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Inflammatory Biomarkers and Bladder Cancer Prognosis: A Systematic Review
European Urology, 6, 66, pages 1078 - 1091
Host immune response has an impact on tumour development and progression. There is interest in the use of inflammatory biomarkers (InfBMs) in cancer care. Although several studies assessing the potential prognostic value of InfBMs in cancer have been published in the past decades, they have had no impact on the management of patients with urothelial bladder carcinoma (UBC).
To review and summarise the scientific literature on the prognostic value of tumour, serum, urine, and germline DNA InfBMs on UBC.
A systematic review of the literature was performed searching the Medline and Embase databases for original articles published between January 1975 and November 2013. The main inclusion criterion was the provision of a survival analysis (Kaplan-Meier and/or Cox) according to the Reporting Recommendations for Tumor Marker Prognostic Studies guidelines for the assessment of prognostic markers. We focused on markers assessed at least twice in the literature. Findings are reported following Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines.
Overall, 34 publications, mostly retrospective, fulfilled the main inclusion criterion. Main limitations of these studies were missing relevant information about design or analysis and heterogeneous methodology used. Inflammatory cells, costimulatory molecules in tumour cells, and serum cytokines showed prognostic significance, mainly in univariable analyses. High C-reactive protein values were consistently reported as an independent prognostic factor for mortality in invasive UBC.
There is a dearth of studies on InfBMs in UBC compared with other tumour types. Evidence suggests that InfBMs may have an impact on the management of patients with UBC. Currently, methodological drawbacks of the studies limit the translational potential of results.
In this review, we analysed studies evaluating the impact of inflammatory response on bladder cancer progression. Despite methodological limitations, some inflammatory biomarkers should be further analysed because they hold promise to improve patient care.
Keywords: Bladder cancer, Inflammation, Biomarkers, Progression, Survival.
Evading the immune system is one of the emerging hallmarks of cancer  . It is well established that the inflammatory microenvironment has an impact on tumour prognosis, either positively or negatively  . The proper assessment of the composition and function of the microenvironment is challenging, and consensus is needed in the field about how to best consider the inflammatory response as a component of tumour subclassification  . In this regard, melanoma, colon, and breast cancer have taken the lead, , and .
The definition of inflammatory biomarkers (InfBMs) is in itself challenging. Any molecule involved in innate or adaptive immune response could be considered; this makes the list of candidates very long, and it is difficult to establish a definition of InfBMs due to the interaction between inflammatory pathways and other cellular functions. In this review, we focus on markers with the primary known function in the immune response.
Urothelial bladder carcinoma (UBC) is highly prevalent. It represents an important economic burden, affects patient quality of life, and is life threatening when it invades muscle. However, in many ways, UBC remains a neglected disease  . The dearth of information on InfBMs and UBC is paradoxical, considering that UBC is one of the few tumours for which there is long-standing evidence of the efficacy of immunotherapy.
Studies on the prognostic value of InfBMs in UBC have been published since the 1970s, , and . The infiltration of the tumour by inflammatory cells and their association with prognosis has been explored more extensively than blood or urine cytokine levels and germline DNA polymorphisms in inflammatory genes. Unfortunately, none of these markers has proven to be sufficiently useful for clinical application. Methodological flaws, technical heterogeneity, and lack of appropriately designed validation studies have been the most important limitations. Guidelines were published in 2005 to improve the reporting of prognostic markers, but unfortunately they are rarely followed  . We report a systematic review of the published results and methods applied in studies that assessed tumour, blood, urine, and germline DNA InfBMs related to the prognosis of patients with UBC. The review was conducted following the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) guidelines criteria. The ultimate goals of this effort were to provide a rationale for promoting research in the promising field of immunity and UBC, to identify the main limitations of the studies performed, and to select the most promising markers for prospective studies and clinical trials through an integrative scope ( Fig. 1 ).
2. Evidence acquisition
2.1. Material and methods
2.1.1. Information sources and eligibility criteria
The Medline, Medline In-Process, and Embase databases were searched for all original articles published from January 1975 to November 2013 on the topic of interest. Medline was searched through PubMed. Reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines.
The inclusion criteria were (1) original article, (2) human research, (3) English language, (4) accessibility to the full manuscript, and (5) availability of Kaplan-Meier/Cox regression-derived results about the prognostic value of the InfBMs on UBC outcomes according to the REMARKS guidelines for assessment of a prognostic marker  . Studies using association tests instead of survival analysis, with or without adjustment for other relevant variables, were not included, but they are listed in Supplementary Table 1. The outcomes considered were recurrence and progression for non–muscle-invasive bladder cancer (NMIBC) and local progression, metastasis, and cancer-specific mortality and overall mortality for NMIBC and muscle-invasive bladder cancer (MIBC). We report on studies assessing an InfBM twice or more in the literature. All other studies are listed in Supplementary Table 1.
