Abstract

Introduction: The purpose of the study is to study the potential role of neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), and mean platelet volume (MPV)–platelet ratio as diagnostic and prognostic markers in patients with hepatocellular carcinoma (HCC), prostate cancer, stomach cancer, and aplastic anemia. Materials and Methods: We have conducted the present study by screening 208,486 patients who have got admitted during January 2013–June 2017 as in patients in our hospital. The data collected were analyzed for NLR, PLR, and MPV–platelet ratio. Inclusion Criteria: Patients admitted with a diagnosis of HCC, prostate cancer, stomach cancer, and aplastic anemia irrespective of the age and gender. Exclusion Criteria: Patients with multiple malignancies, the presence of secondary infection, and any source of sepsis. SPSS tool was used for statistical analysis. Results: Cost-effective predictive and prognostic biomarkers identified in the study are – NLR for liver cancer, prostate cancer, and stomach cancer; PLR for prostate and stomach cancer; MPV/plate ratio can be used in addition to NLR for liver cancer. These ratios were not significant in aplastic anemia. Conclusion: From our study, we conclude that NLR and PLR are better cost-effective predictor and prognostic markers of HCC, prostate cancer, and stomach cancer. These ratios can be used at the primary health-care level as it can be derived from a simple complete blood count/peripheral smear. Early identification of carcinoma is possible using these potential markers along with the respective clinical presentations and symptoms. These ratios will reduce the financial burden on the patients from rural and low socioeconomic background and will aid in better management of the disease process.

Introduction

As per statistical reports of 2015, it is estimated that about 14 million new cancer cases were diagnosed, and >8 million cancer deaths occurred worldwide. Out of this, 1 million new cases were reported from India and nearly 700,000 of the deaths occurred only in India.[1] The number of new cancer cases reported will rise to 22 million within the next two decades. When seen globally, nearly 1 in 6 deaths occur due to cancer, of which liver cancer (788,000 deaths) and stomach cancer (754,000 deaths) stand to be the major carcinoma mortality cause.[1],[2]

More than 60% of the world's new cancer cases occur in Africa, Asia, and Central and South America. About 70% of the world's cancer deaths also occur in these regions as these subcontinents are in developing phase when compared to rest of the world and have minimal access to advanced diagnostic modality at the primary health-care centers. Late-stage presentation and poor diagnosis and treatment are a common cause of majority of the death. The total annual economic cost of cancer is estimated to be approximately US$ 1.16 trillion.[2]

In recent years, accumulating evidence demonstrated that increased systemic inflammation is associated with poor cancer-specific survival in a variety of cancers.[3],[4],[5],[6],[7] These studies revealed that the host's inflammatory response to cancer and/or the systemic effects exerted by the cancer cells lead to upregulation of the inflammatory process, inducing the proliferation and metastasis of cancer cells by inhibiting apoptosis, promoting angiogenesis, and repairing DNA damage.[8],[9] The presence of a systemic inflammatory response can be detected by neutrophil–lymphocyte ratio (NLR).[10] Studies have shown that an elevation in NLR correlated with tumor progression, metastasis, and clinical outcome in a variety of cancers.[11],[12],[13],[14],[15],[16] In this study, we are focusing on analyzing the utility of these ratios as predictive and prognostic markers in various cancers.

The prediction is with reference to early identification and timely referral to right oncology center. This will improve the cure rate and survival probability of the carcinoma patients. In the study, the predictive potential of the biomarkers is evaluated. These markers will prove to be useful in predicting the malignancy as a differential diagnosis at primary health-care centers and timely referral to malignancy management.

Although advancements happens across the world in oncology management, there is an increasing trend in Cancer incidence and Cancer mortality. This is mainly due to economic burden of the treatment cost and lack of cost-effective diagnostic modality at primary health-care centers. In this study, we are focusing on using NLR, platelet–lymphocyte ratio (PLR), and mean platelet volume (MPV)/platelet ratio as cost-effective biomarkers for screening and differentiating the common cancers in rural and primary health-care setups.

Materials and Methods

The present study is a retrospective, hospital-based observational study. We conducted the present study by screening 208,486 patients who have got admitted during January 2013–June 2017 as in patients in our hospital. Out of the total population, 100 cases in each of hepatocellular carcinoma (HCC), stomach cancer, prostate cancer, and aplastic anemia were selected as the study group. Maximum number of aplastic anemia cases reported in the study period was 102 cases, and hence, the sample size was chosen as 100 in each of the carcinoma study group. The control group was formed with an equal number of patients without any carcinoma presentation and other comorbidities. Irrespective of the stage of the disease process in each of the carcinoma test group, the predictive and prognostic potential of the biomarkers was evaluated.

