Abstract
Objectives:
We investigated the characteristics of colorectal cancer (CRC) in older patients (≥ 65 years) and the immune-inflammation indexes.
Methods:
This study included 149 patients aged ≥ 65 years with advanced colorectal cancer, who underwent radical surgery (R0 resection). Four immune-inflammation indexes (C-reactive protein-to-albumin ratio (CAR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and neutrophil-to-lymphocyte ratio (NLR)) were calculated. We analyzed the association between immune-inflammation indexes and clinicopathological features or prognosis.
Results:
Tumor depth and lymph node metastasis were independent prognostic factors for recurrence-free survival (RFS) in multivariate analysis (p=0.03, hazard ratio [HR] 2.095, 95% confidence interval (CI) 1.225-3.982 and p=0.008, HR 2.209, 95% CI 1.225-3.982, respectively). Lymphatic invasion and CAR were also independent prognostic factors for overall survival (OS) in multivariate analysis (p=0.04, HR 2.197, 95% CI 1.042-4.632 and p=0.04, HR 2.174, 95% CI 1.032-4.58, respectively). Lymphatic invasion and CAR were independent prognostic factors for cancer specific survival (CSS) in the multivariate analysis (p=0.03, HR 3.004, 95% CI 1.11-8.13 and p=0.03, HR 3.087, 95% CI 1.135-8.394, respectively).
Conclusions:
CAR is a useful immune-inflammation index for predicting the prognosis after radical resection for advanced CRC in older patients.
Keywords: colorectal cancer, older patients, immune-inflammation index, CAR
Introduction
The proportion of aging population is rapidly rising worldwide. According to the World Population Prospects from the United Nations (2022 Revision), the population aged ≥ 65 years has increased from 5.1% of the total population in 1950 to 10% in 2022 and is expected to further increase to 16% by 2050[1]. The incidence of cancer increases with age; therefore, a longer life expectancy indicates a higher incidence of malignancy. Colorectal cancer (CRC) is the third most common malignant tumor and the second major cause of cancer-related mortality worldwide[2]. Hence, there is an increasing number of older patients with CRC.
Currently, TNM staging is the most reliable system for predicting cancer prognosis. However, prognostic heterogeneity was observed among patients even in the same TNM stages[3,4]. This is because not just tumor factors but other factors that are also associated with cancer progression. Systemic inflammation and deterioration of nutritional status are recognized as hallmarks of cancer development and progression, and play important roles in the survival of patients with cancer[5]. In general, older patients are more likely to have chronic inflammation and malnutrition than younger patients, and the degree of systemic inflammation and nutritional status may affect cancer progression and prognosis[4,6].
Cancer-related inflammation is determined by the levels of serum leukocytes, neutrophils, lymphocytes, platelets, and C-reactive protein (CRP), which can be easily evaluated through routine blood examination[3]. Various preoperative immune-inflammation indexes have been proposed using these parameters. The CRP-albumin ratio (CAR) is considered to reflect chronic inflammation and the nutritional status of patients with cancer[7]. Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PKR), and lymphocyte-monocyte ratio (LMR) are simple indexes that use blood cell components and implied systemic inflammation[8]. Recently, a variety of preoperative immune-inflammation indexes were reported to be associated with perioperative complications and prognosis[8]. However, each immune-inflammation index differs in the parameters used, and the appropriate immune-inflammation index for evaluating the prognosis of older patients with CRC have not been determined. Here, we focused on the immune-inflammation indexes of older patients and investigated the characteristics of CRC in older patients (≥ 65 years) as well as the immune-inflammation indexes that are useful for predicting postoperative prognosis.
Methods
Patient selection and treatment strategies
This study included 149 patients ≥ 65 years of age with advanced colorectal cancer (pathological T2 or greater) who underwent radical surgery (R0 resection) in Kurume University hospital from 2015 to 2018. We excluded patients with Stage IV, multiple cancer, double cancer, and colitis-associated cancer from the study. The 7th edition of the Union of International Cancer Control (UICC) was used to diagnose the stage of the tumors[9]. We used pathological stages of tumor depth and lymph node metastaisis in analyses. We performed surgical procedures according to Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2014 for the treatment of CRC[10]. We reviewed the patients' medical charts, laboratory data, and pathological findings to extract relevant data for this retrospective study. We obtained approval from the Institutional Review Board of ethics in Kurume University hospital (Approval No. 21187) and all methods were conducted in accordance with the Declaration of Helsinki. Consent was obtained from all patients using the opt-out method.
