- Research article
- Open Access
- Open Peer Review
Meta-analysis of the prognostic and clinical value of tumor-associated macrophages in adult classical Hodgkin lymphoma
- Baoping Guo1,
- Hong Cen1Email author,
- Xiaohong Tan1 and
- Qing Ke1
- Received: 17 June 2016
- Accepted: 4 October 2016
- Published: 17 October 2016
Abstract
Background
The prognostic significance of tumor-associated macrophages (TAM) in adult classical Hodgkin lymphoma (cHL) remains controversial. Here, we report a meta-analysis of the association of CD68 and CD163 infiltration on the clinical outcome of adult cHL.
Methods
A comprehensive search to identify relevant articles was performed in PubMed, Embase, and Google Scholar on January 31, 2016. Using the fixed effect or random effects model of DerSimonian and Laird, hazard ratios (HR) or odds ratios (OR) with 95 % confidence intervals (CIs) were used as the effect size estimate.
Results
Twenty-two eligible studies with a total of 2959 patients were identified. Our analysis indicated that a high density of CD68+ TAMs in the tumor microenvironment of adult cHL predicted poor overall survival (OS) (HR: 2.41; 95 % CI, 1.92–3.03), shorter progression-free survival (PFS) (HR: 1.78; 95 % CI, 1.45–2.18), and poor disease-specific survival (HR: 2.71; 95 % CI, 1.38–5.29). High density of CD163+ TAMs in the tumor microenvironment of adult cHL also predicted poor OS (HR: 2.75; 95 % CI, 1.58–4.78) and poor PFS (HR: 1.66; 95 % CI, 1.22–2.27). In addition, we demonstrated that a high density of either CD68+ or CD163+ TAMs was associated with the presence of Epstein-Barr virus in neoplastic cells (ORCD68: 3.13; 95 % CI, 2.02–4.84; ORCD163: 2.88; 95 % CI, 1.55–5.34). A high density of either CD68+ or CD163+ TAMs tend to be associated with a more advanced clinical stage (ORCD68: 1.25; 95 % CI, 0.93–1.67; OR CD163: 1.19; 95 % CI, 0.86–1.63), B-symptoms (ORCD68: 1.35; 95 % CI, 0.90–2.01; ORCD163: 2.19; 95 % CI, 0.96–5.03), higher International Prognostic Factors Project Score (ORCD68: 1.20; 95 % CI, 0.67–2.15; ORCD163: 2.00; 95 % CI, 0.92–4.35), and bulky disease (ORCD68: 1.47; 95 % CI, 0.88–2.47; ORCD163: 1.19; 95 % CI, 0.72–1.96).
Conclusions
Our analyses suggest that a high density of either CD68+ or CD163+ TAMs is a robust predictor of adverse outcomes in adult cHL. Increased TAMs should be taken into account to further improve prognostic stratification and the planning of appropriate therapeutic strategies.
Keywords
- Tumor-associated macrophages
- Classical Hodgkin lymphoma
- Meta-analysis
Background
Classical Hodgkin lymphoma (cHL) carries an excellent prognosis for most patients, with more than 80 % of patients experiencing long-term remission following conventional chemotherapy or radiotherapy-based protocols [1–3]. However, approximately 20 % of patients experience relapse or disease that is refractory to all conventional therapies, and many patients may suffer short- and long-term treatment-related complications [4–6]. The International Prognostic Factors Project Score (IPS) is the most widely used prognostic system; however, it is rarely employed to modify treatment [7, 8]. Robust prognostic indicators are thus needed to better risk-stratify patients at diagnosis.
cHL is unique among the lymphomas because malignant cells are heavily outnumbered by reactive cells in the tumor microenvironment, such as macrophages, T cells, B cells, eosinophils, mast cells, and other stromal elements. In an adult cHL microenvironment, malignant Hodgkin-Reed-Sternberg cells express a variety of cytokines and chemokines. This is thought to be the driving force behind an abnormal immune response, perpetuated by additional factors secreted by recruited reactive cells in the microenvironment [9]. Steidl et al. [10] were the first to show, by gene expression profiling followed by immunohistochemistry assay, that the quantity of tumor-associated macrophages (TAMs) predicts progression-free survival (PFS). However, most studies that used various antibodies to stain TAMs were inconclusive regarding the association of CD68+ and CD163+ TAM density and survival. Some studies have indicated that a high density of either CD68+ or CD163+ TAMs in the tumor microenvironment of adult cHL is associated with poorer outcomes [10–22]. Other studies have not confirmed this finding [23–31], and using TAMs as a biomarker to risk-stratify patients remains controversial.
