Journal of the College of Physicians and Surgeons Pakistan
ISSN: 1022-386X (PRINT)
ISSN: 1681-7168 (ONLINE)
Affiliations
doi: 10.29271/jcpsp.2022.04.461ABSTRACT
Objective: To investigate the role of cost-effective and widely used hemogram parameters in predicting stage and histological grade.
Study Design: An analytical study.
Place and Duration of Study: Konya Research and Training Hospital, Turkey from January to June 2020.
Methodology: Pre-nephrectomy hemogram parameters and post-nephrectomy pathology reports of 180 renal cell carcinoma patients, among 553 patients, who had undergone nephrectomy between 2009-2019 were evaluated. The patients were grouped as low risk and high risk in terms of TNM stage and Fuhrman grade; and clinicopathological variables were compared between the groups. Multivariate logistic regression analysis was used to determine the parameters predicting independently the high T stage (T3-T4) and the high Fuhrman grade (G3-G4).
Results: While 31 (17.2%) of 180 patients were in the high T stage; 69 (38.3%) were in the high Fuhrman grade. In the logistic regression analysis, NLR, LMR, and hematocrit predicted independently high T stage, while hematocrit and LMR predicted independently the high Fuhrman grade.
Conclusion: LMR, NLR, and hematocrit were found to be more significant than other parameters, which are among the hemogram parameters that can guide clinicians during staging, which is important for prognosis and treatment decisions.
Key Words: Renal cell carcinoma, Tumor staging, Tumor grading.
INTRODUCTION
In 2018, among all cancers in the world, kidney cancers ranked 14th with 403,262 new cases; and ranked 16th in cancer-related mortality with 175,098 deaths. Survival rates have increased 2-fold in the last 50 years due to curative surgical approaches, early detection of tumours in smaller sizes, and highly effective systemic treatments. Although surgical resection can be curative in localised disease. Since the renal cell carcinoma (RCC) is silent due to its nature, it cannot be diagnosed until it is locally advanced and unresectable or metastatic in approximately one-third of the newly diagnosed cases; between 10 and 30 per cent of nephrectomy cases due to undetected micrometastases return with local recurrence or distant metastasis.1
The stage and prognosis in RCC vary depending on anatomical, clinical, histological and molecular factors.2 The presence of many cytokines, released from the renal tumour with immunosuppressive properties, affecting the immune system and bone marrow, is important in terms of providing more information about active cancer in the hemogram examinations performed before nephrectomy. There are many studies on this subject because of the cost-effectiveness and widespread use of hemogram parameters, which are affected by all factors related to particularly systemic treatment, stage and prognosis.
The use of laboratory parameters as supportive in addition to imaging methods in determining the prognosis of the disease is important for the follow-up and treatment of the patient. Thus, the aim of this study was to investigate the roles of pre-nephrectomy hemogram parameters in predicting both the high Fuhrman grade (FG) and high T-stage.
METHODOLOGY
After obtaining ethical approval, the clinicopathological data of 180 kidney cancer patients diagnosed with renal cell cancer carcinoma, who underwent partial or total nephrectomy between 2009-2019, were evaluated retrospectively. The study was conducted in Konya Research and Training Hospital, Turkey between January 2020 and June 2020. Patients with history of other haematological or solid organ malignancies, autoimmune diseases, inflammatory diseases, infectious diseases and whose Fuhrmann grade was not specified in the pathology report, and those under 18 years of age, were excluded from the study.
Preoperative hemogram parameters include hemoglobin, hematocrit (HCT), red blood cell count (RBC), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), platelet, mean platelet volume (MPV), plateletcrit (PCT), platelet distribution width (PDW), white blood cell count (WBC), neutrophil, lymphocyte, monocyte, basophil and eosinophil counts were evaluated according to the postoperative pathology report results. Platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR) were calculated.
Pathological staging was done according to the American Joint Committee on Cancer (AJCC); 8th Edition. Histological subtypes were determined according to the 1997 WHO Heidelberg classification, and tumour nuclear grading was performed according to the Fuhrman nuclear grading system. The patients were classified as the low stage (T1-T2) and high stage (T3-T4), according to their pathological results. The patients were also classified according to the Fuhrman grade as low grade (G1-G2) and high grade (G3-G4).
