Preoperative systemic inflammatory response index as a prognostic marker for distal cholangiocarcinoma after pancreatoduodenectomy

Abstract

BACKGROUND

The relationship between preoperative inflammation status and tumorigenesis as well as tumor progression is widely acknowledged.

AIM

To assess the prognostic significance of preoperative inflammatory biomarkers in patients with distal cholangiocarcinoma (dCCA) who underwent pancreatoduodenectomy (PD).

METHODS

This single-center study included 216 patients with dCCA after PD between January 1, 2011, and December 31, 2022. The individuals were categorized into two sets based on their systemic inflammatory response index (SIRI) levels: A low SIRI group (SIRI < 1.5, n = 123) and a high SIRI group (SIRI ≥ 1.5, n = 93). Inflammatory biomarkers were evaluated for predictive accuracy using receiver operating characteristic curves. Both univariate and multivariate Cox proportional hazards analyses were performed to estimate SIRI for overall survival (OS) and recurrence-free survival (RFS).

RESULTS

The study included a total of 216 patients, with 58.3% being male and a mean age of 65.6 ± 9.6 years. 123 patients were in the low SIRI group and 93 were in the high SIRI group after PD for dCCA. SIRI had an area under the curve value of 0.674 for diagnosing dCCA, showing better performance than other inflammatory biomarkers. Multivariate analysis indicated that having a SIRI greater than 1.5 independently increased the risk of dCCA following PD, leading to lower OS [hazard ratios (HR) = 1.868, P = 0.006] and RFS (HR = 0.949, P < 0.001). Additionally, survival analysis indicated a significantly better prognosis for patients in the low SIRI group (P < 0.001).

CONCLUSION

It is determined that a high SIRI before surgery is a significant risk factor for dCCA after PD.

Key Words: Distal cholangiocarcinoma; Pancreatoduodenectomy; Biomarker; Systemic inflammatory response index; Prognosis

Core Tip: The objective of this research was to evaluate the prognostic relevance of the systemic inflammatory response index (SIRI) in patients diagnosed with distal cholangiocarcinoma (dCCA) post-pancreatoduodenectomy (PD). A retrospective collection of all clinicopathological data was undertaken to further investigate the utility of SIRI in prognostication for dCCA patients post-PD. The results indicated that SIRI could potentially serve as a prognostic indicator for both overall survival and recurrence-free survival in dCCA patients following PD. Elevated levels of SIRI could predict recurrence and long-term survival in dCCA patients, thereby providing valuable guidance for treatment strategies.

INTRODUCTION

Distal cholangiocarcinoma (dCCA) is a type of cholangiocarcinoma that is located between the choledochal duct and about 1.5 cm closer to the ampulla of Vater[1,2]. Pancreatoduodenectomy (PD) is the primary curative treatment approach for patients with dCCA. Nevertheless, even with PD, the 5-year survival rates for dCCA are approximately 30%, primarily because of the considerable morbidity linked to this operation[3]. Late-stage diagnosis and lack of effective treatments worsen the limited prognosis for dCCA patients, making it crucial to improve outcomes for those undergoing PD[4].

New studies show that preoperative clinical variables can be used to create predictive models for cancer prognosis[5-9]. Preoperative inflammatory biomarkers obtained from laboratory tests have shown associations with tumor progression, metastasis, and poor survival outcomes. In dCCA, preoperative prognostic markers include neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and neutrophil-to-monocyte ratio (NMR)[10]. Moreover, the systemic immune-inflammation index (SII), which is determined by multiplying the number of platelets in the blood with the NLR, has proven to be effective in forecasting prolonged survival in patients with dCCA who have had PD surgery[11]. Another significant biomarker, the albumin-to-bilirubin ratio (ABR), which reflects hepatic function, has shown a significant correlation with poor prognosis in gastrointestinal tumors such as hepatocellular carcinoma (HCC), pancreatic cancer, and gastric cancer[12-14]. The inflammation-combined prognostic index (ICPI), created as a new prognostic tool for gastric cancer, has demonstrated potential in forecasting survival results[15]. The aspartate transaminase-to-platelet (APRI), primarily used to evaluate hepatic fibrosis, has been found to play diverse roles in various cancers[16]. The systemic inflammatory response index (SIRI), which is determined by multiplying the number of neutrophils in the blood by the ratio of monocytes to lymphocytes, has shown to be a useful predictor for the return of tumors and premature death in various tumors such as HCC, pancreatic cancer, colorectal cancer, and colon cancer[17-19]. Notably, SII, ICPI, and SIRI have shown greater significance as independent factors compared to PLR, NLR, NMR, and LMR alone[20,21]. However, the interpretation of SIRI in individuals with dCCA post-PD is still debated. Further research is needed to elucidate its role in this specific patient population. This study aims to assess if SIRI can predict long-term survival in patients who have had PD for dCCA.

