Combination of Baseline and Variation of Prognostic Nutritional Index Enhances the Survival Predictive Value of Patients With Advanced Non-Small Cell Lung Cancer Treated With Programmed Cell Death Protein 1 Inhibitor

Abstract

Background
Low baseline prognostic nutritional index (PNI) scores are associated with poor survival for various malignancies; however, they vary based on the cohort and time resulting in inaccurate results. We determined the predictive value of the PNI score variations in addition to the baseline PNI scores for patients with advanced non-small cell lung cancer (NSCLC) who received programmed cell death protein 1 (PD-1) inhibitor.

Methods
We retrospectively analysed 115 patients with advanced NSCLC who received PD-1 inhibitor. The median follow-up period was 28 months. Patients were clustered into four groups based on the combined PNI scores (combination of baseline and variation of PNI scores): ΔPNI-L-L, ΔPNI-L-H, ΔPNI-H-L, and ΔPNI-H-H subgroups. For instance, if PNI scores of patients with high baseline PNI score increased from baseline to 6 weeks after treatment, they were included in the ΔPNI-H-H subgroup. Cox regression models were used to identify the factors associated with survival.

Results
The baseline PNI score was only related to the overall survival (OS) (P = .026), and not to the overall response rate (ORR) (P = .299) and progression-free survival (PFS) (P = .207). The ORR was associated with the combined PNI scores (P = .017). A multivariable Cox regression analysis confirmed that the combined PNI scores were independent factors for PFS (ΔPNI-L-H, 12 months, hazard ratio [HR] = 0.449, P = .009; ΔPNI-H-L, 14 months, HR = 0.500, P = .019; and ΔPNI-H-H, 17 months, HR = 0.390, P = .012; vs ΔPNI-L-L, 8 months) and OS (ΔPNI-L-H, 27 months, HR = 0.403, P = .019; ΔPNI-H-L, 28 months, HR = 0.369, P = .010; and ΔPNI-H-H, not reached, HR = 0.087, P = .002; vs ΔPNI-L-L, 15 months).

Conclusions
Patients with high baseline PNI and increased PNI score had the better survival outcome. On dynamic monitoring and comprehensive assessment, the combined PNI scores significantly enhanced the survival predictive ability of patients with NSCLC treated with PD-1 inhibitor.

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Clinical Medicine Insights: Oncology
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DOI: 10.1177/11795549221137134
Introduction
Lung cancer has the highest mortality rate and the second
highest incidence rate worldwide, accounting for 13% of all
cancer diagnoses and 23% of all cancer-related deaths.1 Non-
small cell lung cancer (NSCLC) accounts for 85% of all lung
cancers and commonly presents at an advanced stage during
initial diagnosis. The use of programmed cell death protein 1
(PD-1) and programmed death ligand 1 (PD-L1) in targeted
immuno-oncology has revolutionised and reformed the treat-
ment pattern.2 Drugs targeting and binding to PD-1 and
PD-L1 (such as nivolumab plus ipilimumab, pembrolizumab,
atezolizumab, and cemiplimab) as first-line treatment for
advanced or metastatic NSCLC with driver gene negativity
have been approved by the United States Food and Drug
Administration. The lack of predictive indicators is an impor-
tant reason for unsatisfactory immunotherapy outcomes, unlike
those in targeted therapy. At present, different methods to
assess PD-L1 expression of pembrolizumab, nivolumab, dur-
valumab, and atezolizumab have been adopted in the clinic.3 In
the real world, not all patients with positive PD-L1 and high
tumour mutational burden (TMB) expression can benefit from
immunotherapy. Some elderly, weak, or diseased patients are
unable to undergo biopsy for assessing PD-L1 expression or
TMB; thus, next-generation sequencing and whole exome
Combination of Baseline and Variation of Prognostic
Nutritional Index Enhances the Survival Predictive Value
of Patients With Advanced Non-Small Cell Lung Cancer
Treated With Programmed Cell Death Protein 1 Inhibitor
Qiyu Fang1,2 , Jia Yu2, Jie Luo2, Qinfang Deng2, Bin Chen2,
Yay i He 2, Jie Zhang2 and Caicun Zhou2
1Medical College of Soochow University, Soochow, China. 2Department of Medical Oncology,
Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University
School of Medicine, Shanghai, China.
ABSTRACT
BACKGROU ND: Low baseline prognostic nutritional index (PNI) scores are associated with poor survival for various malignancies; however,
they vary based on the cohort and time resulting in inaccurate results. We determined the predictive value of the PNI score variations in addi-
tion to the baseline PNI scores for patients with advanced non-small cell lung cancer (NSCLC) who received programmed cell death protein
1 (PD-1) inhibitor.
METHODS: We retrospectively analysed 115 patients with advanced NSCLC who received PD -1 inhibitor. The median follow-up period was
28 months. Patients were clustered into four groups based on the combined PNI scores (combination of baseline and variation of PNI
score s): ΔPNI-L-L, ΔPNI-L-H, ΔPNI-H-L, and ΔPNI- H-H subgroups. For instance, if PNI scores of patients with high baseline PNI score
increased from baseline to 6 weeks after treatment, they were included in the ΔPNI-H- H subgroup. Cox regression models were used to iden-
tify the factors associated with survival.
RE S ULTS : The baseline PNI score was only related to the overall survival (OS) (P = .026), and not to the overall response rate (ORR)
(P = .299) and progression-free survival (PFS) (P = .207). The ORR was associated with the combined PNI scores (P = .017). A multivariable
Cox regression analysis confirmed that the combined PNI scores were independent factors for PFS (ΔPNI-L-H, 12 months, hazard ratio
[HR] = 0.449, P = .0 09; ΔPNI- H-L, 14 months, HR = 0. 500, P = .019; and ΔPNI- H-H, 17 months, HR = 0. 390, P = .012; vs ΔP NI-L-L, 8 mont hs)
and OS (ΔPNI- L-H, 2 7 months, HR = 0.40 3, P = .019; ΔPNI- H-L, 28 months, H R = 0.369, P = .010; and ΔPNI- H-H, not reached, HR = 0.087,
P = .002; vs ΔPNI- L-L, 15 months).
CONCLUSIONS: Patients with high baseline PNI and increased PNI score had the better survival outcome. On dynamic monitoring and
comprehensive assessment, the combined PNI scores significantly enhanced the survival predictive ability of patients with NSCLC treated
with PD-1 inhibitor.
KEYWORDS: Non-small cell lung cancer, prognostic nutritional index, programmed cell death protein 1 inhibitor, survival, baseline,
variation
RECEIVED: June 15, 2022. ACCEPTED: Oct ober 18, 2022 .
TYPE: Original Research Article
FUNDING: The author(s) di sclose d receip t of the foll owing na ncial su pport fo r the
researc h, author ship, and /or pu blicati on of this ar ticle: This stud y was supp orted, i n part,
by grants fr om the Nat ional Nat ural Sci ence Foun dation of C hina (nos 81871865 and
81802255) and the General Project of Clinical Research of Shanghai Pulmonary Hospital
(FKLY2002 6).
DECLARATION OF CONFLICTING INTERESTS: The author(s) declared no potential
conic ts of interest with r espect t o the resea rch, auth orship, an d/or publicati on of this ar ticle.
CORRESPONDING AUTHORS: Jie Zhang, De partm ent of Medi cal Onc ology, Sha nghai
Pulmona ry Hosp ital, Tongji U niversi ty Medi cal Scho ol Cance r Institu te, Tongji Unive rsity
Schoo l of Medic ine, 507 Zhe ngmin Ro ad, Shang hai 2004 37, China. Email:
zhangji e2172@163.c om Caic un Zhou, De partme nt of Medi cal Onc ology, Shan ghai
Pulmona ry Hosp ital, Tongji U niversi ty Medi cal Scho ol Cance r Institu te, Tongji Unive rsity
Schoo l of Medic ine, 507 Zhe ngmin Ro ad, Shang hai 2004 37, China. Email:
caicunzhoudr@163.com
1137134ONC0010.1177/11795549221137134Clinical Medicine Insights: OncologyFang et al
research-article2022

