The prognostic roles of platelet-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio in gastrointestinal stromal tumours: a meta-analysis
Original Article

The prognostic roles of platelet-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio in gastrointestinal stromal tumours: a meta-analysis

Zhe-Wei Wei1,2#, Wei-Bin Huang1,2#, Dong-Jie Yang1,2, Yu-Jie Yuan1,2, Yu-Long He1,2,3, Chang-Hua Zhang3

1Department of Gastrointestinal Surgery, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; 2Gastric Cancer Center, Sun Yat-sen University, Guangzhou, China; 3Department of Digestive Diseases, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China

Contributions: (I) Conception and design: YL He, CH Zhang; (II) Administrative support: ZW Wei, WB Huang; (III) Provision of study materials or patients: WB Huang, DJ Yang; (IV) Collection and assembly of data: DJ Yang, WB Huang; (V) Data analysis and interpretation: YJ Yuan, ZW Wei; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work.

Correspondence to: Chang-Hua Zhang, MD, PhD. Department of Digestive Diseases, the Seventh Affiliated Hospital of Sun Yat-sen University, 628 Zhenyuan Road, Shenzhen, Guangdong 518000, China. Email: zhchangh@mail.sysu.edu.cn; Yu-Long He, MD, PhD. Gastric Cancer Center, Sun Yat-sen University, 58 Zhongshan 2nd Road, Guangzhou, Guangdong 510080, China. Email: heyulong@mail.sysu.edu.cn.

Background: The platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) have been found to be associated with prognosis in several solid tumours. However, the prognostic roles of PLR and NLR in gastrointestinal stromal tumours (GISTs) remain controversial. The aim of this meta-analysis was to assess the prognostic roles of PLR and NLR in GISTs.

Methods: We searched MEDLINE, EMBASE and the Cochrane Library for relevant articles. A systematic review was performed to calculate pooled hazard ratios (HRs) for disease-free survival (DFS) and overall survival (OS) by fixed-effects/random-effects models.

Results: Fourteen studies containing 3,151 subjects were finally enrolled in this meta-analysis. Eight studies including 2,560 patients investigated the prognostic effect of PLR, and thirteen studies with 2,751 subjects explored the prognostic effect of NLR. Both elevated PLR (HR: 1.29, 95% CI: 1.10–1.52, P=0.002) and NLR (HR: 1.37, 95% CI: 1.15–1.63, P=0.0005) were significantly associated with decreased DFS. The pooled HR for PLR was not significantly different from that for NLR. High PLR and NLR correlated with increased tumour sizes, more advanced tumour stages and mitotic index (>5/50 HPF). In addition, elevated PLR was related to adjuvant tyrosine kinase inhibitor (TKI) therapy.

Conclusions: Elevated preoperative PLR and NLR are associated with poor outcomes in patients with GISTs.

Keywords: Gastrointestinal stromal tumours (GISTs); platelet-to-lymphocyte ratio (PLR); neutrophil-to-lymphocyte ratio (NLR); prognosis; meta-analysis


Submitted Feb 14, 2020. Accepted for publication Aug 05, 2020.

doi: 10.21037/tcr-20-1037


Introduction

Gastrointestinal stromal tumours (GISTs) are the most common mesenchymal tumours of the gastrointestinal tract and account for approximately 0.2% of all GI malignancies (1). They are deemed to arise from the interstitial cells of Cajal (ICC) and are composed of predominantly spindle or epithelioid cells (2,3). GISTs are found primarily in the stomach (60–70%) and the small intestine (30%) but may also occur in the colon, rectum, and oesophagus (4). The tumorigenesis and progression of GISTs are partially attributed to gain-of-function mutations in the KIT proto-oncogene or platelet-derived growth factor receptor alpha (PDGFRα) gene, which serve as therapeutic targets for targeted therapy (5). R0 resection is the first treatment option for localized GISTs (6-9). However, some patients still develop recurrent disease even after R0 resection (10). It is critical to identify factors that predict the treatment response and survival of GIST patients.