MATERIALS AND METHODS

Study population

A retrospective analysis at Beijing Chao-Yang Hospital examined using SIRI as a preoperative marker for prolonged survival in dCCA patients undergoing PD. Data from patients who had PD between January 1, 2011, to December 31, 2022 was collected from the hospital’s electronic medical record system. The research protocol followed the ethical principles set forth in the 1975 Declaration of Helsinki. Approval for the retrospective study was granted by the hospital’s ethics committees, with all patients providing written informed consent at June 26^th 2024 (No. 2024-D-511).

Exposure definition

In this study, several inflammatory biomarkers were defined and calculated based on blood test results obtained from the enrolled patients. NLR was determined by dividing the number of neutrophils by the number of lymphocytes. PLR was calculated by dividing the platelet count by the lymphocyte count. LMR was calculated by dividing the lymphocyte count by the monocyte count. NMR was calculated by neutrophil counts divided by monocyte counts. ABR was calculated by the ratio of the absolute count of albumin to bilirubin. The ICPI score was calculated by combining the values of LMR, NLR, and PLR, with the formula 2.9 multiplied by LMR, plus 2.8 multiplied by NLR, plus 2.8 multiplied by PLR. Furthermore, the APRI was determined by dividing the aspartate transaminase (AST) by the upper limit of normal, multiplying by 100, and then dividing by the platelet counts. The SII was calculated by multiplying the platelet count by the NLR. The calculation of SIRI involved multiplying the monocyte count by the NLR. Before surgery, venous blood samples were collected from all patients for analysis of complete blood count, biochemical examination, and tumor biomarker tests, which included carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9), within 24 hours. Leukopenia, leukocytosis, and cholangitis, which could be potential alterations resulting from acute infectious or inflammatory conditions, were excluded to focus on chronic effects related to cancer. Patients’ pathological stages were determined according to the 8^th edition of the Union for International Cancer Control[20].

Outcome ascertainment and follow-up

Follow-up data was collected for all enrolled patients through various means, including telephone interviews and outpatient or inpatient observations, until April 2023 or death. Surveillance post-surgery typically involves scheduled visits every 3-6 months within the initial 2 years, followed by visits every 6-12 months for up to 5 years or as per clinical necessity[21]. This monitoring regimen commonly includes a blend of clinical assessments, laboratory analyses encompassing liver function tests and tumor markers, as well as thoracic, abdominal, and pelvic computed tomography (CT) scans. Patients experiencing postoperative biliary obstruction necessitate thorough multidisciplinary assessment to pinpoint the obstruction site, assess for recurrence, and devise an optimal drainage strategy[21]. The recurrence of dCCA primarily hinges on a comprehensive evaluation involving clinical manifestations, tumor markers, and imaging assessments. Following surgery, patients may present with abdominal pain, fever, jaundice, cachexia, and other symptoms. Concurrently, postoperative monitoring involves tracking fluctuations in tumor markers. Subsequently, the diagnosis of recurrence is confirmed through contrast-enhanced CT and magnetic resonance imaging to identify biliary duct thickening or new lesion formation. Positron emission tomography-CT plays a crucial role in assessing tumor activity and detecting potential metastases outside the primary surgical site[21]. Recurrent dCCA often manifests as biliary obstruction, accompanied by symptoms such as recurrent fever, signaling the need for heightened vigilance towards the likelihood of recurrence. Once recurrence is detected, a combination of options such as surgery, radiotherapy or chemotherapy are considered and used depending on the patient's condition. Of note, none of the patients diagnosed with dCCA before surgery received chemotherapy or radiotherapy containing gemcitabine or cisplatin. Overall survival (OS) was defined as the time elapsed between the treatment date and the date of death or last follow-up. Recurrence-free survival (RFS) was defined as the duration between the treatment date and the date of recurrence.

Statistical analysis

Continuous variables will be presented as means and standard deviations or medians and interquartile ranges, depending on their distribution. Group comparisons will be done using the Student’s t test or Mann-Whitney U test for continuous variables, and χ² test or Fisher’s exact test for categorical variables. The normality of continuous variables will be assessed with the Kolmogorov-Smirnov test. Receiver operating characteristic (ROC) curves will determine the best threshold values for predicting dCCA prognosis after PD. Kaplan-Meier curves will be used for survival analysis, with differences in time-to-event endpoints assessed using statistical tests. Univariable regression analysis will identify risk factors for death and recurrence in dCCA patients post-PD. Variables with a P value less than 0.2 from the univariable Cox analysis will be considered in the multivariable Cox regression to identify risk factors that are independent. Missing data will be addressed through multiple imputation to minimize bias and enhance the accuracy of the analysis. Statistical significance will be determined by a two-tailed P value below 0.05. Analysis and presentation of data will be conducted with statistical product and service solutions 26.0 (International Business Machines Corporation, Armonk, NY, United States) and GraphPad Prism 8.0 (GraphPad Software, San Diego, CA, United States), respectively.

