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Erschienen in: BMC Cancer 1/2021

Open Access 01.12.2021 | Research

Prognostic significance of the postoperative prognostic nutritional index in patients with glioblastoma: a retrospective study

verfasst von: Yoon Jung Kim, Hyongmin Oh, Sang Jin Lee, Kyung-Min Kim, Ho Kang, Chul-Kee Park, Hee-Pyoung Park

Erschienen in: BMC Cancer | Ausgabe 1/2021

Abstract

Background

The prognostic nutritional index (PNI) reflects immunonutritional status. We evaluated the effects of postoperative PNI and perioperative changes in the PNI on overall survival (OS) in glioblastoma (GBM) patients.

Methods

Demographic, laboratory, and clinical data were retrospectively collected from 335 GBM patients. Preoperative and postoperative PNIs were calculated from serum albumin concentration and lymphocyte count, which were measured within 3 weeks before surgery and 1 month after surgery. Patients were classified into high (n = 206) or low (n = 129) postoperative PNI groups according to the postoperative PNI cutoff value and further classified into four groups according to the cutoff values of the preoperative and postoperative PNIs, as follows: Group HH (both high PNIs, n = 92), Group HL (high preoperative and low postoperative PNI, n = 70), Group LH (low preoperative and high postoperative PNI, n = 37), and Group LL (both low PNIs, n = 136).

Results

The median OS was significantly longer in the high postoperative PNI (PNI ≥ 50.2) group than the low postoperative PNI (PNI < 50.2) group (24.0 vs. 15.0 months, p <  0.001). In multivariate analysis, high postoperative PNI was a significant predictor of OS. OS was significantly longer in Group HH than in Group LL and seemed longer in Group HH than in Group HL and in Group LH than in Group LL. OS was not different between Groups HH and LH or between Groups HL and LL.

Conclusions

High postoperative PNI was associated with improved OS and perioperative changes in PNI may provide additional important information for prognostic prediction in GBM patients.
Hinweise

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1186/​s12885-021-08686-8.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
GBM
Glioblastoma
KPS
Karnofsky performance status
OS
Overall survival
MGMT
O6-methylguanine-DNA methyltransferase
PNI
Prognostic nutritional index
IDH
Isocitrate dehydrogenase
IRB
Institutional Review Board
Group HH
High preoperative PNI + high postoperative PNI group
Group HL
High preoperative PNI + low postoperative PNI group
Group LH
Low preoperative PNI + high postoperative PNI group
Group LL
Low preoperative PNI + low postoperative PNI group

Background

Glioblastoma (GBM) is the most common malignant primary brain tumor characterized by high mortality and recurrence. Despite the use of Stupp protocol (postoperative radiotherapy plus concomitant and adjuvant temozolomide chemotherapy), the median overall survival (OS) is as short as 14.6 months [1, 2]. Moreover, there is a survival gap even among patients who are managed with the same treatment protocol. Numerous studies have attempted to identify prognostic factors in GBM patients. Well-documented prognostic parameters associated with a favorable outcome in patients with GBM include young age, high preoperative Karnofsky performance status (KPS) score, genetic composition (i.e., isocitrate dehydrogenase [IDH] mutation, O6-methylguanine-DNA methyltransferase [MGMT] promoter methylation), and more extensive surgical resection [315].
The prognostic nutritional index (PNI) is calculated from the serum level of albumin and lymphocyte count and reflects immunonutritional status [16]. Literature reviews have revealed the controversy about the role of preoperative PNI in predicting the prognosis of GBM patients [1722]. However, no study has investigated the prognostic significance of the postoperative PNI in GBM patients. Moreover, the effects of combination of preoperative and postoperative PNIs on postoperative survival have not been studied in such patients. A few studies focusing on the prognostic role of postoperative PNI have reported that it is predictive of prognosis in patients with hepatocellular carcinoma and lung cancer and a high postoperative PNI is associated with a good prognosis in such patients [23, 24]. These studies indicate that the postoperative PNI rather than preoperative PNI can better reflect postoperative general conditions in patients undergoing hepatic and pulmonary tumor surgeries. The postoperative PNI may depend on postoperative clinical course and management. Previous studies demonstrated that postoperative complications had a negative relationship with the postoperative PNI [23, 25].
Therefore, we hypothesized that a high postoperative PNI would be associated with improved OS in GBM patients. This study evaluated the effects of the postoperative PNI and the change in perioperative PNI on OS in GBM patients and whether the postoperative PNI is a significant prognostic factor. We also identified demographic and clinical factors that contribute to the prognostic significance of postoperative PNI.