2.1.2. Search strategy
We searched PubMed using the controlled vocabulary of the Medical Subject Heading database along with open text. The algorithm applied was (bladder OR urothelium OR transitional cell) AND (cancer OR tumour OR tumour OR carcinoma OR neoplasm) AND (inflammation OR inflammatory OR immune OR immunity) AND (prognosis OR survival OR recurrence OR progression). The search in Embase used the Emtree vocabulary ‘bladder cancer’ AND (‘inflammation’ OR ‘immunity’) AND ‘prognosis’. All selected articles were further hand-searched to identify additional relevant articles.
2.1.3. Study selection and the data collection process
The first stage of the search in Medline and Embase was performed by A.M.L. to screen and exclude studies unrelated to UBC or InfBMs. Second-stage selection was performed by four investigators (A.M.L., Y.A., F.X.R., and N.M.).
Information was retrieved according to the REMARK guidelines for reporting prognostic markers including author, country, journal, publication year, marker examined, study design, study population (sample size, recruitment period, and follow-up), patient characteristics (age, gender, stage, comorbidities), treatment received, biologic material/matrix used (urine, tumour, serum, saliva), methodology (for urine and blood markers: dosage kit for the marker, period of retrieval, and cut-off for positivity; for immunohistochemistry (IHC) on tumour tissue: antibody, area of interest on the slide, magnification, scoring, cut-off for positivity, and percentage of positive tumours; for germline DNA variants/single-nucleotide polymorphism (SNP): gene name, and genotyping technique), statistical method applied (with variables used for adjustment), and reported impact of examined markers on UCB outcome using univariable or multivariable survival analyses.
We conducted a meta-analysis to summarise quantitatively the overall prognostic value of serum C-reactive protein (CRP) because this was the most frequently studied marker in association with UBC outcome (eight studies). One author (Pr. Saito ) was directly contacted to obtain data required for the meta-analysis. Two studies could not be included due to the lack of important information; the results of Ishioka et al.  could not be included because the variable was not log-transformed. Finally, we were obliged to stratify the meta-analysis according to whether the studies used a dichotomous variable (two studies) or a continuous variable (three studies) to assess CRP. Random effect meta-analysis was performed as a sensitivity analysis. We quantified heterogeneity using the I2statistic  that describes the proportion of heterogeneity across studies that is not due to chance. The analysis showed no heterogeneity between the studies (I2 = 0% for both type of studies). Consequently, a fixed effect model was applied. Risk of publication/reporting bias across studies is likely, although we could not test it appropriately because of the small number of studies included  . Analyses were done using R v.3.0.1 software.
3. Evidence synthesis
A total of 1045 original articles were identified using Medline and Medline In-Process and 1651 using Embase. Figure 2 shows a flow diagram of the study selection strategy. At the end of the process, there were 87 articles assessing the association between germline DNA, blood, urinary, or tumour InfBMs, and UBC outcome (77 from the online search abstract screening and 10 added from reference list screening). From those, 23 articles lacked a survival analysis, as defined in the REMARKS criteria, and 24 investigated a marker that had only been reported once in the UBC domain (see Supplementary Table 1). Six studies evaluated the association of cyclooxygenase-2 tumour expression and prognosis. Our group recently published a meta-analysis on this topic  ; therefore, these studies were not considered in this review. Finally, 34 original articles assessing 13 InfBMs (germline DNA variants in interleukin [IL]-6 and tumour necrosis factor [TNF]-α; serum CRP, IL-6, and CD8 levels, and neutrophil-to-lymphocyte ratio (NLR); and expression of CD3, CD8, CD68, CD83, FOXP3, B7-H1 (PD-L1), HLA class I molecules, HSP70, as well as “inflammatory infiltrate” in tumour samples) were included. None of the urinary InfBMs fulfilled the main study criteria.