The data collected were analyzed for NLR, PLR, and MPV–platelet count ratio.

Laboratory investigations

Laboratory investigation reports of the study groups and control groups were recorded in predesigned pro forma for statistical analysis. CRP, neutrophil count, lymphocyte count, and platelet volume were analyzed and compared with the standard laboratory reference value as mentioned below for understanding the deviations in the study group marker values. NLR, PLR, and MPV–platelet count were calculated and compared to the control group results.

• Neutrophil count (60%–80%)

• Lymphocyte count (20%–40%)

• MPV (6.8–10 f).

Inclusion criteria

The patients admitted with a diagnosis of HCC, prostate cancer, stomach cancer, and aplastic anemia irrespective of the age group.

Exclusion criteria

Patients with >1 malignancy reported the presence of secondary infection, any source of sepsis, and other comorbidities.

Data collection and statistical analysis

For each member of the study groups, demographic information, details of various symptoms and reported clinical presentations, and laboratory investigations as mentioned above were recorded onto a standard data collection sheet as per the study pro forma and later transferred to a Microsoft Excel spreadsheet for further statistical analysis.

In this study, we analyzed complete blood count (CBC)/peripheral smear reports of the patients. All these tests were done in the same machine, and the results were analyzed and stored as computerized database. There is no scope for observer variability. It is an NABH- and ISO-certified laboratory where all the tests conducted are standardized and documented according to certification standards.

Data were organized and compiled into Microsoft Excel Version 2010. (Microsoft Corporation, One Microsoft Way Redmond, WA 98052-6399 USA) and data were systematically analyzed by SPSS 20.0 version. The assumption of P < 0>

Predictive and prognostic significance of laboratory tests has been arrived at by following the below steps:

1. The results of each of the test variables were statically analyzed using “t-test” with the assumption of P < 0>

2. When the tests proved to be significant, ROC curve analysis is done to confirm the specificity and sensitivity over the range of mean values

3. Test variables were confirmed to have significance if the area under curve showed >50% of coverage in area under curve analysis

4. Finally, the predictive significance of the test parameters is substantiated by comparing the mean values of each of the parameters with their respective control group values and symptomatic evaluation of the test groups. This showed the indicative potential of the biomarkers.

The prognostic potential is evaluated similar to the predictive capability of the biomarkers. The indicative cutoff values of the biomarkers are arrived at using data from very high sample size. These cutoff values along with the symptoms and presenting conditions are used for evaluating the disease prognosis during every visit after the start of the treatment course.

Results

Observations and analysis of data in this study are presented in tables and figures listed here. Various carcinoma presentations in the study population are shown in [Figure 1], and [Figure 2] shows the spread spectrum across gender and age. [Figure 3] shows in-hospital mortality observed in various carcinoma study groups.

| Figure 1  Carcinoma presentation – Spectrum across gender and Age

| Figure 2  Presenting age in various carcinoma under study

| Figure 3  In-hospital mortality represented in carcinoma study groups

Statistical analysis for HCC is shown in [Table 1]. The t- test observation showed that NLR and MPV/platelet ratio was highly significant markers as indicated in [Table 1]. ROC analysis for sensitivity and specificity showed NLR had covered 77% and MVP/platelet ratio 70% which were observed to be the most sensitive and specific markers out of the four markers analyzed as indicated in [Table 2] for HCC.

| Figure 4  Analysis of Bio-Markers for Hepatocellular Carcinoma

The outcome of t-test for prostate carcinoma showed that NLR, PLR, and MPV/platelet ratio were highly significant as indicated in [Table 3]. ROC analysis showed NLR had occupied 81% of area in the area under curve analysis, PLR 67%, and MVP/platelet ratio 60% [Table 4].

| Figure 5  Analysis of Bio-Markers for Prostate Carcinoma

Statistical analysis for stomach carcinoma is shown in [Table 5]. The t- test results indicate that NLR and PLR were highly significant markers in stomach cancer.

| Figure 6  Analysis of Bio-Markers for Stomach carcinoma

Post identification of the significance of the NLR, PLR, and MPV/platelet ratios for each of the carcinoma under study as mentioned above, the cutoff range for each of these markers in various carcinoma conditions was arrived by comparing the weighted average of mean values of the biomarkers in every specific carcinoma studied and healthy control group mean values for these biomarkers. The indicative cutoff values are presented in [Table 7]. High correlation was observed between the indicative cutoff values of the biomarkers in a specific carcinoma condition and the presenting clinical conditions and symptoms recorded for the respective carcinoma under study. This significance observed provides a decision pointer for early screening of the carcinoma condition and further reference for effective disease management.

