Available via license: CC BY-NC-ND 4.0
Content may be subject to copyright.
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
Original Article
The prognostic value of pretreatment prognostic nutritional index
in patients with small cell lung cancer and it’s influencing factors:
a meta-analysis of observational studies
Ai-Min Jiang1^, Rui Zhao2, Na Liu1, Yu-Yan Ma1, Meng-Di Ren1, Tao Tian1, Yu Yao1
1Department of Medical Oncology, The First Afliated Hospital of Xi’an Jiaotong University, Xi’an, China; 2Department of Nutrition and Food
Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Contributions: (I) Conception and design: Y Yao, T Tian; (II) Administrative support: Y Yao; (III) Provision of study materials or patients: AM Jiang,
R Zhao; (IV) Collection and assembly of data: AM Jiang, YY Ma, MD Ren; (V) Data analysis and interpretation: AM Jiang, R Zhao, N Liu; (VI)
Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.
Correspondence to: Yu Yao; Tao Tian. Department of Medical Oncology, The First Afliated Hospital of Xi’an Jiaotong University, No. 277 Yanta
West Road, Xi’an 710061, China. Email: 13572101611@163.com; tiantao0607@163.com.
Background: Numerous studies identified that pretreatment prognostic nutritional index (PNI) was
signicantly associated with the prognosis in various kinds of malignant tumors. However, the prognostic
value of PNI in small cell lung cancer (SCLC) remains controversial. We performed the present meta-
analysis to estimate the prognostic value of PNI in SCLC and to explore the relationship between PNI and
clinical characteristics.
Methods: We systematically and comprehensively searched PubMed, EMBASE, and Web of Science for
available studies until April 17, 2020. Pooled hazard ratios (HRs) and their 95% condence intervals (CIs)
were used to evaluate the correlation between PNI and overall survival (OS) and progression-free survival
(PFS) in SCLC. Odds ratios (ORs) and 95% CIs were applied to evaluate the relationship between clinical
features and PNI in SCLC.
Results: A total of nine studies with 4,164 SCLC patients were included in the meta-analysis. The pooled
data elucidated that lower PNI status was an independent risk factor for worse OS in SCLC (HR =1.43;
95% CI: 1.24–1.64; P<0.001), while there was no signicant correlation between PNI status and PFS (HR
=1.44; 95% CI: 0.89–2.31; P=0.134). We also found that Eastern Cooperative Oncology Group (ECOG)
performance status ≥2 (OR =2.72; 95% CI: 1.63–4.53; P<0.001) and extensive-stage (ES) disease (OR =1.93;
95% CI: 1.62–2.30; P<0.001) were risk factors for low PNI, while prophylactic cranial irradiation (PCI) (OR
=0.53; 95% CI: 0.40–0.69; P<0.001) was a protective factor for low PNI.
Conclusions: Our ndings suggested that low PNI status was closely correlated with the decreased OS
in SCLC. Surveillance on PNI, amelioration of nutritional and immune status, and timely initiation of PCI
may improve the prognosis of SCLC.
Keywords: Prognostic nutritional index (PNI); small cell lung cancer (SCLC); prognosis; meta-analysis
Submitted Apr 23, 2020. Accepted for publication Aug 28, 2020.
doi: 10.21037/jtd-20-1739
View this article at: http://dx.doi.org/10.21037/jtd-20-1739
5728
^ ORCID: 0000-0002-4092-342X.
5719Journal of Thoracic Disease, Vol 12, No 10 October 2020
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
Introduction
Lung cancer is the most common malignant tumor type and
the predominant cause of cancer-related deaths worldwide (1).
The 5-year survival rate is only approximately 17% for
lung cancer (2). Although small cell lung cancer (SCLC)
only accounts for 15% of the pathological types of lung
cancer (3), it is usually characterized by highly aggressive,
early distant metastasis, and genomic instability, with an
overall 5-year survival rate of less than 8% (4,5). Even
though an early response to chemotherapy and radiotherapy
is apparent for SCLC patients, they are predisposed to
early recurrence and widespread metastasis, and most
patients already have metastatic dissemination at the time
of diagnosis, with worrisome prognosis (6,7). Therefore,
it is necessary and vital to find appropriate prognostic
biomarkers to effectively predict the prognosis of SCLC,
which will be of great signicance in improving the survival
rate and implementing individual and precise management
for these patients.