Follow-up surveillance
Postoperative follow-up was performed every 3 months to determine carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) levels. Computed tomography (CT) was performed every 6 months, and colonoscopy was performed at the 1st, 2nd, 3rd, and 5th years after surgery. Recurrence-free survival (RFS) and overall survival (OS) were defined as the time between surgery and recurrence or death. Cancer specific survival (CSS) was defined as the time interval between surgery and cancer-related deaths.
Assessment of immune-inflammation indexes
Four immune-inflammation indexes (CAR, PLR, LMR, and NLR) were calculated using preoperative laboratory data collected within 2 months prior to surgery. CAR was defined as serum CRP level (mg/dl) divided by serum albumin level (g/dl), PLR was defined as absolute platelet count divided by absolute lymphocyte count, LMR as absolute lymphocyte count divided by absolute monocyte count, and NLR as absolute neutrophil count divided by absolute lymphocyte count.
Statistical analysis
We divided the patients into two groups (high and low groups) base on the cutoff values for each immune-inflammation index calculated using receiver operating characteristic (ROC) curves for the survival, and then analyzed the association between immune-inflammation indexes and clinicopathological features or prognosis. The calculated cutoff values were CAR: 0.09 (sensitivity: 76.7%, specificity: 44.8%, area under the curve (AUC): 0.537), NLR: 2.38 (sensitivity: 69.2%, specificity: 41.4%, AUC: 0.486), LMR: 6.01 (sensitivity: 36.7%, specificity: 72.4%, AUC: 0.523), and PLR: 173 (sensitivity: 55.2%, specificity: 52.5%, AUC: 0.510). The chi-square test was used to evaluate if there was a significant correlation between the immune-inflammation indexes and clinicopathological features. Survival curves were estimated using the Kaplan-Meier method. The significance of the differences between the survival curves was determined using the log-rank test. Univariate and multivariate analyses were performed using Cox proportional hazards model. All statistical analyses were performed using JMP ver.16 software (SAS Institute, Cary, NC, USA), and a p value < 0.05 was considered statistically significant.
Results
Patients' characteristics based on immune-inflammation index
The patients' characteristics and differences based on each immune-inflammation index is shown in Table 1. Seventy-four (51%) patients were male and 75 (49%) were female; 44 patients (29.5%) were of grade 2 or greater according to the American Society of Anesthesiologists physical status (ASA-PS) and 45 patients (30.2%) were of 1 or greater according to Charlson Comorbidity Index (CCI). The median age was 74±0.6 years (range, 65-98). A total of 86 patients (57.7%) had colon cancer and 63 patients (42.3%) had rectal cancer. Twenty-two patients (14.8%) had stage T4 cancer, and 59 (39.6%) had lymph node metastasis. There were 32 patients (21.5%) with Stage I, 58 patients (38.9%) with Stage II, and 59 cases (39.6%) with Stage III cancer. Seventy-nine patients (53%) had well-differentiated tumors, and 70 patients (47%) had other tissue types. Forty-seven patients (31.5%) had lymphatic invasion and 92 patients (61.7%) had venous invasion.
Table 1.
The Patients’ Characteristics and the Relationships between Each Immune-inflammation Index and Clinicopathological Factors.
