METHODS
101 patients diagnosed with PC who were diagnosed or treated in our center between 2014 and 2024
were included in the study. The values of prognostic nutritional index (PNI), neutrophil-to-lymphocyte
ratio (NLR), platelet-to-lymphocyte ratio (PLR), Gustave Roussy immune score (GRIm-s), and
eosinophil-to-monocyte ratio (EMR) were calculated according to laboratory parameters at the time of
diagnosis. Survival and regression analyses were performed inter-groups for each variable.
RESULTS
Cut-off values were calculated for GRIm-s, PNI, NLR, PLR, hemoglobin, albumin, lactate dehydrogenase,
and EMR. In terms of survival analyses, GRIm-s, PNI, hemoglobin, NLR, albumin, and PLR were
statistically significant for OS (p=0.00, p=0.03, p=0.032, p=0.00, p=0.00, p=0.029). In the multivariate
Cox regression analysis, GRIm-s was the most powerful variable affecting OS independently (HR: 2.538,
95% CI: 1.558-4.135, p:0.000).
CONCLUSION
GRIm-s is a reliable and prognostic value in terms of survival in PC. Besides, the predictive ability of that
score is much better than other values.
Keywords: Gustave Roussy immune score; pancreatic carcinoma; prognostic nutritional index; systemic inflamatuary score
In this case, the factors that have an impact may be the
tumor microenvironment and genetic and epigenetic
changes that vary from person to person. The main cells
found in the tumor microenvironment are fibroblasts,
endothelial cells, and inflammatory cells. In parallel
with this dominance situation, there is a desmoplasticfixed
extracellular matrix, impaired angiogenesis, and
ineffective anti-cancer immunity around pancreatic
cancer.[
Due to limited treatment options and short survival
in pancreatic cancer, cheaper, practical, non-invasive indirect
methods with prognostic prediction are also being
investigated. The oldest and proven parameter is CA19-
9. Tumor burden in pancreatic cancer and biliary tract
malignancies has predictive importance in disease follow-
up and treatment response evaluation.[
Our hypothesis in this study is that the GRIm-s,
one of the laboratory parameters evaluated for pancreatic
cancer survival, will be more predictive than other
parameters and can be used practically and cheaply in
clinical practice.
Patient Selection
One hundred and one patients diagnosed with pancreatic
cancer who received diagnosis and/or treatment at
our center between January 2014 and January 2024 were
included in the study. Criteria for inclusion in the study
included being over 18 years of age, having a pathological
diagnosis of pancreatic cancer (adenocarcinoma, neuroendocrine carcinoma), applying to our center
during the diagnosis or treatment phase, having the
pathology report accessible, having hemogram and biochemistry
laboratory results available before the surgical
procedure, knowing the initial stage of the disease, having
the date of death or the last follow-up date available,
having no additional malignancy at the time of diagnosis,
having no known autoimmune disease at the time of
diagnosis, and having no medication use that would affect
laboratory parameters. Survival time was calculated
from the date of initial pathology (determined by biopsy
or surgery) to the date of death or last follow-up.
GRIm-s and PNI Calculation
GRIm-s was obtained by scoring NLR, LDH, and albumin
values. Groups were created as 0-1 and 2-3 by giving
a score for the value above (for NLR and LDH) or below
(for albumin) the cut-off values of these calculated values.
PNI calculation: It was done as [10×serum albumin
(g/dL)]+[0.005×lymphocyte count per microliter].
Statistical Analysis
In terms of factors affecting survival, variables such as
age, gender, disease stage, tumor location, number of
metastases, operation status, blood group, hemoglobin,
albumin, LDH, EMR, NLR, PLR, PNI, and GRIm-s were
analyzed. Receiver operating characteristic (ROC) analysis
was performed for the cut-off values of numerical
variables, and since there were statistically insignificant
results, the average values were taken as the cut-off value.
Data are given as frequency, percentage, mean ± standard deviation, and median (min-max). The suitability of the data for normal distribution was evaluated with the Shapiro-Wilk test and histogram and q-q graphs. Chi-square tests were used for comparisons between groups. Kaplan-Meier survival analysis and Cox regression methods were used to determine and compare overall survival. Hazard rates were calculated with 95% confidence intervals. Data analysis was evaluated with IBM SPSS version 21 (SPSS Inc, Chicago, IL, USA). A level of p<0.05 was considered significant.
The mean values for the numerical variables hemoglobin,
albumin, LDH, EMR, NLR, PLR, and
PNI were 13.18, 38.78, 259.23, 0.258, 3.8, 166.99, and
47.93, respectively. The GRIm-s of 64 of the patients
(63.4%) was in the 0?1 group. Overall, 77.2% of all patients
were deceased (Table
Survival analyses were performed in terms of NLR,
PLR, PNI, and GRIm-s. While the median survival of
the group with an NLR value <3.8 was 18 months, the
median survival of the >3.8 group was 8 months (Fig.
One of the remarkable survival results relates to
blood type. OS for O, A, B, and AB blood groups was
14 months, 11 months, 5 months, and 70 months, respectively
(p=0.004) (Fig.
When the factors affecting survival were analyzed in
univariate Cox regression analysis, stage, operation status,
number of metastases, blood group, hemoglobin,
albumin, NLR, PLR, PNI, and GRIm-s were found to
be statistically significant (p values: 0.001, 0.002, 0.000,
0.011, 0.055, 0.000, 0.000, 0.029, 0.002, and 0.002, respectively).
Among these, the number of metastases and
GRIm-s were determined to be independent factors affecting
survival in multivariate Cox regression analysis
(HR: 1.389, 95% CI: 1.165?1.657, p=0.000; HR: 2.538,
95% CI: 1.558-4.135, p=0.000, respectively) (Table
In the study by Basoglu et al.,[
In another study conducted by Ma et al.[
MPS is an evaluation method very similar to GRIm-s
and has almost the same variables. Although LDH evaluation
within GRIm-s may make this scoring more
powerful, it may show false elevations in patients with
comorbidities and/or synchronous cancer. The pathological
correlation conducted by Ma et al.[
In a different study, Imaoka et al.[
LDH, an indirect indicator of anaerobic glycolysis
and hypoxia, was associated with treatment resistance
in the study by Koukourakis et al.[
In the meta-analysis conducted by Zhao et al.,[
When examining the relationship between blood
groups and cancer, historical studies report disease
distribution by blood group. In a study by Macafee,
pancreatic cancer was less common in blood group
A and more common in blood group B compared to
the normal population.[
Limitations of the Study
The limitations of our study include its retrospective
nature, limited number of patients, single-center
scope, and non-specificity to disease stage and treatment
modality. Its strengths include random patient
selection, comparison of laboratory parameters with
one another, and the ability to provide predictions for
clinical conditions such as blood type and the number
of metastases, which are limited in the literature.
Acknowledgements: We would like to express our gratitude to our hospital management and IT team for the hospital data system used in the data collection process.
Ethics Committee Approval: The study was approved by the Kayseri City Hospital Non-interventional Clinical Rese Authorship contributions: Concept - H.B.G.; Design - A.A.; Supervision - H.B.G.; Materials - A.A.; Data collection and/or processing - H.B.G.; Data analysis and/or interpretation - H.B.G.; Literature search - A.A.; Writing - H.B.G.; Critical review - A.A.
Conflict of Interest: All authors declared no conflict of interest.
Use of AI for Writing Assistance: No AI technologies utilized.
Financial Support: None declared.
Peer-review: Externally peer-reviewed.