The prognostic nutritional index (PNI) was initially
mentioned in 1980, and it was used to reect the nutritional
and immune status of patients by calculating the serum
albumin level and total lymphocyte count in peripheral
blood (8,9). Mounting evidence has shown that low
PNI status is associated with unfavorable prognosis in
gastrointestinal cancer (10-14), genitourinary cancer
(15,16), gynecological cancer (17,18), and nasopharyngeal
carcinoma (19,20). Recently, several studies revealed that
PNI has a potential prognostic value in non-small cell
lung cancer (NSCLC) (9,21,22). However, there was no
consistent conclusion of whether PNI could be used as a
potential prognostic biomarker in patients with SCLC.
Hence, we presented the following article to estimate the
prognostic value of PNI in SCLC patients and to analyze
the relationship between PNI and clinical characteristics in
these individuals in accordance with the Primary Reporting
Items for Systematic Reviews and Meta-Analyses (PRISMA)
reporting checklist (23) (available at http://dx.doi.
org/10.21037/jtd-20-1739).
Methods
Search strategy
The present meta-analysis was performed according
to the PRISMA statement. We systematically and
comprehensively searched PubMed, EMBASE, and Web of
Science to determine the available literature. The retrieval
time was from database establishment to April 17, 2020.
The following search terms were used for study ltration:
(“the prognostic nutritional index” OR “PNI”) AND (“lung
cancer” OR “lung tumor” OR “lung carcinoma” OR “lung
neoplasm” OR “small cell lung cancer” OR “SCLC”).
Besides, to obtain potential eligible studies, we also manually
searched pertinent references cited in the identied articles.
This meta-analysis was registered in PROSPERO (http://
www.crd.york.ac.uk/PROSPERO) and the registration
number for this article is CRD42020192407.
Eligibility criteria
Studies were considered as eligible based on the following
criteria: (I) patients were diagnosed with SCLC through
histopathological or cytological conrmation; (II) the PNI
value was evaluated before treatment; (III) the correlations
between PNI and overall survival (OS) or progression-free
survival (PFS) were reported in the identied studies; (IV)
hazard ratios (HRs) and their 95% condence intervals (CIs)
were available in the multivariate analysis; (V) case-control
or cohort studies. Studies were excluded if they were
published as reviews, conference abstracts, letters, and case
reports. We also excluded articles not published in English.
Data extraction
Two investigators (AMJ and RZ) extracted the data into
Excel according to standardized formats independently.
Any discrepancies regarding data extraction between them
were resolved by discussion and consulting with another
investigator (NL) for a consensus. The extracted data
mainly included (I) basic characteristics of the included
studies (first author of the study, year of publication,
country, and sample size); (II) clinical characteristics of the
included subjects (gender, age, disease stage, treatment type,
PNI cut-off value, methods of cut-off value determination,
median follow up time, and methods of survival analysis);
(III) HR and its corresponding 95% CI between PNI and
OS or PFS in multivariate analysis.
Quality assessment
The Newcastle-Ottawa Scale (NOS) was applied to quality
assessment for included studies in our meta-analysis (24).
The score for each study was determined from study
selection, comparability assessment, determination of
exposure and outcome, with a total score varies from 0 to 9.
5720 Jiang et al. PNI as a prognostic factor in SCLC
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
Studies with a score of not less than seven were considered
high-quality studies. Two investigators (YYM and MDR)
conducted quality assessment independently.
Statistical analysis
All statistical analyses were performed using STATA version
12.0 (Stata Corporation, College Station, Texas, USA) in
our study. The pooled HRs and 95% CIs were calculated
to estimate the correlation between PNI and the prognosis
of SCLC. Odds ratios (ORs) and 95% CIs were applied
to evaluate the relationship between clinical features and
PNI of SCLC. Cochran’s Q test and I2 test were used to
assess the statistical heterogeneity among the included
studies, with signicant statistical heterogeneity considered
as I2>50% and P≤0.10. A random-effect model was
adopted, and subgroup analyses were performed to explore
the potential sources of heterogeneity when significant
statistical heterogeneity was detected. Otherwise, a fixed-
effect model was adopted for pooled data analysis. We used
sensitivity analysis to assess the stability of the pooled HRs by
excluding each study sequentially from the meta-analysis. We
adopted Begg’s and Egger’s tests to detect publication bias.
Results
Study selection and study characteristics
After a comprehensive and systematic search from electronic
databases, we identied 398 potentially relevant studies. We
remained 316 studies after removing duplicated literature.
Subsequently, we screened titles and abstracts carefully, 304
studies were excluded, including irrelevant studies, reviews,
conference abstracts, and others. After reading the full text,
we excluded three studies that did not meet the inclusion
criteria. Ultimately, a total of nine studies with 4,164 SCLC
patients were included in the present meta-analysis. The
detailed process of literature selection was presented in
Figure 1.
