Oncotarget

Meta-Analysis:

Clinicopathological and prognostic significance of circulating tumor cells in patients with lung cancer: a meta-analysis

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Oncotarget. 2017; 8:62524-62536. https://doi.org/10.18632/oncotarget.19122

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Tingjuan Xu, Guodong Shen, Min Cheng, Weiping Xu, Gan Shen and Shilian Hu _

Abstract

Tingjuan Xu1,2, Guodong Shen1,2, Min Cheng1,2, Weiping Xu1,2, Gan Shen1,2 and Shilian Hu1,2

1Gerontology Institute of Anhui Province, Anhui Provincial Hospital Affiliated Anhui Medical University, Hefei 230001, China

2Anhui Provincial Key Laboratory of Tumor Immunotherapy and Nutrition Therapy, Hefei 230001, China

Correspondence to:

Shilian Hu, email: hushilian@126.com

Keywords: circulating tumor cells, lung cancer, prognosis, clinicopathological parameters, meta-analysis

Received: November 04, 2016    Accepted: April 25, 2017    Published: July 10, 2017

ABSTRACT

Background: The prognostic significance of circulating tumor cells in patients with lung cancer is controversial. Therefore, we aimed to comprehensively and quantitatively assess the prognostic role of CTCs in patients with lung cancer.

Methods: The relevant literature was searched using PubMed, the Cochrane database and the China National Knowledge Internet database (up to June 2016). Using Review Manager 5.1.2, a meta-analysis was performed using hazard ratio (HR), odds ratio (OR) and 95% confidence interval (CI) as effect values.

Results: Thirty studies comprising 2,060 patients with lung cancer were analyzed. The pooled HR values showed that circulating tumor cells were significantly correlated with overall survival (HR =2.63, 95% CI [2.04, 3.39]) and progression-free survival (HR =3.74, 95% CI [2.49, 5.61]) in these patients. Further subgroup analyses were conducted and categorized by sampling time, detection method, and histological type; these analyses showed the same trend. The pooled OR values showed that circulating tumor cells were associated with non small cell lung cancer stage(OR = 2.11, 95% CI [1.42, 3.14]), small cell lung cancer stage (OR = 10.91, 95% CI [4.10, 29.06]), distant metastasis (OR =7.06, 95%CI [2.82, 17.66]), lymph node metastasis (OR =2.31, 95% CI [1.19,4.46]), and performance status(OR =0.42, 95%CI [0.22, 0.78]).

Conclusion: The detection of circulating tumor cells in the peripheral blood of patients with lung cancer can be indicative of a poor prognosis.


INTRODUCTION

Lung cancer is one of the deadliest diseases in the world. Less than 15% of lung cancer patients survive for more than 5 years after being diagnosed [1]. Due to its aggressive behavior and greater invasive ability than other types of cancer, the predominant cause of treatment failure in patients with lung cancer is believed to be distant metastases, even during early-stage disease. Approximately 25% to 50% of patients with early-stage non small cell lung cancer (NSCLC) show tumor recurrence, even after tumor resection [2, 3]. However, current staging methods are unable to detect such occult metastases prior to the emergence of clinical manifestations [4]. Thus, there is an urgent need for more-sensitive prognostic and predictive markers.

Circulating tumor cells (CTCs) can be found in the peripheral blood of patients with cancer. Many studies have demonstrated the potential usefulness of CTCs in predicting patient prognosis for several cancer types [57]. Many studies have also shown associations between CTCs and poor survival in lung cancer [811]. However, the prognostic significance of CTCs in lung cancer remains controversial, as other studies have failed to show an association between CTCs and poor prognosis [12]. In addition, assessing the potential of using CTCs as a prognostic marker has been complicated by inter-study differences in aspects such as study population, methodology and sampling time.

Thus, our meta-analysis aimed to examine the association of CTCs with survival and clinicopathological parameters, and to evaluate the prognostic role of CTCs in patients with lung cancer.

RESULTS

Characteristics of the included studies

After initial literature searches, 153 articles were retrieved, and 4 duplicate articles were excluded. After screening the titles and abstracts, 67 studies remained, and their full texts were assessed for eligibility. Of the eligible studies, 37 studies were excluded because they lacked an outcome of interest. Ultimately, 30 studies were selected for analysis; these comprised 24 studies published in English and 6 studies published in Chinese (Figure 1).

