Fix tests using ADPC after refactor

tests/testthat/_snaps/listing_adal02.md

@@ -1,4 +1,4 @@
 # ADAL02 listing is produced correctly
 
     Code
       result
@@ -8,51 +8,63 @@
 
       Treatment Group: A: Drug X
 
-      ——————————————————————————————————————————————————————
-                               Day 2     Patient Treatment  
-           Subject ID         (Day 1)   Emergent ADA Status 
-      ——————————————————————————————————————————————————————
-      AB12345-BRA-1-id-93     <1.10*    Induced (Persistent)
-      AB12345-CHN-1-id-123     1.28*    Induced (Persistent)
-      AB12345-CHN-1-id-329     1.43*    Induced (Persistent)
-      AB12345-CHN-1-id-53     <1.10*    Induced (Persistent)
-      AB12345-CHN-1-id-71      1.28*    Induced (Persistent)
-      AB12345-CHN-11-id-116    1.36*    Induced (Persistent)
-      AB12345-CHN-11-id-124   <1.10*    Induced (Persistent)
-      AB12345-CHN-11-id-167    1.26*    Induced (Persistent)
-      AB12345-CHN-11-id-256    1.35*    Induced (Persistent)
-      AB12345-CHN-11-id-377    1.17*    Induced (Persistent)
-      AB12345-CHN-12-id-258    1.40*    Induced (Persistent)
-      AB12345-CHN-12-id-266   <1.10*    Induced (Persistent)
-      AB12345-CHN-12-id-57     1.24*    Induced (Persistent)
-      AB12345-CHN-14-id-161   <1.10*    Induced (Persistent)
-      AB12345-CHN-15-id-399   <1.10*    Induced (Persistent)
-      AB12345-CHN-18-id-170   <1.10*    Induced (Persistent)
-      AB12345-CHN-2-id-22     <1.10*    Induced (Persistent)
-      AB12345-CHN-2-id-272     1.20*    Induced (Persistent)
-      AB12345-CHN-2-id-398     1.14*    Induced (Persistent)
-      AB12345-CHN-3-id-128     1.21*    Induced (Persistent)
-      AB12345-CHN-3-id-361     1.32*    Induced (Persistent)
-      AB12345-CHN-5-id-108    <1.10*    Induced (Persistent)
-      AB12345-CHN-8-id-205     1.14*    Induced (Persistent)
-      AB12345-GBR-13-id-80    <1.10*    Induced (Persistent)
-      AB12345-GBR-15-id-293    1.14*    Induced (Persistent)
-      AB12345-JPN-1-id-218    <1.10*    Induced (Persistent)
-      AB12345-NGA-1-id-388    <1.10*    Induced (Persistent)
-      AB12345-NGA-2-id-353    <1.10*    Induced (Persistent)
-      AB12345-PAK-1-id-79      1.26*    Induced (Persistent)
-      AB12345-PAK-11-id-187    1.16*    Induced (Persistent)
-      AB12345-PAK-13-id-251    1.14*    Induced (Persistent)
-      AB12345-PAK-15-id-314   <1.10*    Induced (Persistent)
-      AB12345-RUS-1-id-52      1.22*    Induced (Persistent)
-      AB12345-RUS-6-id-77      1.16*    Induced (Persistent)
-      AB12345-USA-11-id-238    1.31*    Induced (Persistent)
-      AB12345-USA-11-id-339    1.24*    Induced (Persistent)
-      AB12345-USA-17-id-142    1.35*    Induced (Persistent)
-      AB12345-USA-3-id-282    <1.10*    Induced (Persistent)
-      ——————————————————————————————————————————————————————
+      —————————————————————————————————————————————————————
+                               Day 2     Patient Treatment 
+           Subject ID         (Day 1)   Emergent ADA Status
+      —————————————————————————————————————————————————————