2 Clinical Medicine Insights: Oncology
sequencing are subsequently warranted, which could result in a
huge economic burden on these patients. Therefore, finding
more sensitive and affordable predictive biomarkers for anti-
PD-1 in immunotherapy is warranted.
Although characteristics of the tumour itself and tumour
microenvironment are important for determining the biomark-
ers of immunotherapy, host-related factors, particularly the
nutritional and immune status, cannot be ignored. Recent
studies have demonstrated that the nutritional and immune
status of patients with tumours is equally important for cancer
progression and prognosis.4,5
The prognostic nutritional index (PNI) score is calculated
using the serum albumin level and peripheral lymphocyte
count,6 which can indicate the nutritional and immune status
of patients with tumours. The PNI score possesses the charac-
teristics of being non-invasive, has real-time acquisition, and is
economical in the clinic, thereby ensuring convenient applica-
tion and promotion. Several studies have confirmed that the
PNI score is associated with the tumour response and progno-
sis of patients with NSCLC undergoing surgery, chemother-
apy, or chemoradiotherapy.7-9 However, the correlation between
the PNI score and immunotherapy remains poorly studied. A
few studies have demonstrated that a low pre-treatment PNI
score is closely correlated with early progression and is an inde-
pendent risk factor for the survival of patients with advanced
NSCLC receiving PD-1 inhibitor treatment.10,11
Owing to cohort-dependence and time-dependence, the
reported optimal PNI cut-off scores have been highly variable.
Therefore, we could not apply the baseline PNI score to deter-
mine its predictive value for a given patient. This study deter-
mined the predictive value of PNI score variations in addition
to baseline PNI scores for patients with NSCLC who received
PD-1 inhibitor.
Methods
Patients
We performed a retrospective analysis of all consecutive
patients with NSCLC at the Shanghai Pulmonary Hospital
between March 2017 and September 2018. Eligible patients
for inclusion in this study had unresectable disease according to
the International Association for the Study of Lung Cancer
guidelines, Eighth Edition. All the patients had received anti-
PD-1 antibody treatment for at least two cycles. All the follow-
up data of the patients were obtained.
Age at diagnosis, sex, baseline Eastern Cooperative
Oncology Group Performance Status scale score, PD-L1
expression, date of progression, date of death, and date of last
follow-up were obtained from the patients’ electronic medical
records. Routine blood test results and blood biochemical index
score before treatment and six weeks after treatment (0 w and 6
w) were also collected. The neutrophil-to-lymphocyte ratio
(NLR) score, defined as the absolute neutrophil count divided
by the absolute lymphocyte count, was prospectively obtained.
The ΔNLR was defined as the variation between the baseline
NLR value and the values collected at six weeks (after two
treatment cycles). Although the cut-off values of the NLR
score were not constant in all the studies, a value of 5 was
widely applied and adopted for distinguishing between the
high and low groups.12 PD-L1 expression of the tumour sam-
ple at diagnosis was detected by immunohistochemistry
according to standard practice (clone 22C3; DAKO, Denmark).
Considering the percentage of viable tumour cells with partial
or complete membrane staining, the tumour proportion score
(TPS) ⩾ 1% was defined as PD-L1 positive status. This study
was approved by the institutional ethical review board of the
Shanghai Pulmonary Hospital (no. K22-241). The require-
ment for informed consent was waived by the ethical review
board as this was a non-interventional study using anonymised
collected data.
Tumour responses were estimated using the immune
response evaluation criteria in solid tumour (iRECIST) guide-
lines. Progression-free survival (PFS) was defined as the time
between the initiation of PD-1 inhibitor treatment and disease
progression or death. Overall survival (OS) refers to total sur-
vival, that is, the time from the first diagnosis in our hospital to
death for any reason or the last follow-up of the patient. The
median follow-up period was 28 .
PNI
The PNI score was defined as the serum albumin level
(g/L) + 5 × peripheral lymphocytes (109/L) within three days
before each anti-PD-1 antibody treatment administration.
These scores were retrospectively obtained in this study. The
receiver-operating characteristic (ROC) curve was calculated
based on the pre-treatment PNI score. The variable value corre-
sponding to the maximum value of the Youden index was the
PNI cut-off score. The ΔPNI score was defined as the difference
between the baseline PNI score and the PNI score at six weeks
(after two treatment cycles) collected before anti-PD-1 antibody
treatment administration. Patients were clustered into four
groups based on the combined PNI scores (combination of base-
line and variation of PNI scores). If the PNI scores of the patients
with a high baseline PNI score increased from baseline to
six weeks after treatment, they were included in the ΔPNI-H-H
subgroup. Patients with high baseline PNI score who experi-
enced a decrease in the PNI score after treatment were included
in the ΔPNI-H-L subgroup. Patients with low baseline PNI
score who experienced an increase in the PNI score after treat-
ment were included in the ΔPNI-L-H subgroup; those who
experienced a decrease in the PNI score after treatment were
included in the ΔPNI-L-L subgroup (Figure 1).
Statistical analysis
Categorical variables are summarised as numbers and percent-
ages and were compared using the chi-square or the Fisher