Presently, most of the well-established prognostic factors of GISTs rely heavily on the results of tissue biopsy, including the mitotic index, tumour size, location of the primary tumour and tumour rupture (11,12). However, there is a gap between estimated recurrence rates by risk-stratification models and the exact recurrence rates (13). Therefore, it is critical to develop novel criteria or supplement the current stratification systems with new parameters.

Over the past decade, it has been elucidated that systemic inflammation could promote tumour metastasis by inducing angiogenesis or inhibiting apoptosis (14,15). Inflammation-based biomarkers, such as the platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR), have been demonstrated to be independent prognostic factors in several types of tumours (16-19). Recently, several studies have been performed to assess the prognostic value of PLR and NLR in GISTs. One meta-analysis suggested that NLR is an independent prognostic factor in patients with GISTs (20). Based on their results, the prognostic effects of PLR and NLR in GISTs remain inconsistent. Therefore, we performed this systematic analysis to assess the prognostic effects of PLR and NLR in GISTs. We present the following article in accordance with the PRISMA reporting checklist (available at http://dx.doi.org/10.21037/tcr-20-1037).


Methods

Search strategy

We performed a comprehensive search in MEDLINE, EMBASE and the Cochrane Library. The protocol for this systematic review was registered on PROSPERO (ID: CRD42020168505) and is available in full on the University of York website. The following terms were searched: “gastrointestinal stromal tumors” or “GISTs”, “PLR” (or “platelet-lymphocyte ratio”) or “NLR” (or “neutrophil-lymphocyte ratio”), “survival” or “prognostic” or “prognosis” or “recurrence” or “clinical outcome” (Figure 1).

Figure 1 Systematic search and selection strategy.

Study selection

The inclusion criteria included the following: (I) all patients had been diagnosed with GIST by pathological examination; (II) the association between PLR and overall survival (OS) and/or disease-free survival (DFS)/recurrence-free survival (RFS) or between NLR and OS and/or DFS/RFS was evaluated; and (III) all blood samples were obtained before treatment. The following types of studies were excluded: (I) case reports, reviews, conference abstracts and letters; (II) studies with insufficient data to calculate an HR and 95% CI; and (III) overlapping or duplicate publications. If multiple studies were reported by the same team from the same institute or were performed at the same time, only the latest article was included.

Data extraction

Data were reviewed and extracted independently by two authors (ZW Wei and WB Huang). The following information was recorded from each study: first author, study design, year of publication, country, number of subjects, NIH risk categories, PLR and NLR cut-off values, time of follow-up, outcome measures (HRs for OS and DFS/RFS and their 95% CIs), and clinicopathological characteristics. Hazard ratios were provided by the original studies or could be estimated from Kaplan-Meier survival curves (21).

Quality assessment

Study quality assessment was performed independently by two investigators according to the Newcastle-Ottawa Scale (NOS) (22). The range of total scores was from 0 to 9. High-quality trials scored more than 6.

Statistical analysis

The log HR and standard error (SE) were used to pool the survival results (21,23). Cochran’s Q test and the I2 statistic were used to evaluate the heterogeneity of the pooled outcomes. A P value <0.1 for the Q-test or I2>50% suggested significant heterogeneity among the included studies, and a random-effects model was used. A fixed-effects model was used to estimate the effect magnitude when inter-study heterogeneity was absent. Subgroup analyses were performed according to the area of publication, sample size, treatment, analysis method, cut-off value of PLR and NOS score. Publication bias was analysed by assessing the symmetry of the funnel plot and performing Egger’s test. The effect of potentially unpublished studies was investigated using the trim and fill procedure. Statistical analysis was performed with Review Manager Version 5.2 (Nordic Cochrane Centre, the Cochrane Collaboration), Stata version 14 and the R software environment.


Results

Description of studies

The initial search strategy identified 47 articles, and 28 articles were excluded after removing duplicate articles (Figure 1). Fourteen studies published between 2013 and 2019 including 3151 GIST patients were enrolled in this meta-analysis (Table 1) (13,24-36). Eight studies assessed the prognostic impact of both PLR and NLR, and five of the enrolled studies investigated only NLR.