3.1. Study methodology
There were 8 and 18 prospective and retrospective studies, respectively. This information was missing in eight studies. Only one article provided a rationale for sample size and statistical power. Studies included in the main tables were published between 1990 and 2013. Patient recruitment period ranged from 1971 to 2010. Median number of patients included was 69 (range: 30–530). Median age of the patients was 67 yr (range: 23–93 yr). Median follow-up was 29 mo (range: 1–240 mo) ( Table 1 ).
|Study||Marker||Country||No. of patients||NMIBC/MIBC||BCG||Recruitment period||Age, yr (range)||Male/female, no.||Follow-up (range)||Treatment|
|Ahirwar et al. ||IL-6 (rs1800795)||India||136||136/0||69||2004–2007||62 (NA)||119/17||13 (3–60)||TURB ± iBCG|
|Leibovici et al. ||IL-6 (rs1800795)||USA||353||204/149||123||1995–2003||NA||NA||21 (1–74)||TURB ± iBCG or mBCG or RC|
|Leibovici et al. ||TNF-α (rs1800629)||USA||465||204/146||123||1995–2003||NA||NA||21 (1–74)||TURB ± iBCG or mBCG or RC|
|Ahirwar et al. ||TNF-α (rs1799964)||India||73||73/0||73||2003–2007||61 (NA)||NA||14 (3–60)||TURB and iBCG|
|Hwang et al. ||CRP||Japan||67||0/67||0||2004–2010||71(45–86)||53/14||11 (2.5–46.5)||Chemotherapy †|
|Yoshida et al. ||CRP||Japan||88||0/88||0||1997–2006||70 (63–75)||63/25||33 (3–117)||Radiochemotherapy|
|Hilmy et al. ||CRP||UK||103||61/42 *||6||1992–2001||NA||70/33||60 (NA)||NA|
|Gakis et al. ||CRP||Germany||246||0/246||26||1999–2009||67 (43–84)||191/55||30 (6–116)||RC|
|Ishioka et al. ||CRP||Japan||232||0/232||NA||1995–2010||71 (66–77)||162/70||11 (NA)||Radiochemotherapy or BSC †|
|Nakagawa et al. ||CRP||Japan||114||NA||16||1990–2010||67 (32–84)||92/22||11 (0.2–206)||RC ‡|
|Saito et al. ||CRP||Japan||80||NA||NA||2000–2009||NA||57/23||12 (2–99)||Second-line chemo after RC|
|Gondo et al. ||CRP||Japan||189||62/127||NA||2000–2009||68 (38–85)||158/31||25 (2–128)||RC|
|Gondo et al. ||NLR||Japan||189||62/127||NA||2000–2009||68 (38–85)||158/31||25 (2–128)||RC|
|Krane et al. ||NLR||USA||68||NA||NA||2005–2011||67.4 (NA)||55/13||25 (13–61)||RC|
|Andrews et al. ||IL-6||USA||51||15/36||24||1995–2000||65 (41–76)||47/4||46 (4–61)||RC|
|Lin et al. ||CD8||Taiwan||68||NA||NA||2007–2008||67 (26–90)||NA||NA||TURB|
|Otto et al. ||CD3||Germany||61||61/0||NA||1995–1998||NA||NA||74 (11–179)||TURB|
|Winerdal et al. ||CD3||Sweden||37||4/33||NA||1999–2002||67 (46–81)||NA||NA||RC|
|Sharma et al. ||CD8||USA||69||38/31||NA||1996–2001||NA||51/18||NA||TURB or RC|
|Kitamura et al. ||CD8||Japan||30||30/0||30||NA||NA||NA||NA||TURB and iBCG|
|Hanada et al. ||CD68||Japan||63||40/23||NA||NA||65 (34–84)||51/12||65 (3–153)||TURB or RC|
|Kitamura et al. ||CD68||Japan||30||30/0||30||NA||NA||NA||NA||TURB and iBCG|
|Takayama et al. ||CD68||Japan||41||41 CIS/0||41||1995–2005||70 (47–91)||36/5||53 (3–120)||TURB and iBCG|
|Ayari et al. ||CD68||Canada||46||46/0||46||1997–2002||68 (NA)||NA||31 (NA)||TURB and mBCG|
|Ayari et al. ||CD68||Canada||93||93/0||8||1990–1992||NA||NA||66 (NA)||TURB|
|Ayari et al. ||CD83||Canada||53||53/0||53||1997–2002||68 (NA)||NA||31 (NA)||TURB and mBCG|
|Ayari et al. ||CD83||Canada||93||93/0||8||1990–1992||NA||NA||66 (NA)||TURB|
|Winerdal et al. ||FOXP3||Sweden||37||4/33||NA||1999–2002||67 (46–81)||NA||NA||RC|
|Kitamura et al. ||FOXP3||Japan||30||30/0||30||NA||NA||NA||NA||TURB and iBCG|
|Wang et al. ||B7-H1||Japan||50||19/31||NA||2000–2002||62 (42–78)||40/10||28 (6–52)||NA|
|Boorjian et al. ||B7-H1||USA||316||98/218||NA||1990–1994||69 (37–90)||256/60||NA||RC|
|Nakanishi et al. ||B7-H1||Japan||65||36/39||NA||1996–2005||NA||47/18||26 (1–118)||TURB or RC|