Fang et al 3
exact test. Continuous variables were analysed using the
Student t-test. Survival curves were drawn using the Kaplan-
Meier method to estimate the probability of PFS and OS. The
Cox regression analysis with calculated hazard ratios (HRs)
and 95% confidence interval (CI) was applied to adjust for
potential confounders. A heatmap was used to demonstrate the
trends of the PNI scores. Statistical significance was set at
P ⩽ .05. IBM SPSS 22.0 (IBM Corp., Armonk, NY, USA) and
GraphPad Prism 9.0.0 were used for the statistical analyses and
graphing.
Results
Baseline patient characteristics
A total of 115 patients were enrolled in this study. Their baseline
characteristics are summarised in Table 1. The median age at the
time of diagnosis was 61.4 years (±8.3 years), and 83.4% (n = 96)
were males. Lung adenocarcinoma accounted for most the cases
(63.4%; n = 73). Squamous cell carcinoma was 26.1% (n = 30). Not
otherwise specified (NOS) cancer was noted in 12 (10.4%)
patients. Except for 14 patients (12.2%) with stage IIIB/IIIC, all
the other patients were in stage IV. The most common metastatic
sites were bone (40.8%; n = 47), lungs (30.4%; n = 35), pleura
(21.7%; n = 25), and the central nervous system (10.4%; n = 12).
Eight patients had adrenal gland metastases, eight had liver metas-
tases, and another eight had distant lymph node metastasis.
In our group, except for four patients with Kirsten rat sar-
coma virus (KRAS) mutation and one patient with epidermal
growth factor receptor (EGFR) 20 insertion, no driver gene
mutation was observed in the rest of the patients. Programmed
death ligand 1 expression was found to be positive in fifty-nine
(51.3%) patients. Sixty-four (55.6%) patients were treated
according to first-line treatment. Patients who received immu-
notherapy (anti-PD-1) combined with chemotherapy, immu-
notherapy combined with antiangiogenesis treatment, and
monotherapy accounted for 57.4% (n = 66), 15.6% (n = 18), and
27.0% (n = 31) of the total participants, respectively. Baseline
characteristics of the patients are shown in Table 1.
The median PFS and OS for all the patients were 13 months
(95% CI = 10.849-15.151) and 28 months (95% CI = 23.937-
32.063), respectively. The survival rates of all the patients at
one year and three years were 72.2% and 9.7%, respectively.
The ROC curve showed that the PNI cut-off score was
48.775 (Figure 2A). The area under the ROC curve was 0.608
(P = .046), and the corresponding sensitivity and specificity
were 0.604 and 0.629, respectively. According to the cut-off
value (48.775), 55 patients (47.9%) had low pre-treatment
(baseline) PNI scores and 60 patients (52.2%) had high pre-
treatment (baseline) PNI scores. The relationship between the
PNI scores and clinical characteristics of the patients is shown
in Table 1. There were no significant differences in the baseline
characteristics of the two groups.
Figure 1. Groups according to the combined PNI score.
PNI indicates prognostic nutritional index.