Table 1 presented the detailed characteristics of
the included studies. All the included literature were
retrospective studies and published between 2015 and 2020.
Of these, six studies were conducted in China (4,7,25,28-30),
and the rest three studies were conducted in Japan (26),
South Korea (27), and Turkey (31). Among these, six studies
(4,7,25,27,28,31) enrolled SCLC patients with limited-
stage (LS)/extensive-stage (ES) disease, two studies (26,29)
enrolled patients with ES disease, and only one study (30)
Records identified through database searching
(n=398): PubMed (n=50), Embase (n=84), and Web
of Science (n=264)
Exclusion of duplication (n=82)
Excluded for not relevant, reviews,
meta-analysis, conference reports and
others after title and abstract reviewed
(n=304 )
Exclude literatures that do not meet the
inclusion criteria (n=3)
Included Eligibility Screening ldentification
Literatures after duplicates (n=316)
Full-text articles assessed for eligibility (n=12)
Studies included in meta-analysis (n=9)
Figure 1 Flow chart of literature selection.
5721Journal of Thoracic Disease, Vol 12, No 10 October 2020
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
focused on patients with LS disease. The majority of
patients were male (3,148, 75.6%), and the age of the
subjects was ranged from 16 to 86 years old. The median
sample size was 316 for the included studies (range,
97–1,156), and the median PNI cut-off value was 48.5
(range, 37.5–53.9). There were seven high-quality studies
after performing quality assessment (Table 2).
Correlation between PNI and OS in SCLC
A total of nine studies reported HRs and 95% CIs between
OS and PNI in SCLC. As the results of the heterogeneity
test indicated significant heterogeneity among the studies
(I2=66.8%, P=0.002), we applied a random effect model
for pooled data analysis. The result revealed that low
PNI was an independent risk factor for worse OS in
SCLC (HR =1.43; 95% CI: 1.24–1.64; P<0.001, Figure 2).
Subsequently, we performed subgroup analyses stratified
by country, sample size, tumor stage, treatment type, PNI
cut-off value, the methods of cut-off value determination,
and NOS score to explore the potential sources of
heterogeneity. The results demonstrated that the heterogeneity
was significantly reduced after stratified by sample size and
tumor stage, while there was still significant heterogeneity
across the remaining subgroups (Table 3). Therefore, the
sample size and tumor stage might be the potential sources
of heterogeneity. Besides, the subgroup analyses stratified
by the methods of PNI cut-off value determination revealed
that low PNI was associated with the worse OS when
the cut-off value was determined by ROC curve analysis
(HR =1.48; 95% CI: 1.17–1.87; P=0.001) and other methods
(HR =1.37; 95% CI: 1.09–1.72; P=0.007). However, low PNI
was not signicantly correlated with the OS in SCLC when the
median was used to determine the PNI cut-off value (HR =1.45;
95% CI: 0.86–2.43; P=0.160). Moreover, the results of other
subgroups conrmed that low PNI was signicantly correlated
with unfavorable OS in SCLC, as summarized in Table 3.
Correlation between PNI and PFS in SCLC
There were three studies reported HRs and 95% CIs
between PFS and PNI in SCLC. Since the heterogeneity
test suggested that there was significant heterogeneity
among the included studies (I2=63.3%, P=0.066), we
adopted a random effect model to calculate the pooled data.
The result of the pooled data analysis revealed that there
was no signicant correlation between low PNI and PFS in
SCLC (HR =1.44; 95% CI: 0.89–2.31; P=0.134, Figure 3).
Table 1 All relevant information in the literature
Study Year Country Sample
size
Gender (M/
F) Age [range] Disease
stage Treatment Cut-off
value
Cut-off value
determination
Follow-up
(month)
Survival
analysis HR NOS
score
Hong S (7) 2015 China 724 627/97 59 [19–86] LS/ES C 52.5 Cutoff Finder, Web
application
39.5 (median) OS Reported 7
Hong X (25) 2015 China 919 635/284 56 [16–84] LS/ES C/R 45.0 Other NA OS Reported 6
Minami S (26) 2017 Japan 97 77/20 70.5±8.7 ES C 44.3 ROC analysis NA OS, PFS Reported 7
Go SI (27) 2018 South
Korea
220 193/27 68 [43–86] LS/ES C 40.0 Other 49.2 (median) OS, PFS Reported 8
Jin S (28) 2018 China 1,156 745/411 57 [23–85] LS/ES C+S/C+R 53.9 ROC analysis NA OS Reported 7
Liu Q (29) 2019 China 316 258/58 NA ES C/C+R 52.6 ROC analysis 10.0 (median) OS Reported 7
Zhang JQ (30) 2019 China 172 126/46 58 [23–76] LS R/C+R 53.0 Median 56.0 (median) OS, PFS Reported 8
Zhou T (4) 2019 China 451 389/62 60 [19–82] LS/ES C/R 37.5 ROC analysis NA OS Reported 6
Yenibertiz D (31) 2020 Turkey 109 98/11 59.0±8.2 LS/ES C 48.5 Median NA OS Reported 7
M, male; F, female; LS, limited-stage; ES, extensive-stage; C, chemotherapy; R, radiotherapy; S, surgery; NA, not available; OS, overall survival; PFS, progression-free
survival; HR, hazard ratio; NOS, Newcastle-Ottawa Scale.
