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ADNI-Enrollment

Last Updated: July 25, 2025

Source: vignettes/ADNI-Enrollment.Rmd
ADNI-Enrollment.Rmd

Introduction

This article demonstrate how to use the ADNIMERGE2 R package to generate simple enrollment summaries.

Load Required R Packages 

# Abbreviation list
abbrev_list <- paste0(
  paste0(
    "CN: Cognitive Normal; MCI: Mild Cognitive Impairment; DEM: Dementia; "
  ),
  paste0(
    "SD: Standard Deviation; Q1: the 25th percentile; Q3: the 75th percentile"
  )
)
conts_statistic_label <- c("Mean (SD)", "Median (Q1, Q3)", "Range")
# Adjust BMI variable labels
var_label(ADSL$BMI) <- paste0("Baseline ", get_variable_labels(ADSL)$BMI)

ADNI Enrollment Summaries

Enrollment Overtime 

enroll_summary_data <- ADSL %>%
  filter(ENRLFL %in% "Y") %>%
  mutate(ENRLDT = floor_date(ENRLDT, unit = "month")) %>%
  group_by(ENRLDT, ORIGPROT) %>%
  summarise(num_enroll = n()) %>%
  ungroup() %>%
  mutate(ORIGPROT = factor(ORIGPROT, levels = adni_phase())) %>%
  arrange(ENRLDT, ORIGPROT) %>%
  mutate(cum_num_enroll = cumsum(num_enroll))

enroll_summary_plot <- enroll_summary_data %>%
  ggplot(aes(x = ENRLDT, y = cum_num_enroll, color = ORIGPROT)) +
  geom_line() +
  scale_x_date(
    date_minor_breaks = "2 years",
    limits = range(enroll_summary_data$ENRLDT)
  ) +
  labs(
    x = "Timeline Calendar",
    y = "Cumulative Enrollment Per Month",
    color = "ADNI Study Phase"
  ) +
  theme(axis.text.x = element_text(hjust = 0.3, vjust = 0, angle = 15))
enroll_summary_plot

Enrollment overtime by study phase

Demographic Summaries: By Study Phase 

tbl_summary(
  data = ADSL %>%
    filter(ENRLFL %in% "Y"),
  by = ORIGPROT,
  include = c(
    AGE, SEX, EDUC, RACE, ETHNIC, MARISTAT, BMI, DX, APOE,
    ADASTT13, CDGLOBAL, CDRSB, MMSCORE, FAQTOTAL
  ),
  type = all_continuous() ~ "continuous2",
  statistic = list(
    all_continuous() ~ c(
      "{mean} ({sd})",
      "{median} ({p25}, {p75})",
      "{min}, {max}"
    ),
    all_categorical() ~ "{n} ({p}%)"
  ),
  digits = all_continuous() ~ 1,
  percent = "column",
  missing_text = "(Missing)"
) %>%
  add_overall(last = TRUE) %>%
  add_stat_label(label = all_continuous2() ~ conts_statistic_label) %>%
  modify_footnote_header(
    footnote = "Column-wise percentage; n (%)",
    columns = all_stat_cols(),
    replace = TRUE
  ) %>%
  modify_abbreviation(abbreviation = abbrev_list) %>%
  modify_caption(
    caption = "Table 1. ADNI - Subject Characteristics: By Study Phase"
  ) %>%
  bold_labels()
Table 1. ADNI - Subject Characteristics: By Study Phase
Characteristic ADNI1
N = 8191 		ADNIGO
N = 1311 		ADNI2
N = 7901 		ADNI3
N = 6961 		ADNI4
N = 4771 		Overall
N = 2,9131
Age (in Years)





    Mean (SD) 75.2 (6.8) 71.6 (7.9) 72.7 (7.2) 70.7 (7.4) 68.7 (7.4) 72.2 (7.6)
    Median (Q1, Q3) 75.6 (71.2, 80.1) 71.1 (65.8, 77.4) 72.8 (67.8, 77.6) 70.0 (65.9, 75.8) 68.6 (62.9, 74.0) 72.3 (66.9, 77.6)
    Range 54.5, 90.9 55.6, 88.3 55.0, 91.4 50.5, 90.7 55.0, 88.1 50.5, 91.4
Sex, n (%)





    Female 342 (42%) 60 (46%) 379 (48%) 381 (55%) 307 (64%) 1,469 (50%)
    Male 477 (58%) 71 (54%) 411 (52%) 315 (45%) 170 (36%) 1,444 (50%)
Education