+      AB12345-BRA-1-id-105      ---          Enhanced      
+      AB12345-BRA-1-id-134      ---          Enhanced      
+       AB12345-BRA-1-id-42      ---          Enhanced      
+       AB12345-BRA-1-id-93      ---          Enhanced      
+      AB12345-BRA-11-id-217     ---          Enhanced      
+      AB12345-BRA-11-id-345     ---          Enhanced      
+      AB12345-BRA-11-id-397     ---          Enhanced      
+      AB12345-BRA-11-id-50      ---          Enhanced      
+      AB12345-BRA-13-id-177     ---          Enhanced      
+      AB12345-BRA-14-id-23      ---          Enhanced      
+      AB12345-BRA-15-id-36      ---          Enhanced      
+      AB12345-BRA-2-id-296      ---          Enhanced      
+      AB12345-BRA-6-id-369      ---          Enhanced      
+       AB12345-CAN-1-id-18      ---          Enhanced      
+      AB12345-CAN-11-id-139     ---          Enhanced      
+      AB12345-CAN-14-id-104     ---          Enhanced      
+      AB12345-CHN-1-id-119      ---          Enhanced      
+      AB12345-CHN-1-id-123      ---          Enhanced      
+      AB12345-CHN-1-id-133      ---          Enhanced      
+      AB12345-CHN-1-id-199      ---          Enhanced      
+      AB12345-CHN-1-id-216      ---          Enhanced      
+      AB12345-CHN-1-id-235      ---          Enhanced      
+       AB12345-CHN-1-id-25      ---          Enhanced      
+       AB12345-CHN-1-id-26      ---          Enhanced      
+      AB12345-CHN-1-id-275      ---          Enhanced      
+      AB12345-CHN-1-id-277      ---          Enhanced      
+      AB12345-CHN-1-id-287      ---          Enhanced      
+      AB12345-CHN-1-id-315      ---          Enhanced      
+      AB12345-CHN-1-id-316      ---          Enhanced      
+      AB12345-CHN-1-id-329      ---          Enhanced      
+      AB12345-CHN-1-id-360      ---          Enhanced      
+      AB12345-CHN-1-id-371      ---          Enhanced      
+       AB12345-CHN-1-id-47      ---          Enhanced      
+       AB12345-CHN-1-id-53      ---          Enhanced      
+       AB12345-CHN-1-id-62      ---          Enhanced      
+       AB12345-CHN-1-id-69      ---          Enhanced      
+       AB12345-CHN-1-id-71      ---          Enhanced      
+      AB12345-CHN-11-id-116     ---          Enhanced      
+      AB12345-CHN-11-id-124     ---          Enhanced      
+      AB12345-CHN-11-id-132     ---          Enhanced      
+      AB12345-CHN-11-id-153     ---          Enhanced      
+      AB12345-CHN-11-id-167     ---          Enhanced      
+      AB12345-CHN-11-id-256     ---          Enhanced      
+      AB12345-CHN-11-id-354     ---          Enhanced      
+      AB12345-CHN-11-id-356     ---          Enhanced      
+      AB12345-CHN-11-id-377     ---          Enhanced      
+      AB12345-CHN-11-id-379     ---          Enhanced      
+      AB12345-CHN-11-id-392     ---          Enhanced      
+      AB12345-CHN-11-id-88      ---          Enhanced      
+      AB12345-CHN-12-id-258     ---          Enhanced      
+      —————————————————————————————————————————————————————
 