5722 Jiang et al. PNI as a prognostic factor in SCLC
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
Correlation between PNI and clinical characteristics in
SCLC
To explore the risk factors of low PNI in SCLC, we
further analyzed the relationship between low PNI status
and clinical characteristics of the enrolled patients in each
eligible study. The analyzed clinical characteristics mainly
included gender (male vs. female), smoking history (smoker
vs. never smoker), Eastern Cooperative Oncology Group
(ECOG) performance status (2–3 vs. 0–1), disease stage
(ES vs. LS), and whether received prophylactic cranial
irradiation (PCI) (PCI vs. non-PCI). We found that ECOG
performance status ≥2 (OR =2.72; 95% CI: 1.63–4.53;
P<0.001, Figure 4A) and ES disease (OR =1.93; 95% CI:
1.62–2.30; P<0.001, Figure 4B) were risk factors for low
PNI. However, PCI was a protective factor for low PNI in
Table 2 Quality assessment conducted according to the NOS for all included studies
Study
Selection Comparability:
comparability
of cohorts on
the basis of
the design or
analysis
Outcome
Total
Representativeness
of the exposed
cohort
Selection
of the non-
exposed
cohort
Ascertainment
of exposure
Demonstration
that outcome of
interest was not
present at start
of study
Assessment
of outcome
Was follow-
up long
enough for
outcomes to
occur
Adequacy
of follow
up of
cohorts
Hong S ★ ☆ ★ ★ ★☆ ★ ★ ★ 7
Hong X ☆ ★ ★ ★ ★☆ ★ ★ ☆ 6
Minami S ★ ★ ★ ★ ★☆ ★ ★ ☆ 7
Go SI ★ ☆ ★ ★ ★★ ★ ★ ★ 8
Jin S ☆ ★ ★ ★ ★☆ ★ ★ ★ 7
Liu Q ★ ☆ ★ ★ ★☆ ★ ★ ★ 7
Zhang JQ ☆ ★ ★ ★ ★★ ★ ★ ★ 8
Zhou T ★ ☆ ★ ★ ★☆ ★ ★ ☆ 6
Yenibertiz D ☆ ★ ★ ★ ★★ ★ ★ ☆ 7
★, represents points of score; ☆, means no score. NOS, Newcastle-Ottawa Scale.
Figure 2 Forest plot of the association between low PNI status and OS in patients with SCLC. PNI, prognostic nutritional index; OS,
overall survival; SCLC, small cell lung cancer.
5723Journal of Thoracic Disease, Vol 12, No 10 October 2020
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
Table 3 Subgroup analyses for low PNI status on OS in SCLC patients
Variables No. of studies Test of association, pooled-HR (95% CI)
Test of heterogeneity
I2 (%) P
Total 9 1.43 (1.24–1.64) 66.8 0.002
Country
China 6 1.37 (1.18–1.59) 69.5 0.006
Others 3 1.62 (1.13–2.31) 56.1 0.103
Sample size
≥400 4 1.23 (1.14–1.34) 0 0.497
<400 5 1.76 (1.44–2.16) 30.2 0.220
Disease stage
LS/ES 6 1.25 (1.14–1.37) 17.4 0.301
ES 2 1.96 (1.58–2.42) 0 1.000
LS 1 1.90 (1.22–2.97) - -
Treatment
Chemotherapy 4 1.53 (1.22–1.93) 44.0 0.147
Mix 5 1.37 (1.14–1.64) 74.4 0.004
PNI cut-off value
>48.5 4 1.53 (1.22–1.92) 75.0 0.007
≤48.5 5 1.35 (1.10–1.65) 61.4 0.035
PNI cut-off value determination
ROC curve analysis 4 1.48 (1.17–1.87) 81.4 0.001
Median 2 1.45 (0.86–2.43) 65.3 0.090
Others 3 1.37 (1.09–1.72) 58.0 0.093
NOS score
≥7 7 1.56 (1.29–1.88) 66.8 0.006
<7 2 1.17 (1.04–1.33) 0 0.790
PNI, prognostic nutritional index; OS, overall survival; SCLC, small cell lung cancer; LS, limited-stage; ES, extensive-stage; NOS,
Newcastle-Ottawa Scale.