    Mean (SD) 15.5 (3.0) 15.8 (2.7) 16.3 (2.6) 16.4 (2.3) 16.0 (2.8) 16.0 (2.7)
    Median (Q1, Q3) 16.0 (13.0, 18.0) 16.0 (14.0, 18.0) 16.0 (14.0, 18.0) 16.0 (15.0, 18.0) 16.0 (14.0, 18.0) 16.0 (14.0, 18.0)
    Range 4.0, 20.0 10.0, 20.0 8.0, 20.0 10.0, 20.0 8.0, 20.0 4.0, 20.0
    (Missing) 1 0 0 0 1 2
Race, n (%)





    American Indian or Alaskan Native 1 (0.1%) 1 (0.8%) 1 (0.1%) 2 (0.3%) 3 (0.6%) 8 (0.3%)
    Asian 14 (1.7%) 1 (0.8%) 14 (1.8%) 29 (4.2%) 45 (9.4%) 103 (3.5%)
    Black or African American 39 (4.8%) 4 (3.1%) 34 (4.3%) 105 (15%) 158 (33%) 340 (12%)
    Native Hawaiian or Other Pacific Islander 0 (0%) 0 (0%) 2 (0.3%) 1 (0.1%) 0 (0%) 3 (0.1%)
    Other Pacific Islander 0 (0%) 0 (0%) 0 (0%) 0 (0%) 2 (0.4%) 2 (<0.1%)
    White 762 (93%) 118 (90%) 728 (92%) 537 (77%) 237 (50%) 2,382 (82%)
    More than one race 3 (0.4%) 5 (3.8%) 10 (1.3%) 13 (1.9%) 22 (4.6%) 53 (1.8%)
    Unknown 0 (0%) 2 (1.5%) 1 (0.1%) 9 (1.3%) 10 (2.1%) 22 (0.8%)
Ethnicity, n (%)





    Hispanic or Latino 19 (2.3%) 8 (6.1%) 31 (3.9%) 58 (8.3%) 66 (14%) 182 (6.2%)
    Not Hispanic or Latino 794 (97%) 122 (93%) 755 (96%) 637 (92%) 409 (86%) 2,717 (93%)
    Unknown 6 (0.7%) 1 (0.8%) 4 (0.5%) 1 (0.1%) 2 (0.4%) 14 (0.5%)
Marital Status, n (%)





    Divorced 52 (6.4%) 17 (13%) 82 (10%) 79 (11%) 89 (19%) 319 (11%)
    Domestic Partnership 0 (0%) 0 (0%) 0 (0%) 0 (0%) 11 (2.3%) 11 (0.4%)
    Married 629 (77%) 95 (73%) 586 (74%) 517 (74%) 281 (59%) 2,108 (72%)
    Never married 28 (3.4%) 3 (2.3%) 33 (4.2%) 35 (5.0%) 56 (12%) 155 (5.3%)
    Unknown 1 (0.1%) 4 (3.1%) 2 (0.3%) 2 (0.3%) 0 (0%) 9 (0.3%)
    Widowed 108 (13%) 12 (9.2%) 87 (11%) 62 (8.9%) 39 (8.2%) 308 (11%)
    (Missing) 1 0 0 1 1 3
Baseline Body Mass Index





    Mean (SD) 27.6 (4.1) 24.0 (NA) 30.8 (7.2) 30.0 (NA) 29.3 (6.5) 29.2 (6.2)
    Median (Q1, Q3) 28.8 (24.7, 30.5) 24.0 (24.0, 24.0) 28.7 (26.4, 31.0) 30.0 (30.0, 30.0) 28.7 (24.7, 31.9) 28.7 (24.7, 31.0)
    Range 21.8, 31.0 24.0, 24.0 25.1, 44.7 30.0, 30.0 18.6, 47.9 18.6, 47.9
    (Missing) 815 130 784 695 450 2,874
Baseline Diagnostics Status, n (%)





    CN 225 (29%) 1 (1.0%) 295 (37%) 380 (55%) 292 (61%) 1,193 (42%)
    MCI 373 (48%) 99 (99%) 344 (44%) 243 (35%) 148 (31%) 1,207 (42%)
    DEM 182 (23%) 0 (0%) 151 (19%) 73 (10%) 37 (7.8%) 443 (16%)
    (Missing) 39 31 0 0 0 70
APOE Genotype, n (%)





