# Predictive value of controlling nutritional status score for prostate cancer diagnosis

## TL;DR

This study shows that the CONUT score can help diagnose prostate cancer when combined with other clinical markers like PSA and MRI.

## Contribution

The study demonstrates that the CONUT score improves diagnostic accuracy when combined with existing prostate cancer markers.

## Key findings

- The CONUT score showed a statistically significant difference between prostate cancer and non-cancer groups.
- Combining CONUT score with PSA and PSAD increased diagnostic accuracy (AUC = 0.784).
- Adding mpMRI to the combination further improved diagnostic accuracy (AUC = 0.881).

## Abstract

This study aims to explore the predictive value of the Controlling Nutritional Status (CONUT) score for prostate cancer (PCa) diagnosis.

The data of 114 patients who underwent prostate needle biopsies from June 2020 to December 2022 were retrospectively analyzed. The relationship between CONUT score and various clinical factors as well as PCa diagnosis was evaluated.

The pathological results classified patients into the PCa (n = 38) and non-PCa (n = 76) groups. Compared with the non-PCa group, the PCa group exhibited statistically significant differences in age, prostate-specific antigen (PSA), PSA density (PSAD), the proportion of PI-RADS ≥ 3 in mpMRI, and the CONUT score, prostate volume, lymphocyte count, and total cholesterol concentration (p < 0.05). ROC curve analyses indicated the diagnostic accuracy as follows: age (AUC = 0.709), prostate volume (AUC = 0.652), PSA (AUC = 0.689), PSAD (AUC = 0.76), PI-RADS ≥ 3 in mpMRI (AUC = 0.846), and CONUT score (AUC = 0.687). When CONUT score was combined with PSA and PSAD, AUC increased to 0.784. The AUC of CONUT score combined with PSA, PSAD, and mpMRI was 0.881, indicates a higher diagnostic value. Based on the optimal cut-off value of CONUT score, compared with the low CONUT score group, the high CONUT score group has a higher positive rate of PCa diagnosis (p < 0.05).

CONUT score is an excellent auxiliary index for PCa diagnosis in addition to the commonly used PSA, PSAD, and mpMRI in clinical practice. Further prospective trials with a larger sample size are warranted to confirm the present study findings.