Methods

This retrospective study was conducted after approval from the Institutional Review Board of Seoul National University Hospital (number: 2101–092-1189). The Institutional Review Board of Seoul National University Hospital waived the requirement for written informed consent because of the retrospective design of the study. We included patients newly diagnosed with histological GBM who underwent brain tumor surgery under general anesthesia (total intravenous anesthesia with propofol and continuous infusion of remifentanil) at Seoul National University Hospital from 2010 to 2016. Exclusion criteria were patients with surgical mortality, recurrent GBM, missing data on preoperative or postoperative laboratory examinations, and infectious or chronic autoimmune disease or glucocorticoid replacement, which can affect the immune system and nutritional status. In addition, patients with concurrent steroid use at the time of PNI calculations were excluded.

Data collection

We retrospectively reviewed the electronic medical records of subjects to collect data categorized into four parts: preoperative data, including demographic information, comorbidities, daily activities, represented by the KPS score, preoperative laboratory findings (serum albumin concentration and lymphocyte count); intraoperative data, including surgical time and intraoperative transfusions; postoperative data, including postoperative laboratory findings (albumin levels and lymphocyte count), KPS score at hospital discharge, the extent of surgical resection, which was radiographically confirmed and classified into gross total resection, near-total resection, subtotal resection, partial resection, and biopsy, and postoperative adjuvant therapy (application and completion of the Stupp protocol [1], radiotherapy only, chemotherapy only, or none); and gene expression profiles, including MGMT methylation, epidermal growth factor receptor amplification, and the IDH mutation.

Definition

The PNI was defined as 10 × albumin level (g/dL) + 0.005 × lymphocyte count (106/L) [16], and the preoperative and postoperative PNIs were calculated from preoperative (within 3 weeks before surgery) and postoperative (1 month after surgery but before postoperative adjuvant therapy) laboratory findings, respectively. High and low PNIs were defined when a PNI value was greater than or equal to the optimal cutoff value of the PNI and less than the optimal cutoff value, respectively. OS was defined as the time interval from the date of surgery to the date of death, or the date of the last follow-up.

Statistical analysis

The Kolmogorov-Smirnov test was used to evaluate the normality of the distributions of all continuous variables. The Student’s t-test was used to analyze normal variables, and the Mann-Whitney U-test was used to compare skewed variables. Categorical variables were analyzed using the chi-square or Fisher’s exact test. The OS of GBM patients was analyzed using the Kaplan-Meier method. Univariate analysis was first performed to identify predictive factors of postoperative survival in GBM patients. Variables with a p-value < 0.1 in univariate analysis and well-known significant factors of postoperative survival of GBM were entered into multivariate logistic regression analysis with the forward stepwise conditional method. Receiver operating characteristic curve analysis were performed to identify the optimal cutoff values of the preoperative and postoperative PNIs to predict OS. The optimal cut-off point was determined by maximizing the sum of sensitivity and specificity (Youden’s index). To evaluate the effects of a change in the perioperative PNI on OS, patients were reclassified into four groups according to the cutoff values of the preoperative and postoperative PNIs: Group HH (high preoperative PNI + high postoperative PNI group), Group HL (high preoperative PNI + low postoperative PNI group), Group LH (low preoperative PNI + high postoperative PNI group), and Group LL (low preoperative PNI + low postoperative PNI group). Differences in OS among the four groups were analyzed using the Kaplan-Meier method and the log-rank test. The alpha value was adjusted with the Bonferroni correction to compensate for multiple comparisons, and the statistical significance of the alpha value was < 0.008 (0.05/6). The relationships between preoperative and postoperative PNIs and other clinical characteristics were evaluated with the Pearson correlation test.
All statistical analyses were conducted using SPSS statistical software for Windows, version 25.0 (IBM, Armonk, NY, USA) and R version 4.0.3 (The R Foundation for Statistical Computing, Vienna, Austria). A p-value < 0.05 was considered significant.