| Total N=149 | CAR<0.09 N=104 | CAR≥0.09 N=45 | p value | PLR<173 N=112 | PLR≥173 N=37 | p value | LMR<6.01 N=94 | LMR≥6.01 N=55 | p value | NLR<2.38 N=101 | NLR≥2.38 N=48 | p value | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Gender | Male | 74 | 56 | 18 | 55 | 19 | 43 | 31 | 53 | 21 | ||||
| Female | 75 | 48 | 27 | 0.12 | 57 | 18 | 0.81 | 51 | 24 | 0.21 | 48 | 27 | 0.32 | |
| ASA-PS class | 1 | 105 | 81 | 24 | 83 | 22 | 64 | 41 | 75 | 30 | ||||
| ≥2 | 44 | 23 | 21 | 0.003 | 29 | 15 | 0.09 | 30 | 14 | 0.4 | 26 | 18 | 0.14 | |
| Heart disease | negative | 129 | 91 | 38 | 97 | 32 | 77 | 52 | 88 | 41 | ||||
| positive | 20 | 13 | 7 | 0.62 | 15 | 5 | 0.99 | 17 | 3 | 0.03 | 13 | 7 | 0.78 | |
| Pulmonary disease | negative | 139 | 98 | 41 | 105 | 34 | 86 | 53 | 96 | 43 | ||||
| positive | 10 | 6 | 4 | 0.49 | 7 | 3 | 0.7 | 8 | 2 | 0.25 | 5 | 5 | 0.21 | |
| Renal disease | negative | 139 | 96 | 43 | 104 | 35 | 85 | 54 | 93 | 46 | ||||
| positive | 10 | 8 | 2 | 0.47 | 8 | 2 | 0.71 | 9 | 1 | 0.07 | 8 | 2 | 0.39 | |
| Collagen disease | negative | 147 | 103 | 44 | 110 | 37 | 93 | 54 | 99 | 48 | ||||
| positive | 2 | 1 | 1 | 0.54 | 2 | 0 | 0.41 | 1 | 1 | 0.7 | 2 | 0 | 0.33 | |
| CCI | 0 | 104 | 71 | 33 | 77 | 27 | 67 | 37 | 69 | 35 | ||||
| ≥1 | 45 | 33 | 12 | 0.54 | 35 | 10 | 0.63 | 27 | 18 | 0.61 | 32 | 13 | 0.57 | |
| Tumor location 1 | Colon | 86 | 58 | 28 | 60 | 26 | 60 | 26 | 55 | 31 | ||||
| Rectum | 63 | 46 | 17 | 0.46 | 52 | 11 | 0.08 | 34 | 29 | 0.048 | 46 | 17 | 0.24 | |
| Tumor location 2 | Right | 34 | 20 | 14 | 24 | 10 | 25 | 9 | 21 | 13 | ||||
| Left | 115 | 84 | 31 | 0.11 | 88 | 27 | 0.48 | 69 | 46 | 0.15 | 80 | 35 | 0.39 | |
| CEA | <5 | 84 | 58 | 26 | 66 | 18 | 54 | 30 | 56 | 28 | ||||
| ≥5 | 65 | 46 | 19 | 0.82 | 46 | 19 | 0.27 | 40 | 25 | 0.73 | 45 | 20 | 0.74 | |
| Surgical procedure | Laparoscopic | 98 | 74 | 24 | 76 | 22 | 57 | 41 | 32 | 69 | ||||
| Open | 51 | 30 | 21 | 0.04 | 36 | 15 | 0.35 | 37 | 14 | 0.08 | 18 | 29 | 0.34 | |
| Lymph node dissection | D1-2 | 36 | 23 | 13 | 29 | 7 | 23 | 13 | 27 | 9 | ||||
| D3 | 113 | 81 | 32 | 0.38 | 83 | 30 | 0.39 | 71 | 42 | 0.91 | 74 | 39 | 0.29 | |
| Blood loss (ml) | <150 | 110 | 81 | 29 | 85 | 25 | 66 | 44 | 78 | 32 | ||||
| ≥150 | 39 | 23 | 16 | 0.09 | 27 | 12 | 0.32 | 28 | 11 | 0.19 | 23 | 16 | 0.17 | |
| Operation time (min) | <270 | 77 | 51 | 26 | 55 | 22 | 51 | 26 | 53 | 24 | ||||
| ≥270 | 72 | 53 | 19 | 0.33 | 57 | 15 | 0.28 | 43 | 29 | 0.41 | 48 | 24 | 0.78 | |
| Adjuvant chemotherapy | negative | 122 | 85 | 37 | 95 | 27 | 76 | 46 | 84 | 38 | ||||
| positive | 27 | 19 | 8 | 0.94 | 17 | 10 | 0.11 | 18 | 9 | 0.67 | 17 | 10 | 0.55 | |
| Tumor depth | T2-3 | 127 | 91 | 36 | 95 | 32 | 80 | 47 | 87 | 40 | ||||
| T4 | 22 | 13 | 9 | 0.24 | 17 | 5 | 0.81 | 14 | 8 | 0.95 | 14 | 8 | 0.65 | |
| Lymph node metastasis | N0 | 90 | 63 | 27 | 66 | 24 | 59 | 31 | 60 | 30 | ||||
| N1-3 | 59 | 41 | 18 | 0.95 | 46 | 13 | 0.52 | 35 | 24 | 0.49 | 41 | 18 | 0.72 | |
| Tumor differentiation | well | 79 | 54 | 25 | 58 | 21 | 52 | 27 | 53 | 26 | ||||
| other | 70 | 50 | 20 | 0.68 | 54 | 16 | 0.6 | 42 | 28 | 0.46 | 48 | 22 | 0.85 | |
| lymphatic invasion | negative | 102 | 70 | 32 | 79 | 23 | 65 | 37 | 72 | 30 | ||||
| positive | 47 | 34 | 13 | 0.65 | 33 | 14 | 0.34 | 29 | 18 | 0.81 | 29 | 18 | 0.28 | |
| venous invasion | negative | 57 | 41 | 16 | 48 | 9 | 32 | 25 | 42 | 15 | ||||
| positive | 92 | 63 | 29 | 1 | 64 | 28 | 0.04 | 62 | 30 | 0.17 | 59 | 33 | 0.23 | |
| budding | negative | 42 | 35 | 7 | 35 | 7 | 24 | 18 | 34 | 8 | ||||
| positive | 107 | 69 | 38 | 0.02 | 77 | 30 | 0.15 | 70 | 37 | 0.35 | 67 | 40 | 0.03 |
