Abstract
Objective
To analyze the prognostic significance of the pretreatment platelet/lymphocyte ratio (PLR) for targeted therapy in patients with epidermal growth factor receptor (EGFR)-mutated non-small-cell lung cancer (NSCLC).
Methods
We conducted a retrospective study of 96 patients with EGFR-mutated advanced NSCLC who were treated at Dongguan People’s Hospital, Southern Medical University from May 2014 to December 2017. All patients received EGFR-targeted therapy until disease progression, unacceptable toxicity, or other factors. Approximately 3 days before the initial treatment, data including a detailed clinical history, physical examination, radiographic results, pathological diagnosis, and laboratory parameters including complete blood cell counts and albumin levels were evaluated.
Results
Patients in the PLR ≥ 190 group had shorter progression-free survival (PFS) than those in the PLR < 190 group. Furthermore, the 1-year PFS rate was worse in the PLR ≥ 190 group than in the PLR< 190 group. Multivariate analysis indicated the possible role of PLR as a prognostic factor for patients with advanced NSCLC who received EGFR-targeted therapy.
Conclusions
Pretreatment PLR may be an independent prognostic factor for patients with NSCLC receiving EGFR tyrosine kinase inhibitor treatment. Further studies are needed to identify the impact of PLR on EGFR-mutated NSCLC.
Keywords: Non-small-cell lung cancer, epidermal growth factor receptor, targeted therapy, platelet/lymphocyte ratio, prognostic factor, tyrosine kinase inhibitor, progression-free survival
Introduction
Lung cancer, the most frequent cancer diagnosed each year, is commonly classified as small-cell lung cancer or non-small-cell lung cancer (NSCLC).1,2 NSCLC comprises approximately 80% of all lung cancers, and 40% to 50% of Asian patients harbor epidermal growth factor receptor (EGFR) mutations.3–5 NSCLC is closely associated with inflammation and chronic infection.6,7 The tumor microenvironment of lung cancer is composed of tumor cells, inflammatory cells, and fibroblasts, among others. It is postulated that tumor progression may be promoted by a variety of inflammatory factors, which may eventually affect chemotherapeutic efficacy.8
For patients treated with EGFR tyrosine kinase inhibitors (EGFR-TKIs), it is unknown whether inflammatory factors affect the antitumor efficacy of targeted drugs. To date, the EGFR mutation status remains an extremely powerful predictive factor. However, only some patients with EGRF-mutated cancer benefit from targeted therapy. Hence, other predictive factors are needed to complement the mutation status, such as biomarkers of systemic inflammatory responses.
Over the last decade, hematological inflammatory response markers such as the platelet/lymphocyte ratio (PLR) and C-reactive protein/albumin ratio (CAR) have been studied as prognostic factors in patients with various cancers.9,10 Studies found that the T cell population is predominant in the tumor microenvironment compared with the abundance of other inflammatory cells such as natural killer cells. Tumor-infiltrating T cells in advanced lung cancer could cause malignancy-induced immunosuppression, which probably weakens the antitumor effect of targeted therapy for advanced NSCLC. In addition, several reports revealed that high baseline platelet counts were closely associated with shorter overall survival (OS) in patients with advanced NSCLC.11,12 Although PLR has been extensively investigated in different tumor categories, few studies have examined the predictive relationship between PLR and the efficacy of EGFR-targeted therapy.
Therefore, we analyzed the predictive utility of PLR in patients with EGFR-mutated NSCLC to verify our hypothesis regarding its prognostic role in such patients.
Patients and Methods
Patients
This was a retrospective study of patients with advanced NSCLC who received EGFR-targeted therapy at Dongguan People’s Hospital, Southern Medical University from May 2014 to December 2017. The inclusion criteria were age ≥18 years, life expectancy of 4 weeks or more, adequate bone marrow function, a diagnosis of stage IIIB (with pleural effusion) or stage IV NSCLC (The International Association for the Study of Lung Cancer 7th edition of Tumor Node Metastasis Staging classification) harboring EGFR gene mutations, and no prior receipt of antitumor treatment. EGFR mutations were identified in tumor tissues using standard sequencing methods. Patients were excluded from the study if they met the following criteria: allergy to targeted therapies, primary organ failure, pregnancy, hematological or autoimmune disease, serious liver or kidney dysfunction, and missing follow-up data. The clinical data of the included patients were collected carefully. The present study was approved by the Ethics Committee of Dongguan People’s Hospital (approval date, 16 November 2017), and the study was conducted according to the Declaration of Helsinki. Patients provided informed written consent.