Results

During the entire study period, 495 patients were diagnosed with histologically confirmed GBM. Among them, 160 patients (95 underwent surgery under local anesthesia, two died, 44 were lost to follow-up due to transfer to other local hospitals for postoperative adjuvant therapy, and 19 had incomplete laboratory data related to the PNI) were excluded from the study. Finally, 335 patients were included in the data analysis.
The preoperative and postoperative PNIs revealed area under the curve values of 0.579 (95% CI; 0.496–0.661; P = 0.061) and 0.599 (0.522–0.676; P = 0.018) for OS, respectively. The optimal cut-off values for the preoperative and postoperative PNIs were 50.1 and 50.2, respectively.
Patients in the high preoperative PNI group were younger than those in the low preoperative PNI group, and the high preoperative PNI group had a greater proportion of male patients and patients with preoperative and postoperative KPS score ≥ 70 than the low preoperative PNI group. (Table 1). Patients were younger, more patients had preoperative and postoperative KPS scores ≥70, underwent more frequent gross total resection of GBM and completion of Stupp protocol in the high postoperative PNI group.
Table 1
Demographic, perioperative laboratory results, genetic, and postoperative treatment-related data
 
Preoperative PNI
Postoperative PNI
Low (PNI < 50. 1) (n = 173)
High (PNI ≥ 50. 1) (n = 162)
P value
Low (PNI < 50. 2) (n = 206)
High (PNI ≥ 50. 2) (n = 129)
P value
Age (yr)
56.5 ± 13.9
52.3 ± 13.7
0.005
57.2 ± 13.9
50.1 ± 12.9
<  0.001
<  60
96 (55.5%)
108 (66.7%)
0.047
108 (52.4%)
96 (74.4%)
<  0.001
< 70
136 (78.6%)
148 (91.4%)
0.002
161 (78.2%)
123 (95.3%)
<  0.001
Male gender (n)
91 (52.6%)
104 (64.2%)
0.041
114 (55.3%)
81 (62.8%)
0.218
BMI (kg/m2)
22.6 ± 3.2
23.5 ± 3.2
0.019
22.7 ± 3.2
23.6 ± 3.1
0.021
ASA physical status (n)
  
0.116
  
0.235
 I
57 (32.9%)
63 (38.9%)
 
69 (33.5%)
51 (39.5%)
 
 II
93 (53.8%)
88 (54.3%)
 
112 (54.4%)
69 (53.5%)
 
 III
23 (13.3%)
11 (6.8%)
 
25 (12.1%)
9 (7.0%)
 