SCLC patients (OR =0.53; 95% CI: 0.40–0.69; P<0.001,
Figure 4C). Besides, it showed that gender (OR =1.04; 95%
CI: 0.78–1.37; P=0.798, Figure 4D) and smoking history
(OR =1.10; 95% CI: 0.74–1.65; P=0.631, Figure 4E) were
not signicantly correlated with the occurrence of low PNI.
Sensitivity analysis and publication bias
To evaluate the stability of the pooled data, we performed
sensitivity analysis by omitting each study sequentially
from the meta-analysis. It showed that the pooled HRs
for OS uctuated between the pooled 95% CIs, indicating
the pooled HRs for OS in SCLC were stable (Figure 5).
Subsequently, to detect the existence of publication bias, we
performed Begg’s test and Egger’s test. Begg’s funnel plot
showed good symmetry (Figure 6), indicating that there was
no signicant publication bias. Further quantitative analyses
revealed that the literature included in the present study
did not exist publication bias (Begg’s test: P=0.175, Egger’s
test: P=0.254). Because of limited data are available for low
5724 Jiang et al. PNI as a prognostic factor in SCLC
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
PNI and PFS in the included studies, we did not perform
sensitivity analysis and publication bias test.
Discussion
SCLC is considered as a lethal and highly aggressive
malignant tumor due to its characteristics of rapid tumor
growth, early recurrence, and widespread metastasis (32).
Although significant improvements have been seen in
early detection and treatment in SCLC, it remains a worse
prognosis (32). There is an urgent need to nd a potential
biomarker that can effectively predict the prognosis of
SCLC to improve the clinical outcome. In recent decades,
numerous studies identified that PNI status before
treatment was significantly associated with the survival
outcomes in various malignant tumors. Previously published
meta-analyses also showed that low PNI was closely related
with worse OS (9,21,22) and PFS (21,22) in NSCLC.
Although there is an increasing number of studies reported
that PNI was also related to the prognosis in SCLC, these
results derived from different centers, with controversial
conclusions. Therefore, we conducted this study to evaluate
the prognostic value of PNI in SCLC via meta-analysis,
and to explore the relationship between PNI and clinical
characteristics of these individuals.
A total of nine studies with 4,164 SCLC patients were
included in the current meta-analysis. The result indicated
that low PNI status before treatment was significantly
associated with a reduced OS in SCLC. Consistent with the
pooled result, the results of subgroup analyses showed that
low PNI was also signicantly associated with worse OS in
SCLC when the studies were stratied by country, sample
size, disease stage, treatment type, PNI cut-off value,
and NOS score. However, subgroup analysis stratified by
the methods of PNI cut-off value determination showed
that low PNI was associated with the worse OS when
the cut-off value was determined by ROC curve analysis
and other methods, while low PNI was not significantly
associated with the OS in SCLC when the median was
used to determine the PNI cut-off value. On the one hand,
it may be attributed to the fact that only two studies used
the median to determine the PNI cut-off value in the
include studies. On the other hand, it also suggests that the
appropriate methods should be applied to determine the
cut-off value in future studies. Further sensitivity analysis
and publication bias test showed that the pooled data
with good robustness. Therefore, PNI can be significant
in predicting the OS in SCLC. However, the result of
our study showed that PNI status was not significantly
associated with the PFS in SCLC. Considering only three
studies reported the data for PFS, it needs to be further
validated in the future.
PNI is a widely used nutritional indicator that can
reflect the nutritional and immune status of patients
with malignancy based on the serum albumin level and
total lymphocyte count in peripheral blood (9). Several
potential mechanisms can explain the relationship between
low PNI and poor prognosis in SCLC. First of all, the
serum albumin level in PNI can significantly reflect the
nutritional status of patients. Previous studies reported
that hypoproteinemia was frequently related to reduced
quality of life and diminished life expectancy due to
Figure 3 Forest plot of the association between low PNI status and PFS in patients with SCLC. PNI, prognostic nutritional index; PFS,
progression-free survival; SCLC, small cell lung cancer.