       Minimum reportable titer = 1.10 (example only)
       --- = No sample evaluated
       ADA = Anti-Drug Antibodies (is also referred to as ATA, or Anti-Therapeutic Antibodies)
       Number of patients positive for Treatment Emergent ADA = the number of post-baseline evaluable patients determined to
@@ -60,11 +72,11 @@
       negative or missing baseline ADA result(s) and at least one positive post-baseline ADA result.
       Treatment-enhanced ADA = a patient with positive ADA result at baseline who has one or more post-baseline titer
       results that are at least 0.60 t.u. greater than the baseline titer result.
       Transient ADA = ADA positive result detected (a) at only one post-baseline sampling timepoint (excluding last
       timepoint) OR (b) at 2 or more timepoints during treatment where the first and last ADA positive samples  are
       separated by a period of < 16 weeks, irrespective of any negative samples in between.
       Persistent ADA =  ADA positive result detected (a) at the last post-baseline sampling timepoint, OR (b) at 2 or more
       time points during treatment where the first and last ADA positive samples are separated by a period ≥ 16 weeks,
       irrespective of any negative samples in between.
       Asterisk denotes sample that tested positive for Neutralizing Antibodies.
 

tests/testthat/_snaps/table_adat03.md

@@ -1,26 +1,26 @@
 # ADAT03 is produced correctly
 
     Code
       res
     Output
-      Treatment Group                                                                                                                              
-        Visit                   Total Number                                                                                          Samples with 
-                                of Measurable                                                                                         Concentration
-                                 Samples {1}      Mean         SD        Median      Minimum     Maximum    CV (%)   Geometric Mean   ≤ 15μg/mL {2}
-      —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
-      A: Drug X (N=670)                                                                                                                            
-        Day 1                        536        3.152e+00   5.516e+00   0.000e+00   0.000e+00   1.557e+01   175.0          NA          531 (99.1%) 
-        Day 2                        134        1.618e+01   1.626e+00   1.619e+01   1.260e+01   1.986e+01    10.0      1.610e+01       39 (29.1%)  
+      Treatment Group                                                                                                                             
+        Visit                  Total Number                                                                                          Samples with 
+                               of Measurable                                                                                         Concentration
+                                Samples {1}      Mean         SD        Median      Minimum     Maximum    CV (%)   Geometric Mean   ≤ 15μg/mL {2}
+      ————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+      A: Drug X (N=536)                                                                                                                           
+        Day 1                       402        0.000e+00   0.000e+00   0.000e+00   0.000e+00   0.000e+00     NA           NA          402 (100%)  
+        Day 2                       134        1.618e+01   1.626e+00   1.619e+01   1.260e+01   1.986e+01    10.0      1.610e+01       39 (29.1%)  
 
-      C: Combination (N=1056)                                                                                                                      
-        Day 1                        792        6.459e+00   9.961e+00   0.000e+00   0.000e+00   3.100e+01   154.2          NA          654 (82.6%) 
-        Day 2                        264        2.468e+01   8.645e+00   2.251e+01   1.264e+01   3.947e+01    35.0      2.315e+01       28 (10.6%)  
+      C: Combination (N=792)                                                                                                                      
+        Day 1                       528        0.000e+00   0.000e+00   0.000e+00   0.000e+00   0.000e+00     NA           NA          528 (100%)  
+        Day 2                       264        2.468e+01   8.645e+00   2.251e+01   1.264e+01   3.947e+01    35.0      2.315e+01       28 (10.6%)  
 
-      Overall                       1726        8.975e+00   1.104e+01   0.000e+00   0.000e+00   3.947e+01   123.0          NA         1252 (72.5%) 
-      —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+      Overall                      1328        6.540e+00   1.095e+01   0.000e+00   0.000e+00   3.947e+01   167.5          NA          997 (75.1%) 
+      ————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
 
       {1} - footnote1
       {2} - footnote2
-      —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+      ————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
 
 

tests/testthat/test-listing_adal02.R

@@ -1,6 +1,6 @@
 testthat::test_that("ADAL02 listing is produced correctly", {
   adab <- adab_raw %>%
-    filter(NRELTM1 %% 1 == 0 & NRELTM1 > 0)
+    filter(NFRLT %% 1 == 0 & NFRLT > 0)
 
   trt <- "A: Drug X"
   drug_a <- "A: Drug X Antibody"
@@ -11,29 +11,30 @@
     filter(
       ARM == trt,
       PARCAT1 == drug_a,
-      ADAPBLFL == "Y"
+      ADPBLPFL == "Y"
     ) %>%
-    select(-PARAMCD, -AVALC, -AVALU, -ARELTM2, -NRELTM2) %>%
+    select(-PARAMCD, -AVALC, -AVALU, -ARRLT, -NRRLT) %>%
     unique() %>%
     tidyr::pivot_wider(
       names_from = PARAM,
       values_from = AVAL
     ) %>%
-    filter(`Treatment Emergent - Positive` == 1) %>%
+    filter(if_any(matches("Treatment Emergent - Positive"), ~ .x == 1)) %>%
+    # filter(`Treatment Emergent - Positive` == 1) %>%
     mutate(
       VISN = factor(paste0(
         VISIT, "\n(Day ",
         ifelse(
-          NRELTM1 %% 1 == 0,
-          NRELTM1,
-          as.character(format(round(NRELTM1, 2), nsmall = 2))
+          NFRLT %% 1 == 0,
+          NFRLT,
+          as.character(format(round(NFRLT, 2), nsmall = 2))
         ),
         ")"
       )),
       PTES = ifelse(
-        `Treatment induced ADA` == 1,
+        ifelse("Treatment induced ADA" %in% names(.), `Treatment induced ADA` == 1, FALSE),
         ifelse(
-          `Transient ADA` == 1,
+          "Transient ADA" %in% names(.) & `Transient ADA` == 1,
           "Induced (Transient)",
           "Induced (Persistent)"
         ),
@@ -42,16 +43,24 @@
     ) %>%
     mutate(
       AVAL = paste0(
-        ifelse(`ADA interpreted per sample result` == 0,
+        ifelse(
+          ifelse("ADA interpreted per sample result" %in% names(.), `ADA interpreted per sample result` == 0, FALSE),
           "NEGATIVE",
-          ifelse(is.na(`Antibody titer units`),
-            "---",
-            ifelse(`Antibody titer units` < min_titer,
+          ifelse(
+            ifelse("Antibody titer units" %in% names(.), !is.na(`Antibody titer units`), FALSE),
+            ifelse(
+              `Antibody titer units` < min_titer,
               paste0("<", format(min_titer, nsmall = 2)),
               as.character(format(round(`Antibody titer units`, 2), nsmall = 2))
-            )
+            ),
+            "---"
           )
-        ), ifelse(`NAB interpreted per sample result` == 1, "*", "")
+        ),
+        ifelse(
+          ifelse("NAB interpreted per sample result" %in% names(.), `NAB interpreted per sample result` == 1, FALSE),
+          "*",
+          ""
+        )
       )
     )
 