Comorbidity (n)
 Hypertension
45 (26.0%)
46 (28.4%)
0.713
58 (28.2%)
33 (25.6%)
0.697
 Diabetes mellitus
16 (9.2%)
9 (5.6%)
0.281
16 (7.8%)
9 (7.0%)
0.957
 Cardiac disease
13 (7.5%)
6 (3.7%)
0.204
16 (7.8%)
3 (2.3%)
0.050
 Respiratory disease
7 (4.0%)
4 (2.5%)
0.544
11 (5.3%)
0 (0.0%)
0.008
 Liver disease
9 (5.2%)
8 (4.9%)
1.000
11 (5.3%)
6 (4.7%)
0.981
 Renal disease
3 (1.7%)
0 (0.0%)
0.249
3 (1.5%)
0 (0.0%)
0.287
 Cerebrovascular disease
12 (6.9%)
6 (3.7%)
0.285
10 (4.9%)
8 (6.2%)
0.777
 Extracranial malignancy
11 (6.4%)
4 (2.5%)
0.113
12 (5.8%)
3 (2.3%)
0.177
Daily activity
 Preoperative KPS score
80 (70–90)
90 (80–90)
0.009
85 (70–90)
90 (80–90)
0.023
  ≥ 70 (n)
144 (83.2%)
154 (95.1%)
0.001
177 (85.9%)
121 (93.8%)
0.040
 KPS score at hospital discharge
90 (70–90)
90 (80–90)
0.024
90 (70–90)
90 (80–90)
<  0.001
  ≥ 70 (n)
145 (83.8%)
146 (90.1%)
0.122
166 (80.6%)
125 (96.9%)
<  0.001
Laboratory findings
 Albumin (g/dL)
  Preoperative
3.9 ± 0.4
4.4 ± 0.3
<  0.001
4.1 ± 0.4
4.3 ± 0.4
<  0.001
  Postoperative
3.9 ± 0.4
4.1 ± 0.3
<  0.001
3.8 ± 0.4
4.3 ± 0.2
<  0.001
  Delta (preoperative – postoperative)
−0.01 ± 0.49
−0.26 ± 0.38
<  0.001
−0.23 ± 0.49
0.03 ± 0.35
<  0.001
Lymphocyte count (106/L)
 Preoperative
1280.8 ± 495.2
2064.3 ± 667.6
<  0.001
1521.9 ± 646.7
1879.6 ± 736.3
<  0.001
  < 1500 (n)
127 (73.4%)
37 (22.8%)
<  0.001
116 (56.3%)
48 (37.2%)
0.001
 Postoperative
1558.5 ± 646.7
1827.0 ± 578.6
<  0.001
1422.4 ± 466.5
2113.1 ± 621.4
<  0.001
  < 1500 (n)
89 (51.4%)
47 (29.0%)
<  0.001
120 (58.3%)
16 (12.4%)
<  0.001
 Delta (preoperative – postoperative)
− 277.8 ± 680.1
237.3 ± 755.2
<  0.001
99.5 ± 702.4
−233.4 ± 808.5
<  0.001
PNI
 Preoperative
45.5 ± 3.6
54.4 ± 3.2
<  0.001
48.2 ± 5.2
52.4 ± 5.3
<  0.001
 Postoperative
46.8 ± 5.2
50.6 ± 5.1
<  0.001
45.4 ± 4.0
53.8 ± 3.0
<  0.001
 Delta (preoperative – postoperative)
−1.3 ± 5.8
3.8 ± 5.2
<  0.001
2.8 ± 5.9
−1.4 ± 5.3
<  0.001
Surgery time (hr)
4.4 ± 1.3
4.5 ± 1.4
0.581
4.4 ± 1.4
4.5 ± 1.2
0.471
Intraoperative transfusion (n)
41 (23.7%)
25 (15.4%)
0.077
54 (26.2%)
12 (9.3%)
<  0.001
Tumor resection (n)
  
0.642
  
0.072
 Gross total
102 (59.0%)
107 (66.0%)
0.220
119 (57.8%)
90 (69.8%)
0.037
 Near total
24 (13.9%)
16 (9.9%)
0.338
24 (11.7%)
16 (12.4%)
0.973
 Subtotal
32 (18.5%)
28 (17.3%)
0.883
42 (20.4%)
18 (14.0%)
0.178
 Partial
8 (4.6%)
7 (4.3%)
1.000
11 (5.3%)
4 (3.1%)
0.422
 Biopsy
7 (4.0%)
4 (2.5%)
0.544
10 (4.9%)
1 (0.8%)
0.056
Gene expression profiles (n)
 MGMT Promoter methylation*
97 (56.4%)
80 (50.0%)
0.291
110 (54.2%)
67 (51.9%)
0.774
 EGFR amplification
45 (26.0%)
41 (25.6%)
1.000
53 (25.9%)
33 (25.8%)
1.000
 IDH mutation
19 (12.2%)
30 (19.6%)
0.103
27 (14.4%)
22 (18.0%)
0.493
Postoperative new neurologic deficit (n)
43 (24.9%)
24 (14.8%)
0.031
54 (26.2%)
13 (10.1%)
<  0.001
Postoperative treatment (n)
  