    ε2/ε2 2 (0.2%) 0 (0%) 3 (0.4%) 1 (0.1%) 2 (1.7%) 8 (0.3%)
    ε2/ε3 53 (6.5%) 9 (7.0%) 66 (8.5%) 52 (7.7%) 6 (5.1%) 186 (7.4%)
    ε2/ε4 18 (2.2%) 2 (1.6%) 14 (1.8%) 17 (2.5%) 4 (3.4%) 55 (2.2%)
    ε3/ε3 363 (44%) 67 (52%) 352 (45%) 347 (52%) 53 (45%) 1,182 (47%)
    ε3/ε4 295 (36%) 42 (33%) 269 (35%) 204 (30%) 46 (39%) 856 (34%)
    ε4/ε4 88 (11%) 8 (6.3%) 75 (9.6%) 52 (7.7%) 7 (5.9%) 230 (9.1%)
    (Missing) 0 3 11 23 359 396
Baseline ADAS-Cog Item 13 Total Score





    Mean (SD) 18.4 (9.2) 12.4 (5.4) 16.1 (10.1) 13.1 (8.9) 13.0 (8.1) 15.4 (9.4)
    Median (Q1, Q3) 17.7 (11.0, 24.3) 11.2 (8.7, 15.3) 13.7 (8.3, 21.7) 11.0 (6.7, 16.7) 12.0 (7.0, 17.0) 13.3 (8.3, 20.7)
    Range 1.0, 54.7 2.3, 28.3 0.0, 52.3 0.0, 48.3 0.0, 51.0 0.0, 54.7
    (Missing) 8 1 7 11 39 66
Baseline CDR Global Score, n (%)





    0 229 (28%) 0 (0%) 296 (37%) 385 (55%) 290 (61%) 1,200 (41%)
    0.5 495 (61%) 131 (100%) 407 (52%) 269 (39%) 171 (36%) 1,473 (51%)
    1 93 (11%) 0 (0%) 86 (11%) 40 (5.7%) 16 (3.4%) 235 (8.1%)
    2 0 (0%) 0 (0%) 1 (0.1%) 2 (0.3%) 0 (0%) 3 (0.1%)
    (Missing) 2 0 0 0 0 2
Baseline CDR Sum of Boxes Score





    Mean (SD) 1.8 (1.8) 1.2 (0.7) 1.5 (1.9) 1.0 (1.6) 0.9 (1.5) 1.4 (1.7)
    Median (Q1, Q3) 1.5 (0.0, 3.0) 1.0 (0.5, 1.5) 1.0 (0.0, 2.5) 0.0 (0.0, 1.5) 0.0 (0.0, 1.5) 0.5 (0.0, 2.0)
    Range 0.0, 9.0 0.5, 4.0 0.0, 10.0 0.0, 10.0 0.0, 15.0 0.0, 15.0
    (Missing) 2 0 0 0 0 2
Baseline MMSE Score





    Mean (SD) 26.7 (2.7) 28.3 (1.5) 27.4 (2.7) 28.0 (2.5) 27.9 (2.4) 27.5 (2.6)
    Median (Q1, Q3) 27.0 (25.0, 29.0) 28.0 (27.0, 30.0) 28.0 (26.0, 30.0) 29.0 (27.0, 30.0) 29.0 (27.0, 30.0) 28.0 (26.0, 29.5)
    Range 18.0, 30.0 23.0, 30.0 19.0, 30.0 16.0, 30.0 15.0, 30.0 15.0, 30.0
    (Missing) 2 0 0 0 3 5
Baseline FAQ Total Score





    Mean (SD) 5.0 (6.6) 1.9 (3.2) 3.9 (6.2) 2.6 (5.3) 2.3 (4.4) 3.6 (5.9)
    Median (Q1, Q3) 2.0 (0.0, 8.0) 1.0 (0.0, 2.0) 1.0 (0.0, 5.0) 0.0 (0.0, 2.0) 0.0 (0.0, 2.0) 0.0 (0.0, 5.0)
    Range 0.0, 30.0 0.0, 22.0 0.0, 28.0 0.0, 30.0 0.0, 25.0 0.0, 30.0
    (Missing) 7 2 6 28 63 106
Abbreviation: CN: Cognitive Normal; MCI: Mild Cognitive Impairment; DEM: Dementia; SD: Standard Deviation; Q1: the 25th percentile; Q3: the 75th percentile
1 Column-wise percentage; n (%) 
var_label_list <- get_variable_labels(ADSL)
cont_var_list <- c(
  "AGE", "EDUC", "BMI", "ADASTT13", "CDGLOBAL",
  "CDRSB", "MMSCORE", "FAQTOTAL"
)
cont_bl_violin_plot <- lapply(cont_var_list, function(x) {
  ADSL %>%
    filter(ENRLFL %in% "Y") %>%
    rename_with(~ paste0("yvalue"), all_of(x)) %>%
    ggplot(data = ., aes(x = yvalue)) +
    geom_histogram() +
    labs(x = var_label_list[[x]], y = "Count")
})
names(cont_bl_violin_plot) <- cont_var_list
plots(cont_bl_violin_plot, n_columns = 2)