4 Clinical Medicine Insights: Oncology
Table 1. Baseline characteristics of the patients.
CHARACTERISTICS ALL PATIENTS (n) % PNI >48.775 (n) %PNI ⩽48.775 (n) %P
Tot a l 115 60 52.2 55 47. 8
Age
⩽65 78 67.8 44 73.3 34 61.8 0 .18 7
>65 37 32.2 16 26.7 21 38.2
Sex
Male 96 83.5 54 90.0 42 76.4 0.091
Female 19 16.5 610.0 13 23.6
ECOG
0 88 76.5 46 76.7 42 76.4 0.969
1-2 score 27 23.5 14 23.3 13 23.6
Histology
LUAD 73 63.5 40 66.7 33 60.0 0. 674
LUSC 30 26 .1 15 25.0 15 2 7. 3
Other 12 10.4 58.3 712.7
Stage
IIIB/IIIC 14 12.2 711 .7 712 .7 1.000
IV 101 87.8 53 88.3 48 87.3
Metastatic sites
Lung 35 30.4 16 26.7 19 34.5 0.796
Pleura 25 21.7 12 20.0 13 23.6
Liver 87. 0 46.7 47.3
Bone 47 40.9 26 43.3 21 38.2
CNS 12 10.4 46.7 814.5
Adrenal gland 87.0 3 5.0 5 9.1
Distant lymph node metastasis 87.0 58.3 35.5
Line of therapy
1 64 55.7 37 61.7 26 47. 3 0 .121
⩾251 44.3 23 38.3 29 52.7
PD-L1 expression
Negative 56 48.7 32 53.3 24 43.6 0.299
Positive 59 51.3 28 46.7 31 56.4
Regimen
Combination with chemotherapy 66 57. 4 39 65.0 27 49 .1 0 .13 5
Monotherapy 31 27.0 15 25.0 16 29 .1
Combination with antiangiogenic 18 15.7 610.0 12 21.8
Abbreviations: CNS, central nervous system; ECOG, Eastern Cooperative Oncology Group; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; PD-L1,
programmed death ligand 1; PNI, prognostic nutritional index.

Fang et al 5
Correlation of tumour response and survival
outcomes with baseline PNI scores
Based on the level of the baseline PNI scores, the overall
response rates (ORRs) of the patients at high and low levels
were 53.3% (32/60) and 43.6% (24/55), respectively; however,
the difference was not statistically significant (P = .299). The
disease control rates for the patients with high and low baseline
PNI scores were 95% (57/60) and 94.5% (52/55), respectively
(not significantly different; P = .913).
The PFS median values were 15 (95% CI = 12.926-17.074)
and 10 (95% CI = 7.617-12.383) months for the patients with
high and low baseline PNI scores, respectively. Although the
difference was large, it was not statistically significant (P = .207).
However, the baseline PNI scores were closely associated with
the OS. The median OS of the patients at the high baseline
level was much longer than that of the patients at the low base-
line level (30 months [95% CI = 23.949-36.051] vs 19 months
[95% CI = 8.414-29.586]; P = .026) (Figure 3A and B).
Correlation of the tumour response and survival
outcomes with the variations of the PNI scores
We examined whether the variations in the PNI scores from
baseline to six weeks correlated with the response to treatment.
An increase in the PNI score was observed in 55 patients
(defined as the ΔPNI-H subgroup), whereas a decrease in the
PNI score was observed in 60 patients (defined as the ΔPNI-L
subgroup). The ORR of the ΔPNI-H subgroup (33/55; 60.0%)
was higher than that of the ΔPNI-L subgroup (23/60; 38.3%;
P = .025). In addition, the difference in the disease control rate
was not statistically significant (P = .913).
Furthermore, the patients were divided into two groups
according to their tumour respo.nse. Increased PNI scores were
more often observed in the partial response group (33/56;
58.9%) than in the stable disease group (19/53; 35.8%)
(P = .021) (Figure 4). Patients in the ΔPNI-L subgroup had
significantly worse PFS and OS than those in the ΔPNI-H
subgroup (median PFS: 12 months [95% CI = 8.864-15.136] vs
15 months [95% CI = 10.420-19.580], P = .037; median OS:
25 months [95% CI = 19.974-30.026] vs 36 months [95%
CI = 23.834-48.166], P = .047) (Figure 3C and D).
Predictive ability of the combination of baseline
and variation of PNI scores
Patients were clustered into four groups based on the com-
bined PNI scores (combination of baseline PNI scores and
PNI score variations). The difference in the ORR of the four
subgroups was statistically significant (P = .017): 78.9% (15/19,
ΔPNI-H-H subgroup), 41.5% (17/41, ΔPNI-H-L subgroup),
50% (18/36, ΔPNI-L-H subgroup), and 31.6% (6/19, ΔPNI-
L-L subgroup).
The PFS median values were 8 (95% CI = 5.867-10.133),
12 (95% CI = 7.076-16.924), 14 (95% CI = 12.101-15.899),
and 17 (95% CI = 13.513-20.487) months for the ΔPNI-
L-L, ΔPNI-L-H, ΔPNI-H-L, and ΔPNI-H-H subgroups,
respectively (P = .013). The OS median values were 15 (95%
CI = 11.855-18.145), 27 (95% CI = 13.397-40.603), 28 (95%
CI = 24.032-31.968) months, and not reached for the ΔPNI-
L-L, ΔPNI-L-H, ΔPNI-H-L, and ΔPNI-H-H subgroups,
respectively (P < .001) (Figure 3E and F). Patients in the
ΔPNI-L-H subgroup had longer survival than those in the
ΔPNI-L-L subgroup (PFS: 12 months vs 8 months, P = .019;
Figure 2. The ROC analysis of the baseline PNI scores and combined PNI score to predict the survival of patients with advanced NSCLC treated with
anti-PD-1 immunotherapy. (A) The ROC curve analysis of the baseline PNI score. (B) The ROC curve analysis of the combined PNI score.
NSCLC indicates non-small cell lung cancer; PD-1, programmed cell death protein 1; PNI, prognostic nutritional index; ROC, receiver-operating characteristic.