The objective of this study was to evaluate the prognostic significance of elevated density of CD68+ and CD163+ TAMs in the tumor microenvironment on overall survival (OS) and PFS in patients with adult cHL. In addition, the relationship between CD68+ and CD163+ TAMs in the tumor microenvironment of adult cHL and other clinical characteristics was also examined.
Methods
The present meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement [32].
Literature search
We performed a systematic electronic search in PubMed, Embase, and Google scholar for articles published before January 31, 2016. We identified studies by using Medical Subject Heading (MeSH) terms and corresponding keywords, including “macrophages”, “tumor-associated macrophage”, “tumor-infiltrating macrophage”, “intratumoral macrophage”, “TAMs”, “Hodgkin disease”, “classical Hodgkin lymphoma”. No language restriction was applied. We also manually checked the bibliographies of previous reviews and references in all selected studies. Investigators were contacted and asked to supply additional data when key information relevant to the meta-analysis was missing.
Selection criteria
Studies were included if they (1) were prospective or retrospective cohort studies or clinical trials; (2) contained immunochemistry data used to evaluate TAM by anti-CD68 or anti-CD163; (3) were studies that involved patients with a proven diagnosis of cHL performed to investigate the correlation of CD68+ and CD163+ TAM density and survival; or (4) tumor-associated macrophages in adult cHL were described as high (above the cut-off value) and low (below the cut-off value) density. Studies were excluded if they were (1) review articles, case reports, animal or in vitro studies; or (2) analyzing pediatric patients or serum CD68 or CD163 samples.
Study selection, data extraction, and end points
Two investigators (BPG and HC) independently selected articles and extracted data from eligible studies. Disagreements were resolved by consensus. Baseline characteristics and outcomes were extracted from the selected articles. Information taken from each study included the name of the first author, year of publication, country, number of patients, stage, sex, treatment, WHO subtype, Epstein-Barr virus (EBV) status, antibodies, thresholds, median follow-up, and outcome correlation. In situ hybridization (ISH) analysis for EBV-encoded RNA (EBER) was performed in all included studies. Among the included studies, there were six studies using a follow-up time of less than 5 years [13, 16, 23, 26, 27, 29]. We chose OS and PFS as endpoints for our meta-analysis. Various endpoints for PFS were reported in the selected studies, including event-free survival (EFS [12, 14, 18, 19, 22]) and failure-free survival (FFS) [15]. As PFS, EFS, and FFS had a similar definition in these articles, we operationally defined PFS to include EFS or FFS for studies that did not provide PFS.
Quality assessment
The Newcastle-Ottawa Scale (NOS) was used to assess the quality of each individual study; this was performed independently by two authors (BPG and XHT). The NOS comprises three quality parameters: selection (0–4 points), comparability (0–2 points), and outcome assessment (0–3 points). Studies with NOS scores of ≥ 6 were determined to be high-quality [33].
Statistical analysis
The primary outcome was survival in patients with a high density of either CD68+ or CD163+ TAMs compared to those with a low density of CD68+ or CD163+ TAMs. The cut-off value for “high versus low” CD68+ or CD163+ TAM density was determined by the investigators in each study. Hazard ratios (HRs) with 95 % confidence intervals (CIs) were combined to obtain an effective value. For studies in which HRs and CIs were not available, we used the method proposed by Parmar et al. [34] to derive estimates from survival curves. An HR > 1 indicated poor survival in the group with high CD68+ or CD163+ TAM density.
For the pooled analysis of the relationship between high CD68+ or CD163+ TAM density and EBV status or other clinical parameters (such as stage), odds ratios (OR) and their 95 % CIs were combined to give the effective value. An OR > 1 indicated a higher probability that EBV was present and advanced stage in the group with high CD68+ or CD163+ TAM density. The point estimate of the HR or OR was considered statistically significant at the P < 0.05 level if the 95 % CI did not include the value 1. Heterogeneity was assessed by the χ2 test and expressed as I 2 index [35], which describes the percentage of total variation across studies due to heterogeneity rather than chance (25 % low heterogeneity, 50 % medium, 75 % high). If heterogeneity existed between primary studies, a random effects model was used. Otherwise, a fixed effects model was used in meta-analysis [36]. If results of both univariate and multivariate Cox regression analyses were reported, multivariate models were used for a more accurate estimate of the effect of CD68 or CD163 expression. Begg’s test [37] and Egger’s test [38] were used to detect possible publication bias. All analyses were carried out using STATA statistical software package version 12.0 (STATA, College Station, TX).