Regarding the differences in each immune-inflammation index, low LMR had heart disease more and was associated with the rectum rather than with the colon (p=0.03 and p=0.048, respectively). The prevailance of grade 2 or greater according to the ASA-PS was statistically significant in thise with high CAR (p=0.003). Patients with high CAR mostly underwent open surgery rather than laparoscopic surgery (p=0.04). Surgery time and blood loss were not different for any immune-inflammation index. Tumor characteristics, such as pathological tumor depth, the status of lymph node metastasis, and TNM stage did not differ between each immune-inflammation index. Regarding other pathological findings, budding showed a significant difference in CAR (p=0.02) and NLR (p=0.03), and venous invasion did in PLR (p=0.04). Postoperative adjuvant chemotherapy was not associated with any index.
Postoperative outcomes
Short-term outcome
Postoperative outcomes are shown in Table 2. Postoperative morbidity of Clavien-Dindo (CD) class III or greater occurred in 11 patients. The duration of hospital stay after surgery was 16±2.5 days (mean ± standard error). Postoperative morbidity in patients with CD class III or greater and the duration of postoperative hospital stay were not different for each immune-inflammation index.
Table 2.
Comparisons of Short-term Outcome, Long-term Outcome and Cause of Death by Each Immune-inflammation Index.
| Total N=149 | CAR<0.09 N=104 | CAR≥0.09 N=45 | p value | PLR<173 N=112 | PLR≥173 N=37 | p value | LMR<6.01 N=94 | LMR≥6.01 N=55 | p value | NLR<2.38 N=101 | NLR≥2.38 N=48 | p value | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Short-term outcome | ||||||||||||||
| Postoperative morbidity | Clavien-Dindo ≥III | 11 | 5 | 6 | 0.07 | 7 | 4 | 0.36 | 7 | 4 | 0.97 | 8 | 3 | 0.72 |
| Postoperative hospital stay (day) | 16±2.6 | 16±3.6 | 16±1.4 | 0.66 | 16±0.9 | 17±9.9 | 0.17 | 16±4 | 16±1.5 | 0.63 | 16±1 | 16±7.6 | 0.3 | |
| Long-term outcome | ||||||||||||||
| Recurrence free at 1 year post-surgery | 95.3% | 97.1% | 91.1% | 0.11 | 95.5% | 94.6% | 0.83 | 93.6% | 98.2% | 0.2 | 97% | 91.7% | 0.15 | |
| Survival at 1 year post-surgery | 97.9% | 100.0% | 92.7% | 0.006 | 99.1% | 94.6% | 0.1 | 96.7% | 100.0% | 0.18 | 100.0% | 94% | 0.01 | |
| Recurrence free at 5 year post-surgery | 50.0% | 54.6% | 40.7% | 0.24 | 50.8% | 46.7% | 0.76 | 49.1% | 52.0% | 0.81 | 52.7% | 44.4% | 0.48 | |
| Survival at 5 year post-surgery | 69.4% | 73.9% | 61.5% | 0.27 | 71.2% | 61.5% | 0.49 | 72.6% | 61.9% | 0.37 | 67.4% | 73.1% | 0.62 | |
| Number of recurrence | 32 | 19 | 13 | 0.15 | 26 | 6 | 0.37 | 23 | 9 | 0.25 | 19 | 13 | 0.25 | |
| Number of death | 29 | 15 | 14 | 0.02 | 24 | 5 | 0.29 | 20 | 9 | 0.47 | 18 | 11 | 0.46 | |
| Cause of death | Colorectal cancer | 17 | 7 | 10 | 0.006 | 13 | 4 | 0.9 | 13 | 4 | 0.22 | 10 | 7 | 0.4 |
| Others | 12 | 8 | 4 | 0.81 | 11 | 1 | 0.17 | 7 | 5 | 0.72 | 8 | 4 | 0.93 |
Long-term outcome
The median follow-up period was 52 months (range 13-100 months). During the follow-up period, 32 patients (21.5%) had recurrence, and 29 (19.5%) died. CAR and NLR had a statistically significant 1 year OS rate (p=0.006 and p=0.01, respectively). Five year OS and RFS rates were not statistically associated with immune-inflammation indexes. The proportions of deaths and cancer-related deaths were significantly higher in the high CAR group (p=0.02 and p=0.006, respectively). The Kaplan-Meier curves of RFS, OS, and CSS according to CAR are shown in Figure 1. The high CAR groups had a significantly poorer prognosis for OS and CSS in the log-rank test (p=0.03 and p=0.01, respectively).