|Sharma et al. ||HLA class 1||USA||69||38/31||NA||1996–2001||NA||51/18||NA||TURB or RC|
|Levin et al. ||HLA class 1||Israel||33||0/33||NA||NA||NA||NA||NA||RC|
|Kitamura et al. ||HLA class 1||Japan||30||30/0||30||NA||NA||NA||NA||TURB and iBCG|
|Homma et al. ||HLA class 1||Japan||65||0/65||NA||1991–2002||65 (38–79)||51/14||35 (3–172)||RC|
|Yu et al. ||HSP70||Taiwan||530||530/0||NA||1991–2005||72 (23–92)||452/78||86 (1–240)||TURB|
|Syrigos et al. ||HSP70||Greece||67||15/52||NA||NA||NA||NA||NA||NA|
|Cai et al. ||Infl. infiltrate||Italy||410||321/98||201||Jan–Dec 1995||68 (32–93)||306/104||NA||TURB or RC|
|Samaratunga et al. ||Infl. infiltrate||Australia||60||NA||29||NA||72 (28–91)||51/9||57 (5–168)||TURB|
|Offersen et al. ||Infl. infiltrate||Denmark||107||16/91||8||1992–1998||NA||91/16||NA||TURB|
|Sanchez et al. ||Infl. infiltrate||Spain||194||194/0||NA||1976–1990||62 (18–93)||174/20||NA||TURB ± instillations|
|Flamm and Havekec ||Infl. infiltrate||Austria||345||345/0||NA||1971–1982||69 (NA)||235/110||NA||TURB ± instillations|
* T1G3 tumours were considered MIBC.
† Series of advanced urothelial bladder cancer.
‡ Series of recurrence after RC.
± = with or without; BSC = best supportive care; CIS = carcinoma in situ; CRP = C-reactive protein; iBCG = induction bacillus Calmette-Guérin; IL = interleukin; Infl. = inflammatory; Jan–Dec = January through December; mBCG = maintenance bacillus Calmette-Guérin; MIBC = muscle-invasive bladder cancer; NA = not available; NLR = neutrophil-to-lymphocyte ratio; NMIBC = non–muscle-invasive bladder cancer; RC = radical cystectomy; TNF = tumour necrosis factor; TURB = transurethral resection of the bladder.
Missing information about study or patient characteristics was common: 11 (33%), 10 (30%), 5 (15%), 10 (30%), and 28 (84%) studies lacked information on age, gender, stage, follow-up, and comorbidities, respectively. Treatment information was provided by 31 studies (91%). When assessing germline DNA variants, all studies included NMIBC patients treated with bacillus Calmette-Guérin (BCG). Two studies also included a second cohort of cystectomised patients. For blood biomarkers, CRP was mainly investigated in patients undergoing radical cystectomy (RC) or among those with locally advanced/recurrent UBC treated by chemotherapy. NMIBCs were considered together with MIBC in two studies. Note that, in the study by Himly et al., pT1G3 patients were considered as having muscle-invasive UBC. For tumour markers, cohorts included both NMIBC and MIBC, separately or merged ( Table 1 ).
3.2. Assay methodology
The three studies considering germline DNA biomarkers analysed candidate SNPs in blood-extracted DNA. Genotyping was performed using methods based on polymerase chain reaction methods. Regarding blood biomarkers (11 studies), the dosage technique/kit was specified in four of eight studies on CRP. The threshold chosen to define positivity of CRP ranged from 0.5 to 1 mg/dl. In all studies, CRP was assessed before treatment (transurethral resection of the bladder [TURB] for NIMBC; RC or chemotherapy for MIBC). Two of eight studies considered CRP on a continuous scale. One study assessed serum IL-6 and categorised the levels using a threshold of 4.80 pg/ml (median value). NLR was assessed in two studies; both applied the same threshold (2.5). One study assessed the percentage of blood CD8 lymphocytes using flow cytometry; no further specification was given about the technique or threshold chosen for the analysis ( Table 2 ).