Results
Selection and characteristics of studies
Flow diagram of the systematic review and meta-analysis process
Characteristics of studies included in the meta-analysis
Study, Year | Country | Number of subjects | Stage | Treatment, n (%) | WHO subtypes, n (%) | Hodgkin-Reed-Sternberg EBV status, n (%) | Antibodies (clone) | Scoring | Threshold(s) | Follow-up median (range) & mean (range) (in years) | Outcome correlation |
|---|---|---|---|---|---|---|---|---|---|---|---|
Steidl et al., 2010 [10] | Canada | 166 | Limited/advanced | ABVD ± RT 165 (99), RT alone 1 (1) | NS 140 (84), MC 11 (7), Others 5 (3), NOS 10 (6) | Neg 137 (84), Pos 27 (16) | CD68 (KP1) | Visual estimation | 5 %, 25 % | 4.0 (0.5–20.8) | CD68, adverse (PFS, DSS) |
Tzankov et al., 2010 [11] | Switzerland | 105 | Limited/advanced | ABVD ± RT 30 (28), COPP ± RT 48 (46), RT alone 27 (26) | NS 60 (57), MC 32 (30), Others 5 (5), NOS 8 (8) | Neg 85 (81), Pos 20 (19) | CD68 (PGM1) | Visual, cell counting | 0.82 % | 11.8 (1.0–27.6) | CD68, adverse (OS) |
Kamper et al., 2011 [12] | Denmark | 288 | Limited/advanced | ABVD/COPP ± RT, ABVD ± RT, RT alone | NS 237 (82), MC 47 (16), NOS 4 (1) | Neg 193 (67), Pos 95 (33) | CD68 (KP1), CD163 (10D6) | Computer-assisted point counting | 7.8 % (CD68), 21.1 % (CD163) | 7.0 (0.2–18.6) | CD68, adverse (EFS, OS); CD163, adverse (EFS, OS) |
Hohaus et al., 2011 [13] | Italy | 93 | Limited/advanced | ABVD ± RT 55 (59), BEACOPP ± RT 32 (34), MOPP/Other ± RT 6 (7) | NS 64 (69), MC 4 (4), Other 6 (8), NOS 19 (20) | Neg 37 (69), Pos 17 (31) | CD68 (PGM1) | Visual estimation | 5 % | 1.1 (0.1–6.8) | CD68, adverse (PFS) |
Zaki et al., 2011 [23] | Japan | 82 | Limited/advanced | ABVD ± RT, RT alone | NS 20 (24), MC 52 (63), Other 10 (12) | NR | CD68 (PGM1), CD163 (10D6) | Visual, cell counting in 0.146 mm2 | Median (CD68), Median (CD163) | Mean: 4.0 (0.8–9.6) | CD68, NSS (OS); CD163, adverse (OS) |
Azambuja et al., 2012 [24] | USA | 265 | Limited/advanced | ABVD ± RT 265 (100) | NS 180 (68), MC 52 (20), Others 18 (6), NOS 15 (6) | Neg 122 (58), Pos 87 (42) | CD68 (KP1), CD163 (10D6) | Visual estimation | 5 %, 25 % (CD68), 5 %, 25 % (CD163) | 6 (1.5–11.7) | CD68, NSS (PFS, DSS); CD163, NSS (PFS, DSS) |
Yoon et al., 2012 [14] | South Korea | 144 | Limited/advanced | ABVD 113 (79), C-MOPP 10 (7), ABVD/C-MOPP hybrid 15 (10), BEACOPP 6 (4) | NS 90 (63), MC 34 (24), Others 11 (7), NOS 9(6) | Neg 66 (46), Pos 78 (54) | CD68 (KP1), CD163 (10D6) | Visual estimation | 20 % (CD68), 20 % (CD163) | 5.4 (0.7–19.0) | CD68, adverse (EFS, OS); CD163, adverse (EFS, OS) |
Tan et al., 2012 [15] | Canada | 287 | Advanced | ABVD ± RT 144 (50), Stanford V ± RT 143 (50) | NS 223 (78), MC 38 (13), Others 9 (3), NOS 17(6) | Neg 238 (83), Pos 49 (17) | CD68 (KP1), CD163 (10D6) | Computer-assisted image analysis | 12.7 % (CD68), 16.8 % (CD163) | 5.5 | CD63, adverse (FFS, OS); CD163, adverse (FFS, OS) |
Sanchez-Espiridion et al., 2012 [31] | USA | 103 | Advanced | NR | NS 74 (73), MC 22 (22), Others 6 (6) | NR | CD68 (KP1 and PGM1), CD163 (10D6) | Computer-assisted point counting | 5 %, 25 %, median (CD68), 5 %, 25 %, median (CD163) | NR | CD68, NSS (FFS, OS); CD163, NSS (FFS, OS) |
Abdou et al., 2013 [16] | Egypt | 61 | Limited/advanced | Chemotherapy | NS 33 (54), MC 20 (33), Others 8 (13) | NR | CD68 (KP1) | Visual, cell counting | 40 % (CD68) | Mean: 1.2 ± 1.7 | CD68, adverse (OS) |
Greaves et al., 2013 [17] | United Kingdom | 122 | Limited/advanced | Anthracycline-based ± RT 56 (46), Alkalator-based ± RT 52 (43), RT alone 14 (11) | NS 93 (78), MC 25 (20), Others 2 (2) | Neg 84 (69), Pos 38 (31) | CD68 (KP1) | Computer-assisted image analysis | 5 %, 15 % | 16.5 (2–40) | CD68, adverse (FFTF, OS) across the 3 defined groups |