Clinical management
All patients with advanced NSCLC in the study were treated with a standard dose of EGFR-TKIs, including gefitinib, erlotinib, and icotinib. Approximately 3 days before initial treatment, the following data were evaluated: detailed clinical history, physical examination, radiographic results, pathological diagnosis, and laboratory parameters including complete blood cell counts and albumin levels. Patients received targeted therapy daily until unendurable toxicity or disease progression occurred. All patients were followed for at least 6 months after the initiation of EGFR-TKI therapy. Computed tomography, radionuclide bone scan, and magnetic resonance imaging were conducted to evaluate treatment efficacy. Tumor response was evaluated according to the Response Evaluation Criteria in Solid Tumors. Disease control was defined as complete response, partial response (PR), stable disease (SD), or progression disease (PD). Toxicities were recorded according to the National Cancer Institute Common Terminology Criteria for Adverse Events version 3.0.
Statistical analysis
All statistical analyses were performed using SPSS version 22.0 (IBM, Armonk, NY, USA). We selected the cutoff for PLR using receiver operating characteristic (ROC) curve analysis. The associations of PLR with clinicopathological parameters were assessed via Pearson’s chi-squared test. PFS was defined as the time from the start of the treatment to disease progression or death, with data censored for patients alive without progression at the last follow-up visit. The cutoff date for PFS data was 28 June 2018. By that time, sufficient data had been collected to analyze the efficacy and toxicities of targeted therapy. The objective response rate (ORR) and disease control rate (DCR) were also recorded. Estimates of PFS were calculated using the Kaplan–Meier method, and two-sided 95% confidence intervals (CIs) were obtained. A two-sided log-rank test was used to compare PFS between different PLR groups. Prognostic analysis was conducted using univariate and multivariate Cox regressions models. Variables significant at P < 0.05 in the univariate analysis of PFS were included in the subsequent multivariate analysis. Two-sided P < 0.05 was considered statistically significant.
Results
Patient characteristics
Ninety-six patients with cytological or histological confirmed NSCLC were enrolled in this study. As presented in Table 1, all clinical characteristics were comparable between the included patients after grouping by PLR. The median age at the time of diagnosis was 61 years (range, 27–83 years), and 58.3% of patients were women. Most patients had a Eastern Cooperative Oncology Group performance status of 0–2 (90.6%) and sensitive EGFR mutations (95.8%), including exon 19 deletion and exon 21 L858R. All patients received treatment with first-line EGFR-TKIs as follows: gefitinib (250 mg/day) in 46 patients, icotinib (375 mg/day) in 36 patients, erlotinib (150 mg/day) in 12 patients, and afatinib (40 mg/day) in 2 patients. There was no difference in the rates of use of each drug between the high and low PLR groups. The follow-up period ranged from 5.1 to 49.2 months (median, 21.7 months). No patients discontinued EGFR-TKI treatment because of severe adverse events. At the end of the last follow-up, 83 patients exhibited tumor progression.
Table 1.
Correlations between PLR and patient characteristics before targeted therapy.