A flow chart of the study design.

Figure 1: A flow chart of the study design. A systematic literature search yielded a total of 153 articles related to the relationship between CTCs and lung cancer. After the screening of titles, abstracts and full texts, 123 articles were excluded for reasons detailed in the main text. A meta-analysis was then performed on 30 studies to assess the clinicopathological and prognostic significance of CTCs in patients with lung cancer.

The analyzed studies were from the Netherlands, the United Kingdom, America, Spain, Japan, Korea and China, and included a total of 2,060 patients. The median number of patients in each study was 69 (range, 28-208). Of these 30 studies, 2 studies addressed both NSCLC and small cell lung cancer (SCLC); 22 studies addressed NSCLC alone, and 6 addressed SCLC alone. The sampling time was divided into two time points: namely, pre- and post-treatment. Both time points were included in 12 studies [911, 1321], pretreatment alone in 15 studies [8, 12, 2234] and post-treatment alone in 3 studies [3537]. Nine studies used the reverse-transcriptase polymerase chain reaction (RT-PCR) method, and 21 studies used other methods. Hazard ratio (HR) for overall survival (OS) and progression-free survival (PFS) could be extracted from 12 studies and 4 studies, respectively. The patient clinical characteristics and the design variables of the studies are summarized in Table 1. The quality of the 30 included studies was evaluated according to the Newcastle-Ottawa scale (NOS) (Table 2). Twenty-five studies were of high quality (NOS score ≥ 5), and 5 studies were of low quality (NOS score < 5).

Table 1: Characteristics and design variables of the including studies

Author

Country

No. of patients

Age

Histological features

Treatment

Sampling volume

Methods

Markers

Sampling time

Cutoff of CTC

Chen TF et al

China

67

62(40-75)

ADC 32 SQC 32 Others 3

chemo. and radio.

8ml

RT-PCR

CK19 mRNA

pre and post

NR

Hiltermann TJ et al

Holland

59

64(47-84)

SCLC 59

chemo. and radio.

7.5ml

Cellsearch

EpCAM,CK8,18,19,DAPI

pre and post

2 CTCs

Hofman V et al

NR

208

63(37-84)

ADC 115 SQC 54 Others 39

surg.

10ml

ISET

NR

pre

50

Hou JM et al

UK

97

68(28-84)

SCLC 97

chemo.

7.5ml

Cellsearch, ISET

EpCAM,CK8,18,19,DAPI

pre and post

50 CTCs

Igawa S et al

Japan

30

69(51-85)

SCLC 30

chemo.

7.5ml

IF

GFP

pre and post

2 CTCs

Krebs MG et al

UK

101

67(43-84)

ADC 31 SQC 32 Other 38

chemo. and radio.

7.5ml

Cellsearch

EpCAM,CK8,18,19,DAPI

pre and post

2 CTCs

Naito T et al

Japan

51

67(34-92)

SCLC 51

chemo. or radio.

7.5ml

Cellsearch

EpCAM,CK8,18,19,DAPI

pre

8 CTCs

Nieva J et al

America

28

64(31-82)

ADC 21 SQC 5 Others 2

chemo. or biotherapy

NR

IF

CK 1,4-8,10,13,18,19, DAPI

pre

1CTC

Shi WJ et al

China

55

59(41-75)

SCLC 55

chemo.

10ml

RTQ-PCR

CK19 mRNA

pre and post

3.8

Yamashita J et al

Japan

103

68(35-83)

ADC 66 SQC 37

surg.

NR

RT-PCR

CEA mRNA

pre and post

NR

Yie SM et al

China

143

57(30-84)

ADC 87 SQC 56

surg. or chemo.

2ml

RT-PCR

Survivin mRNA

pre

1.02pg/ml

Yoon SO et al

Korea

79

66(42-87)

ADC 45 SQC 27 Others 7

surg.

NR

RT-PCR

TTF-1,CK19 mRNA

pre and post

NR

Juan O et al

Spain

37

71(44-85)

ADC 14 SQC 14 Others 9

chemo.