RESULTS

Demographic and baseline characteristics of patients

A flowchart depicting the inclusion and exclusion of patients has been provided in Figure 1. A sum of 216 patients who were diagnosed with dCCA after PD and met the inclusion and exclusion criteria were recruited during the entire study period. After a thorough examination, it was determined that the average age of the patients who were registered was 65.6 ± 9.6 years, with males making up 58.3% (126 out of 216). Records indicate a median follow-up time of 36.5 months.

Figure 1 Flowchart of the study cohort. dCCA: Distal cholangiocarcinoma.

In Table 1, there is a summary of the initial traits of the low and high SIRI groups. The low SIRI group consisted of 123 patients, while the high SIRI group comprised 93 patients. Significant variations were noted between the two groups in terms of age (P = 0.004), cardiocerebrovascular disease (P = 0.001), preoperative biliary drainage (P < 0.001), platelet counts (P = 0.026), white blood count (WBC) (P < 0.001), neutrophil counts (P < 0.001), monocyte counts (P < 0.001), lymphocyte counts (P < 0.001), PLR (P < 0.001), NLR (P < 0.001), LMR (P < 0.001), ABR (P = 0.034), SII (P < 0.001), and ICPI (P < 0.001). Compared to the low SIRI group, hemoglobin counts (P = 0.027), albumin counts (P = 0.013), total bilirubin (TB) levels (P = 0.040), CA19-9 levels (P = 0.001) were significantly higher in the high SIRI group. Nonetheless, there were no significant differences (P > 0.05) in sex, smoking, diabetes, epigastrium surgery, alanine aminotransferase, AST, direct bilirubin, g-glutamyl transpeptidase, CEA, NMR, APRI, operative outcomes including operative duration, total blood loss, blood transfusion, postoperative outcomes including ventilator use duration, intensive care unit duration and postoperative time between the two groups. The results from the pathological analysis of both groups were examined and are displayed in Table 2. There were no statistically significant differences in pathological stage, tumor differentiation, microscopic lymphatic invasion, microscopic venous invasion, microscopic arterial invasion, peripheral organ invasion, venous invasion type, perineural invasion, distant metastasis, incisal edge and residual tumor status. It is important to mention that there were notable variations between the two groups regarding tumor size (P = 0.045) and type of venous invasion (P = 0.014).

Table 1 The clinical characteristics of primary cohort.