| Characteristic | Cases (n = 96) | PLR < 190 (n = 45) | PLR ≥ 190 (n = 51) | P |
|---|---|---|---|---|
| Age (years) | ||||
| <65 | 57 (59.4%) | 28 (62.2%) | 29 (56.9%) | 0.59 |
| ≥65 | 39 (40.6%) | 17 (37.8%) | 22 (43.1%) | |
| Sex | ||||
| Male | 40 (41.7%) | 17 (37.8%) | 23 (45.1%) | 0.47 |
| Female | 56 (58.3%) | 28 (62.2%) | 28 (54.9%) | |
| ECOG PS | ||||
| <2 | 71 (73.9%) | 32 (71.1%) | 39 (76.5%) | 0.55 |
| ≥2 | 25 (26.1%) | 13 (28.9%) | 12 (23.5%) | |
| Tumor location | ||||
| Left | 41 (42.7%) | 23 (51.1%) | 18 (35.3%) | 0.12 |
| Right | 55 (57.3%) | 22 (48.9%) | 33 (64.7%) | |
| Smoking | ||||
| Yes | 21 (21.9%) | 9 (20%) | 12 (23.5%) | 0.68 |
| No | 75 (78.1%) | 36 (80%) | 39 (76.5%) | |
| Metastases | ||||
| <3 | 53 (55.2%) | 27 (60%) | 26 (50.9%) | 0.38 |
| ≥3 | 43(44.8%) | 18 (40%) | 25 (49.1%) | |
| Brain metastasis | ||||
| Yes | 38 (39.6%) | 21 (46.7%) | 17 (33.3%) | 0.18 |
| No | 58 (60.4%) | 24 (53.3%) | 34 (66.7%) | |
| Pleural effusion | ||||
| No | 44 (45.8%) | 24 (53.3%) | 20 (39.2%) | 0.17 |
| Yes | 52 (54.2%) | 21 (46.7%) | 31 (60.8%) | |
| BMI | ||||
| <25 | 75 (78.1%) | 34 (75.6%) | 41 (80%) | 0.57 |
| ≥25 | 21 (21.9%) | 11 (24.4%) | 10 (20%) | |
| Albumin (g/L) | ||||
| <40 | 75 (78.1%) | 33 (73.3%) | 42 (82.4%) | 0.29 |
| ≥40 | 21 (21.9%) | 12 (26.7%) | 9 (17.6%) | |
| EGFR mutation status | ||||
| Exon 19 del | 44 (45.8%) | 18 (40%) | 26 (51%) | 0.45 |
| Exon 21 L858R | 44 (45.8%) | 22 (48.9%) | 22 (43.1%) | |
| Other | 8 (8.4%) | 5 (11.1%) | 3 (5.9%) | |
| Drugs | ||||
| Gefitinib | 46 (47.9%) | 22 (48.9%) | 24 (47.1%) | 0.98 |
| Erlotinib | 12 (12.5%) | 5 (11.1%) | 7 (13.7%) | |
| Icotinib | 36 (37.5%) | 17 (37.8%) | 19 (37.3%) | |
| Afatinib | 2 (2.1%) | 1 (2.2%) | 1 (1.9%) |
PLR, platelet/lymphocyte ratio; ECOG PS, Eastern Cooperative Oncology Group performance status; BMI, body mass index; EGFR, epidermal growth factor receptor; del, deletion.
The mean PLR and albumin level were 198 (range, 53–489) and 36.9 g/L (range, 25.1–45 g/L), respectively. According to the ROC curves, the optimal cutoff for PLR was 190, corresponding to maximum joint sensitivity and specificity. For PLR, the area under the ROC curve for PFS was 0.667, and the sensitivity and specificity were 64.7 and 64.4%, respectively (Figure 1). Based on the cutoff of 190, 51 patients (53.1%) had high pretreatment PLR (≥190). Patients were also divided into subgroups according to the lower limit level of serum albumin (<40 g/L versus ≥40 g/L). The relationships of clinicopathological parameters with pretreatment PLR in patients with EGFR-mutated NSCLC are presented in Table 1. There were no statistically significant differences between the two PLR groups.
Figure 1.
ROC curves for pretreatment PLR.
ROC, receiver operating characteristic; PLR, platelet/lymphocyte ratio.