1.  Mallath MK, Taylor DG, Badwe RA, Rath GK, Shanta V, Pramesh CS. et al. The growing burden of cancer in India: Epidemiology and social context. Lancet Oncol 2014; 15: e205-12
2.  Cancer report 2014 and Cancer Fact sheet. http://www.who.int/mediacentre/factsheets/fs297/en/ Available from: [Last accessed on 2017 Feb 23]
3.  Proctor MJ, Talwar D, Balmar SM, O'Reilly DS, Foulis AK, Horgan PG. et al. The relationship between the presence and site of cancer, an inflammation-based prognostic score and biochemical parameters. Initial results of the Glasgow inflammation outcome study. Br J Cancer 2010; 103: 870-6
4.  Szkandera J, Gerger A, Liegl-Atzwanger B, Absenger G, Stotz M, Samonigg H. et al. Validation of the prognostic relevance of plasma C-reactive protein levels in soft-tissue sarcoma patients. Br J Cancer 2013; 109: 2316-22
5.  Gomez D, Morris-Stiff G, Toogood GJ, Lodge JP, Prasad KR. Impact of systemic inflammation on outcome following resection for intrahepatic cholangiocarcinoma. J Surg Oncol 2008; 97: 513-8
6.  Coussens LM, Werb Z. Inflammation and cancer. Nature 2002; 420: 860-7
7.  Balkwill F, Mantovani A. Inflammation and cancer: Back to Virchow?. Lancet 2001; 357: 539-45
8.  Jaiswal M, LaRusso NF, Burgart LJ, Gores GJ. Inflammatory cytokines induce DNA damage and inhibit DNA repair in cholangiocarcinoma cells by a nitric oxide-dependent mechanism. Cancer Res 2000; 60: 184-90
9.  McMillan DC, Canna K, McArdle CS. Systemic inflammatory response predicts survival following curative resection of colorectal cancer. Br J Surg 2003; 90: 215-9
10.  Zahorec R. Ratio of neutrophil to lymphocyte counts – Rapid and simple parameter of systemic inflammation and stress in critically ill. Bratisl Lek Listy 2001; 102: 5-14
11.  Aliustaoglu M, Bilici A, Ustaalioglu BB, Konya V, Gucun M, Seker M. et al. The effect of peripheral blood values on prognosis of patients with locally advanced gastric cancer before treatment. Med Oncol 2010; 27: 1060-5
12.  Cho H, Hur HW, Kim SW, Kim SH, Kim JH, Kim YT. et al. Pre-treatment neutrophil to lymphocyte ratio is elevated in epithelial ovarian cancer and predicts survival after treatment. Cancer Immunol Immunother 2009; 58: 15-23
13.  Walsh SR, Cook EJ, Goulder F, Justin TA, Keeling NJ. Neutrophil-lymphocyte ratio as a prognostic factor in colorectal cancer. J Surg Oncol 2005; 91: 181-4
14.  Halazun KJ, Aldoori A, Malik HZ, Al-Mukhtar A, Prasad KR, Toogood GJ. et al. Elevated preoperative neutrophil to lymphocyte ratio predicts survival following hepatic resection for colorectal liver metastases. Eur J Surg Oncol 2008; 34: 55-60
15.  Templeton AJ, Pezaro C, Omlin A, McNamara MG, Leibowitz-Amit R, Vera-Badillo FE. et al. Simple prognostic score for metastatic castration-resistant prostate cancer with incorporation of neutrophil-to-lymphocyte ratio. Cancer 2014; 120: 3346-52
16.  Templeton AJ, McNamara MG, Šeruga B, Vera-Badillo FE, Aneja P, Ocaña A. et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: A systematic review and meta-analysis. J Natl Cancer Inst 2014; 106: dju124
17.  Mittal S, El-Serag HB. Epidemiology of hepatocellular Carcinoma: Consider the population. J Clin Gastroenterol 2013; 47 Suppl S2-6 DOI: 10.1097/MCG.0b013e3182872f29.
18.  Xiao WK, Chen D, Li SQ, Fu SJ, Peng BG, Liang LJ. et al. Prognostic significance of neutrophil-lymphocyte ratio in hepatocellular carcinoma: A meta-analysis. BMC Cancer 2014; 14: 117
19.  Liao W, Zhang J, Zhu Q, Qin L, Yao W, Lei B. et al. Preoperative neutrophil-to-lymphocyte ratio as a new prognostic marker in hepatocellular carcinoma after curative resection. Transl Oncol 2014; 7: 248-55
20.  Cho SY, Yang JJ, You E, Kim BH, Shim J, Lee HJ. et al. Mean platelet volume/platelet count ratio in hepatocellular carcinoma. Platelets 2013; 24: 375-7
21.  Yin X, Xiao Y, Li F, Qi S, Yin Z, Gao J. et al. Prognostic role of neutrophil-to-lymphocyte ratio in prostate cancer: A systematic review and meta-analysis. Medicine (Baltimore) 2016; 95: e2544
22.  Langsenlehner T, Pichler M, Thurner EM, Krenn-Pilko S, Stojakovic T, Gerger A. et al. Evaluation of the platelet-to-lymphocyte ratio as a prognostic indicator in a European cohort of patients with prostate cancer treated with radiotherapy. Urol Oncol 2015; 33: 201.e9-16
23.  Hu ZD, Huang YL, Qin BD, Tang QQ, Yang M, Ma N. et al. Prognostic value of neutrophil to lymphocyte ratio for gastric cancer. Ann Transl Med 2015; 3: 50
24.  Sun J, Chen X, Gao P, Song Y, Huang X, Yang Y. et al. Can the neutrophil to lymphocyte ratio be used to determine gastric cancer treatment outcomes? A systematic review and meta-analysis. Dis Markers 2016; 2016: 7862469
25.  Dogan M, Eren T, Ozdemir N, Cigirgan CL, Zengin N. The relationship between platelet-lymphocyte ratio, neutrophil-lymphocyte ratio, and survival in metastatic gastric cancer on firstline modified docetaxel and cisplatinum plus 5 Fluorourasil Regimen: A single institute experience. Saudi J Gastroenterol 2015; 21: 320-4
26.  Matowicka-Karna J, Kamocki Z, Polińska B, Osada J, Kemona H. Platelets and inflammatory markers in patients with gastric cancer. Clin Dev Immunol 2013; 2013: 401623