0.033
  
0.030
 Stupp protocol
151 (87.3%)
151 (93.2%)
0.102
180 (87.4%)
122 (94.6%)
0.050
 Completed
99 (57.2%)
104 (64.2%)
0.219
113 (54.9%)
90 (69.8%)
0.009
 Chemotherapy
6 (3.5%)
5 (3.1%)
1.000
7 (3.4%)
4 (3.1%)
1.000
 Radiotherapy
1 (0.6%)
3 (1.9%)
0.357
2 (1.0%)
2 (1.6%)
0.641
 None
15 (8.7%)
3 (1.9%)
0.007
17 (8.3%)
1 (0.8%)
0.002
Data are expressed as number (proportion), mean ± standard deviation, or median (interquartile range). BMI body mass index, ASA American Society of Anesthesiologists, KPS Karnofsky performance status, delta; preoperative –postoperative, PNI prognostic nutritional index, MGMT O6-methylguanine-DNA methyltransferase, EGFR epidermal growth factor receptor, IDH isocitrate dehydrogenase. Data are expressed as number (proportion), mean ± standard deviation, or median (interquartile range). *: n = 172 in preoperative PNI low group, n = 160 in preoperative PNI high group, and n = 203 in postoperative PNI low group. †: n = 160 in preoperative PNI high group, and n = 205 in postoperative PNI low group, and n = 128 in postoperative PNI high group. : n = 156 in preoperative PNI low group, n = 153 in preoperative PNI high group, and n = 187 in postoperative PNI low group, and n = 122 in postoperative PNI high group
A total of 233 (69.6%), 92 (27.5%), and 66 (19.7%) patients survived 1, 3, and 5 years after surgery, respectively. Fifty-seven (17.0%) patients survived at the last follow-up. The median (95% CI) OS of all patients was 19.0 (15.9–22.1) months. The duration of OS was significantly longer in the high postoperative PNI group than in the low postoperative PNI group (median OS: 24.0 vs. 15.0 months, P <  0.001, Fig. 1A) and longer in the high preoperative PNI group than in the low preoperative PNI group (median OS: 22.0 vs. 17.0 months, P = 0.008, Fig. 1B).
Significant predictive factors for postoperative OS in multivariate analysis (Table 2) were age <  60 years (odd ratio [95% CI], 2.07 [1.02–4.21]; P = 0.045), high postoperative PNI (2.17 [1.14–4.10]; P = 0.018), MGMT promoter methylation (2.61 [1.33–5.11]; P = 0.005), and completion of the Stupp protocol (5.39 [2.18–13.27]; P <  0.001).
Table 2
Univariate and multivariate analysis for predictive factors associated with postoperative overall survival in glioblastoma patients
 
Univariate analysis
Multivariate analysis*
Odds ratio
95% CI
P value
Odds ratio
95% CI
P value
Age < 60 years (n)
2.50
1.29–4.84
0.007
2.07
1.02–4.21
0.045
Male gender (n)
0.59
0.33–1.05
0.070
   
Preoperative KPS score ≥ 70 (n)
1.07
0.42–2.69
0.891
   
KPS score at hospital discharge ≥70 (n)
3.11
0.93–10.43
0.066
   
Albumin (g/dL)
 Preoperative
1.93
0.93–4.01
0.078
   
 Postoperative
3.43
1.47–7.98
0.004
   
High preoperative PNI (PNI ≥ 50. 1) (n)
2.26
1.25–4.10
0.007
   
High postoperative PNI (PNI ≥ 50. 2) (n)
2.39
1.34–4.26
0.003
2.17
1.14–4.10
0.018
Extent of surgical resection
  