Prognostic factors
The PLR < 190 group included 28 patients with PR, 13 patients with SD, and 4 patients with PD. Conversely, the PLR ≥190 group included 27, 14, and 10 patients with PR, SD, and PD, respectively. There was no significant difference of ORR (62.2% versus 52.9%) and DCR (91.1% versus 80.4%) between the two groups (Table 2). However, Kaplan–Meier analysis illustrated that patients in the PLR ≥190 group who received EGFR-TKIs had significantly shorter PFS than those in the PLR < 190 group (P = 0.009, Table 2). The 1-year PFS rate in the PLR ≥ 190 group was lower than that in the PLR < 190 group (55.6% versus 27.5%, P = 0.008, Table 2). Further analyses were performed to demonstrate whether PLR is an independent predictor for PFS in patients with NSCLC treated with EGFR-TKIs.
Table 2.
Efficacy results of patients according to pretreatment PLR.
| Variable | PLR < 190 (n = 45) | PLR ≥ 190 (n = 51) | P |
|---|---|---|---|
| Response | |||
| PR, n (%) | 28 (62.2%) | 27 (52.9%) | |
| SD, n (%) | 13 (28.9%) | 14 (27.5%) | |
| PD, n (%) | 4 (8.9%) | 10 (19.6%) | |
| Response rate, % | 62.2% | 52.9% | 0.36 |
| 95% CI | 37.3–67.2 | 44.1–69.8 | |
| Disease control rate, % | 91.1% | 80.4% | 0.14 |
| 95% CI | 70.3–93.3 | 79.5–96.4 | |
| Median PFS (months) | 12.4 months | 6.6 months | 0.009 |
| 95% CI | 9.5–15.4 | 4.8–8.4 | |
| One-year PFS rate (%) | 55.6% | 27.5% | 0.008 |
| 95% CI | 40.8–70.3 | 15.1–39.8 |
PLR, platelet/lymphocyte ratio; PR, partial response, SD, stable disease; PD, progressive disease; CI, confidence interval; PFS, progression-free survival.
In univariate analysis, PLR (P = 0.011), pleural effusion (P = 0.026), and albumin levels (P = 0.001) were significantly associated with PFS (Table 3). In the multivariate Cox regression model, PLR (hazard ratio [HR] = 1.781, 95% CI = 1.123–2.825, P = 0.014) and albumin levels (HR = 0.388, 95% CI = 0.21–0.715, P = 0.002) were significantly associated with PFS, whereas pleural effusion was not predictive of PFS (Table 3). The Kaplan–Meier PFS curves for patients treated with EGFR-TKIs as stratified by PLR and albumin levels are presented in Figures 2 and 3.
Table 3.
Univariate and multivariate analyses of PFS in patients with advanced NSCLC.
| Variable | Univariate HR (95% CI) | P | Multivariate HR (95% CI) | P |
|---|---|---|---|---|
| Age | ||||
| <65 | 1 | |||
| ≥65 | 0.717 (0.458–1.122) | 0.145 | ||
| Sex | ||||
| Male | 1 | |||
| Female | 1.153 (0.742–1.792) | 0.526 | ||
| ECOG PS | ||||
| <2 | 1 | |||
| ≥2 | 1.134 (0.68–1.893) | 0.629 | ||
| Tumor location | ||||
| Left | 1 | |||
| Right | 1.5 (0.956–2.352) | 0.078 | ||
| Smoking | ||||
| Yes | 1 | |||
| No | 1.18 (0.68–2.047) | 0.555 | ||
| Metastases | ||||
| <3 | 1 | |||
| ≥3 | 1.4 (0.898–2.183) | 0.137 | ||
| Brain metastasis | ||||
| Yes | 1 | |||
| No | 0.741 (0.474–1.159) | 0.189 | ||
| Pleural effusion | ||||
| No | 1 | 1 | ||
| Yes | 1.649 (1.061–2.562) | 0.026 | 1.185 (0.748–1.879) | 0.469 |
| BMI | ||||
| <25 | 1 | |||
| ≥25 | 1.117 (0.667–1.87) | 0.675 | ||
| Albumin (g/L) | ||||
| <40 | 1 | 1 | ||
| ≥40 | 0.376 (0.208–0.678) | 0.001 | 0.388 (0.21–0.715) | 0.002 |
| PLR | ||||
| <190 | 1 | 1 | ||
| ≥190 | 1.795 (1.147–2.811) | 0.011 | 1.781 (1.123–2.825) | 0.014 |
| EGFR mutation status | ||||
| Exon 19 del | 1 | |||
| Exon 21 L858R | 1.047 (0.666–1.646) | 0.842 | ||
PFS, progression-free survival; NSCLC, non-small-cell lung cancer; ECOG PS, Eastern Cooperative Oncology Group performance status; BMI, body mass index; PLR, platelet/lymphocyte ratio; EGFR, epidermal growth factor receptor; del, deletion; HR, hazard ratio; CI, confidence interval.