Statistical analysis was performed with SPSS version 25.0 (SPSS Inc., Chicago, Illinois, USA). The clinicopathological variables of the patients were first evaluated in terms of normal distribution by the Kolmogorov-Smirnov test. Normally distributed variables were shown as mean ± standard deviation, while non-normally distributed variables were shown as median (minimum-maximum). Numeric variables were compared with Student's t-test or Mann-Whitney U-test, according to normal distribution status; and the categorical variables were compared with Chi-square or Fisher’s Exact test, according to their suitability. Receiver operating curve (ROC) analysis was performed to determine the area under curve (AUC), cut-off values, sensitivity, and specificities of the variables that were found to be significant between the groups. In addition, logistic regression analysis was performed to determine the parameters indicating stage and nuclear grade, independently among the variables that were found to be statistically significant between the groups in terms of stage and nuclear grade. Statistically, p <0.05 was considered significant.
RESULTS
Of the 180 patients analysed, 78 were females (43.3%) and 102 were males (56.7%). The mean age of the patients at the time of nephrectomy was 60.6 ± 15.4 years. According to tumor pathological staging, 82.8% of the patients were in the low stage, while 17.2% of them were in the high stage. According to the histopathological nuclear grading, 61.7% of the patients were in the low grade, while 38.3% of them were in the high grade. The groups were compared in terms of clinicopathological characteristics (Table I).
There was no statistically significant difference between the low T stage and high T stage groups in terms of age, gender and histological subtype. Among the hemogram parameters, hematocrit (p = 0.045), NLR (p <0.001), LMR (p = 0.005), neutrophil percentage (p = 0.044), and lymphocyte percentage (p=0.012) were statistically significantly different between the two groups (Table I).
There was no statistically significant difference between low Fuhrman grade and high Fuhrman grade groups in terms of age and gender. When the groups were compared in terms of histological subtypes, it was seen that the mixed type in the other category was more in the Fuhrman high-grade group. Among the hemogram parameters, haemoglobin (p = 0.001), hematocrit (p = 0.001), red blood cell count (RBC) (p = 0.008), red cell distribution wide (RDW) (p = 0.007), PLR (p = 0.046), NLR (p = 0.011), monocyte count (p = 0.036), and LMR(p = 0.006) were statistically significantly different between the groups (Table I).
NLR, LMR, and haemoglobin were statistically different between low and high groups in both T staging and Fuhrman grading. In logistic regression analysis, NLR (OR: 6.268) (2.088-18.816) (p = 0.001) and percentage of neutrophils (OR: 0.869) (0.777-0.971) (p = 0.013) were found as haematological parameters independently indicating the high T stage. Haemoglobin (OR: 0.804) (0.695-0.930) (p = 0.003) and LMR (OR: 0.761) (0.618-0.937) (p = 0.010) were also found as haematological parameters that independently showed the high Fuhrman nuclear grade (Table II).
In ROC analysis indicating the high T stage, while hematocrit (cut-off ≤43.7) (AUC: 0.615 (0.539-0.686) (p = 0.040), NLR (cut-off >3.5) (AUC: 0.634 (0.559-0.704) (p = 0.029), LMR (cut-off ≤3.1) (AUC:0.662) (0.588-0.731) (p = 0.006), and lymphocyte percentage (cut-off ≤20.5) (AUC: 0.644) (0.570-0.71 4) (p = 0.017) were statistically significant. The percentage of neutrophils (cut-off >62.5) (AUC: 0.607 (0.531-0.679) (p = 0.086) was statistically insignificant but at borderline. In indicating the high Fuhrman grade, while RDW (cut-off >13.3) (AUC: 0.620) (0.545-0.691) (p = 0.004), hematocrit (cut-off ≤40.3) (AUC: 0.642 (0.568-0.712) (p <0.001), haemoglobin (cut-off ≤14.8) (AUC: 0.643 (0.568-0.713) (p <0.001), RBC (cut-off ≤ 5.05) (AUC: 0.636 (0.561-0.706) (p = 0.001), and LMR (cut-off ≤2.9) (AUC: 0.622 (0.547-0.693) (p = 0.004) were statistically significant; monocyte count (cut-off >0.48) (AUC: 0.580 (0.504-0.653) (p = 0.066), and PLR (cut off >186.6) (AUC: 0.589 (0.513-0.661) (p = 0.051) were statistically insignificant but at borderline (Table III).
DISCUSSION
Despite advances in diagnostic methods, routine diagnosis and prognostic evaluation of RCC is still performed with pathological tissue examination and traditional clinicopathological prognostic variables.