Figure 1.
Kaplan-Meier curves for recurrence free survival, overall survival, and cancer specific survival according to CAR.
Analysis of RFS
The univariate and multivariate analyses of RFS is shown in Table 3. Tumor depth and lymph node metastasis were prognostic factors for recurrence in univariate analysis (p=0.01, and p=0.004, respectively). Both of tumor depth and lymph node metastasis were independent prognostic factors in multivariate analysis (p=0.03, HR 2.095, 95% CI 1.073-4.09 and p=0.008, HR 2.209, 95% CI 1.225-3.982, respectively).
Table 3.
Univariate and Multivariate Cox Proportional Analyses for Recurrence Free Survival.
| Characteristic | ≥65 years, N=149 | ||||
|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | ||||
| HR (95% CI) | p value | HR (95% CI) | p value | ||
| Gender | Male | ||||
| Female | 0.801 (0.451-1.424) | 0.45 | |||
| ASA-PS class | 1 | ||||
| ≥2 | 1.602 (0.86-2.984) | 0.14 | |||
| CCI | 0 | ||||
| ≥1 | 0.86 (0.452-1.635) | 0.65 | |||
| Tumor location 1 | Colon | ||||
| Rectum | 1.277 (0.718-2.273) | 0.41 | |||
| Tumor location 2 | Right | ||||
| Left | 0.585 (0.315-1.084) | 0.09 | |||
| Tumor depth | T2-3 | ||||
| T4 | 2.391 (1.233-4.635) | 0.01 | 2.095 (1.073-4.09) | 0.03 | |
| Lymph node metastasis | negative | ||||
| positive | 2.378 (1.327-4.262) | 0.004 | 2.209 (1.225-3.982) | 0.008 | |
| Lymph node dissection | D1-2 | ||||
| D3 | 1.156 (0.572-2.335) | 0.69 | |||
| lymphatic invasion | negative | ||||
| positive | 1.486 (0.822-2.687) | 0.19 | |||
| venous invasion | negative | ||||
| positive | 1.766 (0.928-3.359) | 0.08 | |||
| budding | negative | ||||
| positive | 1.291 (0.655-2.544) | 0.46 | |||
| Postoperative complications | CD1 | ||||
| CD2,3 | 1.189 (0.426-3.326) | 0.74 | |||
| Adjuvant chemotherapy | negative | ||||
| positive | 1.584 (0.819-3.065) | 0.18 | |||
| CEA | <5 | ||||
| ≥5 | 1.359 (0.766-2.409) | 0.3 | |||
| CAR | <0.09 | ||||
| ≥0.09 | 1.705 (0.943-3.083) | 0.08 | |||
| NLR | <2.38 | ||||
| ≥2.38 | 1.462 (0.81-2.64) | 0.21 | |||
| LMR | <6.01 | ||||
| ≥6.01 | 0.724 (0.392-1.337) | 0.3 | |||
| PLR | <173 | ||||
| ≥173 | 0.701 (0.326-1.507) | 0.36 | |||
Analysis of OS
Univariate and multivariate analyses of OS is shown in Table 4. Lymphatic invasion and CAR were associated with poor OS in the univariate analysis (p=0.03 and p=0.04, respectively). Lymphatic invasion and CAR were independent prognostic factors in multivariate analysis (p=0.04, HR 2.197, 95% CI 1.042-4.632 and p=0.04, HR 2.174, 95% CI 1.032-4.58, respectively).