7.5ml

Cellsearch

EpCAM,CK8,18,19,DAPI

pre and post

2 CTCs

Sher YP et al

China

54

65(28-81)

ADC 35 SQC 14 Others 5

surg. or chemo.

3-4ml

RT-PCR

keratin 19, Ubiquitin thiolesterase C, HSFIB1

pre

NR

Bayarri-Lara C et al

Spain

56

67.4(45-80)

ADC 25 SQC 29 Others 2

surg.

10ml

IF

EGFR,CK

pre and post

NR

Chen X et al

China

169

NR

ADC 112 SQC 51 Others 6

NR

7.5ml

Cellsearch

EpCAM,CK8,18,19,DAPI

pre

1CTC

Hirose T et al

Japan

33

64(46-74)

ADC 24 SQC 8 Others 1

chemo.

7.5ml

Cellsearch

EpCAM,CK8,18,19,DAPI

pre

1CTC

Ji JL et al

China

56

68(38-80)

NSCLC

surg.

2ml

ICC

EpCAM

post

1CTC

Lou JT et al

China

33

58(33-76)

ADC 16 SQC 11 Others 6

chemo.

3ml

LT-PCR

CK,FR,DAPI

pre

8.5

Peck K et al

China

86

66(26-82)

ADC 47 SQC 17 SCLC 15 Others 7

surg. or chemo. or radio.

3-5ml

RT-PCR

CK19 mRNA

pre

NR

Sheu CC et al

China

100

64(37-87)

ADC 72 SQC 28

NR

5ml

RT-PCR

17genes

pre

NR

Wang B et al

China

42

68(37-80)

ADC 25 SQC 17

surg.

10ml

ICC

EpCAM

post

1CTC

Wu C et al

China

47

NR

ADC 27 SQC 7 SCLC 13

chemo.

7.5ml

IF

CK18,19,DAPI

pre

2CTCs

Xu YH et al

China

66

69(34-80)

ADC 35 SQC 31

chemo.

7.5ml

Cellsearch

EpCAM,CK8,18,19,DAPI

pre and post

1CTC

Feng YQ et al

China

49

NR

ADC 20 SQC 29

NR

7.5ml

IF

EpCAM,CK,DAPI

pre

1CTC

HuangTH et al

China

51

58.6(43-75)

ADC 21 SQC 30

surg. or chemo. or radio.

4ml

ICC

CK

pre

1CTC

Li J et al

China

30

67(43-79)

ADC 12 SQC 18

chemo.

7.5ml

IF

CK

pre and post

1CTC

Lin XM et al

China

60

56(35-76)

ADC 32 SQC 28

surg.

10ml

ICC

CK

pre

1CTC

Qian Z et al

China

35

48(21-69)

SCLC 35

NR

7.5ml

Cellsearch

EpCAM,CK8,18,19,DAPI

pre

1CTC

Zhao SW et al

China

35

58(43-80)

ADC 31 SQC 4

surg.

3.2ml

IF

DAPI

post

2CTCs

ADC, adenocarcinoma; SQC, squamous cell carcinoma; SCLC, small-cell lung cancer; chemo., chemotherapy; radio., radiotherapy; surg., surgery; IF, immunofluorescence; ISET, isolation by size of epithelial tumor cells; ICC, immunocytochemistry; pre, pre-treatment; post, post-treatment; NR, not reported

Table 2: The assessment of the risk of bias in each Cohort study using the Newcastle—Ottawa scale

Study

Selection(0-4)

Comparablility (0-2)

Outcome(0-3)