Table 1

The characteristics of the studies included in this study

Author Year Country Study type Follow-up [months] Treatment Sample size Stage Models Cutoff value Outcome Analysis HRs NOS score
Perez et al. 2013 USA R 27 [6–59] Surg ± TKIT 335 Non-metastasis NLR NLR: 2.7 RFS UV Reported 6
Atila et al. 2014 Turkey R 49 [1–110] Surg 67 Non-metastasis NLR NLR: 1.92 DFS UV Reported 8
Jiang et al. 2016 China R NA Surg ± TKIT 129 Non-metastasis NLR NLR: 2.07 OS MV Reported 6
Xue et al. 2017 China R NA Surg ± TKIT 510 Non-metastasis PLR & NLR PLR: 127; NLR: 2.0 RFS MV Reported 6
Racz et al. 2015 Canada R 39.1 [0–124.25] Surg ± TKIT 93 Non-metastasis PLR & NLR PLR:245; NLR: 2.04 RFS UV Reported 7
Goh et al. 2016 Singapore R 43.5 [1.0–184.0] Surg ± TKIT 300 Non-metastasis PLR & NLR PLR:275; NLR: 3.0 RFS MV Reported 6
Feng et al. 2016 China R 31.6 [2–83] Surg 274 Non-metastasis PLR & NLR PLR:141.29; NLR: 2.24 DFS UV Reported 8
Yin et al. 2017 China R 44 [16–134] Surg ± TKIT 400 Non-metastasis PLR PLR:153.075 RFS MV Reported 7
Yin et al. [2] 2017 China R NA Surg ± TKIT 363 Non-metastasis PLR & NLR PLR:200; NLR: 1.245 RFS MV Reported 7
Stotz et al. 2016 Austria R 57.6 [3–166.8] Surg ± TKIT 149 Mixed PLR & NLR PLR:NA; NLR: 2.7 RFS, OS MV Reported 6
Rutkowski et al. 2018 Poland R 55 TKIT 385 Metastasis NLR NLR:2.7 PFS MV Reported 7
Sobczuk et al. 2019 Poland R 70.1 [64–104.5] TKIT 146 Metastasis NLR NLR:2.4 PFS MV Reported 7
Shi et al. 2019 China R 44.3 Surg ± TKIT 340 Non-metastasis PLR & NLR PLR:148.6; NLR: 2.03 RFS UV Reported 6
Sun et al. 2019 China R NA Surg ± TKIT 431 Non-metastasis PLR & NLR PLR: 203.2; NLR: 2.18 RFS MV Reported 7

NOS, Newcastle-Ottawa Scale; ;R, retrospective; Surg, surgery; TKIT, tyrosine kinase inhibitors therapy; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; OS, overall survival; DFS, disease-free survival; RFS, recurrence-free survival; PFS, progression-free survival; UV, univariate; MV, multivariate; NA, not available.

The number of subjects in each study varied from 67 to 510. Seven studies were from China, 2 were from Poland, 1 was from Singapore, 1 was from Canada, 1 was from Turkey, 1 was from the USA and 1 was from Austria. Thirteen studies determined DFS, and only 2 studies reported OS. Nine of the studies had ≥200 patients, and the other five had <200 patients (Table 1).

Prognostic impact of PLR and NLR

A total of 9 studies including 2,860 patients investigated the association between PLR and DFS. Significant heterogeneity was detected among the 9 studies (I2=64%, P=0.002) (Figure S1A). The heterogeneity seemed to be attributed to the study by Goh et al. After excluding this study, the heterogeneity decreased (P=0.38, I2=7%), and DFS was still significantly worse for the high PLR group than for the low PLR group, with a pooled HR of 1.29 (95% CI: 1.10–1.52, P=0.002; Figure 2A).

Figure 2 Forest plots of (A) platelet-to-lymphocyte ratio (PLR) and (B) neutrophil-to-lymphocyte ratio (NLR) in predicting disease-free survival.

Twelve studies reported the impact of NLR on DFS/RFS in GISTs. As shown in Figure 2B, the pooled analysis of the 12 studies showed that the DFS of patients with a high NLR was significantly inferior to that of patients with a low NLR (HR =1.37, 95% CI: 1.15–1.63; P=0.0005).