6 Clinical Medicine Insights: Oncology
OS: 27 months vs 15 months, P = .035). For patients with a
high baseline level (ΔPNI-H-H and ΔPNI-H-L subgroups),
the difference between the PFS values was not statistically
significant (P = .181); however, a significant difference was
found between their OS values (P = .018). For patients with a
decreased PNI score (ΔPNI-H-L and ΔPNI-L-L sub-
groups), the prognosis was worse for patients with a low
baseline PNI score than for patients with a high PNI score
(PFS: P = .009; OS: P = .007). Considering patients with
increased PNI scores (ΔPNI-L-H and ΔPNI-H-H), a sig-
nificant difference was observed between the median OS
values (P = .011); however, no significant difference was
observed in the median PFS values (P = .381). Patients in the
ΔPNI-L-H subgroup appear to have a similar survival rate to
that of patients in the ΔPNI-H-L subgroup (PFS: 12 months
vs 14 months, P = .572; OS: 27 months vs 28.0 months,
P = .911).
The area under the ROC curve of the combined PNI score
(baseline PNI scores combined with the PNI score variations)
was 0.652 (P = .005). The sensitivity and specificity were 0.585
and 0.710, respectively (Figure 2B).
Cox regression model of the survival outcomes
According to the univariable analyses, the Eastern Cooperative
Oncology Group Performance Status Scale Score (HR = 2.022;
95% CI = 1.344-3.043; P = .001), PD-L1 expression positive
(HR = 0.572; 95% CI = 0.376-0.870; P = .009), NLR variation
(HR = 1.529; 95% CI = 1.002-2.331; P = .049), PNI variation
(HR = 0.657; 95% CI = 0.435-0.992; P = .046), and combined
PNI (ΔPNI-L-H, HR = 0.442, 95% CI = 0.242-0.805, P = .008;
ΔPNI-H-L, HR = 0.506, 95% CI = 0.285-0.899, P = .020; and
ΔPNI-H-H, HR = 0.330, 95% CI = 0.160-0.680, P = .003; vs
ΔPNI-L-L) were independent factors for PFS.
Figure 3. Baseline PNI scores and PNI score variations and their effects on the PFS and OS of patients with advanced NSCLC who received PD-1
inhibitor treatment. Kaplan- Meier curves for the PFS and OS (A, B) stratied by the baseline PNI score, (C, D) PNI score variations, and (E, F) combined
PNI score.
NSCLC indicates non-small cell lung cancer; OS, overall survival; PD-1, programmed cell death protein 1; PFS, progression-free survival; PNI, prognostic nutritional index.