Table 4.
Univariate and Multivariate Cox Proportional Analyses for Overall Survival.
| Characteristic | ≥65 years, N=149 | ||||
|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | ||||
| HR (95% CI) | p value | HR (95% CI) | p value | ||
| Gender | Male | ||||
| Female | 0.743 (0.353-1.564) | 0.44 | |||
| ASA-PS class | 1 | ||||
| ≥2 | 2.044 (0.949-4.403) | 0.07 | |||
| CCI | 0 | ||||
| ≥1 | 0.653 (0.275-1.552) | 0.34 | |||
| Tumor location 1 | Colon | ||||
| Rectum | 0.785 (0.37-1.664) | 0.53 | |||
| Tumor location 2 | Right | ||||
| Left | 0.464 (0.208-1.037) | 0.06 | |||
| Tumor depth | T2-3 | ||||
| T4 | 1.73 (0.767-3.89) | 0.19 | |||
| Lymph node metastasis | negative | ||||
| positive | 1.841 (0.884-3.835) | 0.1 | |||
| Lymph node dissection | D1-2 | ||||
| D3 | 1.7 (0.685-4.223) | 0.25 | |||
| lymphatic invasion | negative | ||||
| positive | 2.247 (1.061-4.756) | 0.03 | 2.197 (1.042-4.632) | 0.04 | |
| venous invasion | negative | ||||
| positive | 1.358 (0.594-3.101) | 0.47 | |||
| budding | negative | ||||
| positive | 1.095 (0.464-2.581) | 0.84 | |||
| Postoperative complications | CD1-2 | ||||
| CD3 | 0.868 (0.468-1.608) | 0.65 | |||
| Adjuvant chemotherapy | negative | ||||
| positive | 0.944 (0.356-2.504) | 0.91 | |||
| CEA | <5 | ||||
| ≥5 | 1.965 (0.933-4.139) | 0.08 | |||
| CAR | <0.09 | ||||
| ≥0.09 | 2.208 (1.051-4.639) | 0.04 | 2.174 (1.032-4.58) | 0.04 | |
| NLR | <2.38 | ||||
| ≥2.38 | 1.114 (0.518-2.396) | 0.78 | |||
| LMR | <6.01 | ||||
| ≥6.01 | 0.872 (0.394-1.931) | 0.74 | |||
| PLR | <173 | ||||
| ≥173 | 0.94 (0.351-2.516) | 0.9 | |||
Analysis of CSS
Univariate and multivariate analyses of CSS is shown in Table 5. Lymphatic invasion, venous invasion, postoperative complications, and CAR were associated with poor CSS (p=0.03, p=0.03, p=0.03, and p=0.02, respectively). Lymphatic invasion and CAR were independent prognostic factors in the multivariate analysis (p=0.03, HR 3.004, 95% CI 1.11-8.13 and p=0.03, HR 3.087, 95% CI 1.135-8.394, respectively).
Table 5.
Univariate and Multivariate Cox Proportional Analyses for Cancer Specific Survival.
| Characteristic | ≥65 years, N=149 | ||||
|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | ||||
| HR (95% CI) | p value | HR (95% CI) | p value | ||
| Gender | Male | ||||
| Female | 0.606 (0.223-1.648) | 0.33 | |||
| ASA-PS class | 1 | ||||
| ≥2 | 2.242 (0.844-5.959) | 0.11 | |||
| CCI | 0 | ||||
| ≥1 | 0.136 (0.018-1.028) | 0.05 | |||
| Tumor location 1 | Colon | ||||
| Rectum | 1.659 (0.623-4.42) | 0.31 | |||
| Tumor location 2 | Right | ||||
| Left | 1.022 (0.29-3.602) | 0.97 | |||
| Tumor depth | T2-3 | ||||
| T4 | 1.665 (0.569-4.873) | 0.35 | |||
| Lymph node metastasis | negative | ||||
| positive | 1.695 (0.652-4.403) | 0.28 | |||
| Lymph node dissection | D1-2 | ||||
| D3 | 0.959 (0.263-3.498) | 0.95 | |||
| lymphatic invasion | negative | ||||
| positive | 2.941 (1.123-7.688) | 0.03 | 3.004 (1.11-8.13) | 0.03 | |
| venous invasion | negative | ||||
| positive | 4.122 (0.938-18.113) | 0.03 | 3.739 (0.834-16.771) | 0.09 | |
| budding | negative | ||||
| positive | 2.687 (0.614-11.769) | 0.19 | |||
| Postoperative complications | CD1 | ||||
| CD2,3 | 3.582 (1.152-11.133) | 0.03 | 2.412 (0.733-7.933) | 0.15 | |
| Adjuvant chemotherapy | negative | ||||
| positive | 0.947 (0.27-3.316) | 0.93 | |||
| CEA | <5 | ||||
| ≥5 | 2.653 (0.979-7.19) | 0.06 | |||
| CAR | <0.09 | ||||
| ≥0.09 | 3.156 (1.198-8.309) | 0.02 | 3.087 (1.135-8.394) | 0.03 | |
| NLR | <2.38 | ||||
| ≥2.38 | 1.249 (0.464-3.362) | 0.66 | |||
| LMR | <6.01 | ||||
| ≥6.01 | 0.603 (0.195-1.867) | 0.38 | |||
| PLR | <173 | ||||
| ≥173 | 1.288 (0.413-4.022) | 0.66 | |||
Discussion
In this study, we focused on the systemic inflammation and nutritional status of older patients with advanced CRC, comparing patient characteristics, surgical outcomes, and pathological findings using immune-inflammation indexes. Additionally, we compared four immune-inflammation indexes to warrant which index would be suitable for the evaluation of older patients' prognosis. Very few studies have explored the association between immune-inflammation indexes and the prognosis of older patients with CRC[11,12]. Our results indicated that CAR was the most effective immune-inflammation index for predicting postoperative OS and CSS for advanced CRC in older patients.
