The prognostic value of IDO expression in solid tumors: a systematic review and meta-analysis

DOI: https://doi.org/10.21203/rs.2.18707/v2

Abstract

Background: Indoleamine 2,3-dioxygenase (IDO) is a rate-limiting enzyme in the metabolism of tryptophan into kynurenine. It is considered to be an immunosuppressive molecule that plays an important role in the development of tumors. However, the association between IDO and solid tumor prognosis remains unclear. Herein, we retrieved relevant published literature and analyzed the association between IDO expression and prognosis in solid tumors.

Methods: Studies related to IDO expression and tumor prognosis were retrieved using PMC, EMbase and web of science database. Overall survival (OS), time to tumor progression (TTP) and other data in each study were extracted. Hazard ratio (HR) was used for analysis and calculation, while heterogeneity and publication bias between studies were also analyzed.

Results: A total of 31 studies were included in this meta-analysis. Overall, high expression of IDO was significantly associated with poor OS (HR 1.92, 95% CI 1.52–2.43, P<0.001) and TTP (HR 2.25 95% CI 1.58–3.22, P<0.001). However, there was significant heterogeneity between studies on OS (I2=81.1%, P<0.001) and TTP (I2=54.8%, P=0.007). Subgroup analysis showed lower heterogeneity among prospective studies, studies of the same tumor type, and studies with follow-up periods longer than 45 months.

Conclusions: The high expression of IDO was significantly associated with the poor prognosis of solid tumors, suggesting that it can be used as a biomarker for tumor prognosis and as a potential target for tumor therapy.

1. Background

Indoleamine 2,3-dioxygenase (IDO) is an intracellular and immunosuppressive rate-limiting enzyme in metabolism of tryptophan to kynurenine [1]. Tryptophan is an essential amino acid in protein synthesis and many important metabolic processes and cannot be synthesized in vivo. The main metabolic pathway for tryptophan in mammals is the kynurenine pathway, and this pathway requires participation of members from the IDO family. The IDO family of genes includes IDO1 and IDO2. IDO1 has higher catalytic efficiency than IDO2 and is more abundant in tissues [2]. In this systematic review and meta-analysis, the term ‘IDO’ will refer to IDO1.

 

IDO can exert immunosuppressive effects through a variety of mechanisms. The high expression and activity of IDO leads to a large consumption of tryptophan in the cell microenvironment, which makes the cells in a "tryptophan starvation" state. Depletion of tryptophan causes T cells arrest in the G1 phase of cell cycle, thereby inhibiting T cell proliferation. The main metabolite of tryptophan degradation, kynurenine, also has a direct toxic effect on T cells and induces T cell apoptosis. Kynurenine is also a natural ligand for aryl hydrocarbon receptors. By activating aryl hydrocarbon receptors, kynurenine can regulate the differentiation direction of Th17/Treg cells, thereby promoting the balanced differentiation of Th17/Treg to Treg cells [3-5].

 

IDO plays an important role in a variety of disease processes such as chronic inflammatory diseases, infection, and cancer [4, 6-8]. Increased expression of IDO is observed in many types of tumors, including colorectal, hepatocellular, ovarian and melanomas [5]. Tumors with high expression of IDO tend to increase metastatic invasion and have a poor clinical outcome in cancer patients. IDO is considered to be a new target for tumor therapy, and inhibition of IDO activity by using IDO inhibitors can increase patient survival [9-11].

 

Although IDO-targeted tumor therapy strategies are currently being developed, the association between expression level of IDO in tumor tissues and prognosis of patients remains unclear. Therefore, we constructed this meta-analysis to explore the correlation between IDO expression and tumor prognosis.

2. Methods

The present systematic review and meta-analysis was conducted and reported according to the standards of quality detailed in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [12]. Comprehensive and systematic search of published literature using the following database, such as PMC, Embase, and Web of Science (up to May 31, 2019). We used keyword such as: ("IDO" or Indoleamine 2,3-dioxygenase) AND (cancer or carcinoma or tumor or neoplasms) AND prognosis to search in the database. The retrieved information of relevant literature was downloaded and imported into the literature management software for further browsing and screening.

 

Studies included in this meta-analysis needed to meet the following inclusion criteria: 1) The included literature needed to provide appropriate prognostic indicators in evaluating the expression of IDO and prognosis of solid tumors, such as overall survival (OS), progression-free survival (PFS), disease-free survival (DFS) or relapse-free survival (RFS). 2) The included literature needed to provide hazard ratios (HRs) with 95% confidence intervals (CIs). 3) The included literature needed to provide criteria for defining IDO expression as positive and negative, or strong and weak expression.