5725Journal of Thoracic Disease, Vol 12, No 10 October 2020
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
immunosuppression and diminished muscle mass in
patients with malignancy (33,34). Furthermore, Paccagnella
et al. also reported that hypoproteinemia in cancer patients
could result in malnutrition and weight loss, thus leading
to a poor prognosis and raised cancer-associated deaths
in these patients (35,36). Moreover, in recent years, the
importance of inflammation and the immune system has
been highlighted in numerous studies (37-39). On the one
hand, inflammation within the tumor microenvironment
is closely related to cancer development and progression
A B
C D
E
Figure 4 Forest plot of the association between low PNI status and clinical characteristics of patients with SCLC. (A) ECOG performance
status, (B) disease stage, (C) PCI, (D) gender, (E) smoking histology. PNI, prognostic nutritional index; SCLC, small cell lung cancer;
ECOG, Eastern Cooperative Oncology Group; PCI, prophylactic cranial irradiation.
5726 Jiang et al. PNI as a prognostic factor in SCLC
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
due to various mechanisms (37). On the other hand,
lymphocyte in peripheral blood can reflect the systemic
inammatory state of patients with malignancy, and it plays
a crucial role in cell-mediated immune response (9). A
recent retrospective study conducted in Japan also reported
that lymphocytopenia was associated with worse OS in LS-
SCLC (39). Taken together, PNI is a signicant prognostic
factor in SCLC.
We then explored the relationship between PNI status
and clinical features of SCLC patients. It revealed that
ECOG performance status ≥2 and ES disease were risk
factors for the occurrence of low PNI. However, PCI was
a protective factor for the occurrence of low PNI. It can
be explained by the fact that patients with worse ECOG
performance status and ES disease are frequently associated
with malnutrition, cachexia, and impaired immune response.
Besides, Suzuki et al. reported that LS-SCLC patients who
received PCI were correlated with favorable OS and higher
total lymphocyte count (39).
To the best of our knowledge, our study is the rst meta-
analysis that comprehensively evaluated the prognostic
value of PNI in SCLC and explored the relationship
between PNI and clinical characteristics in these patients.
However, several limitations in the present study need to
be noticed. First of all, there was signicant heterogeneity
in our pooled analysis, and the results of subgroup analyses
revealed that sample size and disease stage might be the
potential sources of heterogeneity. Furthermore, the
majority of included studies were conducted in Asia, with
retrospective design, lacking prospective studies and data
from other regions. Moreover, considering only three
studies focused on the prognostic value of PNI for PFS in
SCLC, the correlation between PNI and PFS needs to be
further validated. Therefore, large-scale, multicenter, and
well-designed prospective studies are needed to validate our
results.
Conclusions
In summary, PNI can be significant in predicting the
prognosis in SCLC. The current meta-analysis also
suggested that low PNI was associated with ECOG
performance status, disease stage, and PCI. Surveillance
Hong S (2015)
Hong X (2015)
Minami S (2017)
Go SI (2018)
Jin S (2018)
Liu Q (2019)
Zhang JQ (2019)
Zhou T (2019)
Yenibertiz D (2020)
Meta-analysis random-effects estimates (exponential form)
Study ommited
1.19 1.24 1.43 1.64 1.76
Figure 5 Sensitivity analysis of the relationship between low PNI status and OS in patients with SCLC. PNI, prognostic nutritional index;
OS, overall survival; SCLC, small cell lung cancer.
1
0.5
0
−0.5
lnhr
Begg’s funnel plot with pseudo 95% confidence limits
0 0.1 0.2 0.3
s.e. of: Inhr
Figure 6 Funnel plot of publication bias for OS in patients with
SCLC. OS, overall survival; SCLC, small cell lung cancer.
5727Journal of Thoracic Disease, Vol 12, No 10 October 2020
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
on PNI, amelioration of nutritional and immune status,
and timely initiation of PCI may improve the prognosis
of patients with SCLC. More large-scale and multicenter
prospective studies are warranted to validate our results.
Acknowledgments
Funding: None.
Footnote
Reporting Checklist: The authors have completed the
PRISMA reporting checklist. Available at http://dx.doi.
org/10.21037/jtd-20-1739
Conflicts of Interest: All authors have completed the
ICMJE uniform disclosure form (available at http://dx.doi.
org/10.21037/jtd-20-1739). The authors have no conicts of
interest to declare.
Ethical Statement: The authors are accountable for all
aspects of the work in ensuring that questions related
to the accuracy or integrity of any part of the work are
appropriately investigated and resolved.
Open Access Statement: This is an Open Access article
distributed in accordance with the Creative Commons
Attribution-NonCommercial-NoDerivs 4.0 International
License (CC BY-NC-ND 4.0), which permits the non-
commercial replication and distribution of the article with
the strict proviso that no changes or edits are made and the
original work is properly cited (including links to both the
formal publication through the relevant DOI and the license).