In addition, only two studies with 278 patients explored the prognostic effect of NLR on OS. The OS of the high NLR group seemed worse, but the difference was not significant (HR =1.74; P=0.29) (Figure S1B). Only Stotz et al. (29) investigated the association between PLR and OS and revealed that high PLR is an unfavourable predictor of OS.

Subgroup analysis of PLR for DFS

In addition, we performed meta-regression and subgroup analyses by area, sample size, analysis method, PLR cut-off value and NOS score, as shown in Table 2. Elevated PLR was correlated with poor DFS in studies performed in Eastern countries (HR =1.52, 95% CI: 1.13–2.04; P=0.006). In the subgroup analysis by sample size, a high PLR was associated with inferior DFS in studies with sample sizes ≥200 (HR =1.80, 95% CI: 1.27–2.57; P=0.001). The prognostic impact of high PLR was significant regardless of the analysis method (univariate or multivariate). The cut-off values of PLR ranged from 127 to 275. According to the cut-off value of PLR, studies were stratified into two subgroups: <200 and ≥200. Stratification based on the cut-off value showed that a high PLR was associated with poor DFS in studies with cut-off values ≥200 (HR =2.08, 95% CI: 1.04–4.15; P=0.040). Moreover, subgroup analysis suggested that elevated PLR significantly predicted decreased DFS in studies with NOS scores ≥7 (HR =1.76, 95% CI: 1.27–2.44; P=0.0007).

Table 2

Pooled hazard ratios (HRs) for DFS/RFS according to subgroup analyses based on the platelet-to-lymphocyte ratio (PLR)

Subgroup No. of studies No. of patients Effects model HR (95% CI) P value     Heterogeneity
I2 (%) P
Overall 9 2,860 Fixed 1.29 (1.10–1.52) 0.002 7 0.38
Area
   Eastern 7 2,618 Fixed 1.52 (1.13–2.04) 0.006 0 0.83
   Western 2 242 Random 2.30 (0.91–5.81) 0.080 89 <0.001
Sample size
   ≥200 7 2,618 Fixed 1.80 (1.27–2.57) 0.001 38 0.14
   <200 2 242 Random 1.75 (0.60–5.07) 0.290 69 0.07
Analysis method
   Univariate 4 1,092 Fixed 1.19 (1.06–1.33) 0.003 20 0.20
   Multivariate 5 1,768 Fixed 2.02 (1.41–2.91) <0.001 32 0.20
Cut-off value of PLR
   ≥200 4 1,187 Random 2.08 (1.04–4.15) 0.040 87 <0.001
   <200 4 1,524 Fixed 1.44 (0.99–2.11) 0.060 0 0.64
NOS score
   ≥7 5 1,561 Fixed 1.76 (1.27–2.44) <0.001 0 0.77
   <7 4 1,299 Random 1.67 (0.86–3.23) 0.130 82 0.001

NOS, Newcastle-Ottawa Scale.

Subgroup analysis of NLR for DFS

Among all the studies on NLR, 5 studies were performed in Eastern countries, and 7 studies were conducted in Western countries (Table 3). Subgroup analysis suggested that the correlations between NLR and DFS were still significant in both the Eastern countries (HR =2.22, 95% CI: 1.30–3.81; P=0.004) and Western countries (HR =1.28, 95% CI: 1.07–1.53; P=0.006) (Table 3). The results of the pooled analysis of 8 studies with sample sizes greater than 200 revealed that an elevated NLR was associated with poor survival (HR =1.96, 95% CI: 1.24–3.08; P=0.004). Concerning the analysis method, the prognostic impact of NLR on DFS was still significant according to univariate and multivariate analyses. Subgroup analyses stratified by NOS score showed that high NLR was correlated with shorter DFS regardless of NOS score.