Figure 2.
Kaplan–Meier curves for progression-free survival according to pretreatment PLR.
PLR, platelet/lymphocyte ratio.
Figure 3.
Kaplan–Meier curves for progression-free survival according to the albumin level.
PLR and toxicities
The primary toxicities possibly related to EGFR-targeted therapy are listed in Table 4. Adverse events were generally mild in both PLR groups. The most common grade 1/2 adverse events in both groups were non-hematologic toxicities, including rash, aminopherase elevation, anorexia, and fatigue. There were no significant differences in grade 1/2 adverse event rates between the groups (Table 4).
Table 4.
Treatment-related toxicities in patients according to PLR.
| Grade 1/2 |
Grade 3/4 |
|||||
|---|---|---|---|---|---|---|
| Toxicity | PLR < 190 (n = 45) |
PLR ≥ 190 (n = 51) |
P | PLR < 190 (n = 45) |
PLR ≥ 190 (n = 51) |
P |
| Rash | 12 | 17 | 0.483 | 4 | 7 | 0.463 |
| Pruritus | 6 | 8 | 0.748 | 0 | 0 | |
| Dizziness | 3 | 8 | 0.17 | 0 | 0 | |
| Fever | 3 | 7 | 0.263 | 0 | 0 | |
| Diarrhea | 9 | 5 | 0.161 | 1 | 7 | 0.042 |
| Fatigue | 6 | 12 | 0.206 | 0 | 2 | 0.183 |
| Nausea | 7 | 10 | 0.608 | 0 | 0 | |
| Vomiting | 9 | 7 | 0.416 | 0 | 0 | |
| Anorexia | 10 | 19 | 0.112 | 0 | 0 | |
| Aminopherase elevation | 12 | 18 | 0.368 | 1 | 0 | 0.289 |
| Dyspnea | 6 | 6 | 0.819 | 1 | 4 | 0.22 |
| Hemorrhage | 1 | 5 | 0.128 | 0 | 1 | 0.35 |
PLR, platelet/lymphocyte ratio.
Discussion
Targeted therapy is the recommended treatment for patients with EGFR-mutated advanced NSCLC. The efficacy and toxicities of targeted therapy are closely related to the EGFR mutation status. To date, no predictive factor for targeted therapy excluding the EGFR status has been extensively applied in the clinic. Previous studies investigated the utility of several biomarkers for predicting the prognosis of NSCLC, such as PLR, neutrophil counts, and CAR. However, the predictive roles of these biomarkers are uncertain in the setting of precision medicine. Therefore, we conducted the present study to identify a helpful predictive factor for targeted treatment in patients with advanced NSCLC.
Chronic inflammation is involved in cancer formation and progression. PLR is a reproducible and inexpensive hematological marker that was suggested to be a marker of thrombotic and inflammatory conditions.13,14 As previously reported, elevated pretreatment PLR in peripheral blood is an independent prognostic factors for various cancers, including advanced NSCLC.15,16 One study revealed that high pretreatment PLR was associated with poor survival rates in patients with NSCLC. Nonetheless, the marker was not associated with the response to chemoradiotherapy.17 Another study revealed that PLR was a prognostic marker in patients with metastatic NSCLC who received nivolumab independently of other prognostic factors.18 To date, it remains unknown whether PLR is a prognostic factor for patients diagnosed with EGFR-mutated NSCLC.