0.083
   
 Gross total resection
Reference
     
 Near total resection
0.09
0.01–0.70
0.021
   
 Subtotal resection
0.64
0.39–1.40
0.268
   
 Partial resection
0.26
0.03–2.03
0.199
   
 Biopsy
0.36
0.05–2.92
0.342
   
Postoperative new neurologic deficit (n)
0.61
0.27–1.35
0.220
   
Gene expression profiles (n)
 MGMT Promoter methylation
2.62
1.40–4.89
0.003
2.61
1.33–5.11
0.005
 IDH mutation
2.08
1.03–4.19
0.041
   
Completed Stupp protocol (n)
5.84
2.56–13.32
<  0.001
5.39
2.18–13.27
<  0.001
KPS Karnofsky performance status, PNI prognostic nutritional index, MGMT O6-methylguanine-DNA methyltransferase, IDH isocitrate dehydrogenase, RT radiation therapy. *Multivariate analysis with the forward stepwise conditional method was performed and male gender, preoperative KPS score ≥ 70, KPS score at hospital discharge ≥70, preoperative and postoperative serum albumin level, high preoperative PNI, the extent of surgical resection, postoperative new neurologic deficit, IDH mutation, were adjusted. Nagelkerke R2 statistic in step 4 is 0.208
In subgroup analysis, OS was significantly longer in the high postoperative PNI group than in the low postoperative PNI group in patients who were male (P <  0.001) and young (age < 60 years, P = 0.003), had MGMT promoter methylation (P = 0.004), received gross total resection of GBM (P = 0.001), had a postoperative KPS score ≥ 70 (P = 0.005), and received postoperative chemoradiotherapy, P = 0.001, Fig. 2A-F). OS was significantly longer in the high preoperative PNI group than in the low preoperative PNI group in patients who were male and young, had an unmethylated MGMT promoter, underwent gross total resection, had a preoperative KPS score ≥ 70 and postoperative KPS score <  70, and received adjuvant chemoradiotherapy (Supplementary Fig. 1).
A significant difference in OS was observed among the four groups (P = 0.001, Fig. 3). The median (95% CI) OS durations were 24.0 (18.9–29.1), 15.0 (9.7–20.3), 24.0 (14.1–33.9), and 15.0 (11.2–18.4) months in Group HH (n = 92), Group HL (n = 70), Group LH (n = 37), and Group LL (n = 136), respectively. A significant difference in OS was observed between Group HH and Group LL (P <  0.001). OS was longer in Group HH than in Group HL (P = 0.029), and in Group LH than in Group LL (P = 0.027). OS was not significantly different between Groups HH and LH or between Groups HL and LL.
Both preoperative and postoperative PNIs showed significant negative correlation with age (r = − 0.214 and − 0.321, P <  0.001 in both). Preoperative PNI was positively correlated with preoperative and postoperative KPS scores (r = 0.221 and 0.147, P <  0.001 and P = 0.007 respectively) but was not correlated with completion of the Stupp protocol. Postoperative PNI was positively correlated with preoperative and postoperative KPS scores and completion of the Stupp protocol (r = 0.231, 0.442, and 0.215, P <  0.001 respectively). The delta PNI (preoperative PNI – postoperative PNI) was negatively correlated with the duration of OS in patients with mortality (r = − 0.160, P = 0.007). Also, the delta PNI was higher in patients with 1-year and 3-year mortalities, compared with those with 1-year and 3-year survivals (1-year: 2.2 ± 6.2 vs. 0.7 ± 5.9, P = 0.029; 3-year: 1.6 ± 6.0 vs. 0.1 ± 6.0, P = 0.040).