|Study||Marker||Threshold in analysis||Assessment period|
|Hwang et al. ||CRP||1 mg/dl||1 d before first chemotherapy cycle|
|Yoshida et al. ||CRP||0.5 mg/dl||Before radiochemotherapy|
|Hilmy et al. ||CRP||1 mg/dl||Before transurethral resection|
|Gakis et al. ||CRP||0.5 mg/dl or continuous||1–3 d before radical cystectomy|
|Ishioka et al. ||Log CRP||Continuous, mg/l||Before chemo/radiation or best supportive care|
|Nakagawa et al. ||CRP||0.5 mg/dl||At recurrence|
|Saito et al. ||CRP||Continuous, mg/l||Before second-line treatment|
|Gondo et al. ||CRP||0.5 mg/dl||Before radical cystectomy|
|Gondo et al. ||NLR||2.5||Before radical cystectomy|
|Krane et al. ||NLR||2.5||Before radical cystectomy|
|Andrews et al. ||IL-6||4.80 pg/ml||Morning of radical cystectomy|
|Lin et al. ||CD8||NA||Immediately before surgery|
CRP = C-reactive protein; IL = interleukin; NA = not applicable; NLR = neutrophil-to-lymphocyte ratio.
As for tumour InfBMs (20 studies), all markers were assessed by IHC. Overall, reporting of technique and interpretation of results were heterogeneous. Full sections and tissue microarrays were used in 12 and 2 studies, respectively. This information was missing in five studies. Only seven studies reported how the region and compartment (tumoural/stroma) of interest were selected. Definition of a high-power field varied from × 200 to × 1000 magnification. Quantification of staining was highly variable. In six studies, no information was provided about the method of quantification. Similarly, six studies lacked information regarding the cut-off applied in survival analysis or the reference value chosen for Cox regression analysis. Five studies reported “inflammatory infiltrate” as a marker without further characterisation. The definition of “strong inflammatory infiltrate” varied widely ( Table 3 ).
|Study||Marker||Ab||FS/TMA||Region selection||Area of interest||Magnification||Quantification of staining||Cut-off for positivity/Reference in survival analysis||% of PM|
|Otto et al. ||CD3||Rabbit mono.||FS||10 HPF in high CD3 + area||Tumour nest||×1000||No. of CD3+ cells||≤4 vs >4 CD3 + cells/HPF||NA|
|Winerdal et al. ||CD3||Mouse mono.||FS||Random selection of 3 HPF||Tumour nest||×400||No. of CD3+ cells||<3 vs≥3 CD3 + cells/field (mean)||NA|
|Sharma et al. ||CD8||Mouse mono.||FS||3 fields of 0.0625 mm2 in the high CD8 + area||Tumour nest||NA||No. of CD8+ cells||<8 vs ≥8 CD8 + cells/field (mean)||NA|
|Kitamura et al. ||CD8||Mono.||FS||NA||NA||×400||0–10 CD8+ cells/HPF = − ; 10–50 = + ; >50 = + +||NA||NA|
|Hanada et al. ||CD68||Mono.||FS||3 areas with the highest CD68 density||Tumour nest||×200||NA||<67 vs ≥67||NA|
|Kitamura et al. ||CD68||Mono.||FS||NA||NA||×400||–||NA||NA|
|Takayama et al. ||CD68||Mono.||FS||6 random fields of 0.0625 mm2||Stroma and TN||×400||No. of CD68+ cells in S and TN||<4 vs ≥4 TN/<24 vs ≥24 S||61|
|Ayari et al. ||CD68||Mono.||FS||NA||Stroma and TN||×200||0 (no CD68+ cells),1 (1–5),2 (6–10),3 (>10)||0–1 vs 2–3 (mean of S and TN)||46|
|Ayari et al. ||CD68||Mono.||FS||NA||Stroma and TN||×200||Same as 2009||0–1 vs 2–3 (mean of S and TN)||78|
|Ayari et al. ||CD83||Mono.||FS||NA||Stroma and TN||×200||0 (no CD68+ cells),1 (1–5), 2 (6–10), 3 (>10)||0–1 vs 2–3 (mean of S and TN)||54|