Table I: Clinical characteristics according to T-stage and Fuhrman grade (low vs. high).
|
|
Total |
Low stage |
High stage |
p-value |
Low grade |
High grade |
p-value |
|
Age |
60.6±15.4 |
60.7±15.2 |
59.8±16.6 |
0.758 |
60.4±16.1 |
60.7±14.2 |
0.897 |
|
Gender |
0.171 |
|
|
0.975 |
|||
|
Female |
78(43.3%) |
68(45.6%) |
10(32.3%) |
48(43.2%) |
30(43.5%) |
|
|
|
Male |
102(56.7%) |
81(54.4%) |
21(67.7%) |
63(56.8%) |
39(56.5%) |
|
|
|
Histology |
0.133 |
|
|
0.006 |
|||
|
Clear cell |
116(64.4%) |
99(66.4%) |
17(54.8%) |
77(69.4%) |
39(56.5%) |
|
|
|
Papillary |
29(16.1%) |
23(15.4%) |
6(19.4%) |
17(15.3%) |
12(17.4%) |
|
|
|
Chromophobe |
14(7.8%) |
13(8.7%) |
1(3.2%) |
11(9.9%) |
3(4.3%) |
|
|
|
Others |
21(11.7%) |
14(9.4%) |
7(22.6%) |
6(5.4%) |
15(21.7%) |
|
|
|
Haemoglobin |
14(6.4-18.3) |
14.1(6.4-18.3) |
13.6(8.1-17.6) |
0.114 |
14.4(8.1-18.3) |
13.5(6.4-16.7) |
0.001 |
|
Low haemoglobin* |
37(20.6%) |
26(17.4%) |
11(35.5%) |
0.024 |
17(15.3%) |
20(29%) |
0.024 |
|
High haemoglobin |
143(79.4%) |
123(82.6%) |
20(64.5%) |
94(84.7%) |
49(71%) |
|
|
|
Hematocrit |
42.2(21.2-57.6) |
42.3(21.2-57.6) |
41.5(26.3-50.3) |
0.045 |
43(24.7-57.6) |
41.2(21.2-50.2) |
0.001 |
|
Low hematocrit** |
40(22.2%) |
28(18.8%) |
12(38.7%) |
0.015 |
18(16.2%) |
22(31.9%) |
0.014 |
|
High hematocrit |
140(77.8%) |
121(81.2%) |
19(61.3%) |
93(83.8%) |
47(68.1%) |
|
|
|
RBC |
4.9±0.7 |
4.9±0.6 |
4.7±0.8 |
0.112 |
5±0.6 |
4.7±0.7 |
0.008 |
|
MCV |
86.2(61.1-103.5) |
86.3(61.6-103.5) |
84.9(61.1-102.9) |
0.293 |
86.4(61.6-103.5) |
84.9(61.1-102.9) |
0.245 |
|
MCH |
28.7(18-33.2) |
28.7(19.4-33.2) |
28.6(18-33.1) |
0.420 |
28.9(19.4-33.2) |
27.9(18-33.1) |
0.109 |
|
MCHC |
33±1.5 |
33±1.4 |
33±1.6 |
0.853 |
33.2±1.4 |
32.7±1.5 |
0.064 |
|
RDW |
14.1(11.7-33.4) |
14.1(11.7-33.4) |
14.1(12.3-19.4) |
0.997 |
13.8(11.7-33.4) |
14.5(12.7-32) |
0.007 |
|
Platelet |
293.3±91.8 |
293.2±88.7 |
294.1±107.3 |
0.960 |
283.7±81.9 |
308.8±104.6 |
0.074 |
|
PLR |
126.5(10.8-471.1) |
123.9(10.8-462.4) |
137.3(68.6-471.1) |
0.133 |
123.2(10.8-289.4) |
137.2(68.6-471.1) |
0.046 |
|
MPV |
10.1(6.6-13) |
10.1(6.6-13) |
10.2(8.4-12) |
0.295 |
10.1(6.6-13) |
10.1(6.8-12.2) |
0.934 |
|
WBC |
7.8(3.8-17.1) |
7.8(3.9-17.1) |
7.2(3.8-15.5) |
0.953 |
7.7(4.2-17.1) |
7.8(3.8-15.5) |
0.693 |
|
Neutrophil |
4.9±1.6 |
4.8±1.4 |
5.4±2.4 |
0.085 |
4.8±1.4 |
5.1±1.9 |
0.224 |
|
Lymphocyte |
2.2(0.8-12.9) |
2.3(1-12.9) |
2(0.8-4.1) |
0.063 |
2.3(1.1-12.9) |
2.1(0.8-4.6) |
0.118 |
|
NLR |
2.3±1.1 |
2.2±0.7 |
3.1±2.1 |
<0.001 |
2.2±0.7 |
2.6±1.6 |
0.011 |
|
Monocyte |
0.6±0.2 |
0.6±0.2 |
0.7±0.2 |
0.112 |
0.6±0.2 |
0.7±0.2 |
0.036 |
|
LMR |
3.7(0.9-18.9) |
3.7(1.6-18.9) |
2.9(0.9-7.1) |
0.005 |
3.8(1.6-18.9) |
3.3(0.9-7.9) |
0.006 |
|
Basophil |
0(0-0.2) |
0(0-0.2) |
0(0-0.1) |
0.468 |
0(0-0.2) |
0(0-0.1) |
0.369 |
|
Neutrophil % |
61±8.3 |
60.4±7.8 |
63.7±10 |
0.044 |
60.3±8.1 |
62.1±8.5 |
0.147 |
|
Lymphocyte % |
28.9(7.2-75.1) |
29.6(16.5-75.1) |
25.4(7.2-44.8) |
0.012 |
29.6(17.6-75.1) |
27.4(7.2-44.8) |
0.134 |
|
Monocyte % |
7.7(1.7-16.6) |
7.6(1.7-13.7) |
8.3(4.8-16.6) |