Fang et al 7
However, the Eastern Cooperative Oncology Group
Performance Status Scale Score (HR = 2.384; 95% CI = 1.380-
4.120; P = .002), positive PD-L1 expression (HR = 0.507; 95%
CI = 0.292-0.881; P = .016), baseline NLR score (H R = 1.891;
95% CI = 1.083-3.302; P = .025), baseline PNI score
(HR = 0.544; 95% CI = 0.313-0.944; P = .030), and combined
PNI scores (ΔPNI-L-H, HR = 0.421, 95% CI = 0.198-0.894,
P = .024; ΔPNI-H-L, HR = 0.410, 95% CI = 0.195-0.865,
P = .019; and ΔPNI-H-H, HR = 0.079, 95% CI = 0.017-0.358,
P = .001; vs ΔPNI-L-L) were independent factors for OS
(Tables 2 and 3).
The factors that were significant in the univariable analyses
were included in a multivariable Cox regression model. We
found that the combined PNI scores were related to the PFS
(ΔPNI-L-H, HR = 0.449, 95% CI = 0.246-0.822, P = .009;
ΔPNI-H-L, HR = 0.500, 95% CI = 0.280-0.894, P = .019; and
ΔPNI-H-H, H R = 0.390, 95% CI = 0.187-0.814, P = .012; vs
ΔPNI-L-L) and OS (ΔPNI-L-H, HR = 0.403, 95% CI = 0.189-
0.861, P = .019; ΔPNI-H-L, HR = 0.369, 95% CI = 0.173-0.787,
P = .010; and ΔPNI-H-H, HR = 0.087, 95% CI = 0.019-0.396,
P = .002; vs ΔPNI-L-L). Eastern Cooperative Oncology Group
Performance Status Scale Score (PFS, HR = 1.935, 95%
CI = 1.272-2.944, P = .002; OS, HR = 2.115, 95% CI = 1.218-
3.674, P = .008), positive PD-L1 expression (PFS, HR = 0.568,
95% CI = 0.372-0.869, P = .009; OS, HR = 0.493, 95%
CI = 0.281-0.864, P = .014) were found as independent predic-
tive indicators of PFS and OS in the multivariable analysis.
Discussion
The goal of this study was to discover and explore the correla-
tion between the baseline PNI scores and PNI score variations
with immunotherapy for lung cancer. To our knowledge, this is
the first study investigating this relationship. We found the
baseline PNI scores to be only relevant to the OS, and not to
the ORR and PFS. Prognostic nutritional index score varia-
tions and combined PNI scores were associated with the ORR,
PFS, and OS. A multivariable Cox regression analysis con-
firmed that only the combined PNI scores were independent
risk factors for PFS and OS. The combination of the baseline
and variation of the PNI scores significantly enhanced the sur-
vival predictive ability of patients with NSCLC treated with
PD-1 inhibitor. These results can help clinicians in formulat-
ing better treatment strategy making.
The PNI was originally proposed by Smale et al.13 It is
mainly used to evaluate the risk of recurrence and survival fol-
lowing surgical treatment; however, it has not been popularised
owing to its complex calculation. Nevertheless, the formula
used to calculate the PNI score has been simplified by Onodera
et al14 based on the serum albumin level and lymphocyte count.
Recently, a growing number of studies have used the PNI to
determine the prognosis of patients with tumours, including
lung cancer. As relatively a few studies exist on the PNI scores
of patients with NSCLC, the optimal threshold of the PNI
score has not been determined. Owing to the heterogeneity
between patients and small sample sizes, the cut-off scores
reported in different studies are diverse. The critical PNI score
for NSCLC ranges from 45.0 to 52.525.8,15,16 In this study, the
best PNI cut-off score calculated from the ROC curve was
48.775. However, owing to individual patient variation, a mere
standard value across the board cannot be followed. Our
research demonstrated that the median OS of patients with
high baseline PNI scores was much longer than that of patients
with low baseline PNI scores (30 months vs 19 months), similar
to the results of some other studies.8,15,16 A meta-analysis
revealed that a low PNI score was significantly associated with
poor OS for patients with lung cancer.17
However, some studies did not find an association between
the baseline PNI scores and survival outcomes. The predictive
efficacy of the baseline PNI is controversial.18,19 Therefore,
studying PNI score variation during anti-PD-1 treatment is
noteworthy. To the best of our knowledge, no previous studies
have explored PNI score variations as predictors of NSCLC
outcomes treated with PD-1. The baseline PNI scores did not
influence the ORR and PFS in this study; however, the PNI
score variations did demonstrate such an influence. Patients
with an increased PNI score had an ORR of 60.0%, and median
PFS of 15 months, whereas the ORR was 38.3% and median
PFS was 12 months for patients with a decreased PNI score.
An increase in the PNI score indicates a higher response to
anti-PD-1 treatment. The nutritional statuses of patients of
the same stage varied widely when they sought medical advice.
This could imply that either the nutritional status of the
patients were different before they got sick or the time from
illness to the first visit was inconsistent. Some patients under-
went further medical consultations owing to physical examina-
tion. Some patients visit a doctor as soon as they feel unwell,
Figure 4. PNI score variations for patients with NSCLC in groups with
different tumour responses.
NSCLC indicates non-small cell lung cancer; PD, progressive disease; PNI,
prognostic nutritional index; PR, partial response; SD,stable disease.

8 Clinical Medicine Insights: Oncology
Table 2. Cox regression analysis for progression-free survival (PFS).
UNIVARIABLE ANALYSIS MULTIVARIABLE ANALYSIS
HR 95% CI PHR 95% CI P
PFS
Age
⩽65 1
>65 0.942 0. 613 -1. 448 0.785
Sex
Female 1
Male 1.089 0 .63 2 -1. 874 0 .759
ECOG
0 1
1-2 score 2.022 1.344-3.043 0.001 1.9 35 1.2 72-2.9 44 0.002
Histology
LUSC 1
LUAD 0.808 0.504-1.296 0.377
Other 1. 318 0.659-2.637 0.435
Stage
IIIB/IIIC 1
IV 1.10 5 0.573-2.133 0.766
Line of therapy
1 1
⩾21.14 4 0.76 2-1.716 0. 517
Regimen
Combination with chemotherapy 1
Monotherapy 0.952 0.696-1.301 0.756
Combination with antiangiogenic 0.892 0.676 -1.177 0.419
PD-L1 expression
Negative 1 1
Positive 0.572 0.376- 0.870 0.009 0.568 0.372-0.869 0.009
Baseline NLR
Low 1
High 1.14 8 0.720-1.830 0.563
Variation of NLR
Low 1
High 1.529 1.002-2.331 0.049
Baseline PNI
Low 1
(Continued)

