More than meets the eye: predicting adrenocortical carcinoma outcomes with pathomics
Authors' conclusion
The development of a pathomics-based nomogram for ACC presents a superior prognostic tool, enhancing personalized clinical decision making. This study highlights the potential of pathomics in refining prognostic models for complex malignancies like ACC, with implications for improving prognosis prediction and guiding treatment strategies in clinical practice.
Study context
- Population
- Patients with adrenocortical carcinoma (ACC) who underwent radical adrenalectomy, 2002–2019
- Participants
- 159 patients
- Exposure
- Pathomics signature (PSACC) and pathomics-based nomogram vs conventional clinicopathological model for ACC prognosis
- Trainingn = 111
- Validationn = 48
- Outcome
- Association of PSACC with ACC prognosis
Methodological detailstraining and validation cohorts, LASSO-Cox regression
- Training and validation cohorts
- LASSO-Cox regression
Main finding
As reported in the abstract
Hazard ratio (95% CI)P value
TrainingPSACC, training cohort
3.380(1.687–6.772)
P < 0.001ValidationPSACC, validation cohort
3.904(1.039–14.669)
P < 0.001Observational data: associations, not effects.
Further findings
Prediction accuracy (concordance index): nomogram (PSACC + M stage) vs conventional clinicopathological model
- Training cohort: C-index nomogram vs conventional model (P = .002)
- 0.779 versus 0.668
- Validation cohort: C-index nomogram vs conventional model (P = .003)
- 0.752 versus 0.603
Original publication
More than meets the eye: predicting adrenocortical carcinoma outcomes with pathomics. Eur J Endocrinol. Published 28 January 2025. doi:10.
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