Deau et al., 2013 [25] | France | 59 | Limited/advanced | ABVD 47 (80), EBVP 8 (14), BEACOPP 3 (5) | NS 54 (92), Non-NS 5 (8) | NR | CD68 (KP1) | Visual estimation | 25 % | NR | CD68, adverse (PFS); CD68, NSS (OS) |
Panico et al., 2015 [26] | Italy | 121 | Limited/advanced | ABVD ± RT 101 (83), ABVD-like ± RT 20 (17) | NS 73 (60), MC 40 (33), Others 8 (7) | NR | CD68 (KP1) | Visual, cell counting | 30 per 0.023 mm2 | Mean: 3.5 (0.1–9.3) | CD68, adverse (OS); CD68, NSS(PFS) |
Casulo et al., 2013 [18] | USA | 81 | Limited/advanced | ABVD 38 (47), Stanford V 11(13), ABVD/MOPP 16 (20), others 16 (20) | NR | NR | CD68 (KP1) | Computer-assisted image analysis | 30 % | 8.8 | CD68, adverse (OS) |
Koh et al., 2014 [19] | South Korea | 116 | Limited/advanced | ABVD ± RT 116 (100) | NS 78 (67), MC 22 (19), Others 8 (7), NOS 8 (7) | Neg 73 (63), Pos 43 (37) | CD68 (KP1), CD163 (10D6) | Visual estimation | 20 % (CD68), 20 % (CD163) | 6.2 (3.8–10.3) | CD68, adverse (EFS, DSS, OS); CD163, adverse (EFS, DSS, OS) |
Ping et al., 2014 [27] | China | 72 | Limited/advanced | ABVD 49(68), BEACOPP 13(18), others 10 (14) | NS 41(57), MC 23 (32), Others 8 (11) | NR | CD68 (KP1) | Visual estimation | 250/HPF | 3.9 (0.7–15) | CD68, NSS (OS); |
Klein et al., 2014 [28] | USA | 88 | Limited/advanced | ABVD ± RT 88 (100) | NS 55 (63), MC 6 (7), Others 1 (1), NOS 19 (22) | NR | CD68 (KP1), CD163 (10D6) | Visual estimation | 5 %, 25 % (CD68), 5 %, 25 % (CD163) | NR | CD68, NSS (OS); CD163, adverse (OS) 25 % threshold |
Touati et al., 2014 [20] | France | 158 | Limited/advanced | ABVD 102(65), ABVD/MOPP 26 (17), BEACOPP 11 (7), ABVD-like 9 (5), others 10 (6) | NS 130 (82), MC 21 (13), Others 7 (5) | Neg 106 (67), Pos 40 (25), Not done 12 (8) | CD68 (PGM1) | Visual estimation | 25 % | 5.5 (0.2–16.2) | CD68, adverse (PFS, OS) |
Kayal et al., 2014 [30] | India | 100 | Limited/advanced | ABVD ± RT 88 (88), EVAP RT 11 (11), Other 1 (1) | NS 51 (51), MC 47 (47), Others 2 (2) | NR | CD68 (CD68/G2) | Visual, cell counting | 12.9 %, 18.2 %, 25 % (the quartiles) | 5.7 | CD68, NSS (PFS, DSS) |
Agur et al., 2015 [29] | Israel | 98 | Limited/advanced | ABVD 60(60), BEACOPP 29(29), others 9 (1) | NS 33 (34), MC 7 (7), Others 58 (59) | NR | CD68 (PGM1) | Visual, cell counting | 25 % | Mean: 3.8 (0.9–7.8) | CD68, NSS (PFS) |
Moreno et al., 2015 [21] | Spain | 249 | Advanced | NR | NS 162 (65), MC 68 (27), Others 19 (8) | NR | CD68 (PGM1), CD163 (10D6) | Computer-assisted point counting | 30 % | NR | CD68, adverse (OS) |
Jakovic et al., 2016 [22] | Serbia | 101 | Advanced | ABVD ± RT 101 (100) | NS 80 (79), MC 13 (13), Others 8 (8) | NR | CD68 (PGM1) | Visual estimation | 25 % | 8.6 (0.2–16) | CD68, adverse (EFS, OS) |
Assessment of the risk of bias in each cohort study using the Newcastle–Ottawa scale
Study | Selection (0–4) | Comparability (0–2) | Outcome (0–3) | Total | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
REC | SNEC | AE | DO | SC | AF | AO | FU | AFU | ||
Steidl et al. [10] | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
Tzankov et al. [11] | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 6 |
Kamper et al. [12] | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 8 |
Hohaus et al. [13] | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 5 |
Zaki et al. [23] | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 4 |
Azambuja et al. [24] | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 8 |
Yoon et al. [14] | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 8 |