Fang et al 9
Table 3. Cox regression analysis for overall survival (OS).
UNIVARIABLE ANALYSIS MULTIVARIABLE ANALYSIS
HR 95% CI PHR 95% CI P
OS
Age (years)
⩽65 1
>65 1.2 32 0 .70 6 - 2 .14 9 0.462
Sex
Female 1
Male 1.18 1 0.575-2.423 0.651
ECOG
0 1
1-2 score 2.384 1. 3 8 0 - 4.12 0 0.002 2 .115 1.2 18 - 3 .6 74 0.008
Histology
LUSC 1
LUAD 1.03 0 0.530 -2.003 0.931
Other 2.075 0.846-5.091 0.111
Stage
IIIB/IIIC 1
IV 1.2 69 0 . 5 4 0 -3 .19 6 0.614
Line of therapy
1 1
⩾20.976 0. 5 68-1.677 0.930
UNIVARIABLE ANALYSIS MULTIVARIABLE ANALYSIS
HR 95% CI PHR 95% CI P
High 0.778 0. 5 2 0 -1.16 6 0.225
Variation of PNI
Low 1
High 0.657 0.435-0.992 0.046
Combined PNI
ΔPNI-L-L 1 1
ΔPN I - L- H 0.442 0.242-0.805 0.008 0.449 0.246-0.822 0.009
ΔPNI-H-L 0.506 0.285-0.899 0.020 0.500 0.280-0.894 0.019
ΔPNI-H-H 0.330 0.160-0.680 0.003 0.390 0.187-0.814 0.0 12
Abbreviations: CI, condence interval; ECOG, Eastern Cooperative Oncology Group; HR, hazard ratio; LUAD, lung adenocarcinoma; LUSC, lung squamous cell
carcinoma; NLR, neutrophil-to-lymphocyte ratio; PD-L1, programmed death ligand 1; PFS, progression-free survival; PNI, prognostic nutritional index.
(Continued)
Table 2. (Continued)

10 Clinical Medicine Insights: Oncology
whereas some delay diagnosis and treatment related to poor
nutritional status owing to various causes, such as neglecting
symptoms, strong tolerance to pain or discomfort, or lack of
medical knowledge. Therefore, the nutritional status at the
baseline of diagnosis cannot be used to comprehensively evalu-
ate the prognosis. Prognostic nutritional index variation may
not only evaluate short-term efficacy but also correlate with
long-term prognosis.
Furthermore, we combined the baseline PNI scores and
PNI score variations and found combined PNI score to be sig-
nificant independent predictive factors of patients with
NSCLC treated with PD-1 inhibitor on univariable and mul-
tivariable analysis. This study revealed that patients with low
level of baseline PNI experienced decreased PNI, the prognosis
of which is the worst (PFS: 8 months, OS: 15 months).
Although patients with high level of baseline PNI score who
showed increased PNI scores had the best survival outcomes
(PFS: 17 months, OS: not reached). Patients with low baseline
and increased variation appear to have a similar prognosis to
that of the patients with high baseline and decreased variation
(PFS: 12 months vs 14 months, OS: 27 months vs 28.0 months).
Based on the combined PNI scores, different strategies should
be adopted. The status of patients in the PNI-L-L subgroup
with low baseline PNI and increased variation, which could be
attributed to insensitivity to immunotherapy, deteriorate dur-
ing immunotherapy, and experienced unfavourable survival
UNIVARIABLE ANALYSIS MULTIVARIABLE ANALYSIS
HR 95% CI PHR 95% CI P
Regimen
Combination with chemotherapy 1
Monotherapy 0.958 0.6 41-1. 432 0.836
Combination with antiangiogenic 0.961 0.663-1.393 0.834
PD-L1 expression
Negative 1 1
Positive 0.507 0.292-0.881 0.016 0.493 0.281-0.864 0. 014
Baseline NLR
Low 1
High 1.8 91 1.083-3.302 0.025
Variation of NLR
Low 1
High 1.2 97 0.742-2.266 0.361
Baseline PNI
Low
High 0.544 0.313-0.944 0.030
Variation of PNI
Low 1
High 0.576 0.3 31-1.0 0 4 0.052
Combined PNI
ΔPNI-L-L 1 1
ΔPN I - L- H 0.421 0.198- 0.894 0.024 0.403 0.189-0.861 0. 019
ΔPNI-H-L 0. 410 0.195-0.865 0 .019 0.369 0.173-0.787 0. 010
ΔPNI-H-H 0.079 0.017-0.358 0.0 01 0.087 0.019-0.396 0.002
Abbreviations: CI, condence interval; ECOG, Eastern Cooperative Oncology Group; HR, hazard ratio; LUAD, lung adenocarcinoma; LUSC, lung squamous cell
carcinoma; NLR, neutrophil-to-lymphocyte ratio; OS, overall survival; PD-L1, programmed death ligand 1; PNI, prognostic nutritional index.
Table 3. (Continued)