@@ -61,7 +70,7 @@
       names_from = VISN,
       values_from = AVAL
     ) %>%
-    select(USUBJID, unique(adab_x$VISN[order(adab_x$NRELTM1)]), PTES)
+    select(USUBJID, unique(adab_x$VISN[order(adab_x$NFRLT)]), PTES)
 
   formatters::var_labels(out) <- names(out)
 
@@ -80,7 +89,7 @@
       "\nProtocol: ", unique(adab$PARCAT1)[1]
     ),
     subtitles = paste("\nTreatment Group:", trt),
     main_footer = "Minimum reportable titer = 1.10 (example only)
 --- = No sample evaluated
 ADA = Anti-Drug Antibodies (is also referred to as ATA, or Anti-Therapeutic Antibodies)
 Number of patients positive for Treatment Emergent ADA = the number of post-baseline evaluable patients determined to
@@ -88,12 +97,12 @@
 negative or missing baseline ADA result(s) and at least one positive post-baseline ADA result.
 Treatment-enhanced ADA = a patient with positive ADA result at baseline who has one or more post-baseline titer
 results that are at least 0.60 t.u. greater than the baseline titer result.
 Transient ADA = ADA positive result detected (a) at only one post-baseline sampling timepoint (excluding last
 timepoint) OR (b) at 2 or more timepoints during treatment where the first and last ADA positive samples  are
 separated by a period of < 16 weeks, irrespective of any negative samples in between.
 Persistent ADA =  ADA positive result detected (a) at the last post-baseline sampling timepoint, OR (b) at 2 or more
 time points during treatment where the first and last ADA positive samples are separated by a period ≥ 16 weeks,
 irrespective of any negative samples in between.
 Asterisk denotes sample that tested positive for Neutralizing Antibodies."
   ) %>% head(50), "sorting incoming data by key columns")
 

tests/testthat/test-listing_pkcl01.R

@@ -1,16 +1,16 @@
 testthat::test_that("PKCL01 listing is produced correctly", {
   adpc <- adpc_raw
   analyte <- "Plasma Drug X"
   out <- adpc %>%
     filter(PARAM == analyte) %>%
-    select(ARM, USUBJID, VISIT, NRELTM1, ARELTM1, AVAL)
+    select(ARM, USUBJID, VISIT, NFRLT, AFRLT, AVAL)
 
   formatters::var_labels(out) <- c(
     ARM = "Treatment Group",
     USUBJID = "Subject ID",
     VISIT = "Visit",
-    NRELTM1 = paste0("Nominal Sampling\nTime (", adpc$RELTMU[1], ")"),
-    ARELTM1 = paste0("Actual Time\nFrom First\nDose (", adpc$RELTMU[1], ")"),
+    NFRLT = paste0("Nominal Sampling\nTime (", adpc$RELTMU[1], ")"),
+    AFRLT = paste0("Actual Time\nFrom First\nDose (", adpc$RELTMU[1], ")"),
     AVAL = paste0("Concentration\n(", adpc$AVALU[1], ")")
   )
 

tests/testthat/test-table_adat03.R

@@ -1,9 +1,9 @@
-adpc <- adpc_raw %>% select(USUBJID, NRELTM1, AVAL, AVALU, AVALC)
+adpc <- adpc_raw %>% select(USUBJID, NFRLT, AVAL, AVALU)
 anl <- adab_raw %>%
   filter(., PARAM == "ADA interpreted per sample result") %>%
-  select(-AVAL, AVALC, AVALU)
+  select(-AVAL, AVALU)
 