Table 3

Pooled hazard ratios (HRs) for DFS/RFS according to subgroup analyse based on neutrophil-to-lymphocyte ratio (NLR)

Subgroup No. of studies No. of patients Effects model HR (95% CI)       P value     Heterogeneity
    I2 (%)     P
Overall 12 3,393 Fixed 1.37 (1.15–1.63) 0.0005 54 0.01
Area
   Eastern 5 1,918 Fixed 2.22 (1.30–3.81) 0.004 0 0.88
   Western 7 1,475 Random 1.28 (1.07–1.53) 0.006 64 0.010
Sample size
   ≥200 8 2,938 Random 1.96 (1.24–3.08) 0.004 64 0.007
   <200 4 455 Fixed 1.31 (0.93–1.83) 0.12 35 0.20
Analysis method
   Univariate 5 1,109 Fixed 2.92 (1.83–4.65) <0.001 0 0.90
   Multivariate 7 2,284 Fixed 1.12 (1.05–1.19) <0.001 16 0.31
NOS score
   ≥7 7 1,759 Fixed 1.61 (1.09–2.38) 0.02 46 0.08
   <7 5 1,634 Random 1.80 (1.08–3.00) 0.02 68 0.01

Associations between PLR, NLR and clinicopathological features

The present meta-analysis explored the effect of PLR on 7 clinical factors previously identified in GISTs. The pooled analysis demonstrated that elevated PLR was correlated with larger tumour size (>5 vs. <5 cm; OR =2.46, 95% CI: 1.87–3.22; P<0.001), mitotic index (>5/50 HPF vs. <5/50 HPF; OR =2.09, 95% CI: 1.61–2.71; P<0.001), adjuvant tyrosine kinase inhibitor (TKI) therapy (yes vs. no; OR =5.05, 95% CI: 1.07–23.75; P=0.04), and NIH risk category (high/intermediate vs. very low/low; OR =2.72, 95% CI: 2.03–3.64; P<0.001). Meanwhile, no significant association was found for sex (male vs. female), primary tumour site (stomach vs. non-stomach) or cellular type (spindle vs. non-spindle). The correlations between PLR and the clinicopathological features of GISTs are shown in Table S1.

As shown in Table S2, the correlations between NLR and clinicopathological features were also investigated. Similarly, a high NLR can predict the prognosis of patients with GISTs larger than 5 cm (OR =1.91, 95% CI: 1.48–2.47; P<0.001) and those in the high/intermediate risk groups (OR =2.41, 95% CI: 1.49–3.89; P<0.001). Moreover, elevated NLR was correlated with male sex and mitotic index (>5/50 HPF vs.<5/50 HPF; OR =1.80; P=0.006).

Comparison between PLR and NLR

Presently, PLR and NLR are the two most widely available markers in GISTs (25). Seven and four studies reported the HR for PLR and NLR in univariate and multivariate analyses, respectively. The pooled HR for PLR was not significantly different from that for NLR (Table S3).

Publication bias

Funnel plots of PLR and NLR were used to evaluate publication bias, as shown in Figure 3. Then, the asymmetry of the funnel plots was further tested by Egger’s test. No evidence of obvious publication bias was detected by Egger’s test (P=0.072) for PLR. For NLR, significant publication bias was found by Egger’s test (P<0.001). Then, a trim and fill analysis was performed to investigate the potential effect of publication bias. After incorporating 7 hypothetical studies, the funnel plots were shown to be symmetrical (Figure 4). The adjusted pooled analysis with the 7 additional studies showed that the DFS of patients with a high NLR was still worse than that of patients with a low NLR (HR =1.19, 95% CI: 1.01–1.42).

Figure 3 Funnel plots of DFS for (A) platelet-to-lymphocyte ratio (PLR) and (B) neutrophil-to-lymphocyte ratio (NLR).
Figure 4 Funnel plots with trim-and-fill analysis for neutrophil-to-lymphocyte ratio (NLR).

Discussion

Emerging evidence has demonstrated that inflammation-based factors, including PLR and NLR, which are representative of the inflammatory response, are associated with worse outcomes in several malignant tumours (37). Several studies demonstrated that PLR and NLR are independent prognostic factors in GISTs, while some other studies did not find similar results. A meta-analysis performed by Luo et al. suggested that an elevated preoperative NLR is associated with unfavourable outcomes in patients with GISTs (20). However, the prognostic role of PLR and NLR in GISTs remains controversial. We enrolled 14 studies involving 3,151 patients that investigated the prognostic roles of PLR and NLR in patients with GISTs. This meta-analysis aimed to identify the effects of elevated PLR and NLR on prognosis in patients with GISTs.