|Ayari et al. ||CD83||Mono.||FS||NA||Stroma and TN||×200||Same as 2009||0–1 vs 2–3 (mean of S and TN)||29|
|Winerdal et al. ||FOXP3||Mono. mouse||FS||Random selection of 3 HPF||Tumour nest||×400||No. of FOXP3 + cells||<3 vs ≥3 FOXP3 + cells/field||NA|
|Kitamura et al. ||FOXP3||Mono.||FS||NA||NA||×400||Same as CD8 and CD68||NA||NA|
|Wang et al. ||B7-H1||Poly.||TMA||NA||NA||×400||% positive cells||>10%||NA|
|Boorjian et al. ||B7-H1||NA||FS||NA||NA||NA||% positive cells||>5%||12|
|Nakanishi et al. ||B7-H1||Mouse mono.||FS||Random selection of 3 HPF in high B7H1 + area||Tumour nest||×400||% positive cells||NA||NA|
|Sharma et al. ||HLA 1||Mono.||NA||NA||NA||NA||% positive cells||10%||NA|
|Levin et al. ||HLA 1||Rabbit||FS||NA||NA||NA||% positive cells||20%||57|
|Kitamura et al. ||HLA 1||Mono.||FS||NA||NA||×400||0,1–2 (low mb/cytoplasm),||0, 1, 2 vs 3||NA|
|3 (mb and cytoplasm >80% cells)|
|Homma et al. ||HLA 1||Mono.||FS||5 areas; no more precision||Tumour cells||×400||0–1 = no/incomplete mb/cytoplasm staining, 2 = >80% mb staining||0–1 vs 2||66.2|
|Yu et al. ||HSP70||NA||TMA||NA||NA||NA||Intensity (0–3) × % stained cells||NA||NA|
|Sirigos et al. ||HSP70||Rabbit poly.||FS||NA||NA||NA||Intensity (0–3) × % stained cells||3 × 25%||66|
|Cai et al. ||Infl. inf||NA||NA||NA||NA||×400||NA||>20 lymphocytes||29|
|Samaratunga et al. ||Infl. inf||NA||NA||NA||NA||NA||NA||Inflammation vs oedema||36|
|Offersen et al. ||Infl. inf||NA||NA||NA||NA||×200||NA||Stroma not visible||30|
|Sanchez et al. ||Infl. inf||NA||NA||NA||NA||NA||NA||NA||NA|
|Flamm and Havekec ||Infl. inf||NA||NA||Selection of 10 HPF||NA||NA||NA||>100 cells/HPF||NA|
Ab = antibody; mb = membrane; FS = full section; HPF = high-power field; Infl. inf = inflammatory infiltrate; mono. = monoclonal; NA = not available; PM = positive marker; poly. = polyclonal; S = stroma; TMA = tumour microarray; TN = tumour nest.
3.3. Study findings
InfBMs identified from the literature could be grouped in three large categories according to their biologic significance: inflammatory cells, inflammatory costimulatory molecules in tumour cells, and serum cytokines. Table 4 provides a detailed list of the biomarkers according to these three categories.
|Inflammatory cells||Costimulatory molecules in tumour cells||Serum cytokines|
|CD3 (cytotoxic TL)||PDL1||CRP|
|CD8 (cytotoxic TL)||HLA||IL-6|
|FOXP3 (regulatory TL)||HSP||TNF-α|
|CD83 (dendritic cells)|
CRP = C-reactive protein; IL = interleukin; TL = T lymphocyte; TNF = tumour necrosis factor.
3.3.1. Germline DNA inflammatory biomarkers
Two studies assessed the association between germline IL-6 rs1800795 variant and UBC outcome and ( Table 5 ). Ahirwar et al. found a decreased risk of NMIBC recurrence among carriers (hazard ratio [HR]: 0.41; 95% confidence interval [CI], 0.17–0.94)  ; Leibovici et al. described a 4.6-fold higher risk of recurrence among high-risk NMIBC carriers receiving maintenance BCG therapy (n = 38)  . As for TNF-α, two polymorphisms were studied (rs1800629 and rs1799964) and . Both studies found that the SNP considered was associated with a decreased risk of recurrence among patients with NMIBC. However, the findings among patients with MIBC were discordant.