Discussion

Despite recent advancements in diagnostic and therapeutic techniques, GBM is associated with poor clinical outcomes. Thus, it is relevant to identify potential prognostic serum biomarkers for poor clinical outcomes in GBM patients to help stratify patients. The PNI, which is easily calculated from laboratory tests, is a simple, economic, and convenient parameter for that purpose. This is the first study to evaluate the effects of postoperative PNI and perioperative changes in the PNI on prognosis in patients with GBM. This study demonstrated that high postoperative PNI was a significant independent predictor of OS in GBM patients and the change in the perioperative PNI helped predict the postoperative prognosis.
In clinical practice, various nutritional indices incorporating serum albumin concentration have been used to reflect nutritional status including PNI, the albumin/globulin ratio, and nutritional risk index [20, 23, 24, 26, 27]. PNI is an immunonutritional indicator. A recent study demonstrated that nutritional status was associated with postoperative survival in patients with GBM, and PNI rather than other nutritional indices robustly reflected the nutritional status [22]. However, All previous studies investigating the relationship between the PNI and prognosis of GBM focused only on the effect of preoperative PNI on OS and reported inconsistent results [1722]. In contrast with previous studies, we evaluated the prognostic significance of the postoperative PNI in GBM patients and found a positive association between postoperative PNI and OS. Since GBM is characterized by rapid progression, quick and complete surgical resection is the treatment of choice. In our clinic, when a patient was suspected of GBM, the surgery was performed as soon as possible. It took an average of 7 days, up to 10 days, from the visit of the suspected patient to the surgery. Therefore, intensive nutritional intervention was practically available in the postoperative period in patients with GBM. Moreover, we think that postoperative PNI can better reflect postoperative general conditions than preoperative PNI and that improving nutritional status just before starting postoperative adjuvant therapy (for example, the Stupp protocol) can be helpful in achieving a favorable outcome. For the reason, we chose postoperative PNI and investigated its association with prognosis in patients with GBM.
In the present study, some results showed that the postoperative PNI might take an advantage over the preoperative PNI in predicting prognosis in GBM patients. First, a high postoperative PNI was an independent prognostic factor for GBM in multivariate analysis, whereas a high preoperative PNI was not. Second, the high postoperative PNI was related to increased survival in the subgroups of MGMT promoter methylation and postoperative KPS score ≥ 70, while the high preoperative PNI increased survival in the subgroups of MGMT promoter unmethylation and postoperative KPS score <  70. It is well known that MGMT promoter methylation and high KPS score were associated with favorable outcomes in patients with GBM [3, 8, 10, 12, 13]. Third, a significant difference in OS was observed among the four groups according to perioperative changes in the PNI. In other words, patients in Group HH (high preoperative and high postoperative PNI) showed significantly better OS than those in Group LL. OS was likely to be better in Group HH than Group HL, and in Group LH than in Group LL. However, OS was not significantly different between Groups HH and LH or between Groups HL and LL. Similar to our results, previous retrospective studies have demonstrated that the combination of the preoperative and postoperative PNI played an important role in predicting the precise postoperative prognosis in patients with various malignant tumors [25, 27, 28]. Moreover, the delta PNI showed a significant negative correlation with the duration of OS in patients with mortality. Namely, it was significantly higher in patients with 1-year and 3-year mortalities than those without respectively. Finally, completion of the Stupp protocol was positively correlated with postoperative PNI, not preoperative PNI. In this study, completion of the Stupp protocol was the most powerful predictor of favorable outcomes in patients with GBM. Similarly, previous studies have been highlighted the importance of completion of the Stupp protocol in predicting a favorable prognosis in GBM patients [1, 2]. Taken together, our results suggest that although both PNIs played a key role in predicting OS in GBM patients, the postoperative PNI rather than the preoperative PNI may provide more useful information for predicting GBM prognosis.