In the present meta-analysis, we demonstrated that elevated PLR and NLR are associated with worse DFS in GISTs. Although the specific mechanism remains unclear, our results are consistent with other studies that demonstrated that PLR or NLR was predictive of poorer prognosis in multiple types of malignancies, including colorectal cancer, hepatocellular carcinoma, and oesophageal tumours (38-42). PLR and NLR indicate the levels of systematic inflammation, which play vital roles in tumour progression (43,44). Platelets can release a variety of cytokines and chemokines to promote tumour metastasis (45). Labelle et al. reported that platelets recruit granulocytes and facilitate the formation of premetastatic niches, which are critical for metastasis (46). Moreover, there is increasing evidence suggesting crosstalk between platelets and tumour cells that contributes to tumour growth and progression (47). Lymphocytopenia and the suppression of lymphocyte activity induced by the systemic inflammatory response may result in the impairment of innate cellular immunity, leading to inferior survival (48). Given their important roles, elevated PLR combined with the effects of thrombocytosis and lymphocytopenia may be associated with the prognosis of GISTs. Moreover, it is well established that neutrophils act as key regulators of tumour-associated inflammation and the immune response (49). Neutrophils, especially tumour-associated neutrophils, are recruited into the tumour microenvironment by cytokines and chemokines to regulate inflammation, immunosuppression and tumour growth (50). Moreover, neutrophils counteract the function of immune cells to facilitate tumorigenesis via reactive oxygen species (ROS) and arginase-I (ARG) (51). Thus, NLR, as a marker of neutrophilia and lymphocytopenia, is correlated with poor prognosis in GISTs.

Subgroup analysis revealed that elevated PLR and NLR remain significant prognostic factors of DFS/RFS for GISTs in studies with sample sizes ≥200. The nonsignificant associations between PLR, NLR and DFS may be due to the limited number of studies with fewer than 200 subjects. Given that the cut-off values of PLR varied among the included studies, we performed subgroup analysis to assess the effects of different cut-off values on the prognostic impact of PLR and demonstrated that patients with elevated PLR suffer worse prognosis than those with low PLR in studies with cut-off values ≥200. Subgroup analysis of PLR for DFS revealed that no differences could distinctly be observed in Western countries. However, the limited sample size, with only 242 subjects from Western countries, might be responsible for this result. For NLR, significant differences were detected in both Eastern and Western countries. Moreover, elevated PLR and NLR predicted worse DFS/RFS in patients with GISTs, regardless of the analysis method.

PLR and NLR reflect the systemic inflammatory status, which is a hallmark of tumours. Yang et al. reported that PLR is elevated with TNM stage in colon cancers (52). Our data suggested that patients with high PLR tend to fall into the NIH high- and intermediate-risk categories. Liu et al. reported that elevated NLR is associated with increased tumour size in thyroid cancer (53). Consistent with the studies mentioned above, the present meta-analysis demonstrated that GISTs larger than 5 cm seem to correlate with high PLR and NLR. The innate immune system in early-stage tumours can recognize and eliminate tumour cells, and afterwards, with the progression of tumours, tumour cells can evade immune surveillance, leading to more advanced tumours (54). Hence, high PLR and NLR, indicators of systemic inflammation, correlate with advanced tumour stages in GISTs.

For GISTs, PLR and NLR are currently the two most widely available inflammatory markers. Racz et al. demonstrated that only PLR but not NLR is associated with prognosis in GISTs by univariate analysis (24). Goh et al. concluded that both PLR and NLR are independent prognostic factors in GISTs (25). Herein, we attempted to compare the prognostic influence of PLR and NLR, and no significant difference was observed.

Nevertheless, several limitations need to be addressed in the current meta-analysis. First, significant heterogeneity existed among the studies. The difference in cutoff values may be the major reason for the heterogeneity. Second, all the included studies were retrospective, and there were no randomized controlled trials (RCTs). Given the retrospective nature of the enrolled studies, the magnitude of any confounding factors would have been further amplified, and original articles supplied only summarized but not original data, which may have increased the heterogeneity. Third, HRs and their 95% CIs were extracted from univariable analysis in five studies. Consequently, the prognostic effect of PLR and NLR might be overestimated.