Variables	Total (n = 216)	Low SIRI (n = 123)	High SIRI (n = 93)	P value
Patient basic factors
Age (year)
≥ 70	79	35	44	0.004a
< 70	137	88	49
Gender
Male	126	67	59	0.186
Female	90	56	34
Main symptom
Abdominal pain	23	16	7	0.213
Jaundice	182	99	83
Other	11	8	3
Smoking
Yes	64	31	33	0.101
No	152	92	60
Diabetes
Yes	58	31	27	0.530
No	158	92	66
Epigastrium surgery
Yes	20	13	7	0.445
No	196	110	86
Cardiocerebrovascular disease
Yes	109	50	59	0.001a
No	107	73	34
Preoperative biliary drainage
ERCP	24	18	6	< 0.001a
PTBD	81	36	45
No	111	69	42
Laboratory parameters
Platelet (109/L)
≥ 311	43	18	25	0.026a
< 311	173	105	68
WBC (109/L)
≥ 7.2	65	16	49	< 0.001a
< 7.2	151	107	44
Neutrophil (109/L)
≥ 3.6	137	51	86	< 0.001a
< 3.6	79	72	7
Monocyte (109/L)
≥ 0.5	78	17	61	< 0.001a
< 0.5	138	106	32
Lymphocyte (109/L)
≥ 1.8	49	42	7	< 0.001a
< 1.8	167	81	86
ALT (U/L)
≥ 190.5	35	23	12	0.252
< 190.5	181	100	81
AST (U/L)
≥ 16.5	206	118	88	0.650
< 16.5	10	5	5
Hemoglobin (g/L)
≥ 112	132	83	49	0.027a
< 112	84	40	44
Albumin (g/dL)
≥ 35.7	100	66	34	0.013a
< 35.7	116	57	59
TB (μmol/L)
≥ 144.4	83	40	43	0.040a
< 144.4	133	83	50
DB (μmol/L)
≥ 113.8	84	42	42	0.100
< 113.8	132	81	51
-GGT (U/L)
≥ 646.5	66	39	27	0.673
< 646.5	150	84	66
CEA (ng/mL)
≥ 0.2	209	117	92	0.118
< 0.2	7	6	1
CA19-9 (U/mL)
≥ 235.8	61	24	37	0.001a
< 235.8	155	99	56
PLR
≥ 143	145	65	80	< 0.001a
< 143	71	58	13
NLR
≥ 3.1	112	32	80	< 0.001a
< 3.1	104	91	13
LMR
≥ 3.2	100	92	8	< 0.001a
< 3.2	116	31	85
NMR
≥ 11.2	69	37	32	0.499
< 11.2	147	86	61
ABR
≥ 0.3	120	76	44	0.034a
< 0.3	96	47	49
SII
≥ 682	123	39	84	< 0.001a
< 682	93	84	9
ICPI
≥ 445.4	133	57	76	< 0.001a
< 445.4	83	66	17
APRI
≥ 0.3	178	103	75	0.554
< 0.3	38	20	18
Operative outcomes
Operative duration (hours)	10.1 ± 2.6	10.1 ± 2.6	10.1 ± 2.6	0.900
Total blood loss (mL)	618.8 ± 517.5	621.3 ± 535.6	616.8 ± 505.2	0.950
Blood transfusion (mL)	308.3 ± 538.8	259.6 ± 511.0	345.9 ± 558.7	0.244
Postoperative outcomes
Ventilator use duration (hours)	20.9 ± 27.5	18.4 ± 20.9	22.9 ± 31.6	0.234
ICU duration (days)	3.5 ± 3.3	3.4 ± 3.2	3.7 ± 3.6	0.347
Postoperative time (days)	27.0 ± 18.2	26.0 ± 15.8	27.7 ± 19.9	0.498

^aP < 0.05.

PLR: Platelet-to-lymphocyte ratio; NLR: Neutrophil to lymphocyte ratio; LMR: Lymphocyte to monocyte ratio; NMR: Neutrophil-to-monocyte ratio; APRI: Aspartate transaminase-to-platelet; ABR: Albumin to bilirubin ratio; ICPI: Inflammation-combined prognostic index; SII: Systemic immune-inflammation index; SIRI: Systemic inflammatory response index; ERCP: Endoscopic retrograde cholangio pancreatography; PTBD: Percutaneous transhepatic biliary drainage; WBC: White blood count; ALT: Alanine aminotransferase; AST: Aspartate transaminase; TB: Total bilirubin; DB: Direct bilirubin; -GGT: -glutamyl transpeptidase; CEA: Carcinoembryonic antigen; CA19-9: Carbohydrate antigen 19-9; ICU: Intensive care unit.

Table 2 Pathological characteristics of the patients classified by the systemic inflammatory response index.

Variables	Total (n = 216)	Low SIRI (n = 123)	High SIRI (n = 93)	P value
pT stage
Tis	3	2	1	0.654
T1, T2	26	17	9
T3, T4	184	103	81
Unknown	3	1	2
pN stage
N0	111	67	44	0.676
N1	74	41	33
N2	29	14	15
Unknown	2	1	1
pM stage
M0	204	118	86	0.271
M1	12	5	7
Tumor differentiation
Well	25	19	6	0.097
Moderate	90	54	36
Poor	26	13	13
Other	75	37	38
Tumor size (cm)
≥ 1.8	140	74	66	0.045a
< 1.8	74	49	25
Unknown	2	0	2
Microscopic lymphatic invasion
Yes	103	55	48	0.578
No	111	67	44
Unknown	2	1	1
Microscopic venous invasion
Yes	36	17	19	0.214
No	179	106	73
Unknown	1	0	1
Microscopic arterial invasion
Yes	6	2	4	0.344
No	207	120	87
Unknown	3	1	2
Peripheral organ invasion
Yes	3	2	1	0.670
No	210	120	90
Unknown	3	1	2
Venous invasion type
1-2	24	15	9
3-4	12	2	10	0.014a
No	180	106	74
Perineural invasion
Yes	189	104	85	0.268
No	25	18	7
Unknown	2	1	1
Distant metastasis
Yes	12	5	7	0.189
No	204	118	76
Incisal edge
Positive	24	14	10	0.884
Negative	192	109	83
Residual tumor status
R0	191	109	82	0.490
R1	19	10	9
R2	6	2	4

^aP < 0.05.

