psychopdaROC Cardiac Data - Myocardial Infarction Biomarkers
Source:R/data_psychopdaROC_docs.R
psychopdaROC_cardiac.RdCardiac biomarker dataset with 180 patients for ROC analysis of MI diagnosis. Features three key cardiac markers: troponin, creatinine, and BNP with realistic clinical distributions.
Format
A data frame with 180 rows and 5 variables:
- patient_id
Character: Patient identifier (PT001-PT180)
- mi_status
Factor: "MI" or "No_MI" (25%/75% prevalence)
- troponin
Numeric: Troponin level (ng/mL), mean: 2.5 for MI, 0.3 for No_MI
- creatinine
Numeric: Creatinine level (mg/dL), mean: 1.3 for MI, 0.9 for No_MI
- bnp
Numeric: BNP level (pg/mL), mean: 850 for MI, 200 for No_MI
Details
Realistic cardiac biomarker distributions for evaluating diagnostic performance in acute MI. Troponin shows strong discrimination, while creatinine and BNP provide complementary diagnostic information.
Examples
data(psychopdaROC_cardiac)
psychopdaROC(data = psychopdaROC_cardiac,
dependentVars = c("troponin", "creatinine", "bnp"),
classVar = "mi_status", positiveClass = "MI",
refVar = "troponin",
method = "maximize_metric", metric = "youden")
#> Multiple optimal cutpoints found, applying break_ties.
#> Multiple optimal cutpoints found, applying break_ties.
#> Multiple optimal cutpoints found, applying break_ties.
#>
#> ADVANCED ROC ANALYSIS
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#> Procedure Notes
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#>
#> The ROC analysis has been completed using the following
#> specifications:
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#> Measure Variable(s): troponin, creatinine, bnp
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#> Class Variable: mi_status
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#> Positive Class: MI
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#> Method: maximize_metric
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#> All Observed Cutpoints: FALSE
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#> Metric: youden
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#> Direction (relative to cutpoint): >=
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#> Tie Breakers: mean
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#> Metric Tolerance: 0.05
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#> <hr />
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#> <div style='padding: 10px; background-color: #f8f9fa; border: 1px
#> solid #dee2e6; border-radius: 4px; margin-bottom: 15px;'>
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#> Analysis Status
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#> Seed: 123Positive Class: MI (Prevalence: 30.6%)Analysis Mode: Basic
#>
#> ROC Analysis Summary
#> ─────────────────────────────────────────────────────────────────────────
#> Variable AUC 95% CI Lower 95% CI Upper p-value
#> ─────────────────────────────────────────────────────────────────────────
#> troponin 0.8961455 0.8481203 0.9441706 < .0000001
#> creatinine 0.8808727 0.8291091 0.9326363 < .0000001
#> bnp 0.9294545 0.8894481 0.9694609 < .0000001
#> ─────────────────────────────────────────────────────────────────────────
#> Note. AUC 95% confidence intervals computed using the DeLong
#> method.
#>
#>
#> Clinical Interpretation
#> ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Test Performance Level Clinical Recommendation Detailed Interpretation
#> ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> troponin Good Suitable for clinical use with appropriate cutpoint The test 'troponin' has an AUC of 0.896 indicating good discriminatory ability. This test performs well for clinical decision making.
#> creatinine Good Suitable for clinical use with appropriate cutpoint The test 'creatinine' has an AUC of 0.881 indicating good discriminatory ability. This test performs well for clinical decision making.
#> bnp Excellent Suitable for clinical use with appropriate cutpoint The test 'bnp' has an AUC of 0.929 indicating excellent discriminatory ability. This test can reliably distinguish between diseased and healthy patients.
#> ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>
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#> OPTIMAL CUTPOINTS AND PERFORMANCE
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#> no title
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Cutpoint Sensitivity Specificity PPV NPV Youden's J AUC Metric Score
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> 1.7027586 76.36364 82.40000 65.62500 88.79310 0.5876364 0.8961455 0.5876364
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────
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#>
#> no title
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Cutpoint Sensitivity Specificity PPV NPV Youden's J AUC Metric Score
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> 1.1500000 80.00000 80.80000 64.70588 90.17857 0.6080000 0.8808727 0.6080000
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>
#>
#> no title
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Cutpoint Sensitivity Specificity PPV NPV Youden's J AUC Metric Score
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> 565.0294118 76.36364 87.20000 72.41379 89.34426 0.6356364 0.9294545 0.6356364
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>
#>
#> Area Under the ROC Curve
#> ─────────────────────────────────────────────────────────────────────────
#> Variable AUC 95% CI Lower 95% CI Upper p-value
#> ─────────────────────────────────────────────────────────────────────────
#> troponin 0.8961455 0.8481203 0.9441706 < .0000001
#> creatinine 0.8808727 0.8291091 0.9326363 < .0000001
#> bnp 0.9294545 0.8894481 0.9694609 < .0000001
#> ─────────────────────────────────────────────────────────────────────────
#> Note. AUC 95% confidence intervals computed using the DeLong
#> method.
#>