Conclusions

The current meta-analysis demonstrated that elevated preoperative PLR and NLR play significant roles in the prognosis of patients with GISTs. Additionally, PLR and NLR are cost-effective markers that may serve as potential prognostic biomarkers for GISTs in clinical practice. More well-designed and high-quality multicentre clinical trials are warranted to validate the impact of PLR and NLR in risk stratifications.

Figure S1 Forest plots of (A) platelet-to-lymphocyte ratio (PLR) in predicting DFS including the study of Goh et al. and (B) neutrophil-to-lymphocyte ratio (NLR) in predicting OS.

Table S1

Meta-analysis of the association between platelet-to-lymphocyte ratio (PLR) and clinicopathological features of gastrointestinal stromal tumours (GISTs)

Characteristics No. of studies No. of patients OR (95% CI)     P Heterogeneity
I2 (%) P
Gender (male vs. female) 5 1,407 1.14 (0.76–1.71) 0.52 54 0.09
Tumor size (>5 vs. <5 cm) 5 1,406 2.46 (1.87–3.22) <0.001 0 0.65
Primary tumor site (stomach vs. non-stomach) 5 1,407 0.85 (0.27–2.66) 0.78 93 <0.001
Mitotic index (>5 vs. <5) 5 1,402 2.09 (1.61–2.71) <0.001 0 0.73
Cellular type (spindle vs. non-spindle) 1 274 0.68 (0.25–1.85) 0.45
Adjuvant TKI therapy (yes vs. no) 4 1,133 5.05 (1.07–23.75) 0.04 91 <0.001
NIH risk category (high/intermediate vs. very low/low) 4 1,314 2.72 (2.03–3.64) <0.001 0 0.91

Mitotic index, per 50 high-power field (HPF). OR, odds ratio; TKI, tyrosine kinase inhibitors.

Table S2

Meta-analysis of the association between neutrophil-to-lymphocyte ratio (NLR) and clinicopathological features of gastrointestinal stromal tumours (GISTs)

Characteristics No. of studies No. of patients OR (95% CI) P Heterogeneity
I2 (%) P
Gender (male vs. female) 8 2,514 2.05 (1.75–2.41) <0.001 80 <0.001
Tumor size (>5 vs. <5 cm) 7 2,074 1.91 (1.48–2.47) <0.001 44 0.11
Primary tumor site (stomach vs. non-stomach) 9 2,452 0.82 (0.60–1.13) 0.23 68 0.002
Mitotic index (>5 vs. <5) 8 2,117 1.80 (1.18–2.74) 0.006 78 <0.001
Cellular type (spindle vs. non-spindle) 3 841 1.16 (0.74–1.81) 0.52 38 0.20
Adjuvant TKI therapy (yes vs. no) 6 1,968 1.13 (0.87–1.47) 0.28 20 0.35
NIH risk category (high/intermediate vs. very low/low) 6 1,881 2.41 (1.49–3.89) <0.001 83 <0.001

Mitotic index, per 50 high-power field (HPF). OR, odds ratio; TKI, tyrosine kinase inhibitors.

Table S3

Comparison of relative risk of HR between platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR)

Studies Pooled HR for PLR (95% CI) Pooled HR for NLR (95% CI) Subgroup difference P
PLR vs. NLR (univariate) 7 2.568 (1.385–4.760) 2.409 (1.725–3.365) 0.858
PLR vs. NLR (multivariate) 4 1.892 (1.282–2.792) 2.307 (1.432–3.716) 0.528

Acknowledgments

Funding: This study was supported by the National Natural Science Foundation of China (81702325) and natural Science Foundation of Guangdong Province (2017A030310565).


Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at http://dx.doi.org/10.21037/tcr-20-1037

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tcr-20-1037). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


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Cite this article as: Wei ZW, Huang WB, Yang DJ, Yuan YJ, He YL, Zhang CH. The prognostic roles of platelet-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio in gastrointestinal stromal tumours: a meta-analysis. Transl Cancer Res 2020;9(9):5128-5138. doi: 10.21037/tcr-20-1037

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