tests/testthat/test-estimators-survival.R

In rifttable: Results Tables to Bridge the Rift Between Epidemiologists and Their Data

testthat::test_that(
  desc = "survival outcomes work",
  code = {
    data(cancer, package = "survival")

    cancer <- cancer |>
      tibble::as_tibble() |>
      dplyr::mutate(
        # The exposure (here, 'sex') must be categorical (a factor)
        sex = factor(
          sex,
          levels = 1:2,
          labels = c(
            "Male",
            "Female"
          )
        ),
        time = time / 365.25, # transform to years
        status = status - 1
      )

    object <- tibble::tribble(
      ~label,                                  ~type,
      "**Absolute estimates**",                "",
      "*Counts and sums*",                     "",
      "  Observations, *N*",                   "total",
      "  Events, *n*",                         "events",
      "  Events/observations",                 "events/total",
      "  Events/person-years",                 "events/time",
      "*Follow-up*",                           "",
      "  Person-years",                        "time",
      "  Maximum follow-up, years",            "maxfu",
      "  Median follow-up, years",             "medfu",
      "  Median follow-up (IQR), years",       "medfu (iqr)",
      "*Rates*",                               "",
      "  Rate per 1000 person-years",          "rate",
      "  Rate per 1000 person-years (95% CI)", "rate (ci)",
      "  Events/py (rate per 1000 py)",        "events/time (rate)",
      "*Risks*",                               "",
      "  1-year survival",                     "surv",
      "  1-year survival (95% CI)",            "surv (ci)",
      "  1-year risk/cumulative incidence",    "cuminc",
      "  1-year risk (95% CI)",                "cuminc (ci)",
      "  Median survival, years",              "medsurv",
      "  Median survival (95 CI), years",      "medsurv (ci)",
      "",                                      "",
      "**Comparative estimates**",             "",
      "  1-year survival difference",          "survdiff",
      "  1-year risk difference",              "cumincdiff",
      "  1-year survival ratio",               "survratio",
      "  1-year risk ratio",                   "cumincratio",
      "  Hazard ratio (95% CI)",               "hr"
    ) |>
      dplyr::mutate(
        time = "time",
        event = "status",
        exposure = "sex",
        arguments = list(list(timepoint = 1))
      ) |>
      rifttable(
        data = cancer,
        overall = TRUE
      )

    expected <- tibble::tribble(
      ~Summary,                               ~Overall,               ~Male,                   ~Female,
      "**Absolute estimates**",               "",                     "",                      "",
      "*Counts and sums*",                    "",                     "",                      "",
      "  Observations, *N*",                  "228",                  "138",                   "90",
      "  Events, *n*",                        "165",                  "112",                   "53",
      "  Events/observations",                "165/228",              "112/138",               "53/90",
      "  Events/person-years",                "165/191",              "112/107",               "53/84",
      "*Follow-up*",                          "",                     "",                      "",
      "  Person-years",                       "191",                  "107",                   "84",
      "  Maximum follow-up, years",           "2.80",                 "2.80",                  "2.64",
      "  Median follow-up, years",            "1.61",                 "2.30",                  "1.45",
      "  Median follow-up (IQR), years",      "1.61 (0.82, 2.64)",    "2.30 (1.11, 2.77)",     "1.45 (0.76, 2.25)",
      "*Rates*",                              "",                     "",                      "",
      "  Rate per 1000 person-years",         "866.0",                "1046.6",                "634.6",
      "  Rate per 1000 person-years (95% CI)","866.0 (743.4, 1008.7)","1046.6 (869.7, 1259.6)","634.6 (484.8, 830.6)",
      "  Events/py (rate per 1000 py)",       "165/191 (866.0)",      "112/107 (1046.6)",      "53/84 (634.6)",
      "*Risks*",                              "",                     "",                      "",
      "  1-year survival",                    "0.41",                 "0.34",                  "0.53",
      "  1-year survival (95% CI)",           "0.41 (0.34, 0.49)",    "0.34 (0.26, 0.43)",     "0.53 (0.42, 0.66)",
      "  1-year risk/cumulative incidence",   "0.59",                 "0.66",                  "0.47",
      "  1-year risk (95% CI)",               "0.59 (0.51, 0.66)",    "0.66 (0.57, 0.74)",     "0.47 (0.34, 0.58)",
      "  Median survival, years",             "0.85",                 "0.74",                  "1.17",
      "  Median survival (95 CI), years",     "0.85 (0.78, 0.99)",    "0.74 (0.58, 0.85)",     "1.17 (0.95, 1.51)",
      "",                                     "",                     "",                      "",
      "**Comparative estimates**",            "",                     "",                      "",
      "  1-year survival difference",         "",                     "0 (reference)",         "0.19 (0.05, 0.34)",
      "  1-year risk difference",             "",                     "0 (reference)",         "-0.19 (-0.33, -0.04)",
      "  1-year survival ratio",              "",                     "1 (reference)",         "1.57 (1.12, 2.19)",
      "  1-year risk ratio",                  "",                     "1 (reference)",         "0.71 (0.55, 1.00)",
      "  Hazard ratio (95% CI)",              "",                     "1 (reference)",         "0.59 (0.42, 0.82)"
    )

    expect_equal(
      object = object,
      expected = expected
    )
  }
)