0.230 |
7.6(1.7-13.3) |
8(4.8-16.6) |
0.074 |
|
Basophil % |
0.4(0-2.9) |
0.4(0-2.9) |
0.4(0-0.7) |
0.331 |
0.4(0-2.9) |
0.4(0-1.2) |
0.370 |
|
PCT |
0.3(0.1-0.6) |
0.3(0.1-0.6) |
0.3(0.2-0.6) |
0.417 |
0.3(0.1-0.5) |
0.3(0.1-0.6) |
0.265 |
|
PDW |
12.3(9.5-57.2) |
12.4(9.5-57.2) |
12(9.7-52.5) |
0.291 |
12.2(9.5-57.2) |
12.6(9.7-52.5) |
0.861 |
|
Eosinophil |
0.1(0-1.1) |
0.1(0-1.1) |
0.2(0-0.6) |
0.594 |
0.1(0-1.1) |
0.1(0-0.6) |
0.261 |
|
Eosinophil % |
1.7(0-8.8) |
1.7(0-8.1) |
2.1(0.1-8.8) |
0.976 |
1.9(0-8.1) |
1.6(0-8.8) |
0.233 |
|
Data were shown as number (per cent) for categoric variables and median (minimum-maximum) for numeric skewed distributed variables and mean ± standard deviation for numeric normally distributed variables. Numeric variables were compared with Student's t-test or Mann-Whitney U-test according to normal distribution status, and categorical variables were compared with chi-square or exact test according to their suitability. *Defined low as haemoglobin <11 g/dL for female and haemoglobin <13 g/dL for male. **Defined low as hematocrit <35% for female and hematocrit <40% for male. |
|||||||
Table II: Determination of haematological parameters that independently predict the high stage and grade.
|
|
OR |
95% CI |
p-value |
|
T stage (low versus high)1 |
|||
|
Neutrophil % |
0.869 |
0.777-0.971 |
0.013 |
|
NLR |
6.268 |
2.088-18.816 |
0.001 |
|
Constant |
13.951 |
|
0.257 |
|
Fuhrman grade (low versus high)2 |
|||
|
Haemoglobin |
0.804 |
0.695-0.930 |
0.003 |
|
LMR |
0.761 |
0.618-0.937 |
0.010 |
|
Constant |
35.057 |
|
0.001 |
|
OR: Odds ratio, CI: Confidence interval, NLR: Neutrophil to lymphocyte ratio, LMR: Lymphocyte to monocyte ratio. |
|||
|
1Logistic regression Backward Stepwise (Likelihood Ratio); χ2 (2) = 19.207, p <0.001, Nagelkerke R Square=0.168; Hct, Hct subgroup, Hgb subgroup, Neutrophil, Lymphocyte, NLR, LMR and Neutrophil % are included in multivariate analyses. The last step (step 7) is shown in the Table. |
|||
|
2Logistic Regression Backward Stepwise (Likelihood Ratio); χ2 (2) = 19.873, p <0.001, Nagelkerke R Square=0.142 Histology, haemoglobin, haemoglobin subgroup, hematocrit, hematocrit subgroup, RBC, MCHC, RDW, Plt, PLR, NLR, Monocyte, LMR, Monocyte % are included in multivariate analyses. The last step (step 13) is shown in the Table. |
|||
New molecular diagnostic methods cannot be used routinely because of the high costs, the time-consuming preparation of the samples to be examined, and the lack of sufficient clinical data on how these new molecular markers might affect both diagnostic and therapeutic decisions.3 For this reason, widespread use, cost-effectiveness, and easy evaluation make hemogram parameters to be more preferred in RCC risk assessment.4
Increasing scientific evidence shows that systemic inflammatory response plays an important role in all stages of malignancies from the onset to progression. Various inflammatory response markers such as NLR, LMR, PLR, platelet count, and C-reactive protein (CRP) are used as potential prognostic factors in RCC patients.