 

This meta-analysis had the following exclusion criteria: 1) The type of literature was not a research article but the following types:reviews, case reports, letters, editorials,  and meeting abstracts; 2) Animal experiments or in vitro experiments rather than patient-based clinical studies; 3) HRs and 95% CI were not directly provided in the study; 4) Research was not published in English; 5) Sample size was too small, less than 50; 6) IDO expression was not detected in tumor tissues.

 

The data extraction included in the studies were independently completed by two researchers according to the same criteria, and if there was inconsistency, a group discussion was conducted. This meta-analysis used two outcome endpoints: OS (overall survival) and TTP (time to tumor progression). Since PFS, DFS and RFS are similar outcome endpoints, we in this meta-analysis used the same prognostic parameter TTP to represent them. We extracted the following information from each study: first author’s name, publication year, country, cancer type, case number, study type, IDO detection method, cut off values for IDO expression, endpoints and HR. When the study provided HR for both univariate and multivariate analyses, we preferred results from multivariate analysis. The main features for these eligible studies are summarized in fig 1. Quality assessment for the included studies using the Newcastle-Ottawa Scale (NOS)[13]. According to the NOS system, the quality judgment for the studies were based on three parts: selection of study groups (4 points), comparability of study groups (2points), and outcome assessment (3 points). Studies with NOS scores above 5 were considered to have higher quality.

 

Combined HR and 95% CI were used to assess the effect of IDO expression on tumor prognosis. HR>1 and 95% CI did not overlap 1 indicating that overexpression of IDO had a negative impact on tumor prognosis. Heterogeneity analysis using the Q test, and P < 0.1 was considered statistically significant. The heterogeneity was evaluated according to I2. When I2 was 0%-50%, it showed no or moderate heterogeneity, and when I2>50%, it showed significant heterogeneity. According to the I2 and P values, different effect models were used. When I2>50%, or P<0.1, a random effects model was used. Otherwise we used a fixed effect model when the heterogeneity was low or there was no heterogeneity. Begg's test and Egger's test were used to determine if there was a potential publication bias in the selected studies. Sensitivity analysis was used to assesse the stability of results by excluding one study at a time. All statistical analysis and data generation were done using STATA software (StataMP 14, USA).

3. Results

Figure 1 shows our literature search and screening strategy. After removing 613 duplicate studies, a total of 4739 studies were further explored for the title and abstract. A total of 4,657 studies were excluded due to non-conformity or irrelevant topics. 82 studies conducted further full-text evaluations, 35 of which were excluded due to lack of HR information on HR and 95%Cl, 16 studies were excluded because of detected IDO levels in the serum. Therefore, the final 31 studies included a total of 3939 patients for meta-analysis to analyze the association between IDO expression and prognosis in solid tumor patients [14-44].

The 31 studies included in this meta-analysis were derived from 10 countries, 6 studies originating from Europe (respectively from Belgium, Netherlands, Poland, Croatia and Germany), 18 from Asia (10 from China; and 8 from Japan), 2 from Africa (Tunisia), 3 from USA, 2 from Australia. All of these studies were published between 2006 and 2019. As for the cancer types, among the studies, esophageal cancer was the most common type of cancer (n=4), followed by endometrial cancer, colorectal cancer, melanoma, and vulvar squamous cell carcinoma (n=2). Other tumor types were involved in one study each. Since PFS, DFS and RFS are similar outcome endpoints, we used TTP to represent them in this meta-analysis. In these studies, 3 studies used polymerase chain reaction (qRT-PCR) to detect IDO expression in tumor tissues, while the other 28 studies used immunohistochemistry (IHC) staining to detect IDO expression. 28 datasets had information on OS, and 14 had information on TTP (PFS /DFS). According to NOS tool, we systematically evaluated the quality of the included studies, and all of these studies had high quality and the NOS scores were between 6-9 points. (Table 1).