|Study||Marker||Outcome||Log rank p value||Cox regression||Adjusted for||Note|
|Univariate p value||Multivariate HR (95% CI) p value|
|Ahirwar et al. ||IL-6||Recurrence||0.41 (0.17–0.94)||0.03||Age, gender||All NMIBC|
|Leibovici et al. ||IL-6||Recurrence||0.73 (0.38–1.39)||NS||Age, gender, smoking status, grade||iBCG|
|–||Recurrence||4.6 (1.24 -17.1)||NA||Age, gender, smoking status, grade||mBCG|
|–||Progression||0.88 (0.80–4.41)||NA||Age, gender, smoking status, grade||All NMIBC|
|–||CSS||0.018||0.39 (0.15–1.00)||NA||Age, gender, smoking status, grade||Only for MIBC|
|–||OS||0.43 (0.19–0.94)||NA||Age, gender, smoking status, grade||Only for MIBC|
|Leibovici et al. ||TNF-α||Recurrence||1.69 (0.86–3.32)||NA||Age, gender, smoking status, grade||iBCG|
|–||Recurrence||0.43 (0.12–0.49)||NA||Age, gender, smoking status, grade||mBCG|
|–||Progression||0.71 (0.27–1.85)||NA||Age, gender, smoking status, grade||All NMIBC|
|–||CSS||1.54 (0.58–4.12)||NA||Age, gender, smoking status, grade||Only for MIBC|
|–||OS||2.35 (1.07–5.16)||NA||Age, gender, smoking status, grade||Only for MIBC|
|Ahirwar et al. ||TNF-α||Recurrence||0.024||0.38 (0.14–0.98)||0.048||Age, gender, smoking status||iBCG|
|Hwang et al. ||CRP||OS||0.001||0.001||NS||NS||Age, gender, metastasis by location, albumin level, ECOG|
|Yoshida et al. ||CRP||CSS||0.0003||0.003||1.80 (1.01–2.97)||0.046||stage|
|Himly et al. ||CRP||CSS||NA||0.016||2.89 (1.42–5.91)||0.004||Ki-67/COX2 expression, adjuvant therapy||Stratified by stage|
|Gakis et al. ||CRP||CSS||<0.001||0.0012||1.18 (1.09–1.27)||<0.001||Stage, LN density, margins||CRP = continuous variable|
|Ishioka et al. ||Log CRP||OS||<0.0001||<0.001||1.6 (1.19–2.15)||<0.01||Age, gender, PS, Hb, LDH, visceral metastasis * , LN metastasis|
|Nakagawa et al. ||CRP||OS||<0.0001||<0.0001||2.62 (1.6–4.4)||0.0002||Time to recurrence, symptoms at recurrence, no. of metastatic organs, LDH, chemo, metastasectomy|
|Saito et al. ||CRP||OS||NA||<0.01||1.02 (1.01–1.02)||0.001||ECOG, number of metastatic sites and nadir CRP after treatment||CRP = continuous variable|
|Gondo et al. ||CRP||CSS||0.025||0.02||NA||NA||NA|
|Gondo et al. ||NLR||DSS||0.0015||0.0015||1.94 (1.03–3.66)||0.038||Tumour size, hydronephrosis, hemoglobin|
|Krane et al. ||NLR||OS||0.04||NA||2.49 (1.14–6.09)||NA||pT, pN, albuminemia, creatininemia, refraction to BCG|
|Andrews et al. ||IL-6||MFS||0.024||NA||1.41 (0.95–2.10)||0.08||Stage, grade, LVI, nodal status|
|–||–||CSS||0.015||NA||2.17 (1.29–3.65)||0.05||Stage, grade, LVI, nodal status|
|Lin et al. ||CD8||Recurrence||0.018||0.044||0.40 (0.17–0.94)||0.036||NA||Ref. = high CD8|
* Liver, lung, and bone.
BCG = bacillus Calmette-Guérin; CI = confidence interval; COX = cyclooxygenase; CRP = C-reactive protein; CSS = cancer-specific survival; ECOG = Eastern Cooperative Oncology Group; Hb = hemoglobin; HR = hazard ratio; iBCG = induction bacillus Calmette-Guérin; IL = interleukin; LDH = lactate dehydrogenase; LN = lymph node; LVI = lymphovascular invasion; BCG = maintenance bacillus Calmette-Guérin; MFS = metastasis-free survival; NA = not available; NLR = neutrophil-to-lymphocyte ratio; NMIBC = non–muscle-invasive bladder cancer; NS = nonsignificant; OS = overall survival; PS = performance status; TNF = tumor necrosis factor.
3.3.2. Blood inflammatory biomarkers
CRP was the most widely studied serum marker. Eight studies assessed the association of high CRP levels with overall or cancer-specific survival, , , , , , , and . All of them reported consistent results showing that high CRP levels are associated with adverse outcome. In one study, the association was only significant in univariable analysis  . Another study lacked multivariable analysis  . In the six remaining studies, three using dichotomised CRP levels and three using a continuous variable, CRP was an independent prognostic factor for both cancer-specific and overall mortality, although variables for adjustment varied among studies ( Table 5 ; Supplementary Fig. 1 and 2). CD8 cell count was assessed as a serum marker using flow cytometry  . Authors observed that serum CD8 was inversely correlated to tumour infiltration with CD8 cells (r2 = 0.63;p < 0.0001). Low levels of CD8 cells in blood were associated with lower intravesical recurrence after TURB applying a multivariable analysis (HR: 0.4; 95% CI, 0.17–0.94). Two studies reported prognostic value for NLR after RC for UCB and . With a threshold of 2.5, both studies observed that high NLR was an independent adverse prognostic factor for survival after RC (HR: 1.94; 95% CI, 1.03–3.66, and HR: 2.49; 95% CI, 1.14–6.09).
