history (8.05 ng/mL) and those with a positive family history (7.22 ng/mL).
ggplot(prostate_factors) +
aes(x = p_vol, y = preop_psa, col = aa) +
geom_point() +
geom_smooth(method = "lm") +
facet_grid(aa ~ fam_hx) +
labs(x = 'Prostate Volume', y = "Preoperative PSA",
title = 'Relationship Between Prostate Volume and Preop PSA,\nSubdivided by Family History and Race') +
theme(legend.position = "bottom")
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 11 rows containing non-finite outside the scale range
## (`stat_smooth()`).
## Warning: Removed 11 rows containing missing values or values outside the scale range
## (`geom_point()`).
On visual inspection, across both racial groups, patients without a family history of prostate cancer exhibited higher preoperative PSA levels and greater prostate volume compared to those with a positive family history. However, formal statistical testing would be required to confirm this observation.
prostate %>%
summarise(
mean_age = mean(age, na.rm = TRUE),
min_age = min(age, na.rm = TRUE),
max_age = max(age, na.rm = TRUE),
sd_age = sd(age, na.rm = TRUE)
)
## mean_age min_age max_age sd_age
## 1 61.15728 38.4 79 7.240269
The study cohort had a mean age of 61 years (SD: X, range: 38–79 years).
The majority of patients in this cohort had no family history of prostate cancer. A smaller proportion reported a positive family history, which appeared associated with lower preoperative PSA levels across both racial groups.
Prior to formal statistical testing, descriptive analysis suggested that patients without a family history of prostate cancer demonstrated higher preoperative PSA levels and greater prostate volume compared to those with a positive family history, regardless of racial background. An independent samples t-test was subsequently conducted to assess the statistical significance of PSA differences between racial groups.
prostate_factors %>%
t_test(formula = preop_psa ~ aa,
detailed = TRUE)
## # A tibble: 1 × 15
## estimate estimate1 estimate2 .y. group1 group2 n1 n2 statistic p
## * <dbl> <dbl> <dbl> <chr> <chr> <chr> <int> <int> <dbl> <dbl>
## 1 -1.89 7.86 9.75 preop… White Afric… 259 54 -1.96 0.0534
## # ℹ 5 more variables: df <dbl>, conf.low <dbl>, conf.high <dbl>, method <chr>,
## # alternative <chr>
An independent samples t-test was conducted to compare preoperative PSA levels between African-American and White patients. Preoperative PSA levels were higher in African-American patients (mean = 9.74 ng/mL) compared to White patients (mean = 7.86 ng/mL), with a mean difference of 1.88 ng/mL (95% CI: -0.03 to 3.81, p = 0.053). This difference did not reach statistical significance, though the trend towards higher PSA levels in African-American patients is consistent with existing literature and may warrant further investigation in a larger cohort.