SIRI: Systemic inflammatory response index.

Preoperative inflammatory biomarkers and prognosis of patients with dCCA

ROC curves were utilized to establish the connection between preoperative inflammatory markers and patient outcomes in dCCA following PD (Figure 2). The optimal cutoff values for CA19-9, PLR, NLR, LMR, NMR, APRI, ABR, ICPI, SII, and SIRI to predict OS were identified as 235.8, 143, 3.1, 3.2, 11.2, 0.3, 0.3, 445.4, 682, and 1.5, respectively. The corresponding area under the curves (AUCs) for these biomarkers were calculated as 0.661, 0.637, 0.672, 0.654, 0.555, 0.503, 0.632, 0.636, 0.667, and 0.674, respectively (Supplementary Table 1). The results of the ROC analysis indicated that APRI exhibited the highest sensitivity of 0.880, while CA19-9 and NMR demonstrated the highest specificity of 0.907 and 0.773, respectively, compared to other markers. The postoperative RFS rates for the markers mentioned above ranged from 0.503 to 0.604, with AUC values of 0.516, 0.543, 0.553, 0.556, 0.565, 0.568, and 0.569 (Supplementary Table 2). In the ROC analysis, it was found that LMR had the highest sensitivity at 0.975, whereas ABR showed the highest specificity at 0.958 among all the markers.

Figure 2 The receiver operating characteristic curves explore the value of preoperative inflammatory biomarkers in predicting the long-time prognosis in distal cholangiocarcinoma after pancreatoduodenectomy. A: The value of receiver operating characteristic (ROC) in predicting overall survival in distal cholangiocarcinoma (dCCA) after pancreatoduodenectomy (PD); B: The value of ROC in predicting recurrence-free survival in dCCA after PD. PLR: Platelet-to-lymphocyte ratio; NLR: Neutrophil to lymphocyte ratio; LMR: Lymphocyte to monocyte ratio; NMR: Neutrophil-to-monocyte ratio; APRI: Aspartate transaminase-to-platelet; ABR: Albumin to bilirubin ratio; ICPI: Inflammation-combined prognostic index; SII: Systemic immune-inflammation index; SIRI: Systemic inflammatory response index.

The outcomes of univariate and multivariate Cox proportional hazard regression analyses for forecasting OS and RFS were showed in Table 3 and 4. Several independent factors significantly associated with OS were identified through multivariate Cox regression analysis.

Table 3 Cox regression analysis of the effects of clinicopathological factors on the overall survival of patients.

Variables	Univariate analysis		Multivariate analysis
	HR (95%CI)	P value	HR (95%CI)	P value
Age (year)	1.022 (1.003-1.042)	0.025a	1.008 (0.987-1.029)	0.471
Cardiocerebrovascular disease	1.424 (1.020-1.986)	0.038a	1.428 (0.989-2.063)	0.058
Preoperative biliary drainage	1.166 (0.974-1.396)	0.094	0.746 (0.401-1.389)	0.355
Platelet (109/L)	1.002 (1.000-1.004)	0.101	1.001 (0.996-1.007)	0.661
WBC (109/L)	1.044 (0.975-1.118)	0.219
Neutrophil (109/L)	1.089 (1.011-1.174)	0.025a	1.110 (0.900-1.369)	0.330
Monocyte (109/L)	2.000 (1.048-3.818)	0.036a	0.078 (0.003-1.761)	0.109
Lymphocyte (109/L)	0.624 (0.469-0.830)	0.001a	0.598 (0.287-1.245)	0.169
Hemoglobin (g/L)	0.990 (0.981-0.999)	0.022a	1.001 (0.989-1.013)	0.895
Albumin (g/dL)	1.560 (1.104-2.204)	0.012a	0.983 (0.948-1.019)	0.345
TB (μmol/L)	1.002 (1.001-1.004)	0.003a	1.002 (1.000-1.004)	0.030a
CA19-9 (U/mL) (> 235.8)	1.000 (1.000-1.000)	0.000a	1.000 (0.999-1.000)	0.000a
PLR (> 143)	1.003 (1.002-1.005)	0.000a	1.000 (0.995-1.005)	0.898
NLR (> 3.1)	1.093 (1.042-1.146)	0.000a	0.702 (0.525-0.939)	0.017
LMR (> 3.2)	0.807 (0.726-0.898)	0.000a	0.934 (0.712-1.225)	0.621
NMR (> 11.2)	0.992 (0.969-1.015)	0.490
ABR (> 0.3)	0.937 (1.091-2.054)	0.403
SII (> 682)	1.000 (1.000-1.001)	0.000a	1.000 (0.999-1.001)	0.644
SIRI (> 1.5)	1.167 (1.092-1.247)	0.000a	1.868 (1.194-2.920)	0.006a
ICPI (> 445.4)	1.001 (1.001-1.002)	0.000a	3.108 (1.710-5.651)	0.305
APRI (> 0.3)	1.016 (0.877-1.177)	0.831
Tumor size (cm) (> 1.8)	1.292 (1.116-1.497)	0.001a	1.343 (1.130-1.596)	0.001a
Venous invasion type	1.371 (0.430-4.368)	0.594

^aP < 0.05.