 

In the included studies, a total of 28 studies analyzed the association between IDO expression and OS. Of these 28 studies, 3 studies with HR <1 [38, 39, 41], and 18 studies with HR> 2[14-16, 18-22, 24, 27, 29, 30, 33, 34, 37, 42-44]. We performed a meta-analysis of 28 studies. Since I2 values was 81.1%, the random effects model was used to calculate the pooled HR and 95% CI. The combined analysis of 28 datasets indicated that compared with IDO negative/low expression, IDO positivity/high expression was highly correlated with poor prognosis in cancer patients (pooled HR 1.92, 95% CI 1.52–2.43, P<0.001) (Fig. 2). A total of 14 studies were used to assess the association between IDO expression and TTP. We calculated the pooled HR using a random effects model, because the heterogeneity test indicated an I2 value of 54.8% and a P value of 0.007. The results indicated that high expression of IDO was highly correlated with poor prognosis of TTP (pooled HR = 2.25, 95% CI 1.58–3.22, P<0.001) (Fig. 3).

 

Since the results from the meta-analysis indicated significant heterogeneity, we performed heterogeneity analysis in order to identify potential factors that may cause heterogeneity. We classified the included studies and performed heterogeneity analysis based on study location, detection method, sample size, study type, cancer type, age and follow-up periods. Subgroup analysis showed that the high expression of IDO was highly correlated with poor OS and TTP, but the heterogeneity was not significantly reduced according to different study locations, detection method, sample size grouping, and average age. However, in a prospective study group, we found that high expression of IDO was highly correlated with poor OS prognosis (HR1.98, 95% CI 1.57-2.49, P<0.001) and there was no heterogeneity (I2 = 0%, P = 0.6) (Table 2). Subgroup analysis showed that there was no heterogeneity among bladder cancer, colorectal cancer, endometrial cancer and esophageal cancer studies. Heterogeneity was also significantly reduced among studies of the same type of tumor, such as digestive system tumors and reproductive system tumors (Table 2). In addition, there was no significant heterogeneity (HR 3.41, 95% CI 2.41-4.83, P<0.001. I2 = 0%, P = 0.97) between studies with an average follow-up period of more than 45 months (Table 2).

 

Evaluation of publication bias between studies was done using Begg's funnel plot and Egger's test. The shape of the OS and TTP funnel plots were not significantly asymmetrical, and the Egger's test indicated OS (P=0.47) and TTP (P=0.89). These results suggested that there was no significant publication bias in the meta-analysis of IDO expression in relation to OS and TTP prognosis (Fig. 4). Sensitivity analysis refers to the removal of a study each time to analyze the impact of individual studies on the stability of meta-analysis results. Sensitivity analysis showed that no single study had a significant impact on the conclusions of this meta-analysis (Fig. 5).

4. Discussions

In this study, we systematically assessed IDO expression level and prognostic indicators of 3939 solid tumor patients from 31 different studies. Our results showed that high expression of IDO predicted poor OS and TTP in cancer patients. However, the results from this meta-analysis indicated that there was significant heterogeneity between these studies. The Begg's funnel plot and Egger's test showed that there was no significant publication bias in this meta-analysis, and the sensitivity analysis showed that no single study can influence the conclusion of this meta-analysis.

 

High expression of IDO was highly correlated with poor prognosis of OS and TTP. However, the heterogeneity was also obvious. It was not difficult to understand that there will be heterogeneity in our study. In 31 studies, a total of 10 tumor types were included, and the role of IDO in different tumors may be inconsistent. For example, three studies have concluded to the contrary. In addition, the study type, IDO test method, number of patients included, follow-up period, and study quality were different in each study, all these factors can lead to heterogeneity. To this end, we performed a subgroup analysis to explore the source of heterogeneity. Subgroup analysis showed that the study location, sample size, and age were not sources of heterogeneity. For OS, no heterogeneity in prospective studies and follow-up period over 45 months studies. These results indicate that the type of study and follow-up period were the reasons for the heterogeneity in this meta-analysis. In addition, in the same type of tumor research (such as digestive system tumors and reproductive system tumors), there was no obvious heterogeneity. Subgroup analysis also showed no heterogeneity in bladder cancer, colorectal cancer, endometrial cancer and esophageal cancer, gastric cancer and vulvar squamous cell carcinoma studies. This meta-analysis included 10 studies of different types of tumors, and the merger between studies of different tumor types also led to heterogeneity.

 

Our study further enhanced the view that high expression of IDO has a poor prognosis for cancer patients by performing meta-analysis on a large number of research data. In addition, this meta-analysis also gives hints on several other aspects. First, the high expression of IDO may be a universal prognostic biomarker for solid tumors. We analyzed 10 different types of solid tumors, including colorectal cancer, endometrial cancer, renal cell carcinoma, hepatocellular carcinoma, etc. Secondly, we verified that both Asian patients and other country patients harboring high expression of IDO were highly correlated with poor prognosis in patients with solid tumors, which did not vary because of ethnic differences. Moreover, our results suggested that the IDO expression can be used as a more widely prognostic biomarker. Finally, this study suggested that IDO had the potential to develop into a prognostic biomarker and a therapeutic target for solid tumors.