See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
References
1. Chen Z, Fillmore CM, Hammerman PS, et al. Non-small-
cell lung cancers: a heterogeneous set of diseases. Nat Rev
Cancer 2014;14:535-46.
2. Chen W, Zheng R, Baade PD, et al. Cancer statistics in
China, 2015. CA Cancer J Clin 2016;66:115-32.
3. Byers LA, Rudin CM. Small cell lung cancer: Where do
we go from here? Cancer 2015;121:664-72.
4. Zhou T, Zhao Y, Zhao S, et al. Comparison of the
prognostic value of systemic inammation response
markers in small cell lung cancer patients. J Cancer
2019;10:1685-92.
5. Sabari JK, Lok BH, Laird JH, et al. Unravelling the
biology of SCLC: implications for therapy. Nat Rev Clin
Oncol 2017;14:549-61.
6. Shepherd FA, Crowley J, Van Houtte P, et al. The International
Association for the Study of Lung Cancer Lung Cancer
Staging Project: Proposals Regarding the Clinical Staging of
Small Cell Lung Cancer in the Forthcoming (Seventh) Edition
of the Tumor, Node, Metastasis Classication for Lung
Cancer. J Thorac Oncol 2007;2:1067-77.
7. Hong S, Zhou T, Fang W, et al. The prognostic nutritional
index (PNI) predicts overall survival of small-cell lung
cancer patients. Tumour Biol 2015;36:3389-97.
8. Buzby GP, Mullen JL, Matthews DC, et al. Prognostic
nutritional index in gastrointestinal surgery. Am J Surg
1980;139:160-7.
9. Li D, Yuan X, Liu J, et al. Prognostic value of prognostic
nutritional index in lung cancer: a meta-analysis. J Thorac
Dis 2018;10:5298-307.
10. Schwegler I, von Holzen A, Gutzwiller JP, et al.
Nutritional risk is a clinical predictor of postoperative
mortality and morbidity in surgery for colorectal cancer.
Br J Surg 2010;97:92-7.
11. Nazha B, Moussaly E, Zaarour M, et al. Hypoalbuminemia
in colorectal cancer prognosis: Nutritional marker or
inammatory surrogate? World J Gastrointest Surg
2015;7:370-7.
12. Nakatani M, Migita K, Matsumoto S, et al. Prognostic
signicance of the prognostic nutritional index in
esophageal cancer patients undergoing neoadjuvant
chemotherapy. Dis Esophagus 2017;30:1-7.
13. Saito H, Kono Y, Murakami Y, et al. Inuence of
prognostic nutritional index and tumor markers on survival
in gastric cancer surgery patients. Langenbecks Arch Surg
2017;402:501-7.
14. Lee SH, Chung MJ, Kim B, et al. The Signicance of the
Prognostic Nutritional Index for All Stages of Pancreatic
Cancer. Nutr Cancer 2017;69:512-9.
15. Fan L, Wang X, Chi C, et al. Prognostic nutritional index
predicts initial response to treatment and prognosis in
metastatic castration-resistant prostate cancer patients
treated with abiraterone. Prostate 2017;77:1233-41.
16. Peng D, Gong YQ, Hao H, et al. Preoperative Prognostic
Nutritional Index is a Signicant Predictor of Survival with
Bladder Cancer after Radical Cystectomy: a retrospective
study. BMC Cancer 2017;17:391.
17. Zhang W, Ye B, Liang W, et al. Preoperative prognostic
nutritional index is a powerful predictor of prognosis in
patients with stage III ovarian cancer. Sci Rep 2017;7:9548.
5728 Jiang et al. PNI as a prognostic factor in SCLC
© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2020;12(10):5718-5728 | http://dx.doi.org/10.21037/jtd-20-1739
18. Haraga J, Nakamura K, Omichi C, et al. Pretreatment
prognostic nutritional index is a signicant predictor
of prognosis in patients with cervical cancer treated
with concurrent chemoradiotherapy. Mol Clin Oncol
2016;5:567-74.
19. Miao J, Xiao W, Wang L, et al. The value of the
Prognostic Nutritional Index (PNI) in predicting outcomes
and guiding the treatment strategy of nasopharyngeal
carcinoma (NPC) patients receiving intensity-modulated
radiotherapy (IMRT) with or without chemotherapy. J
Cancer Res Clin Oncol 2017;143:1263-73.
20. Du XJ, Tang LL, Mao YP, et al. Value of the prognostic
nutritional index and weight loss in predicting metastasis
and long-term mortality in nasopharyngeal carcinoma. J
Transl Med 2015;13:364.