| Figure 1  Carcinoma presentation – Spectrum across gender and Age

| Figure 2  Presenting age in various carcinoma under study

| Figure 3  In-hospital mortality represented in carcinoma study groups

| Figure 4  Analysis of Bio-Markers for Hepatocellular Carcinoma

| Figure 5  Analysis of Bio-Markers for Prostate Carcinoma

| Figure 6  Analysis of Bio-Markers for Stomach carcinoma

1.  Mallath MK, Taylor DG, Badwe RA, Rath GK, Shanta V, Pramesh CS. et al. The growing burden of cancer in India: Epidemiology and social context. Lancet Oncol 2014; 15: e205-12
2.  Cancer report 2014 and Cancer Fact sheet. http://www.who.int/mediacentre/factsheets/fs297/en/ Available from: [Last accessed on 2017 Feb 23]
3.  Proctor MJ, Talwar D, Balmar SM, O'Reilly DS, Foulis AK, Horgan PG. et al. The relationship between the presence and site of cancer, an inflammation-based prognostic score and biochemical parameters. Initial results of the Glasgow inflammation outcome study. Br J Cancer 2010; 103: 870-6
4.  Szkandera J, Gerger A, Liegl-Atzwanger B, Absenger G, Stotz M, Samonigg H. et al. Validation of the prognostic relevance of plasma C-reactive protein levels in soft-tissue sarcoma patients. Br J Cancer 2013; 109: 2316-22
5.  Gomez D, Morris-Stiff G, Toogood GJ, Lodge JP, Prasad KR. Impact of systemic inflammation on outcome following resection for intrahepatic cholangiocarcinoma. J Surg Oncol 2008; 97: 513-8
6.  Coussens LM, Werb Z. Inflammation and cancer. Nature 2002; 420: 860-7
7.  Balkwill F, Mantovani A. Inflammation and cancer: Back to Virchow?. Lancet 2001; 357: 539-45
8.  Jaiswal M, LaRusso NF, Burgart LJ, Gores GJ. Inflammatory cytokines induce DNA damage and inhibit DNA repair in cholangiocarcinoma cells by a nitric oxide-dependent mechanism. Cancer Res 2000; 60: 184-90
9.  McMillan DC, Canna K, McArdle CS. Systemic inflammatory response predicts survival following curative resection of colorectal cancer. Br J Surg 2003; 90: 215-9
10.  Zahorec R. Ratio of neutrophil to lymphocyte counts – Rapid and simple parameter of systemic inflammation and stress in critically ill. Bratisl Lek Listy 2001; 102: 5-14
11.  Aliustaoglu M, Bilici A, Ustaalioglu BB, Konya V, Gucun M, Seker M. et al. The effect of peripheral blood values on prognosis of patients with locally advanced gastric cancer before treatment. Med Oncol 2010; 27: 1060-5
12.  Cho H, Hur HW, Kim SW, Kim SH, Kim JH, Kim YT. et al. Pre-treatment neutrophil to lymphocyte ratio is elevated in epithelial ovarian cancer and predicts survival after treatment. Cancer Immunol Immunother 2009; 58: 15-23
13.  Walsh SR, Cook EJ, Goulder F, Justin TA, Keeling NJ. Neutrophil-lymphocyte ratio as a prognostic factor in colorectal cancer. J Surg Oncol 2005; 91: 181-4