Total

REC

SNEC

AE

DO

SC

AF

AO

FU

AFU

Chen TF

1

1

1

1

0

0

1

1

1

7

Hiltermann TJ

1

1

1

1

0

0

1

1

1

7

Sher YP

1

1

1

1

0

0

1

1

1

7

Hofman V

1

1

1

1

0

0

1

1

0

6

Hou JM

1

1

1

1

0

0

1

0

1

6

Igawa S

1

1

1

1

0

0

1

0

1

6

Shi WJ

1

1

1

1

0

0

1

0

1

6

Yamashita Y

1

1

1

1

0

0

0

1

1

6

Yie SM

1

1

1

1

0

0

1

1

0

6

Yoon SO

1

1

1

1

0

0

1

1

0

6

Krebs MG

0

1

1

1

0

0

1

0

1

5

Naito T

1

1

1

1

0

0

1

0

0

5

Nieva J

1

1

1

1

0

0

0

0

1

5

Juan O

0

1

1

1

0

0

1

0

1

5

Bayarri-Lara C

1

1

1

1

0

0

0

0

1

5

Chen X

1

1

1

1

0

0

1

0

0

5

Hirose T

0

1

1

1

0

0

1

0

1

5

Ji JL

1

1

1

1

0

0

1

0

0

5

Peck K

1

1

1

1

0

0

1

0

0

5

Sheu CC

1

1

1

1

0

0

1

0

0

5

Wang B

1

1

1

1

0

0

1

0

0

5

Wu C

1

1

1

1

0

0

1

0

0

5

Feng YQ

1

1

1

1

0

0

1

0

0

5

Lin XM

1

1

1

1

0

0

1

0

0

5

Qian Z

1

1

1

1

0

0

1

0

0

5

Lou JT

1

1

1

1

0

0

0

0

0

4

Xu YH

0

1

1

1

0

0

1

0

0

4

Huang TH

1

1

1

1

0

0

0

0

0

4

Li J

0

1

1

1

0

0

1

0

0

4

Zhao SW

1

1

1

1

0

0

0

0

0

4

The prognostic effect (OS and PFS) of CTC detection

The pooled HR values showed a significant correlation between CTCs and OS in patients with lung cancer (HR =2.63, 95% confidence interval (CI) [2.04, 3.39], P<0.00001, I2=19%) (Figure 2). Subsequently, subgroup analyses were conducted after categorization by sampling time, detection method, and histological type to further investigate the prognostic role of CTCs. We found a significant correlation between CTCs and OS in the NSCLC (HR =2.55, 95% CI [1.65, 3.93], P<0.0001, I2=49%) and SCLC subgroups (HR =2.88, 95% CI [2.01, 4.11], P<0.00001, I2=0%). In addition, the results of the analysis showed that CTCs could be a prognostic indicator of OS both pretreatment (HR =2.81, 95% CI [2.03, 3.89], P<0.00001, I2=38%) and post-treatment (HR =3.68, 95% CI [2.39, 5.66], P<0.00001, I2=30%), regardless of whether the RT-PCR method (HR =2.26, 95% CI [1.43, 3.58], P=0.0005, I2=34%) or other methods (HR =2.85, 95% CI [2.09, 3.89], P<0.00001, I2=12%) were used.

Forest plots evaluating the maximally adjusted association between CTC presence and OS.

Figure 2: Forest plots evaluating the maximally adjusted association between CTC presence and OS. (A) A Forest plot assessing the effect of CTC presence on OS in subgroups divided by sampling time. (B) A Forest plot assessing the effect of CTC presence on OS in subgroups divided by detection method. (C) A Forest plot assessing the effect of CTC presence on OS in subgroups divided by histological type.

The pooled HR values revealed a significant correlation between CTCs and PFS in patients with lung cancer (HR =3.74, 95% CI [2.49, 5.61], P<0.00001, I2=0%) (Figure 3). The subgroup analyses showed a significant correlation between CTCs and PFS in the NSCLC (HR =3.91, 95% CI [2.32, 6.60], P<0.00001, I2=0%) and SCLC subgroups (HR =3.49, 95% CI [1.84, 6.63], P=0.0001, I2=0%). In addition, we found that CTCs could be a prognostic indicator of PFS both pretreatment (HR =2.73, 95% CI [1.68, 4.43], P<0.0001, I2=27%) and post-treatment (HR =4.27, 95% CI [2.60, 7.02], P<0.00001, I2=24%), regardless of whether the RT-PCR method (HR =3.38, 95% CI [2.06, 5.56], P<0.0001, I2=0%) or other methods (HR =4.56, 95% CI [2.27, 9.17], P<0.0001, I2=0%) were used.

Forest plots evaluating the maximally adjusted association between CTC presence and PFS.