Inflammation is closely linked to cancer progression. Tumor- and host-derived cytokines, small inflammatory proteins such as prostaglandins or leukotrienes, and infiltrating immune cells in the tumor microenvironment induce local inflammation and promote carcinogenesis[5]. Tumor-derived cytokines and small inflammatory proteins like chemokines and matrix-degrading proteins, are secreted into the systemic circulation to mediate communication with distant sites, and these cytokines and proteins coordinate systemic inflammation[5]. Many studies have confirmed the association between human malignant tumors and systemic inflammation, and several immune-inflammation indexes have been proposed as predictors of long-term outcomes in gastrointestinal malignant tumors[8,12,13]. CAR was originally used to predict mortality in patients with sepsis[14]. Since, CRP is an acute-phase protein secreted in response to acute inflammatory stimuli through the production of interleukin-1 (IL-1) and interleukin-6 (IL-6)[15]. IL-1 and IL-6 are also released during cancer development; therefore, the value of CRP can reflect the inflammatory status around tumor microenvironments that contributes to tumor growth and cancer progression[14,16,17]. Previous studies showed the relationships between CRP and tumor-infiltrating lymphocytes that play pivotal role for inflammation in tumor microenvironment using immunohistochemistry[16,18]. Lu et al reported that perioperative CRP were associated with worse prognosis in gastrointestinal cancer with randomized controlled trial of 419 patients[17]. Albumin is considered to inhibit cancer promotion neutralizing carcinogens, stabilizing cell growth and DNA replication, and indicate immune response[16,19]. Hypoalbuminemia result in imparied immune response which promote cancer progression[16,19-21]. High levels of CAR is associated with poor prognosis in hepatocellular carcinoma, esophageal cancer, lung cancer, and CRC[22-25]. Besides prognosis, some studies revealed the high levels of CAR was associated with larger tumor diameters, lymphovascular invasion, and worse tumor stage in CRC[14,23]. In this study, high CAR levels were associated with poor ASA-PS score, open surgery and budding positivity. This result might reflect the the poor general condition and advanced tumor progression in the high CAR group similar to previous reports[14,23]. Indeed high levels of CAR was an independent prognostic factor for all of OS and CSS.
Focusing on circulating immune-cell concentrations, leukocytes including neutrophils, monocytes, and lymphocytes, play key roles in the systemic inflammatory response in patients with cancer[8]. Neutrophils are the first responders in the innate immune response by tumor necrosis factor-α (TNFα) and IL-6[8]. Neutrophils promote tumor growth and metastasis by remodeling the extracellular matrix and releasing reactive oxygen species, nitric oxide, and arginase, which suppress the activity of cytotoxic T cells[26,27]. Lymphocytes are responsible for immunological monitoring of malignancy and preventing the proliferation and migration of tumor cells[8]. Monocytes play an important role in tumor progression and contribute to tumor infiltration and metastasis[28]. Monocytes differentiate into macrophages at tissues and are considered to contribute to tumor growth and progression, producing inflammatory cytokines like TNF-α, IL-1, or IL-6[5]. Platelets are important for hemostasis or thrombosis; however, they are also responsible for inflammatory response and can promote tumorigenesis in tumor microenvironments[28]. Immune-inflammation indexes using leukocytes have also been reported as prognostic factors. Previous studies have shown that high NLR and PLR are associated with advanced disease and poor prognosis in those with CRC[26]. LMR was also reported to be associated with the OS of patients with CRC[26]. In the present study, NLR was associated with budding positivity and PLR was associated with venous invasion. However NLR, PLR, and LMR were not independent prognostic factors in the multivariate analyses.