 

It should be noted that, there were limitations in this meta-analysis. First, the definitions of IDO positive and high expression were not completely consistent between studies, which may cause heterogeneity between studies. Secondly, due to limitations from the other included studies and large number of tumor types, we were unable to perform a subgroup analysis for each type of tumor. Thirdly, we extracted the HRs data directly from the original literature, and these data were reliable than calculated HRs indirectly deducted from the literature. However, some studies did not provide complete data and were excluded from statistics, hence some missing information might have reduced the power of IDO as a prognostic biomarker in solid tumor patients.

5. Conclusions

In summary, this meta-analysis clearly demonstrated that the high expression of IDO in tumor tissues was closely related to poor survival of tumor patients. Our study suggested that IDO may be used as a potential tumor prognostic biomarker and tumor treatment target.

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Abbreviations

IDO: Indoleamine 2,3-dioxygenase

OS: Overall survival

TTP: Time to progression

HR: Hazard ratio

CI: Confidence interval

Tregs: Regulatory T-cells

1-MT: 1-methyltryptophan

DSS: Disease-specific survival

RFS: Relapse-free survival

DFS: Disease-free survival

TTR: Time to recurrence

NOS: Newcastle-Ottawa Scale

Declarations

Ethics approval and consent to participate

This research work constitutes a meta-analysis of published data and does

not include any studies with human participants or animals performed by

any of the authors. Hence, no informed consent was required to perform this

study.

 

Consent for publication

Not applicable.

 

Availability of data and materials

Not applicable.

 

Competing interests

The authors declare that they have no competing interests.

 

Funding

This work is supported by the National Natural Science Foundation (81601765, 81572074) and Jiangsu Province Postdoctoral Science Foundation (1601155B),including the design of the study and collection, analysis, and interpretation of data and in writing the manuscript

 

Authors’ contributions

SW, HS and JJW conceived of the idea, designed the study, defined the search

strategy and selection criteria, and were the major contributors in writing

the manuscript. SW and JW performed the literature search and the analyses.

All the authors contributed to the writing and editing of the manuscript. All

authors read and approved the final manuscript, and ensured that this is the

case.

 

Acknowledgements

Not applicable.

Tables

Table 1 Characteristics of the patients included in the meta-analysis.

Study

Year

Country

Cancer type

Case (n)

Age (Median/Mean, years)

Tumor stage

(I/II/III/IV)

Follow-up (Median/Mean, months)

Study type

Method

Cut off value

Endpoints

NOS

Gerald. et al

2006

Austria

Colorectal cancer

143

NA

29/24/78/12

51.8a

Retrospective

IHC

High expression: score (5-12)

Low expression: score (0-4)

OS

8

K. et al

2006

Japan

Endometrial cancer

80

57.2a

54/10/10/6

71.6b

Retrospective

IHC

High expression: score (4-6)

Low expression: score (0-3)

OS, PFS

8

Rainer. et al

2007

Japan

Renal cell carcinoma

55

NA

22/33

NA

Retrospective

qPCR

High expression: Above the 80th percentile

OS

6

Ke. et al

2008

China

Hepatocellular carcinoma

138

NA

NA

NA

Retrospective

IHC

High expression: score (5-9)

Low expression: score (0-4)

OS

8

Kazuhiko. et al

2008

Japan

Endometrial Cancer

65

57.7a

44/6/9/6

72b

Retrospective

IHC

High expression: score (4-5)

Low expression: score (0-3)

OS, PFS

8

Hiroshi. et al

2009

Japan

Osteosarcoma

47

15b

0/47/0/0

67.4b

Retrospective

IHC

High expression: score (4)

Low expression: score (0-3)

OS

7

Tomoko. et al

2010

Japan

Cervical cancer

112

NA

67/45/0/0

NA

Retrospective

IHC

High expression: >50% of tumor cells were stained

OS, PFS

7

Jacek. et al

2011

Poland

Vulvar squamous cell carcinoma

76

69.5b

NA

51.23b

Retrospective

IHC

>50% of tumor cells were stained with clusters of higher intensity of expression

OS

8

Reinhart. et al

2011

Belgium

Melanoma

116

52b

NA

71b

Prospective

IHC

Almost none/weak versus strong IDO expression

OS, PFS

9

Renske. et al

2012

Netherland

Endometrial carcinoma

355

64b

196/58/77/44

63.6b

Prospective

IHC

High expression: score (4-6)