In our study, we found that pretreatment PLR was significantly associated with PFS in patients with NSCLC who received EGFR-targeted therapy. Patients in the PLR ≥190 group had shorter PFS than those in the PLR < 190 group (P = 0.009). Furthermore, the 1-year PFS rate in the PLR ≥190 group was inferior to that in the PLR < 190 group (P = 0.016). Multivariate analysis indicated the possible role of PLR as a prognostic factor for patients with advanced NSCLC who received EGFR-targeted therapy. In this study, we found that hypoalbuminemia was negatively associated with the efficacy of EGFR therapy, which is in line with the results of previous reports on several cancer types. Because the number of patients in this study was relatively small, further studies are needed to illuminate the relationship between PLR and survival in patients with EGFR-mutated NSCLC.
Our study revealed that PLR is a superior independent prognostic factor in patients with EGFR-mutated advanced lung cancer. In the recent decade, only the EGFR mutation status has been an effective predictive biomarker for efficacy and toxicity for targeted therapies such as gefitinib and erlotinib.19,20 Recent studies did not consider the crucial impact of pretreatment PLR on therapeutic outcomes in patients receiving EGFR-TKIs compared with studies of chemotherapy and immunotherapy in advanced NSCLC. This study revealed that pretreatment PLR and albumin levels could be predictive of the efficacy of targeted therapy for NSCLC.
Nonetheless, this study had several limitations. First, this was a retrospective analysis with a relatively small number of patients with NSCLC. Hence, comprehensive multivariable analyses were not possible in the study. Second, the results were inevitably affected by residual confounding factors such as NLR, CAR, and hyperfibrinogenemia. Third, there may have been an elevated risk of patient selection bias in the study because this was a single-center investigation. Finally, four EGFR-targeted therapies were used, although previous studies proved that these drugs had similar efficacy.21,22 However, the correlation of high pretreatment PLR with poor PFS was statistical significant and of vital importance clinically.
In conclusion, our study illustrated that pretreatment PLR may be an independent prognostic factor for patients with NSCLC receiving EGFR-TKI treatment. High pretreatment PLR may predict poor PFS for such patients. Further studies are needed to clarify the impact of pretreatment PLR on the outcome of EGFR-TKI treatment. Translational research is suggested to further investigate the mechanism of our clinical findings.
Acknowledgements
We would like to thank colleagues at Dongguan People’s Hospital, Southern Medical University for their kind technical assistance, psychological support, theoretical guidance, and writing assistance during the present study. We would also like to thank the patients and their family members engaged in this clinical trial for their kindness in supporting our study. This manuscript has been released as a pre-print version in Research Square under the doi 10.21203/rs.2.12821/v1.
Footnotes
Declaration of conflicting interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by Dongguan Social Science and Technology Development Project (grant no. 201750715001285).
ORCID iD: Kejun Liu https://orcid.org/0000-0003-1721-2723
References
- 1.Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin 2017; 67: 7–30. [DOI] [PubMed] [Google Scholar]
- 2.Liu KJ, Wu HY. A retrospective analysis of cisplatin, pemetrexed, and bevacizumab in previously treated non-small-cell lung cancer. Oncotarget 2015; 6: 22750–22757. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Chen F, Cole P, Bina WF. Time trend and geographic patterns of lung adenocarcinoma in the united states, 1973–2002. Cancer Epidemiol Biomarkers Prev 2007; 16: 2724–2729. [DOI] [PubMed] [Google Scholar]
- 4.Rosell R, Carcereny E, Gervais R, et al . Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol 2012; 13: 239–246. [DOI] [PubMed] [Google Scholar]