Table III: Receiver operating characteristic (ROC) analysis of haematological parameters to predict stage and grade.
|
|
Cut off |
AUC |
95% CI |
Sensitivity |
Specificity |
Maximum Youden index |
p-value |
|
T stage (low versus high) |
|||||||
|
RDW |
≤13.3 |
0.500 |
0.425-0.562 |
19.4% |
71.1% |
0.095 |
0.996 |
|
PCT |
>0.4 |
0.554 |
0.465-0.641 |
30.4% |
84.3% |
0.147 |
0.443 |
|
PLT |
≤185 |
0.519 |
0.444-0.594 |
22.6% |
90.6% |
0.132 |
0.763 |
|
Neutrophil |
>7.0 |
0.536 |
0.460-0.610 |
25.8% |
93.3% |
0.191 |
0.580 |
|
MPV |
>10.3 |
0.560 |
0.484-0.634 |
45.2% |
67.8% |
0.130 |
0.292 |
|
NLR |
>3.5 |
0.634 |
0.559-0.704 |
29.0% |
97.3% |
0.263 |
0.029 |
|
LMR |
≤3.1 |
0.662 |
0.588-0.731 |
58.1% |
75.5% |
0.325 |
0.006 |
|
Hematocrit |
≤43.7 |
0.615 |
0.539-0.686 |
83.9% |
39.6% |
0.235 |
0.040 |
|
Neutrophil % |
>62.5 |
0.607 |
0.531-0.679 |
64.5% |
59.1% |
0.236 |
0.086 |
|
Lymphocyte % |
≤20.5 |
0.644 |
0.570-0.714 |
32.3% |
93.3% |
0.256 |
0.017 |
|
PLR |
>186.8 |
0.586 |
0.510-0.659 |
32.3% |
88.6% |
0.209 |
0.158 |
|
Fuhrman grade (low versus high) |
|||||||
|
RDW |
>13.3 |
0.620 |
0.545-0.691 |
87.0% |
36.1% |
0.230 |
0.004 |
|
PCT |
>0.3 |
0.559 |
0.469-0.645 |
38.3% |
81.0% |
0.193 |
0.288 |
|
PLT |
>309 |
0.571 |
0.495-0.644 |
52.2% |
67.6% |
0.197 |
0.125 |
|
Neutrophil |
>5.8 |
0.537 |
0.461-0.611 |
33.3% |
83.8% |
0.171 |
0.428 |
|
MPV |
>7.9 |
0.504 |
0.428-0.579 |
97.1% |
9.0% |
0.061 |
0.934 |
|
NLR |
>3.3 |
0.564 |
0.489-0.638 |
23.2% |
92.8% |
0.160 |
0.160 |
|
HCT |
≤40.3 |
0.642 |
0.568-0.712 |
47.8% |
75.7% |
0.235 |
<0.001 |
|
HGB |
≤14.8 |
0.643 |
0.568-0.713 |
82.6% |
39.6% |
0.223 |
<0.001 |
|
RBC |
≤5.05 |
0.636 |
0.561-0.706 |
72.5% |
54.1% |
0.265 |
0.001 |
|
Monocyte |
>0.48 |
0.580 |
0.504-0.653 |
82.6% |
33.3% |
0.160 |
0.066 |
|
LMR |
≤2.9 |
0.622 |
0.547-0.693 |
37.7% |
84.7% |
0.223 |
0.004 |
|
PLR |
>186.6 |
0.589 |
0.513-0.661 |
27.5% |
91.9% |
0.194 |
0.051 |
|
RDW: Red cell distribution width, PCT: Plateletcrit PLT: Platelet, MPV: Mean platelet volume, NLR: Neutrophil to lymphocyte ratio, LMR: Lymphocyte to monocyte ratio, PLR: Platelet to lymphocyte ratio. |
|||||||
The prognostic role of anaemia in operated RCC patients is still not clearly defined. Anaemia is quite common in malignancies, including RCC. Karakiewicz et al. emphasised that preoperative haemoglobin level predicted RCC-specific mortality in all-stage RCC patients.8 In a meta-analysis, a significant increase was found in all-cause mortality, cancer-specific mortality, and disease recurrence in anaemic patients compared to non-anaemic patients, according to preoperative haemoglobin values.9
Seda et. al. showed that low hematocrit levels were associated with poor survival in surgically treated RCC patients.10 Although there are studies on the importance of low hematocrit levels in cancers such as lung cancer, colon cancer, and oesophagal cancer, no other comprehensive study was found in the literature showing the importance of low hematocrit in RCC. In this study, the association of anemia with higher grade and stage indirectly indicates poor prognosis in RCC.