Distribution of response variables: Overall

Demographic Summaries: By Baseline Diagnostics Status 

tbl_summary(
  data = ADSL %>%
    filter(ENRLFL %in% "Y"),
  by = DX,
  include = c(
    AGE, SEX, EDUC, RACE, ETHNIC, MARISTAT, BMI, APOE,
    ADASTT13, CDGLOBAL, CDRSB, MMSCORE, FAQTOTAL
  ),
  type = all_continuous() ~ "continuous2",
  statistic = list(
    all_continuous() ~ c(
      "{mean} ({sd})",
      "{median} ({p25}, {p75})",
      "{min}, {max}"
    ),
    all_categorical() ~ "{n} ({p}%)"
  ),
  digits = all_continuous() ~ 1,
  percent = "row",
  missing_text = "(Missing)"
) %>%
  add_stat_label(label = all_continuous2() ~ conts_statistic_label) %>%
  modify_caption(caption = paste0(
    "Table 2. ADNI - Subject Characteristics: ",
    "By Baseline Diagnosis Status"
  )) %>%
  modify_footnote_header(
    footnote = "Row-wise percentage; n (%)",
    columns = all_stat_cols(),
    replace = TRUE
  ) %>%
  modify_abbreviation(abbreviation = abbrev_list) %>%
  bold_labels()
Table 2. ADNI - Subject Characteristics: By Baseline Diagnosis Status
Characteristic CN
N = 1,1931 		MCI
N = 1,2071 		DEM
N = 4431
Age (in Years)


    Mean (SD) 71.0 (7.0) 72.4 (7.6) 74.6 (8.0)
    Median (Q1, Q3) 70.9 (66.4, 75.9) 72.7 (66.9, 77.8) 75.3 (69.7, 80.3)
    Range 50.5, 90.3 54.5, 91.4 55.1, 90.7
Sex, n (%)


    Female 719 (50%) 525 (36%) 201 (14%)
    Male 474 (34%) 682 (49%) 242 (17%)
Education


    Mean (SD) 16.5 (2.5) 15.9 (2.8) 15.2 (2.9)
    Median (Q1, Q3) 16.0 (15.0, 18.0) 16.0 (14.0, 18.0) 16.0 (13.0, 18.0)
    Range 6.0, 20.0 4.0, 20.0 4.0, 20.0
    (Missing) 1 1 0
Race, n (%)


    American Indian or Alaskan Native 5 (63%) 3 (38%) 0 (0%)
    Asian 60 (59%) 31 (30%) 11 (11%)
    Black or African American 197 (58%) 109 (32%) 33 (9.7%)
    Native Hawaiian or Other Pacific Islander 1 (33%) 2 (67%) 0 (0%)
    Other Pacific Islander 1 (50%) 1 (50%) 0 (0%)
    White 890 (38%) 1,033 (45%) 391 (17%)
    More than one race 30 (57%) 16 (30%) 7 (13%)
    Unknown 9 (41%) 12 (55%) 1 (4.5%)
Ethnicity, n (%)


    Hispanic or Latino 104 (57%) 62 (34%) 16 (8.8%)
    Not Hispanic or Latino 1,084 (41%) 1,139 (43%) 424 (16%)
    Unknown 5 (36%) 6 (43%) 3 (21%)
Marital Status, n (%)


    Divorced 168 (54%) 127 (41%) 18 (5.8%)
    Domestic Partnership 8 (73%) 2 (18%) 1 (9.1%)
    Married 789 (38%) 898 (44%) 369 (18%)
    Never married 86 (56%) 53 (34%) 15 (9.7%)
    Unknown 3 (50%) 3 (50%) 0 (0%)
    Widowed 139 (46%) 121 (40%) 40 (13%)
    (Missing) 0 3 0
Baseline Body Mass Index