Figure 3: Forest plots evaluating the maximally adjusted association between CTC presence and PFS. (A) A Forest plot assessing the effect of CTC presence on PFS in subgroups divided by sampling time. (B) A Forest plot assessing the effect of CTC presence on PFS in subgroups divided by detection method. (C) A Forest plot assessing the effect of CTC presence on PFS in subgroups divided by histological type.

Correlation between CTCs and clinicopathological parameters

The pooled odds ratio (OR) values showed that there was a significant correlation between CTCs and tumor stage in patients with lung cancer. As shown in Table 3, the incidence of CTC detection in patients with stage III/IV was higher than that in patients with stage I/II NSCLC (OR = 2.11, 95% CI [1.42,3.14], P=0.0002, I2= 20%). Similarly, the incidence of CTC detection in extensive SCLC was higher than that in limited SCLC (OR = 10.91, 95% CI [4.10, 29.06], P<0.00001, I2= 4%). However, the subgroup analyses of studies using the RT-PCR method showed no significant correlation between CTCs and tumor stage in either NSCLC patients or SCLC patients.

Table 3: Detailed results of meta-analyses for clinicopathological parameters

Clinicopathological parameters

Sample time

Study no.

Patient no.

OR(95% CI), P

Heterogeneity(I2, P)

NSCLC Stage III/IV vs. I/II

overall

15

1123

2.11 [1.42, 3.14], 0.0002

20%, 0.23

pre

12

990

1.77 [1.17, 2.68], 0.007

16%, 0.29

post

5

248

3.72 [1.79, 7.72], 0.0004

0%, 0.85

PCR

7

464

1.25 [0.71, 2.19], 0.44

7%, 0.37

non-PCR

8

659

2.71 [1.78, 4.13], <0.00001

0%, 0.50

SCLC Extensive vs. Limited

overall

4

202

10.91 [4.10, 29.06], <0.00001

4%, 0.37

pre

4

202

10.91 [4.10, 29.06], <0.00001

4%, 0.37

post

1

55

5.75 [1.58, 20.99], 0.008

PCR

2

70

6.30 [0.60, 65.68], 0.12

49%, 0.16

non-PCR

2

132

13.87 [4.30, 44.77], <0.0001

0%, 0.39

Distant metastasis (+) vs. (-)

overall

5

522

7.06 [2.82, 17.66], <0.0001

46%, 0.11

pre

5

522

7.06 [2.82, 17.66], <0.0001

46%, 0.11

post

1

55

5.75 [1.58, 20.99], 0.008

PCR

2

155

8.58 [2.07, 35.56], 0.003

0%, 0.77

non-PCR

4

367

7.13 [1.80, 28.21], 0.005

70%, 0.03

NSCLC

3

370

5.44 [1.40, 21.15], 0.01

45%, 0.16

SCLC

2

152

11.41 [4.15, 31.39], <0.00001

0%, 0.54

Lymph node metastasis (+) vs. (-)

overall

5

420

2.31 [1.19, 4.46], 0.01

19%, 0.29

pre

5

420

2.31 [1.19, 4.46], 0.01

19%, 0.29

post

2

104

1.60 [0.57, 4.46], 0.37

20%, 0.26

PCR

3

239

2.98 [0.72, 12.29], 0.13

58%, 0.09

non-PCR

2

181

2.17 [0.97, 4.88], 0.06

0%, 0.60

NSCLC

5

420

2.31 [1.19, 4.46], 0.01

19%, 0.29

SCLC

0

0

Performance status 0-1 vs. 2

overall

4

286

0.42 [0.22, 0.78], 0.006

0%, 0.48

pre

4

286

0.42 [0.22, 0.78], 0.006

0%, 0.48

post

1

55

0.85 [0.25, 2.83], 0.79

PCR

1

55

0.69 [0.16, 2.96], 0.62

non-PCR

3

231

0.37 [0.19, 0.74], 0.005

0%, 0.39

NSCLC

2

134

0.59 [0.13, 2.80], 0.51

31%, 0.23

SCLC

2

152

0.38 [0.18, 0.79], 0.01

0%, 0.36

Tumor size (<3cm) vs. (>3cm)