Tan et al. [15] | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
Sanchez-Espiridion et al. [31] | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 4 |
Abdou et al. [16] | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
Greaves et al. [17] | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
Deau et al. [25] | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 4 |
Panico et al. [26] | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 6 |
Casulo et al. [18] | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 7 |
Koh et al. [19] | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 6 |
Ping et al. [27] | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 5 |
Klein et al. [28] | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 6 |
Touati et al. [20] | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 6 |
Kayal et al. [30] | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 6 |
Agur et al. [29] | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 7 |
Moreno et al. [21] | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 5 |
Jakovic et al. [22] | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 6 |
Prognostic significance of CD68+ TAMs
Meta-analysis of the hazard ratios for progression-free survival, disease-specific survival, and overall survival for a high versus a low CD68+ tumor-associated macrophage (TAM) density. Hazard ratios (HRs) and 95 % confidence intervals (CIs) from individual studies are depicted as squares and horizontal lines, respectively. The pooled estimate is shown as a diamond shape, where the center represents the pooled HRs and the horizontal borders represent the 95 % CI. HRs are defined as high CD68+ versus low CD68+ TAM density; therefore, a hazard ratio > 1 represents a higher risk of death or progression associated with a high CD68+ TAM density
Prognostic significance of CD163+ TAMs
Meta-analysis of the hazard ratios for progression-free survival and overall survival for high CD163+ versus low CD163+ tumor-associated macrophage (TAM) density. Hazard ratios and 95 % confidence intervals for death or progression associated with high versus low CD163+ TAM density
CD68+ and CD163+ TAMs and clinical features
Meta-analysis of the association between CD68+ and CD163+ tumor-associated macrophage (TAM) density and clinical features. The Forest plots show (a) the association between a high CD68+ and CD163+ TAM density and presence of Epstein-Barr virus of adult classical Hodgkin lymphoma (cHL); (b) the association between a high CD68+ and CD163+ TAM density and presence of Ann Arbor stage of adult cHL; (c) the association between a high CD68+ and CD163+ TAM density and B-symptoms of adult cHL; (d) the association between a high CD68+ and CD163+ TAM density and International Prognostic Factors Project Score of adult cHL; and (e) the association between a high CD68+ and CD163+ TAM density and bulky disease of adult cHL
Ten studies reported data on CD68+ TAMs and Ann Arbor stage in adult cHL. Meta-analysis of these studies found a trend for a correlation between high CD68+ TAM density and advanced stage, with a pooled OR of 1.25 (95 % CI, 0.93–1.67). No significant heterogeneity was found across the studies (I 2 = 23.6 %, P = 0.23). Four studies reported data on CD163+ TAMs and Ann Arbor stage in adult cHL. Meta-analysis of the four studies showed a trend for a correlation between high CD163+ TAM density and advanced stage, with a pooled OR of 1.19 (95 % CI, 0.86–1.63). No significant heterogeneity was found across the studies (I 2 = 0.0 %, P = 0.91; Fig. 4b).