An important component of the PNI is the serum level of albumin, one of the simplest and most studied factors representing nutritional status. The postoperative serum level of albumin was associated with OS in GBM patients in univariate analysis, but it was not a predictor in multivariate analysis. Previous studies investigating the association between preoperative serum albumin concentration and prognosis of GBM reported that low serum albumin concentration was an independent poor prognostic factor [6, 29, 30]. Lymphocytes, which are the other component of the PNI, play a key role in cell-mediated immunity. Cell-mediated immunosuppression is well documented in GBM patients [31, 32]. GBM itself affects the number and function of T-lymphocytes. Cancer-induced chronic inflammation is associated with increased tumor proliferation and metastasis, and also has an immunosuppressive effect with a reduced lymphocyte count and impaired lymphocyte function [33, 34]. Hematopoiesis of lymphocytes can also be affected by nutritional status and anti-cancer treatment. Their production in bone marrow significantly decreases in patients who are protein malnourished [35, 36]. Postoperative adjuvant radiotherapy and chemotherapy inhibit proliferation of hematopoietic progenitor cells and block differentiation into lymphocytes, leading to lymphopenia. A previous clinical investigation reported a close relationship between postoperative treatment-related lymphopenia and a poor prognosis of GBM in elderly patients [37]. Taken together, these findings suggest that perioperative interventions, such as aggressive nutritional support before surgery and during the early postoperative period, may improve the prognosis of GBM patients by increasing both of the PNIs.
In this study, the postoperative PNI was calculated from serum albumin concentration and lymphocyte count, which were measured at 1 month postoperatively but before the commencement of postoperative adjuvant therapy. The postoperative PNI reflected the immune-nutritional status of the patients who had recovered from the surgery and were ready for postoperative adjuvant therapy (chemotherapy and/or radiotherapy). Our results showed that postoperative PNI was positively correlated with postoperative KPS score and completion of the Stupp protocol. GBM patients with poor nutritional status can have poor functional status and decreased functional reserves to endure various postoperative surgical stress responses. Also, they can be vulnerable to the adverse effects of postoperative adjuvant therapy, resulting in poor tolerance to adjuvant therapy and subsequent poor clinical outcomes. Although the Stupp protocol increases survival time, the standard Stupp protocol might be too aggressive to be tolerable for malnourished GBM patients. In this study, the incidence of completed Stupp protocol was significantly lower in patients with low postoperative PNI. In clinical practice, when deciding on individualized postoperative treatment options for patients with GBM, various factors such as perioperative functional status, patient age, immunonutritional status, and tolerability to the treatment should be considered [38].
Our study had some potential limitations. First, as this was a non-randomized retrospective study, there was a possibility of unexpected selection bias. In addition, the data were collected from a single institution. Second, low Nagelkerke R2 values in multivariate analysis to predict postoperative survival suggest that clinically valid prognostic parameters may have been omitted. Also, the discrimination power of postoperative PNI as a single predictive factor was poor. However, combined analysis of preoperative and postoperative PNIs helped stratify patients by providing the precise prognosis for patients with GBM. Third, patients who underwent a GBM biopsy under local anesthesia were excluded from the data analysis because anesthetics can affect OS and disease-free survival of various cancers [39, 40]. Therefore, caution is needed when interpreting our results.

Conclusions

In conclusion, a high postoperative PNI was associated with improved postoperative OS in GBM patients. Combined analysis of preoperative and postoperative PNIs may provide additional supportive information on postoperative prognosis in such patients. A further large-scaled prospective study is needed to confirm our results and determine whether perioperative interventions to increase both PNIs would improve the prognosis of GBM patients.

Acknowledgements

None.

Declarations

This study was approved by the Institutional Review Board of Seoul National University Hospital (number: 2101–092-1189). This study was conducted in accordance with the declaration of Helsinki. The Institutional Review Board of Seoul National University Hospital waived the requirement for written informed consent because of the retrospective design of the study.
None.

Competing interests

The authors have no conflicts of interest to declare that are relevant to the content of this article.
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Metadaten
Titel
Prognostic significance of the postoperative prognostic nutritional index in patients with glioblastoma: a retrospective study
verfasst von
Yoon Jung Kim
Hyongmin Oh
Sang Jin Lee
Kyung-Min Kim
Ho Kang
Chul-Kee Park
Hee-Pyoung Park
Publikationsdatum
01.12.2021
Verlag
BioMed Central
Erschienen in
BMC Cancer / Ausgabe 1/2021
Elektronische ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-021-08686-8

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