-anl <- merge(anl, adpc, by = c("USUBJID", "NRELTM1")) %>%
+anl <- merge(anl, adpc, by = c("USUBJID", "NFRLT")) %>%
   mutate(AVAL_LT = ifelse(AVAL <= 15, TRUE, FALSE))
 
 # parameters in columns
@@ -13,8 +13,8 @@
   mean = "Mean",
   sd = "SD",
   median = "Median",
   min = "Minimum",
   max = "Maximum",
   cv = "CV (%)",
   geom_mean = "Geometric Mean",
   count_fraction = paste0("Samples with\nConcentration\n≤ 15μg/mL")
@@ -33,10 +33,10 @@
 
 afun_list <- lapply(
   1:9,
   function(i) make_afun(s_summary, .stats = adat03_stats[i], .formats = adat03_fmts[i], .labels = "Overall")
 )
 
 testthat::test_that("ADAT03 is produced correctly", {
   result <- basic_table() %>%
     split_rows_by(
       var = "ARM",
@@ -61,7 +61,7 @@
     analyze_colvars(
       afun_list,
       nested = FALSE,
       extra_args = list(".labels" = "Overall")
     ) %>%
     build_table(anl, alt_counts_df = adsl_raw)
 

tests/testthat/test-table_pkct01.R

@@ -1,6 +1,6 @@
 adpc <- adpc_raw
 
 testthat::test_that("PKCT01 is produced correctly", {
   l <- basic_table() %>%
     split_rows_by(
       var = "ARM",
@@ -24,11 +24,11 @@
     ) %>%
     split_rows_by(var = "PARAM", child_labels = "hidden") %>%
     analyze_vars_in_cols(
-      vars = "AVALC", var_type = "character", .stats = c("n_blq"),
+      vars = "AVALCAT1", var_type = "character", .stats = c("n_blq"),
       .labels = c(n_blq = "n_blq")
     )
 
-  adpc <- adpc %>% mutate(AVALC = as.factor(AVALC))
+  adpc <- adpc %>% mutate(AVALCAT1 = as.factor(AVALCAT1))
   result <- build_table(l2, df = adpc)
 
   res <- testthat::expect_silent(result)
@@ -44,12 +44,12 @@
   # Setting up the data
   adpc_1 <- adpc %>%
     mutate(
-      NRELTM1 = as.factor(NRELTM1),
-      AVALC = as.factor(AVALC)
+      NFRLT = as.factor(NFRLT),
+      AVALCAT1 = as.factor(AVALCAT1)
     ) %>%
     filter(ACTARM %in% c("A: Drug X")) %>%
     mutate(ACTARM = factor(ACTARM, levels = c("A: Drug X"))) %>%
-    select(NRELTM1, ACTARM, VISIT, AVAL, PARAM, AVALC)
+    select(NFRLT, ACTARM, VISIT, AVAL, PARAM, AVALCAT1)
 
   # Row structure
   l_rows <- basic_table() %>%
@@ -64,7 +64,7 @@
       label_pos = "topleft"
     ) %>%
     split_rows_by(
-      var = "NRELTM1",
+      var = "NFRLT",
       split_label = "Norminal Time from First Dose",
       label_pos = "topleft",
       child_labels = "hidden"
@@ -73,7 +73,7 @@
   # Column results for numeric values
   lyt <- l_rows %>%
     analyze_vars_in_cols(
-      vars = c("AVAL", "AVALC", rep("AVAL", 8)),
+      vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
       .stats = c(
         "n", "n_blq", "mean", "sd", "cv",
         "geom_mean", "geom_cv", # "geom_mean_ci",
@@ -100,8 +100,8 @@
         geom_mean = "Geometric Mean",
         geom_cv = "CV % Geometric Mean",
         median = "Median",
         min = "Minimum",
         max = "Maximum"
       ),
       na_level = "NE"
     )
@@ -134,7 +134,7 @@
   tmp_result <- tmp_result[tmp_result != ""]
   testthat::expect_equal(tmp_result, as.character(signif(mean_vals, 3)))
 
   # Pagination works roughly
   pag_works <- paginate_table(result, verbose = FALSE, lpp = 20)
   testthat::expect_equal(length(pag_works), 12L)
 })