PLR: Platelet-to-lymphocyte ratio; NLR: Neutrophil to lymphocyte ratio; LMR: Lymphocyte to monocyte ratio; NMR: Neutrophil-to-monocyte ratio; APRI: Aspartate transaminase-to-platelet; ABR: Albumin to bilirubin ratio; ICPI: Inflammation-combined prognostic index; SII: Systemic immune-inflammation index; SIRI: Systemic inflammatory response index; HR: Hazard ratio; CI: Confidence interval; WBC: White blood count; TB: Total bilirubin; CA19-9: Carbohydrate antigen 19-9.

Table 4 Cox regression analysis of the effects of clinicopathological factors on the recurrence-free survival of patients.

Variables	Univariate analysis		Multivariate analysis
	HR (95%CI)	P value	HR (95%CI)	P value
Age (year)	1.001 (0.980-1.023)	0.931
Cardiocerebrovascular disease	1.225 (0.844-1.777)	0.285
Preoperative biliary drainage	0.679 (0.343-1.342)	0.265
Platelet (109/L)	1.002 (0.999-1.005)	0.229
WBC (109/L)	0.978 (0.906-1.056)	0.565
Neutrophil (109/L)	0.999 (0.914-1.091)	0.982
Monocyte (109/L)	0.839 (0.409-1.720)	0.632
Lymphocyte (109/L)	0.695 (0.516-0.936)	0.017a	0.834 (0.478-1.456)	0.523
Hemoglobin (g/L)	1.001 (0.991-1.011)	0.872
Albumin (g/dL)	1.019 (0.989-1.051)	0.221
TB (μmol/L)	1.001 (0.999-1.002)	0.469
CA19-9 (U/mL) (> 69.3)	1.000 (1.000-1.000)	0.970
PLR (> 159.8)	1.003 (1.001-1.005)	0.001a	1.000 (0.995-1.004)	0.811
NLR (> 2.8)	1.129 (1.024-1.245)	0.015a	0.895 (0.694-1.155)	0.393
LMR (> 1.1)	0.888 (0.798-0.989)	0.030a	0.922 (0.771-1.101)	0.368
NMR (> 11.5)	0.992 (0.959-1.026)	0.624
ABR (> 3.7)	0.938 (0.792-1.112)	0.463
SII (> 496.6)	1.001 (1.000-1.001)	0.002a	1.001 (1.000-1.002)	0.146
ICPI (> 445.4)	1.001 (1.000-1.002)	0.001a	0.894 (0.784-1.020)	0.096
APRI (> 1.7)	1.032 (0.866-1.229)	0.726
SIRI (> 1.1)	1.080 (0.972-1.200)	0.001a	0.949 (0.752-1.199)	0.000a
Tumor size (cm) (> 1.8)	1.258 (1.013-1.561)	0.038a	1.144 (0.887-1.475)	0.229
Venous invasion type	1.503 (0.819-2.759)	0.189	1.577 (0.566-4.391)	0.383

^aP < 0.05.

PLR: Platelet-to-lymphocyte ratio; NLR: Neutrophil to lymphocyte ratio; LMR: Lymphocyte to monocyte ratio; NMR: Neutrophil-to-monocyte ratio; APRI: Aspartate transaminase-to-platelet; ABR: Albumin to bilirubin ratio; ICPI: Inflammation-combined prognostic index; SII: Systemic immune-inflammation index; SIRI: Systemic inflammatory response index; HR: Hazard ratio; CI: Confidence interval; WBC: White blood count; TB: Total bilirubin; CA19-9: Carbohydrate antigen 19-9.