Six studies reported data on CD68+ TAMs and B-symptoms in adult cHL. The result of meta-analysis of the six studies showed a trend for a correlation between a high CD68+ TAM density and B-symptoms, with a pooled OR of 1.35 (95 % CI, 0.90–2.01). No significant heterogeneity was found across the studies (I 2 = 23.7 %, P = 0.26). Two studies reported data on CD163+ TAMs and B-symptoms in cHL. The result of meta-analysis of the two studies showed a trend for a correlation between high CD163+ TAM density and B-symptoms, with a pooled OR of 2.19 (95 % CI, 0.96–5.03). No significant heterogeneity was found across the studies (I 2 = 57.1 %, P = 0.12; Fig. 4c).
Five studies reported data on CD68+ TAMs and IPS in adult cHL. The result of meta-analysis of the five studies showed a trend correlation between a high CD68+ TAM density and higher IPS, with a pooled OR of 1.20 (95 % CI, 0.67–2.15). Three studies reported data on CD163+ TAM density and IPS in adult cHL. The result of meta-analysis of the three studies showed a trend for a correlation between high CD163+ TAM density and a higher IPS, with a pooled OR of 2.00 (95 % CI, 0.92–4.35). Significant heterogeneity was found across the studies (I 2 = 62.0 % for CD68+ TAMs and I 2 = 72.5 % for CD163+ TAMs, all P < 0.05; Fig. 4d).
Five studies reported data on CD68+ TAMs and bulky disease in adult cHL; meta-analysis revealed a trend correlation between a high CD68+ TAM density and bulky disease, with a pooled OR of 1.47 (95 % CI, 0.88–2.47). Two studies reported data on CD163+ TAMs and bulky disease in adult cHL. The result of meta-analysis of the two studies showed a trend for a correlation between a high CD163+ TAM density and bulky disease, with a pooled OR of 1.19 (95 % CI, 0.72–1.96). No significant heterogeneity was found across the studies (I 2 = 40.4 % for CD68+ TAM density and I 2 = 0.0 % for CD163 expression, all P > 0.10; Fig. 4e).
Publication bias
Begg’s funnel plot showed no publication bias among the included studies. a CD68+ tumor-associated macrophages (TAMs) and overall survival OS (P = 0.488). b CD68+ TAMs and PFS (P = 0.732). c CD163+ TAMs and OS (P = 0.230). d CD163+ TAMs and PFS (P = 1.000)
Discussion
Many recent studies have focused on the impact of non-neoplastic cells on disease pathobiology, specifically immunohistochemical typing of cells in the microenvironment, with the goal of identifying potential prognostic markers and therapeutic targets in adult cHL. Due to flawed statistical analyses and an inability to validate findings, few biomarkers have translated into clinical practice. Meta-analysis is a valuable tool in biomarker validation; thus, in this study, we carried out a meta-analysis to examine the correlation between TAMs and adult cHL prognosis.
This is the first meta-analysis investigating survival of cHL patients in which the survival of patients with high and low density of CD68+ and CD163+ TAMs was compared. Our results demonstrated that a high density of either CD68+ or CD163+ TAMs in the tumor microenvironment significantly predicted poor OS and shorter PFS for adult cHL (P = 0.000 and P = 0.000, respectively). A high CD68+ TAM density was associated with worse DSS than that in the group with a low CD68+ TAM density (P = 0.004). Furthermore, we also conducted a pooled analysis on the correlation between macrophage-associated markers and adult cHL EBV positivity. This finding suggests that a high density of either CD68+ or CD163+ TAMs is strongly correlated with EBV positivity (P = 0.000 and P = 0.001, respectively). In addition, these results suggested a trend towards a high density of both CD68+ and CD163+ TAMs with the presence of B-symptoms, advanced stage, bulky disease, and an IPS greater than 3; however, these results were not statistically significant. Taken together, the results of our pooled analysis support that a higher density of either CD68+ or CD163+ TAMs in the tumor microenvironment of adult cHL is associated with a higher risk of worst outcome.