14.  Halazun KJ, Aldoori A, Malik HZ, Al-Mukhtar A, Prasad KR, Toogood GJ. et al. Elevated preoperative neutrophil to lymphocyte ratio predicts survival following hepatic resection for colorectal liver metastases. Eur J Surg Oncol 2008; 34: 55-60
15.  Templeton AJ, Pezaro C, Omlin A, McNamara MG, Leibowitz-Amit R, Vera-Badillo FE. et al. Simple prognostic score for metastatic castration-resistant prostate cancer with incorporation of neutrophil-to-lymphocyte ratio. Cancer 2014; 120: 3346-52
16.  Templeton AJ, McNamara MG, Šeruga B, Vera-Badillo FE, Aneja P, Ocaña A. et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: A systematic review and meta-analysis. J Natl Cancer Inst 2014; 106: dju124
17.  Mittal S, El-Serag HB. Epidemiology of hepatocellular Carcinoma: Consider the population. J Clin Gastroenterol 2013; 47 Suppl S2-6 DOI: 10.1097/MCG.0b013e3182872f29.
18.  Xiao WK, Chen D, Li SQ, Fu SJ, Peng BG, Liang LJ. et al. Prognostic significance of neutrophil-lymphocyte ratio in hepatocellular carcinoma: A meta-analysis. BMC Cancer 2014; 14: 117
19.  Liao W, Zhang J, Zhu Q, Qin L, Yao W, Lei B. et al. Preoperative neutrophil-to-lymphocyte ratio as a new prognostic marker in hepatocellular carcinoma after curative resection. Transl Oncol 2014; 7: 248-55
20.  Cho SY, Yang JJ, You E, Kim BH, Shim J, Lee HJ. et al. Mean platelet volume/platelet count ratio in hepatocellular carcinoma. Platelets 2013; 24: 375-7
21.  Yin X, Xiao Y, Li F, Qi S, Yin Z, Gao J. et al. Prognostic role of neutrophil-to-lymphocyte ratio in prostate cancer: A systematic review and meta-analysis. Medicine (Baltimore) 2016; 95: e2544
22.  Langsenlehner T, Pichler M, Thurner EM, Krenn-Pilko S, Stojakovic T, Gerger A. et al. Evaluation of the platelet-to-lymphocyte ratio as a prognostic indicator in a European cohort of patients with prostate cancer treated with radiotherapy. Urol Oncol 2015; 33: 201.e9-16
23.  Hu ZD, Huang YL, Qin BD, Tang QQ, Yang M, Ma N. et al. Prognostic value of neutrophil to lymphocyte ratio for gastric cancer. Ann Transl Med 2015; 3: 50
24.  Sun J, Chen X, Gao P, Song Y, Huang X, Yang Y. et al. Can the neutrophil to lymphocyte ratio be used to determine gastric cancer treatment outcomes? A systematic review and meta-analysis. Dis Markers 2016; 2016: 7862469
25.  Dogan M, Eren T, Ozdemir N, Cigirgan CL, Zengin N. The relationship between platelet-lymphocyte ratio, neutrophil-lymphocyte ratio, and survival in metastatic gastric cancer on firstline modified docetaxel and cisplatinum plus 5 Fluorourasil Regimen: A single institute experience. Saudi J Gastroenterol 2015; 21: 320-4
26.  Matowicka-Karna J, Kamocki Z, Polińska B, Osada J, Kemona H. Platelets and inflammatory markers in patients with gastric cancer. Clin Dev Immunol 2013; 2013: 401623