Low expression: score (0-3)

DFS

8

Jin. et al

2013

China

Laryngeal squamous cell carcinoma

187

52.4b

20/58/88/21

48.56a

Retrospective

IHC

High expression: score (3-4)

Low expression: score (0-2)

OS, DFS

9

Yunlong. et al

2015

China

Esophageal squamous cell cancer

196

54b

113(I–II)/83(III–IV)

NA

Prospective

IHC

High expression: score (5-12)

Low expression: score (0-4)

OS

8

Maciej. et al

2015

Poland

Melanoma

48

56.9b

NA

30.3b

Retrospective

IHC

High expression: score > 47.39 Low expression: score 47.39

OS

6

Ahlem. et al

2016

Tunisia

Nasopharyngeal carcinoma

71

NA

10(I–II)/53(III–IV)

30b

Prospective

IHC

High expression: score (4-5)

Low expression: score (0-3)

OS, PFS

7

Hao. et al

2016

China

Gastric adenocarcinoma

357

60.3a

80/79/198/0

41b

Retrospective

IHC

With the X-tile software, the cut-off point was 282, 51% patients were separated into the IDO high expression subgroup

OS

7

Tao. et al

2017

China

Pancreatic cancer

80

NA

10(I–II)/53(III–IV)

40b

Prospective

IHC

High expression: score (>4)

Low expression: score (4)

OS

8

Tvrtko. et al

2017

Croatia

Bladder carcinomas

74

65.3a

NA

NA

Prospective

qPCR

IDO-positive group, in which expression of IDO gene was detected, regardless of the level of expression.

OS

7

Daniel. et al

2017

USA

Breast cancer

362

NA

278(I–II)/63(III–IV)

NA

Retrospective

IHC

Median cut-point was used to stratify IDO1 scores in low and high statuses.

OS

8

Lijie. et al

2017

USA

Glioblastoma

148

NA

NA

NA

Prospective

qPCR

IDO1 mRNA levels were stratified into IDO1- low and -high expressing groups based on the determined cutoff values.

OS

8

Wenjuan. et al

2018

China

Colorectal cancer

95

NA

NA

NA

Retrospective

IHC

High expression: score (2-3)

Low expression: score (0-1)

OS

7

Yufeng. et al

2018

Taiwan (China)

Thymic carcinoma

69

54a

1/3/45/20

46b

Retrospective

IHC

High expression: score (2-3)

Low expression: score (0-1)

OS, PFS

8

Hiroto. et al

2018

Japan

Esophageal cancer

182

66.5a

69/63/41/9

NA

Retrospective

IHC

High expression: score (2-3)

Low expression: score (0-1)

RFS

7

Yuki. et al

2018

Japan

Esophageal Cancer

305

66a

123/80/102/0

44.4b

Prospective

IHC

(0; no expression, 1; weak expression, 2; moderate expression or 3; strong expression)

OS

9

Masaaki. et al

2018

Japan

Gastric Cancer

60

67.8a

0/0/60/0

41a

Retrospective

IHC

A total score of greater than 4+ was defined as IDO positive expression

OS, DFS

8

Tamkin. et al

2019

Australia

Malignant pleural

mesothelioma

67

65b

NA

NA

Retrospective

IHC

Negative

Positive (> 0%)

OS

7

Wenjuan. et al

2019

China

Adenosquamous Lung Carcinoma

183

58b

52/41/71/19

NA

Retrospective

IHC

High- and low-expression based on the determined cutoff values.

OS

8

Devarati. et al

2019

USA

Anal cancer

63

61b

7/24/9/21(2 unknown)

35b

Retrospective

IHC

Positive (>50% IDO1 expression)

OS

8

Julia. et al

2019

Germany

Rectal cancer

91

64b

NA

NA

Retrospective

IHC

High expression: score (3-6)

Low expression: score (0-2)

OS, DFS

8

Nadia. et al

2019

Tunisia

Vulvar squamous cell

carcinoma

61

65.61a

29/4/26/2

NA

Retrospective

IHC

High expression: score (3)

Low expression: score (0-2)

OS, DFS

7

Sha. et al

2019

China

Esophageal squamous cell carcinoma

158

56b

0/34/124/0

40.2b

Retrospective

IHC

Positive (>50% IDO1 expression)

RFS

8

Yuhshyan. et al

2019

Taiwan (China)

Bladder cancer

108

68a

45/43/19/1

45b

Retrospective

IHC

Strongly Positive (>25% IDO1 expression)

OS, PFS

8

Abbreviations: IHC: Immunohistochemistry; qPCR: Quantitative Real Time Polymerase Chain Reaction; NOS: Newcastle-Ottawa Scale; OS: overall survival; DFS: disease free survival; PFS: progression free survival. a Mean, b Median. NA: Not Available.