These factors included TB (> 144.4), CA19-9 (> 235.8), SIRI (> 1.5), and tumor size (> 1.8), with hazard ratios (HR) and corresponding P values as follows: TB (HR = 1.002, P = 0.030), CA19-9 (HR = 1.000, P = 0.000), SIRI (HR = 1.868, P = 0.006), and tumor size (HR = 1.343, P = 0.001) (Table 3). In RFS, SIRI (> 1.5) was found to be a significant risk factor with a HR of 0.949 and P value of 0.000 (Table 4). Survival analysis using Kaplan-Meier method was performed to evaluate the extended outlook (Figure 3). In comparison to the high-SIRI group, the low-SIRI group exhibited notably higher 5-year OS rate and RFS rate (14.0% vs 30.0%, log-rank test, P < 0.001; 8.0% vs 14.0%, Breslow-Wilcoxon test, P = 0.006).

Figure 3 Kaplan-Meier curves for long-time prognosis by systemic inflammatory response index. A: Kaplan-Meier curves for overall survival by systemic inflammatory response index (SIRI); B: Kaplan-Meier curves for recurrence-free survival by SIRI. SIRI: Systemic inflammatory response index; OS: Overall survival; RFS: Recurrence-free survival.

DISCUSSION

This study is significant as it is the first to examine the relationship between preoperative SIRI, clinicopathological factors, and PD outcomes in patients with dCCA, with a larger patient cohort than previous studies[5,22-24]. In this retrospective clinical study, the researchers established predictive factors by considering numerous clinicopathological factors, as observed in previous clinical investigations[25-28]. The findings of this study revealed that SIRI functioned as an independent and definitive prognostic indicator for the 5-year OS and RFS of patients who underwent PD for dCCA.

The study found that SIRI was not linked to preoperative biliary drainage or other pathological results, except for tumor size. However, significant differences were seen in TB and CA19-9 levels. These results suggest that SIRI may offer insights into tumor progression mechanisms not captured by traditional methods. Preoperative imaging can provide an early assessment of tumor size, which may be delayed with histopathological tests[29-31]. Multiple studies have linked tumor size detected through imaging to patient prognosis. CA19-9 is a tumor biomarker that can track tumor progression and treatment effectiveness in cancer, particularly in dCCA. It is not useful for early diagnosis but is crucial for comprehensive treatment and follow-up[32]. These findings align with the results of other studies[33,34].

SIRI serves as a novel predictive tool that reflects immune response and inflammatory status. Multiple studies have shown that additional inflammatory indicators like SII[35], PLR[10] and NLR[11] are considered independent risk factors for patients with dCCA after undergoing PD. Furthermore, a recent systematic review and meta-analysis found that PLR may independently predict the prognosis of patients with dCCA[36]. These findings highlight the close correlation between preoperative inflammatory markers and tumor progression. In fact, PLR, NLR, and LMR are superior inflammatory markers for predicting tumor prognosis than individual markers, such as CRP, WBC, neutrophil, and procalcitonin based on many valuable studies[10,37,38]. Moreover, SIRI, SII, and prognostic nutritional index, which combine inflammation markers, are even more effective[35,39]. In contrast to other inflammatory markers, SIRI integrates neutrophil, lymphocyte, and monocyte counts, reflecting both inflammation and immune status. SIRI’s superior predictive power in dCCA may result from its holistic evaluation of the immune-inflammatory balance. It interprets neutrophilia as inflammation, lymphopenia as immunosuppression, and monocyte changes as tumor-related inflammation. This comprehensive perspective provides a more detailed prognosis than individual biomarkers, making SIRI a reliable predictor of dCCA outcomes. Mechanistically, a strict and copious review has indicated that neutrophils play heterogeneous and multifaceted roles either protumoral functions or antitumoral in tumor microenvironment[40]. Neutrophils discharge a sequence of enzymes that cultivate an environment conducive to tumor angiogenesis, a process that can potentially facilitate tumor growth, progression, and metastasis[41,42]. Alternatively, neutrophils can combat tumors by directly eliminating tumor cells and contributing to cellular networks that resist tumors[42]. The two-sided role of neutrophils in tumors has sparked interest in using them for cancer treatment[42,43]. Likewise, activated monocytes have been shown to have anti-tumor functions and can shape the tumor microenvironment to promote the spread of tumor cells. Antitumor functions and antigen-presenting cells activated by monocytes were concluded in many studies[44-46]. In summary, both neutrophils and monocytes demonstrate plasticity and exhibit dual effects in response to environmental stimuli. Lymphocytes, on the other hand, are well-recognized for their roles in human immune responses, including anti-infection and anti-tumor effects[47]. Various T cell subtypes like cluster of differentiation (CD) 4⁺ T cells and CD8⁺ T cells have the ability to suppress the growth, spread, and movement of tumor cells[48-50].

