Could Prognostic Nutritional Index be a new criteria for active surveillance of prostate cancer?

OBJECTIVE

To evaluate the importance of the Prognotic Nutritional Index(PNI) value for patient selection of active surveillance(AS) in prostate cancer.

METHODS

Between September 2020 and June 2022, the data of 125-patients who underwent Robot-Assisted-Laparoscopic-Prostatectomy(RALP) were retrospectively analyzed. All patients were suitable for AS preoperatively. Using the pathological results of RALP, patients have been divided two groups. Patients who met the criteria for AS were defined as the first group, others were defined second. Demographic datas, PNI values and hematological parameters of the groups were compared.

RESULTS

38% (n:48) patients were found suitable for the group1, and 62%(n:77) were found suitable for the group 2. Upgrading and upstaging were found at 76 patients (61%) and 26(21%), respectively. There is no significant difference between groups on age, BMI, PSA, PSA-density, prostate volume, and PIRADS. PNI value was found higher at first group. The value of 49.45 was calculated by ROC analysis as the ideal PNI cut-off value for predicting upgrading and upstaging of prostate cancer (P < ,001). According to the both univariate and multivariate regression analysis, PNI was found a predictor for exclusion from AS (P < ,001).

CONCLUSION

Upgrading and upstaging are detected at a higher rate in patients with low PNI values. The use of PNI value in the selection of patients to AS will increase the success rate of ideal patient selection.

Magnetic resonance spectroscopy to assess hepatic steatosis in patients with lipodystrophy

BACKGROUND/AIMS

Lipodystrophy is a rare metabolic disorder characterized by near total or partial lack of subcutaneous adipose tissue and associated with insulin resistance. We aimed to evaluate the efficacy of magnetic resonance spectroscopy imaging (MRS) to explore the fat content of the liver in patients with lipodystrophy and to determine the relationship between the liver fat accumulation and clinical presentations of lipodystrophy.

MATERIALS AND METHODS

Between July 2014 and February 2016, 34 patients with lipodystrophy were assessed by MRS for quantification of hepatic steatosis. All patients had metabolic abnormalities associated with insulin resistance. Metabolic parameters and the MRS findings were analyzed to identify potential correlations between the liver fat content and disease severity.

RESULTS

The MRS fat ratios (MRS-FR) were markedly higher, indicating severe hepatic steatosis in lipodystrophy. Patients with generalized and partial lipodystrophy had comparable levels of MRS-FRs, although patients with generalized lipodystrophy were significantly younger. Patients with genetically based lipodystrophy had elevated MRS-FR compared to those with acquired lipodystrophy (p=0.042). The MRS-FR was positively correlated with liver enzyme alanine aminotransferase (p=0.028) and serum adiponectin (p=0.043).

CONCLUSION

Our data suggest that MRS might be an effective, noninvasive imaging method to quantify hepatic fat content in patients with lipodystrophy. Further studies are needed to validate the technique and threshold values which would allow accurate comparison of data acquired by different machines and centers.