overall

6

445

0.88 [0.55, 1.42], 0.60

0%, 0.54

pre

4

347

1.06 [0.62, 1.79], 0.83

0%, 0.70

post

4

202

0.53 [0.27, 1.03], 0.06

0%, 0.75

PCR

2

161

0.96 [0.39, 2.31], 0.92

10%, 0.29

non-PCR

4

284

0.84 [0.47, 1.50], 0.56

0%, 0.41

NSCLC

6

445

0.88 [0.55, 1.42], 0.60

0%, 0.54

SCLC

0

0

Gender male vs. female

overall

15

930

1.37 [0.99, 1.89], 0.06

0%, 0.88

pre

14

1032

1.26 [0.93, 1.70], 0.14

0%, 0.81

post

5

268

1.21 [0.54, 2.73], 0.64

36%, 0.18

PCR

5

337

1.29 [0.60, 2.79], 0.51

34%, 0.19

non-PCR

10

593

1.40 [0.95, 2.06], 0.09

0%, 0.99

NSCLC

14

875

1.36 [0.97, 1.90], 0.07

0%, 0.84

SCLC

1

55

1.48 [0.40, 5.50], 0.56

Age non-aged vs. aged

overall

11

695

0.80 [0.57, 1.13], 0.20

0%, 0.82

pre

10

653

0.79 [0.56, 1.13], 0.20

0%, 0.75

post

3

146

1.18 [0.56, 2.48], 0.67

0%, 0.90

PCR

2

139

0.63 [0.30, 1.33], 0.23

0%, 0.39

non-PCR

9

556

0.85 [0.58, 1.25], 0.42

0%, 0.79

NSCLC

11

695

0.80 [0.57, 1.13], 0.20

0%, 0.82

SCLC

0

0

Smoking status Never vs. former or current

overall

7

497

0.66 [0.40, 1.07], 0.09

19%, 0.29

pre

7

497

0.66 [0.40, 1.07], 0.09

19%, 0.29

post

0

PCR

1

54

0.67 [0.20, 2.27], 0.52

non-PCR

6

443

0.66 [0.37, 1.17], 0.16

32%, 0.19

NSCLC

7

497

0.66 [0.40, 1.07], 0.09

19%, 0.29

SCLC

0

0

We found that the presence of CTCs was significantly increased in lung cancer patients with distant metastasis (OR =7.06, 95%CI [2.82, 17.66], P<0.0001, I2= 46%). Further subgroup analyses conducted and categorized by sampling time, detection method, and histological type showed the same trend. The presence of CTCs was also significantly increased in lung cancer patients with lymph node metastasis (OR = 2.31, 95%CI [1.19, 4.46], P=0.01, I2= 19%), but the subgroup analyses showed a significant correlation between CTCs and lymph node metastasis only in the pretreatment subgroup. Moreover, all the studies included in this analysis pertained to NSCLC. We also found that CTCs were associated with performance status (OR = 0.42, 95%CI [0.22, 0.78], P=0.006, I2= 0%). Lower performance scores corresponded to lower CTC incidence. However, the subgroup analyses showed no significant correlation in the post-treatment, PCR or NSCLC subgroups.

Furthermore, pooled analyses of tumor size, performance status, smoking status, and patient age revealed no significant correlation between these clinicopathological parameters and CTCs.

Test of heterogeneity

Except for the ‘non-PCR on distant metastasis’ subgroup (I2= 70%) and the ‘PCR on lymph node metastasis’ subgroup (I2= 58%), the heterogeneity among all the included studies was not significant. However, when one study [26] from the ‘non-PCR on distant metastasis’ subgroup was removed, the I2 value was reduced to 0%, while the correlation of CTCs with distant metastasis was unchanged (OR = 14.87, 95% CI [5.00, 44.29], P<0.00001). Similarly, when one study [17] from the ‘PCR on lymph node metastasis’ subgroup was removed, the I2 value was reduced to 0%, but the correlation of CTCs with lymph node metastasis was changed (OR = 5.92, 95% CI [1.76, 19.91], P =0.004).

Sensitivity analyses

We performed sensitivity analyses to test the robustness of the pooled results. The pooled HR was not significantly altered when any individual study was removed. Moreover, the pooled OR was not significantly influenced when any individual study was removed, with the exception of lymph node metastasis. The pooled OR of lymph node metastasis was significantly altered by removal of the study [17] that was the source of heterogeneity.