The characteristics of CRC in older patients were female predominance, a shift towards right colon distribution, multiple primary cancers, high serum CEA, larger tumors, undifferentiated histology, and advanced pathological T-stage[29]. In older patients, tumor immunity as well as their physical condition is considered to be decreasing. The immune system and blood cell components change dynamically with age[12,30]. Both the number and percentage of lymphocytes decrease with age, because the amount of lymphoid tissue decreases with aging[30], whereas the monocyte count increases continuously. However, the platelet and neutrophil counts do not differ markedly with age[12]. In our study, only CAR was associated with postoperative OS and CSS but not NLR, PLR, or LMR. CAR had the highest AUC (0.537) among the immune-inflammatory indexes that were analyzed, and might strongly reflect the progression of CRC along with intestinal inflammation indicated by CRP and decreased nutritional status by albumin. Only the blood cell components might not be able to reflect the condition of tumor inflammation appropriately due to the varied aging-changes of blood cell components in older patients. Tominaga et al. also reported that the inflammation score using only the complete blood count (CBC) components was insufficient to estimate prognosis in older patients because of the differences that occur in different CBC components with aging, and that it is important to assess both inflammation and nutrition status[12]. Although TNM staging is the most reliable system for predicting prognosis based on lymph node metastasis, the immune-inflammation indexes such as CAR that assess both cancer inflammation and the nutritional status of the patients can be valuable predictive factor of CRC especially in older patiuents. Preoperative treatment for inflammation and nutritional intervention may improve prognosis for the patients with high levels of CAR. Moreover, preoperative CAR can be the indicator for postoperative adjuvant chemotherapy or close follow-up.
Our study had the limitations of being a single-center study with a relatively small sample size, short observation period and a retrospective study design. Furthermore, we should consider the validity of the cutoff values because these immune-inflammation indexes have no standard values, and the cutoff values can differ among different age groups or populations[14]. The cutoff values of each index can be affected by the older population (aged ≥ 65 years), who may more likely have chronic systemic inflammation or malnutrition than the younger populations[12]. Therefore, further large-scale studies and randomized controlled studies by age groups are required to validate these results and overcome the biases in this study. Genetic mutations like RAS, BRAF and microsatellite instability (MSI) that are critical for oncogenesis in CRC can influence anti-tumor immune response[31,32]. We were unable to include the information of these genetic mutations in this study due to the lack of available data. The significance of immune-inflammation indexes by each genetic mutation and prognostic prediction by the combination of immune-inflammation indexes and genetic mutations are expected to elucidate in future studies.
CAR is a useful immune-inflammation index for predicting prognosis after radical resection for advanced CRC in older patients.
Conflicts of Interest
There are no conflicts of interest.
Author Contributions
Study conception and design: Naohiro Yoshida.
Acquisition of data: Naohiro Yoshida, Haruki Yonemori, Yoshiki Miyamoto, Ai Nishihira, Takahiro Shigaki, Kenji Fujiyoshi, Kenichi Koushi, Takefumi Yoshida.
Analysis and interpretation of data: Naohiro Yoshida, Takahiro Shigaki, Kenji Fujiyoshi, Kenichi Koushi.
Drafting of manuscript: Naohiro Yoshida.
Critical revision of manuscript: Takefumi Yoshida, Tomoya Sudo, Toru Hisaka, Nobuya Ishibashi, Fumihiko Fujita.
Approval by Institutional Review Board (IRB)
We obtained approval from the Institutional Review Board of ethics in Kurume University hospital (Approval No. 21187).
Data Availability Statement
All data generated or analyzed during this study are included in this published article.
Informed Consent
The Ethics Committee of Kurume University hospital waived the need for informed consent because the individuals were anonymized for this retrospective study.
Acknowledgements
We would like to thank Editage (www.editage.com) for English language editing.
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