An elevated SIRI in dCCA can significantly influence treatment decisions and postoperative monitoring strategies. Elevated SIRI levels may indicate dysregulated immune responses and heightened tumor-related inflammation, suggesting a more aggressive disease phenotype[51,52]. This insight can direct clinicians towards enhanced postoperative surveillance, potentially requiring closer monitoring and personalized adjuvant therapies to address the increased inflammatory burden and immune dysregulation[53,54]. Furthermore, identifying elevated SIRI levels opens avenues for future research in dCCA. It is crucial to conduct prospective validation studies to validate the prognostic significance of SIRI and its impact on treatment outcomes. Exploring the mechanistic connections between inflammation and tumor progression in dCCA could offer valuable insights into the underlying pathophysiology and unveil potential therapeutic targets. Understanding these intricate relationships may pave the way for targeted interventions aimed at modulating the immune-inflammatory microenvironment to enhance patient outcomes in dCCA. The advancement of minimally invasive techniques has made laparoscopic pancreaticoduodenectomy (LPD) more beneficial than open PD due to shorter hospital stays and comparable short-term health risks. The use of preoperative inflammatory markers can further refine the benefits and indications of LPD, especially in superior mesenteric artery-first approach, mitigating postoperative complications, enhancing patient prognosis in further research[55,56].

SIRI has garnered significant attention as a comprehensive biomarker not only for predicting prognosis but also for assessing the activity of chemotherapy in advanced cancers[57-59]. Pretreatment SIRI has shown potential prognostic significance for cancer patients receiving neoadjuvant chemotherapy and has influenced treatment strategy decisions[58,60]. Doctors can more accurately evaluate the progress of patients receiving neoadjuvant chemotherapy for malignant tumors by using SIRI as an important predictive factor. This highlights the importance of considering dCCA as a systemic disease and underscores the potential of SIRI to reflect the response to chemotherapy and immunotherapy in patients within a multidisciplinary setting.

There are various constraints to this study that need to be taken into account. Firstly, the study was conducted retrospectively at a single center, potentially restricting the applicability of the results. Secondly, preoperative inflammatory biomarkers, including SIRI, can exhibit fluctuations due to internal homeostasis, which may weaken their clinical value if dynamic monitoring is not conducted. Next, although this study adjusted for a variety of clinicopathological characteristics in multivariate analyses, there remain a number of potential confounders that may affect inflammatory biomarker levels or patient prognosis, such as comorbidities, preoperative treatment affecting inflammation, or postoperative complications. Common complications of dCCA, such as biliary tract infection, obstructive jaundice, liver dysfunction, and cholelithiasis, can all serve as confounding factors significantly affecting the predictive value of SIRI[61,62]. Biliary tract infection exacerbates the inflammatory state by releasing pro-inflammatory cytokines and activating immune cells, impacting the accuracy of preoperative inflammatory markers[62]. Obstructive jaundice is a hallmark of advanced dCCA, leading to bile stasis and increased bile pressure, creating a local inflammatory environment within the bile ducts. This local inflammation can trigger systemic inflammation, thereby affecting preoperative inflammatory markers[63]. Furthermore, due to impaired liver function and disrupted bile flow, the synthesis and regulation of inflammatory mediators are compromised, also influencing the accuracy of preoperative inflammatory markers[61]. Concurrent cholelithiasis further escalates inflammation and complicates the interpretation of preoperative inflammatory indicators[64-66]. Medications administered to dCCA patients, particularly those with anti-inflammatory or immunomodulatory properties, can modulate the systemic inflammatory response. These medications may suppress or enhance inflammatory pathways, leading to alterations in preoperative inflammatory marker levels[67,68]. Consequently, the predictive capacity of these markers for prognosis may be influenced by the concurrent use of such medications. Postoperative complications in dCCA patients primarily encompass pancreatic fistula, abdominal infections, hemorrhage, bile leakage, and delayed gastric emptying[69]. While the occurrence of postoperative complications does not directly impact the preoperative inflammatory markers, it significantly influences the patient’s prognosis[69,70]. In severe instances, these complications can precipitate early postoperative mortality. Henceforth, forthcoming research should incorporate the inclusion of dynamic monitoring of preoperative clinical indicators. Meanwhile, LPD combined with preoperative inflammatory markers will further reduce postoperative complications. Future studies need to confirm whether combining LPD with preoperative inflammatory markers can further reduce postoperative complications. Last but not least, long-term follow-up is necessary to assess the predictive value of SIRI and other factors, but follow-up bias may occur over time. In essence, further research with larger samples and collaboration between multiple centers is needed to confirm these findings and overcome study limitations.

CONCLUSION

To summarize, the preoperative SIRI can predict recurrence and long-term survival in dCCA patients, helping guide treatment decisions for better outcomes.