21. Hu Y, Shen J, Liu R, et al. Prognostic value of
pretreatment prognostic nutritional index in non-small cell
lung cancer: A systematic review and meta-analysis. Int J
Biol Markers 2018;33:372-8.
22. Wang Z, Wang Y, Zhang X, et al. Pretreatment
prognostic nutritional index as a prognostic factor in
lung cancer: Review and meta-analysis. Clin Chim Acta
2018;486:303-10.
23. Knobloch K, Yoon U, Vogt PM. Preferred reporting items for
systematic reviews and meta-analyses (PRISMA) statement and
publication bias. J Craniomaxillofac Surg 2011;39:91-2.
24. Stang A. Critical evaluation of the Newcastle-Ottawa scale
for the assessment of the quality of nonrandomized studies
in meta-analyses. Eur J Epidemiol 2010;25:603-5.
25. Hong X, Cui B, Wang M, et al. Systemic Immune-
inammation Index, Based on Platelet Counts and
Neutrophil-Lymphocyte Ratio, Is Useful for Predicting
Prognosis in Small Cell Lung Cancer. Tohoku J Exp Med
2015;236:297-304.
26. Minami S, Ogata Y, Ihara S, et al. Pretreatment Glasgow
prognostic score and prognostic nutritional index predict
overall survival of patients with advanced small cell lung
cancer. Lung Cancer (Auckl) 2017;8:249-57.
27. Go SI, Jeon H, Park SW, et al. Low pre-treatment
nutritional index is signicantly related to poor outcomes
in small cell lung cancer. Thorac Cancer 2018;9:1483-91.
28. Jin S, Cao S, Xu S, et al. Clinical impact of pretreatment
prognostic nutritional index (PNI) in small cell lung cancer
patients treated with platinum-based chemotherapy. Clin
Respir J 2018;12:2433-40.
29. Liu Q, Yang W. Relationship between systemic immune-
inammation index and prognosis of patients with
brain metastases from small cell lung cancer. Tumor
2019;39:649-57.
30. Zhang JQ, Wang YY, Xu KP, et al. Prognostic evaluation
of nutritional indicators in patients with limited-stage
small cell lung cancer. Zhonghua Zhong Liu Za Zhi
2019;41:937-42.
31. Yenibertiz D, Ozyurek BA, Erdogan Y. Is Onodera's
prognostic nutritional index (OPNI) a prognostic factor in
small cell lung cancer (SCLC)? Clin Respir J 2020. [Epub
ahead of print].
32. Gazdar AF, Bunn PA, Minna JD. Small-cell lung cancer:
what we know, what we need to know and the path
forward. Nat Rev Cancer 2017;17:725-37.
33. Soeters PB, Wolfe RR, Shenkin A. Hypoalbuminemia:
Pathogenesis and Clinical Signicance. JPEN J Parenter
Enteral Nutr 2019;43:181-93.
34. Gupta D, Lis CG. Pretreatment serum albumin as a
predictor of cancer survival: a systematic review of the
epidemiological literature. Nutr J 2010;9:69.
35. Paccagnella A, Morassutti I, Rosti G. Nutritional
intervention for improving treatment tolerance in cancer
patients. Curr Opin Oncol 2011;23:322-30.
36. Fruchtenicht AVG, Poziomyck AK, Kabke GB, et al.
Nutritional risk assessment in critically ill cancer patients:
systematic review. Revista Brasileira de terapia Intensiva
2015;27:274-83.
37. Elinav E, Nowarski R, Thaiss CA, et al. Inammation-
induced cancer: crosstalk between tumours, immune cells
and microorganisms. Nat Rev Cancer 2013;13:759-71.
38. Templeton AJ, McNamara MG, Seruga B, et al. Prognostic
role of neutrophil-to-lymphocyte ratio in solid tumors: a
systematic review and meta-analysis. J Natl Cancer Inst
2014;106:dju124.
39. Suzuki R, Wei X, Allen PK, et al. Prognostic
Signicance of Total Lymphocyte Count, Neutrophil-
to-lymphocyte Ratio, and Platelet-to-lymphocyte Ratio
in Limited-stage Small-cell Lung Cancer. Clin Lung
Cancer 2019;20:117-23.
Cite this article as: Jiang AM, Zhao R, Liu N, Ma YY, Ren
MD, Tian T, Yao Y. The prognostic value of pretreatment
prognostic nutritional index in patients with small cell
lung cancer and it’s influencing factors: a meta-analysis of
observational studies. J Thorac Dis 2020;12(10):5718-5728. doi:
10.21037/jtd-20-1739