While high RDW values are a poor prognostic factor in some types of cancer, it has also been shown to be a negative predictor for cancer-specific survival and OS in some types of cancer. Some studies have shown the prognostic importance of RDW value in urological cancers.11-13 In their study, Kisa et al. found that high RDW value was associated with high FG and kidney-limited T stage.14 In this study, while there was a relationship between RDW and high FG, there was no relationship between RDW and high T stage; which suggests that high FG is more important in terms of prognosis.
High neutrophil levels cause the release of free oxygen radicals that provide a microenvironment for tumour invasion and metastasis, trigger cell DNA damage, and genetic instability.15 The decrease in lymphocyte count plays a role in the inflammatory response in tumour biology. While lymphopenia shows the impaired cell-mediated immune system, neutrophilia shows the response to systemic inflammation. NLR, which is obtained by dividing the neutrophil number by the number of lymphocytes, is important for cancers in this respect. Some studies emphasise the increased prognostic value of NLR, especially in malignancies such as colorectal cancers and HCC.16,17 In the studies conducted, the high pretreatment NLR rate in RCC indicates that the clinical course will be worse.18 In this study, the authors showed NLR was significant in predicting the higher FG and the higher T stage. In this regard, Kisa et al. also showed that NLR is significant in predicting both the T stage and the Fuhrman grade.14
According to the 2016 WHO classification, RCC is divided into histological types such as clear cell, papillary, chromophobe, collecting duct, etc. While the clear cell histological subtype is the most common, and has the best prognosis, other subtypes and especially those with sarcomatoid differentiations are more aggressive. Viers et al. divided kidney tumours into histological subtypes as benign and malignant tumours.19 They could not find a significant difference in terms of NLR levels between subtypes of benign kidney tumours. However, they found a significant difference between malignant subtypes in terms of NLR levels. In their study, they found the lowest NLR rate in the clear cell cancer subtype and the highest NLR rate in the collecting duct cell subtype, and this difference was statistically significant. In this study, while the authors found a difference in high FG in terms of histological subgroups, they did not find a difference in terms of high T stage.
Numerous studies have shown that pretreatment PLR is a predictive factor in the metastatic RCC patients.20 The prognostic significance of PLR has been investigated in few studies performed on non-metastatic RCC patients.21,22 Studies are showing that PLR, a potential marker of the systemic inflammatory response, can predict clinical outcomes in metastatic RCC patients treated with tyrosine kinase inhibitör (tKI).23-25 In the present study, the relationship between PLR and high FG, reminds the importance of high FG in terms of prognosis. Prospective studies with a larger number of patients are needed on this subject.
CONCLUSION
LMR, NLR, and haemoglobin were found to be more significant than other parameters, which are among the hemogram parameters that can guide clinicians in predicting stage and determining prognosis and treatment plan. Clinicians are advised to be conscious with regard to micrometastases that cannot be seen in the staging of nephrectomised patients with LMR ≤2.9, and to consider this value in planning and monitoring systemic treatment.
ETHICAL APPROVAL:
The study was approved by the local Ethics Committee of the Selcuk University (2019-335) prior to the initiation of the research work; and was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.
PATIENTS’ CONSENT:
The informed and written consents of the patients were signed by the patients before the beginning of the study.
CONFLICT OF INTEREST:
The authors declared no conflict of interest.
AUTHORS’ CONTRIBUTION:
IO: Conseptualisation, methodology, investigation, formal analysis, writing and original draft preparation.
FS: Conseptualisation, methodology, software, formal analysis, writing and original draft preparation, visualisation, writing review and editing, supervision.
DO: Investigation, visualisation.
REFERENCES