    Mean (SD) 27.9 (5.7) 31.0 (7.5) 31.3 (4.5)
    Median (Q1, Q3) 25.2 (24.1, 31.1) 28.7 (26.7, 31.0) 29.9 (28.7, 33.9)
    Range 18.6, 39.3 21.8, 47.9 27.6, 37.9
    (Missing) 1,174 1,194 439
APOE Genotype, n (%)


    ε2/ε2 5 (63%) 2 (25%) 1 (13%)
    ε2/ε3 109 (60%) 61 (33%) 13 (7.1%)
    ε2/ε4 19 (36%) 24 (45%) 10 (19%)
    ε3/ε3 528 (46%) 500 (43%) 126 (11%)
    ε3/ε4 250 (30%) 392 (47%) 186 (22%)
    ε4/ε4 28 (13%) 113 (50%) 83 (37%)
    (Missing) 254 115 24
Baseline ADAS-Cog Item 13 Total Score


    Mean (SD) 8.9 (4.5) 16.4 (6.7) 30.0 (8.1)
    Median (Q1, Q3) 8.3 (5.3, 11.7) 16.0 (11.3, 21.0) 29.3 (24.3, 34.7)
    Range 0.0, 26.3 0.7, 39.7 12.7, 54.7
    (Missing) 32 20 13
Baseline CDR Global Score, n (%)


    0 1,183 (99%) 13 (1.1%) 0 (0%)
    0.5 10 (0.7%) 1,186 (84%) 214 (15%)
    1 0 (0%) 6 (2.6%) 226 (97%)
    2 0 (0%) 0 (0%) 3 (100%)
    (Missing) 0 2 0
Baseline CDR Sum of Boxes Score


    Mean (SD) 0.0 (0.2) 1.5 (1.0) 4.4 (1.7)
    Median (Q1, Q3) 0.0 (0.0, 0.0) 1.5 (1.0, 2.0) 4.5 (3.0, 5.0)
    Range 0.0, 2.0 0.0, 15.0 1.0, 10.0
    (Missing) 0 2 0
Baseline MMSE Score


    Mean (SD) 29.0 (1.2) 27.6 (1.9) 23.1 (2.3)
    Median (Q1, Q3) 29.0 (29.0, 30.0) 28.0 (26.0, 29.0) 23.0 (21.0, 25.0)
    Range 23.0, 30.0 19.0, 30.0 15.0, 30.0
    (Missing) 0 5 0
Baseline FAQ Total Score


    Mean (SD) 0.2 (0.9) 3.2 (4.2) 13.1 (6.8)
    Median (Q1, Q3) 0.0 (0.0, 0.0) 2.0 (0.0, 5.0) 13.0 (8.0, 18.0)
    Range 0.0, 13.0 0.0, 24.0 0.0, 30.0
    (Missing) 56 38 7
Abbreviation: CN: Cognitive Normal; MCI: Mild Cognitive Impairment; DEM: Dementia; SD: Standard Deviation; Q1: the 25th percentile; Q3: the 75th percentile
1 Row-wise percentage; n (%) 
dx_color_pal <- c("#73C186", "#F2B974", "#DF957C", "#999999")

# Create density plot
cont_violin_plot_bl_dx <- lapply(cont_var_list, function(x) {
  ADSL %>%
    filter(ENRLFL %in% "Y") %>%
    filter(!is.na(DX)) %>%
    rename_with(~ paste0("yvalue"), all_of(x)) %>%
    ggplot(data = ., aes(x = yvalue, fill = DX)) +
    geom_density(alpha = 0.5) +
    labs(
      x = paste0(var_label_list[[x]]),
      y = "Density",
      color = get_variable_labels(ADSL$DX),
      title = var_label_list[[x]],
      subtitle = paste0(" By ", get_variable_labels(ADSL$DX)),
      fill = get_variable_labels(ADSL$DX)
    ) +
    scale_fill_manual(values = dx_color_pal) +
    theme(
      legend.position = "bottom",
      title = element_text(size = 11)
    )
})
names(cont_violin_plot_bl_dx) <- cont_var_list
plots(
  cont_violin_plot_bl_dx,
  n_columns = 2,
  guides = "collect",
  caption = paste0(
    "Based on subjects that have known ",
    "diagnostics status at baseline visit."
  ),
) & theme(legend.position = "bottom")

Distribution of response variables: By baseline diagnostics status