Publication bias

As shown in Figure 4, funnel plots showed no evidence of publication bias. In addition, Egger’s and Begg’s tests were examined to detect publication bias in our article. The results of both Egger’s and Begg’s tests showed no evidence of publication bias (P>0.05).

Assessment of publication bias using funnel plot analysis.

Figure 4: Assessment of publication bias using funnel plot analysis. Funnel plot analyses of studies on OS (A), PFS (B), NSCLC stage (C), SCLC stage (D), distant metastasis (E), lymph node metastasis (F), performance status (G), tumor size (H), gender (I), age (J) and smoking status (K).

DISCUSSION

Although chemoradiotherapy and surgery have been widely used, lung cancer metastasis and recurrence frequently occur. The poor overall survival of patients and the complex heterogeneity of the disease are significant challenges for therapeutic intervention. Therefore, biomarkers that can be used to identify lung cancer recurrence or metastasis are needed to facilitate timely diagnosis and effective treatment strategies for lung cancer patients. CTCs, which are released by primary tumors or metastatic tumors, have been recognized as the cause of tumor metastasis or recurrence [38, 39]. However, the clinicopathological and prognostic significance of CTC detection in patients with lung cancer is not clear. In this meta-analysis, we provide strong evidence that CTCs are significantly associated with poor OS and PFS in lung cancer patients, irrespective of sampling time, detection method, and histological type. All the pooled HRs were above 2.0 in our study. These results demonstrate that a CTC-high status indicates poor prognosis in lung cancer patients; these patients may need more-aggressive treatment that is assessed frequently and closely monitored.

According to the pooled ORs in our meta-analysis, CTCs were associated with tumor stage, lymph node metastasis, distant metastasis, and performance status in patients with lung cancer. The results indicated that CTCs can be predictors of disease progression, and may be used to estimate the degree of malignancy and metastatic ability in lung cancer. However, the analysis of lymph node metastasis showed that the correlation occurred only in the pretreatment subgroup. It is generally believed that lymph node metastasis occurs prior to blood-borne metastasis, but the detection of CTCs in patients with early tumors indicates that blood-borne metastasis can occur before lymph node metastasis. In one study [24], the incidence of CTC detection was higher in patients with lymph node metastasis than in those free of lymph node metastasis. However, in other studies [17, 19, 26, 29], the incidence of CTC detection was not correlated with lymph node metastasis. Thus, the correlation between CTCs and lymph node metastasis may require further investigation.

We analyzed studies reporting the detection of CTCs in peripheral blood before and after treatment. The results from these two sampling time were consistent, except for the correlation of CTCs with lymph node metastasis and performance status. Therefore, CTC detection may offer doctors a simpler, less-invasive method that can be used at an earlier stage of disease (relative to other methods) to estimate disease progression and predict the prognosis of patients before treatment.

In recent years, various new CTC assay metho-dologies have been developed, including RT-PCR, immunocytochemistry, and the CellSearch System, for example. Each method has its advantages and disadvantages. We obtained different results for the PCR and non-PCR subgroups in analyses of tumor stage, lymph node metastasis, and performance status. CTCs were not associated with these clinicopathological parameters in the PCR subgroup. It thus seems that non-PCR-based methods are best for CTC detection in this context. Several studies have been performed to compare CTC detection methods, but no conclusive results have been obtained as of yet [40]. Therefore, further studies within the same lung cancer patient populations are needed to provide comparative data on the clinical significance of CTCs detected by different methods.

We found significant heterogeneity in the non-PCR subgroup on distant metastasis and in the PCR subgroup on lymph node metastasis. In these two subgroups, CTCs were detected before treatment using the same detection methods. However, the optimal cut-off values for CTC detection were obviously different for the two subgroups. In addition, the markers of CTC detection were not uniform in the PCR-subgroup studies that investigated the association between CTCs and lymph node metastasis. We propose that these two factors might be the principal causes of heterogeneity.

This study has some notable limitations. First, our meta-analysis was limited to the published scientific literature, and univariate data were also included in the present meta-analysis because multivariate survival analysis data were not available. Second, the CTC detection assays varied in our study, and included different endpoints, cut-off values, and experimental designs. Moreover, we excluded some papers that did not calculate OS and PFS, which may have influenced the results to some degree [18, 25, 41].