Fang et al 11
rate. Thus, treatment strategies should be performed more
carefully in these patients. Patients with high baseline and
increased variation may have relative low tumour burden and
higher response to anti-PD-1 treatment; thus, positive antitu-
mour therapies can be performed. We conducted an in-depth
research of the baseline PNI scores combined with the dynamic
changes in the PNI score and found that the diagnostic effi-
ciency of the ROC curve was better than that of the baseline
PNI scores. A multivariable Cox regression analysis confirmed
that combined PNI scores are independent risk factors for PFS
and OS; however, the baseline PNI score is not an independent
risk factor. Dynamic monitoring and comprehensive assess-
ment of the PNI score may be useful for observing the curative
effect and assessing the prognosis, thereby providing an indi-
vidualised prognosis and implementing the progress of clinical
treatment strategies, which cannot be determined by the base-
line score alone.
The PNI score is an indicator of the immunologic and
nutritional status of patients as it is composed of lymphocytes
and albumin. Biological evidence has suggested that the PNI
score is associated with the immunotherapy outcomes.
Lymphocytes have a vital role in immune surveillance by inhib-
iting the proliferation, invasion, and migration of tumour
cells,20,21 whereas a low lymphocyte count is related to an
impaired antitumour response, CD8+ T-cell cytotoxicity, and
impaired CD4+ helper T-cell function.22 Decreased lympho-
cyte production results in a weak immune response in tumour
cells.23 For patients treated with nivolumab, a high absolute
lymphocyte count was significantly and independently associ-
ated with a better PFS and OS.24,25 These findings confirm
that high lymphocyte counts are significantly related to better
clinical outcomes of the treated patients. Low albumin levels
are associated with weight loss and malnutrition, which are sig-
nificantly associated with unfavourable clinical outcomes.26,27
Considering immunotherapy, serum albumin ⩾3.5 g/dL was
an independent predictor of disease control and survival,
although it was not a predictor of the ORR of patients with
NSCLC who received PD-1 inhibitor treatment.28 Serum
albumin is suppressed by and reflects the chronic systemic
inflammatory response.29,30 Malnutrition caused by increased
tumour metabolism is the most common cause of immunode-
ficiency; malnutrition could result in a nutrient-deficient
tumour microenvironment. The deficiency of essential nutri-
ents can induce immune cells to alter metabolic reprogra-
mming and influence their functions.31 Dysfunctional
metabolisms can also result in an immunosuppressive tumour
microenvironment, thereby affecting the immune responses.32
The PD-L1 expression is a universally acknowledged pre-
dictor. In this study, we also found that positive PD-L1 expres-
sion is also meaningful in multiple COX regression. After
excluding the influence of PD-L1 expression, the combined
PNI scores were still observed as significant predictors.
Programmed death ligand 1 expression can reflect the
tumour-related features, whereas the PNI scores may mirror
the nutritional and immune status of the host. We also studied
NLR, which was also demonstrated to impact the PFS and OS
in the univariable analyses. However, in the final multiple
regression, no significance was observed. The cut-off point
value of 5, which was commonly used, may not be suitable for
all patients. The predictive value of NLR indicator was uncer-
tain. No consensus was reached and written into the guideline
at present.
Despite the advantages of this study, it has several limita-
tions. First, it was a single-centre retrospective study with a
limited sample size, encompassing a certain extent of a hetero-
geneous patient population (different patterns of immunother-
apy). Second, the haematologic parameters may have been
affected by certain concomitant medications that were not
accounted for in this study. Further large-scale, prospective
clinical studies are warranted to verify our conclusions.
Conclusions
In conclusion, we observed two key findings. First, the base-
line PNI scores were only relevant to the OS, and not to the
ORR and PFS. The PNI score variations were associated
with the ORR, PFS, and OS. The combination PNI scores
significantly enhanced the survival predictive ability of
patients with NSCLC treated with PD-1 inhibitor compared
with the baseline and variation scores of PNI alone. Second,
four subgroups of patients with NSCLC with significantly
different survival rates were divided based on the combined
PNI scores, and patients with high baseline PNI and increased
PNI scores had the best survival outcome. Therefore, baseline
PNI scores should not be used as the sole predictor. The com-
bined PNI scores – which are non-invasive, sensitive, and
inexpensive – can be used as predictive indicators of patients
with NSCLC treated with PD-1 inhibitor to guide personal-
ised treatment.
Author Contributions
QF, JZ, and CZ contributed to the conceptualisation. QF and
JY contributed to the methodology. JY and JL contributed to
the software. QF and BC contributed to the validation. QD
contributed to the formal analysis. JY contributed to the inves-
tigation. JZ contributed to the resources. YH contributed to
the curation. QF contributed to the writing – original draft
preparation. QF, YH, and JZ contributed to the writing –
review and editing. QF contributed to the visualisation. JZ and
CZ contributed to the supervision. CZ contributed to the pro-
ject administration. All the authors have read and agreed to the
published version of the manuscript.
Ethics Approval and Consent to Participate
This study was approved by the institutional ethical review
board of the Shanghai Pulmonary Hospital (K22-241,
2022-6-15).

12 Clinical Medicine Insights: Oncology
ORCID iDs
Qiyu Fang https://orcid.org/0000-0002-7001-143X
Jie Luo https://orcid.org/0000-0002-5168-4719
Data Availability Statement
The data sets generated and/or analysed during this study are
available from the corresponding author on reasonable request.
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