- 5.Shigematsu H, Lin L, Takahashi T, et al. Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst 2005; 97: 339–346. [DOI] [PubMed] [Google Scholar]
- 6.Gomes M, Teixeira AL, Coelho A, et al. The role of inflammation in lung cancer. Adv Exp Med Biol 2014; 816: 1–23. [DOI] [PubMed] [Google Scholar]
- 7.Shiels MS, Pfeiffer RM, Hildesheim A, et al. Circulating inflammation markers and prospective risk for lung cancer. J Natl Cancer Inst 2013; 105: 1871–1880. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Mantovani A, Allavena P, Sica A, et al. Cancer-related inflammation. Nature 2008; 454: 436–444. [DOI] [PubMed] [Google Scholar]
- 9.Zhang WW, Liu KJ, Hu GL, et al. Preoperative platelet/lymphocyte ratio is a superior prognostic factor compared to othersystemic inflammatory response markers in ovarian cancer patients. Tumour Biol 2015; 36: 8831–8837. [DOI] [PubMed] [Google Scholar]
- 10.Zhang WW, Liu KJ, Ye B, et al. Pretreatment C-reactive protein/albumin ratio is associated with poor survival in patients with stage IB-IIA cervical cancer. Cancer Med 2018; 7: 105–113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Gonzalez Barcala FJ, Garcia Prim JM. Platelet count: association with prognosis in lung cancer. Med Oncol 2010; 27: 357–362. [DOI] [PubMed] [Google Scholar]
- 12.Aoe K, Hiraki A, Ueoka H. Thrombocytosis as a useful prognostic indicator in patients with lung cancer. Respiration 2004; 71: 170–173. [DOI] [PubMed] [Google Scholar]
- 13.Smith RA, Ghaneh P, Sutton R, et al. Prognosis of resected ampullary adenocarcinoma by preoperative serum CA19-9 levels and platelet-lymphocyte ratio. J Gastrointest Surg 2008; 12: 1422–1428. [DOI] [PubMed] [Google Scholar]
- 14.Wang D, Yang JX, Cao DY, et al. Preoperative neutrophil-lymphocyte and platelet-lymphocyte ratios as independent predictors of cervical stromal involvement in surgically treated endometrioid adenocarcinoma. Onco Targets Ther 2013; 6: 211–216. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Guthrie GJ, Charles KA, Roxburgh CS, et al. The systemic inflammation-based neutrophil-lymphocyte ratio: experience in patients with cancer. Crit Rev Oncol Hematol 2013; 88: 218–230. [DOI] [PubMed] [Google Scholar]
- 16.Templeton AJ, Ace O, McNamara MG, et al. Prognostic role of platelet to lymphocyte ratio in solid tumors: a systematic review and meta-analysis. Cancer Epidemiol Biomarkers Prev 2014; 23: 1204–1212. [DOI] [PubMed] [Google Scholar]
- 17.Unal D, Eroglu C, Kurtul N, et al. Are neutrophil/lymphocyte and platelet/lymphocyte rates in patients with non-small cell lung cancer associated with treatment response and prognosis? Asian Pac J Cancer Prev 2013; 14: 5237–5242. [DOI] [PubMed] [Google Scholar]
- 18.Diem S, Schmid S, Krapf M, et al. Neutrophil-to-Lymphocyte ratio (NLR) and Platelet-to-Lymphocyte ratio (PLR) as prognostic markers in patients with non-small cell lung cancer (NSCLC) treated with nivolumab. Lung Cancer 2017; 111: 176–181. [DOI] [PubMed] [Google Scholar]
- 19.Perez-Soler R, Chachoua A, Hammond LA, et al. Determinants of tumor response and survival with erlotinib in patients with non–small-cell lung cancer. J Clin Oncol 2004; 22: 3238–3247. [DOI] [PubMed] [Google Scholar]
- 20.Kris MG, Natale RB, Herbst RS, et al. Efficacy of gefitinib, an inhibitor of the epidermal growth factor receptor tyrosine kinase, in symptomatic patients with non-small cell lung cancer: a randomized trial. JAMA 2003; 290: 2149–2158. [DOI] [PubMed] [Google Scholar]
- 21.Burotto M, Manasanch EE, Wilkerson J, et al. Gefitinib and erlotinib in metastatic non-small cell lung cancer: a meta-analysis of toxicity and efficacy of randomized clinical trials. Oncologist 2015; 20: 400–410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Shi YK, Zhang L, Liu XQ, et al. Icotinib versus gefitinib in previously treated advanced non-small-cell lung cancer (ICOGEN): a randomised, double-blind phase 3 non-inferiority trial. Lancet Oncol 2013; 14: 953–961. [DOI] [PubMed] [Google Scholar]