In conclusion, this meta-analysis indicates that the detection of CTCs in peripheral blood may be an indicator of patient prognosis, and provides evidence that CTC detection can be used to estimate the degree of malignancy and metastatic ability in patients with lung cancer. In the future, high-quality, well-designed and large-scale multicenter studies are needed to further substantiate these findings.

METHODS

Literature search

PubMed, the Cochrane database and the China National Knowledge Internet database were searched for studies pertaining to the clinicopathological and prognostic relationship between CTCs and lung cancer without language, publication or time restrictions (up to June 2016). The main search terms were “lung or pulmonary or pulmonic or pneumonic or pneumal” and “cancer or tumor or tumour or carcinoma or neoplasm(s)” and “CTC(s) or circulating tumor cell(s) or circulating cancer cell(s) or circulating epithelial cell(s) or micrometastasis”. Furthermore, relevant articles were identified from references cited in the retrieved articles and in review articles by manual searching.

Selection criteria

Eligible studies were included if they met the following criteria: (i) CTCs were detected in lung cancer patients; (ii) samples were collected from peripheral blood; and (iii) at least one of the outcome measures of interest was reported in the study or calculated from published data. When several studies were reported from the same authors or organizations, the meta-analysis included the most recent study (or the highest-quality study if the most recent study did not fit the inclusion criteria).

Studies were excluded if they met any of the following criteria: (i) the number of patients with lung cancer was fewer than 20; (ii) repeated studies were based on the same database or patients; or (iii) they provided insufficient data.

Data extraction and assessment of study quality

Two independent reviewers evaluated each study and extracted data independently, and any disagreements were resolved via discussion. We performed two types of analysis. The first type of analysis determined whether CTC status was associated with OS or PFS. The second type of analysis determined whether CTC status was correlated with clinicopathological parameters, which included tumor size, lymph node metastasis, distant metastasis, NSCLC stage(III/IV vs. I/II), SCLC stage (extensive disease vs. limited disease), gender, age, smoking and performance status. Data for multivariate survival analyses reported in the included articles were included in this meta-analysis. If these data were not available, then univariate analytical data were included. The quality of studies was evaluated according to the NOS [42], and studies with an NOS score≥ 5 were considered to be of high quality.

Statistical analysis

Statistical analysis was performed using Review Manager 5.1.2software. The estimated HR was used to evaluate the prognostic effect (OS and PFS), and the estimated OR was used to summarize the association between CTC detection and the clinicopathological characteristics of lung cancer. If the HR and its variance were not reported directly in the original study, then these values were calculated from the available reported data using software designed by Tierney et al. [43]. All statistical values were combined with a 95% CI, and the P-value threshold was set at 0.05. The random-effects mode was used to perform the analysis, as this model produced more conservative results than did the fixed-effects model, and it was a better fit for the multicenter clinical studies owing to the existence of heterogeneity [44]. Heterogeneity was calculated using a Q test, and the I2 value represented the degree of heterogeneity. Publication bias was tested using a funnel plot, and by Egger’s and Begg’s tests, in Stata 12.0 software. The overall analysis was completed by evaluating all the relevant studies according to different clinicopathological parameters and prognostic outcomes. Further subgroup analyses were conducted and categorized by sampling time (pretreatment and post-treatment), detection method (PCR and non-PCR), and histological type (NSCLC and SCLC). Sensitivity analyses were performed by excluding one study at a time to evaluate the influence of single studies on summary effect values.

Abbreviations

CI, confidence intervals

CTCs, circulating tumor cells

HR, hazard ratio

NOS, Newcastle-Ottawa scale

NSCLC, non small cell lung cancer

OR, odds ratio

OS, overall survival

PFS, progression-free survival

RT-PCR, reverse-transcriptase polymerase chain reaction

SCLC, small cell lung cancer

ACKNOWLEDGMENTS

This work was supported by the Anhui Provincial Project of the Key Laboratory of Tumor Immunotherapy and Nutrition Therapy (1606c08236) and National Natural Science Foundation of China (81471552). We are grateful for this funding support.

CONFLICTS OF INTEREST

There are no potential conflicts of interest to disclose.

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