The results of our meta-analysis indicate an association between increased density of both CD68+ and CD163+ TAMs in the tumor microenvironment of adult cHL and poor outcome. Among the included studies, different score methods and threshold values were used in the measurement of CD68+ and CD163+ TAMs using immunohistochemistry. Most of the studies used manual visual scoring techniques, ranging from cell counting [11, 23, 24] to computer-assisted methods of point counting [12, 21] and image analysis [15, 17]. The lack of consistent and reproducible of thresholds in these studies made it difficult to separate patients into low- and high-risk populations. Reproducibility of data produced in different laboratories and of assay methods for tissue sections will need to be a focus of future studies. Few biomarkers have translated into clinical practice since the reproducibility of immunohistochemical scoring has been suggested as a reason for inconclusive results, and thus more robust multigene predictors have been reported based on expression profiling [10]. However, these gene expression studies were limited by small case numbers and the lack of available clinical data.
In addition, the antibody used to stain macrophages varied. It has been reported that the KP1 clone does not only react specifically with macrophages, but also reacts with myeloid and fibroblastic cells [39]. The clone 10D6 for CD163 is more specific for macrophages than either the KP1 or PGM1 clones for CD68 [40]. Thus, CD163 may be a better marker for TAMs than CD68. When antibodies to CD68 and CD163 have both been used, some studies have noted discrepancies in the association of macrophages with patient outcomes. Martin-Moreno et al. [21] observed an association between increased CD68-stained cells and DSS in a cohort, but no association was observed using an antibody against CD163. In contrast, Zaki et al. [23] and Klein et al. [28] only saw an association between CD163 and outcome. Some studies indicate that TAMs in adult cHL promote tumor growth and angiogenesis, suppression of adaptive immune responses, and contribute to immune evasion by tumor cells, and thus may be associated with poor prognosis [41–44].
These analyses have some advantages and important implications. First, study quality scores, assessed using the NOS, had a mean score of 6.23, giving validity to the results of the present meta-analysis. Second, Egger’s test did not detect publication bias, indicating that the results are not biased. Third, this study shows that a high density of both CD68+ and CD163+ TAMs is associated with poorer outcome, which suggests that the TAMs may be useful as a drug therapeutic target. Fourth, our study identifies a subgroup of adult cHL tumors with poorer outcome. Finally, it highlights the importance of the development of an accurate biomarker for assessment of adult cHL.
The meta-analysis performed in this study had several limitations. First, negative studies are less frequently published, or are published with less detailed results, making them less assessable, potentially leading to some bias. Second, our meta-analysis is based on data from trials from which the results have been published, and we did not obtain updated individual patient data. Use of individual patient data may further enhance the accuracy and reduce the uncertainty of the estimates. Third, because of the variety of endpoints reported in adult cHL studies, we operationally defined adult cHL PFS to include EFS or FFS in studies that did not provide PFS. Fourth, some of the HRs with 95 % CIs were extracted from the Kaplan–Meier survival curve. Finally, among the included studies in the current meta-analysis, six had a follow-up time of less than 5 years, which may have incorporated bias.
Conclusions
In conclusion, the results presented here indicate that a high density of either CD68+ or CD163+ TAMs in the tumor microenvironment of adult cHL is associated with poor survival. A high density of both CD68+ and CD163+ TAMs was associated with the presence of EBV in neoplastic cells, and might provide essential information for the prediction of advanced stage, B-symptoms, bulky disease, and higher IPS. Evaluation of TAMs should be considered in prospective clinical trials, and patients with increased TAMs may benefit from more intensive chemotherapy or novel agents designed to disrupt crosstalk between Hodgkin-Reed-Sternberg cells and benign macrophages.
Declarations
Acknowledgements
This work was supported by the National Natural Science Foundation of China (NO.81160298). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Authors’ contributions
BPG, XHT, QK, and HC conceived of the study, selected studies and extracted the data, analyzed and interpreted the data, wrote the first draft of the manuscript, and revised the manuscript. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Authors’ Affiliations
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