The Clinical Value of Prognostic Nutritional Index in CAR-T Therapy for Patients with Malignant Lymphoma
Authors: Zhang Na , Liu Rui , Yang Fan , Ma Lixia , Guo Yuelu , Fu Zhonghua , Wu Haifeng , Deng Biping , Ke Xiaoyan , Hu Kai 
Published: December 2024

B ackground:

The Prognostic Nutritional Index (PNI) can evaluate the nutritional and immune status of cancer patients and is a favorable prognostic factor in various cancer types. However, its application has not been studied in patients with hematologic malignancies undergoing CAR-T therapy.

Aims:

This study aimed to investigate the predictive value and clinical significance of PNI in patients with lymphoma undergoing CAR-T therapy.

Methods:

A retrospective analysis was conducted on 506 lymphoma patients treated with CAR-T therapy from December 2018 to January 2024. Baseline data were collected, including pre-treatment albumin and lymphocyte counts used to calculate PNI (albumin + 5 × lymphocyte count). Data analysis was performed using Python. The Shapiro-Wilk test assessed the normality of quantitative data. Kaplan-Meier survival analysis determined the optimal cutoff value for overall survival (OS). Ordered logistic regression analyzed the correlation between PNI and cytokine release syndrome (CRS) as an outcome variable. Cox regression models were used for univariate and multivariate analyses.

Results:

Of the 506 patients, 271 were male and 235 were female, with a median age of 51 years (range 13-86 years). 173 patients (34.3%) had an ECOG score ≥2, 204 (40.3%) had an IPI score ≥3, and 460 (90.9%) were Ann Arbor stage ≥III. Following CAR-T therapy, 388 patients (76.7%) experienced CRS, with 46 (7.5%) having CRS grades 3-5, and 24 (4.7%) experienced ICANS, with 13 (2.6%) having ICANS grades ≥3.

Univariate analysis showed that PNI, IPI score, ECOG score, CRS, and ICANS were influencing factors on lymphoma patient outcomes with CAR-T therapy (P &lt; 0.05).

Multivariate analysis revealed that aside from IPI score and ECOG score being independent risk factors for OS (P &lt; 0.005), PNI was also an independent risk factor affecting OS (HR = -0.07, 95% CI = -0.10, -0.04, P &lt; 0.005).

Ordered logistic regression analysis showed a negative correlation between PNI and CRS occurrence, with a correlation coefficient of -0.5143, P &lt; 0.05, 95% CI (-0.879, -0.149).

The median follow-up time was 381 days (range 4-1959 days), and the median survival time was 33.44 months (95% = 0.44, 0.55). The 3-year and 5-year overall survival rates were 48.98% and 47.27%, respectively. Kaplan-Meier survival analysis identified 43.05 as the optimal cutoff value for OS prediction. The high PNI group (&gt;43.05, 285 cases, 56.3%) and low PNI group (≤43.05, 221 cases, 43.7%) had 5-year overall survival rates of 58.48% and 33.97%, respectively. Log Rank test demonstrated significant statistical differences in OS between the low and high PNI groups (P &lt; 0.005). Kaplan-Meier survival analysis also showed a statistical difference in progression-free survival (PFS) between the low and high PNI groups (P &lt; 0.005).

Conclusion:

PNI can predict CRS, PFS, and OS in patients with malignant lymphoma undergoing CAR-T therapy, providing important clinical significance in assessing patient prognosis.