 

Table 2 Hazard ratio for the association between IDO overexpression and solid tumors prognosis.

Stratified analysis

Effect size

NO. of study

Cases

HR

Heterogeneity

Pooled HR (95% CI)

P value

I2 (%)

p value

All studies

OS

OS

28

3457

1.92 (1.52-2.43)

<0.001

81.1

<0.001

TTP

TTP

14

1815

2.25 (1.58-3.22)

<0.001

54.8

0.007

Study location

Asia

OS

16

2137

2.12 (1.54-2.92)

<0.001

68.5

<0.001

TTP

9

1121

2.48 (1.74-3.55)

<0.001

11.4

0.342

Other countries

OS

12

1320

1.66 (1.17-2.37)

0.005

82.2

<0.001

TTP

5

694

1.99 (1.32-2.98)

0.001

14.3

0.323

Detection method

IHC

OS

25

3180

1.86 (1.46-2.38)

<0.001

81.3

<0.001

TTP

14

1815

2.25 (1.58-3.22)

<0.001

54.8

0.007

qPCR

OS

3

277

2.11 (1.42-3.13)

<0.001

17.7

0.297

Sample size

<70

OS

9

535

2.25 (1.31-3.88)

0.003

75.5

<0.001

TTP

4

255

2.49 (1.51-4.10)

<0.001

0.0

0.72

70-120

OS

10

903

2.37 (1.42-3.95)

0.001

55.9

0.02

TTP

6

578

2.43 (1.09-5.44)

0.03

72.8

0.003

>140

OS

9

2019

1.60 (1.18-2.18)

0.003

75.8

<0.001

TTP

4

882

1.98 (1.12-3.51)

0.019

63.2

0.043

Study type

 

 

 

 

 

 

 

Retrospective

OS

21

2807

1.82 (1.39-2.40)

<0.001

81.5

<0.001

TTP

11

1273

2.32 (1.50-3.60)

<0.001

57.9

0.008

Prospective

OS

7

650

1.98 (1.57-2.49)

<0.001

0

0.6

TTP

3

542

2.09 (1.03-4.23)

0.04

56.2

0.102

Cancer type

 

 

 

 

 

 

 

Digestive system tumor

OS

10

1528

1.79 (1.38-2.31)

<0.001

40.8

0.085

Reproductive system tumor

OS

6

756

2.39 (1.53-3.72)

<0.001

34.9

0.175

Bladder cancer

OS

2

182

2.90 (1.32-6.15)

0.006

0.0

0.521

Colorectal cancer

OS

2

238

2.32 (1.22-4.42)

0.01

0.0

0.655

Endometrial cancer

OS

2

145

6.64 (1.41-31.27)

0.017

0.0

0.99

Esophageal cancer

OS

2

501

1.76 (1.28-2.43)

0.001

0.0

0.79

Esophageal cancer

TTP

2

340

2.23 (0.91-5.49)

0.081

77.9

0.033

Gastric Cancer

OS

2

417

1.68 (1.22-2.32)

0.001

1.5

0.314

Melanoma

OS

2

164

1.95 (0.45-8.49)

0.376

84.8

0.01

Vulvar squamous cell carcinoma

OS

2

137

2.92 (1.69-5.04)

<0.001

0.0

0.69

Age (Mean/Median)

 

 

 

 

 

 

 

<60 years

OS

9

991

2.02 (1.22-3.36)

0.007

83.6

<0.001

>60 years

OS

10

1262

1.76 (1.16-2.67)

0.008

68.8

0.001

Follow-up (Median/Mean)

 

 

 

 

 

 

 

45 months

OS

8

1092

1.90 (1.29-2.78)

0.001

79.4

<0.001

>45 months

OS

8

783

3.41 (2.41-4.83)

<0.001

0.0

0.97

Abbreviations: HR: hazard ratio; CI: confidence interval; OS: overall survival; TTP: time to tumor progression. IHC: Immunohistochemistry; qPCR: Quantitative Real Time Polymerase Chain Reaction.