18.104.22.168. Tumour inflammatory biomarkers: inflammatory cells in the tumour environment
Tumour infiltration by CD3+and CD8+cells was associated with a better outcome ( Table 6 ). All studies showed significant results in univariable analysis. Results were confirmed after adjustment for stage and other prognosticators only in the two studies assessing MIBC and . Winerdal et al. considered the impact of CD3 lymphocyte infiltration in the tumour of 37 patients treated by RC  . Strong infiltration was associated with increased overall survival (HR: 0.24; 95% CI, 0.08–0.71;p = 0.01). Sharma et al. studied CD8 infiltration in a series of 69 patients treated with TURB or RC  . HR for overall survival among MIBC patients with strong CD8 cell infiltration in the tumour on RC specimen was 0.3 (95% CI, 0.09–0.96). The presence of an “inflammatory infiltrate” without further characterisation of the cells has also been widely studied, , , , and . The main limitations of those studies were the heterogeneity in the definition of the studied populations and the terminflammatory infiltrate. Three studies including NMIBC and MIBC patients showed that strong inflammatory infiltrate was an independent good prognosticator for survival after adjustment for stage and other clinicopathologic factors, , and . Despite some caveats, the available evidence supports the notion that strong inflammatory infiltration in the tumour might be associated with a better prognosis, in concordance with the studies of CD3 and CD8. A precise characterisation of the inflammatory infiltrate in the tumour is required to draw further conclusions and establish mechanistic hypotheses.
|Study||Marker||Outcome||Log rank p value||Cox regression||Adjusted for||Notes|
|Univariate p value||Multivariate HR (95% CI) p value|
|Otto et al. 2012||CD3||CSS||0.045||NA||0.40 (0.05–3.24)||0.39||Age, gender, grade, tumour size, CIS, BCG, early or deferred cystectomy|
|Winerdal et al. ||CD3||OS||0.04||0.013||0.24 (0.08–0.71)||0.01||Age, gender, T stage, metastasis, chemotherapy, FOXP3 expression|
|Sharma et al. ||CD8||OS||0.001||0.15||0.3 (0.09–0.96)||0.04||Stage||Only for MIBC|
|Kitamura et al. ||CD8||Recurrence||0.0001||0.33||0.89 (0.12–6.59)||0.9||Stage, grade, HLA, CD4, CD20, CD68, TIA1, S100, FOXP3|
|Hanada et al. ||CD68||Survival||<0.0001||0.0005||5 (1.9–12.6)||0.0005||Age, grade, microvessel count, LVI, distant metastasis|
|Kitamura et al. ||CD68||Recurrence||0.0039||0.32||0.31 (0.03–2.86)||0.29||Stage, grade, HLA, CD4, CD20, CD68, TIA1, S100, FOXP3|
|Takayama et al. ||CD68 T||Recurrence||0.0002||NA||1.73 (1.47–5.03)||0.0012||Age, gender||T = in CIS|
|–||CD68 S||Recurrence||0.77||NA||1.01 (0.91–1.09)||0.87||Age, gender||S = lamina propria|
|Ayari et al. ||CD68||Recurrence||0.093||0.101||3.81 (1.32–11)||0.013||Age (continuous), gender, T stage, number of BCG maintenance|
|Ayari et al. ||CD68||Recurrence||NA||NA||1.19 (0.5–2.5)||0.65||Age (continuous), T stage, grade, number of tumours||Stratified by sex and SS|
|–||Progression||0.09||NA||NA||NA||Age (continuous), T stage, grade, number of tumours||Stratified by sex and SS|
|Ayari et al. ||CD83||Recurrence||NA||0.045||9.81 (1.1–85.7)||0.039||Age (continuous), gender, T stage||Only if >1 mBCG|
|Ayari et al. ||CD83||Recurrence||NA||NA||0.93 (0.5–1.8)||0.84||Age (continuous), T stage, grade, no. of tumours||Stratified by sex and SS|
|–||Progression||0.04||NA||8.25 (1.4–47.3)||0.018||Age (continuous), T stage, grade, no. of tumours||Stratified by sex and SS|
|Winerdal et al. ||FOXP3||OS||0.037||0.019||0.17 (0.05–0.6)||0.006||Age, gender, T stage, metastasis, chemotherapy, CD3 expression|
|Kitamura et al. ||FOXP3||Recurrence||NA||0.11||0.19 (0.02–1.41)||0.106||Stage, grade, HLA, CD4, CD20, CD68, TIA1, S100, FOXP3|
|Wang et al. ||B7-H1||CSS||0.02||NA||2.24 (1.16–4.38)||0.01||Age, gender, stage, grade|
|Boorjian et al. ||B7-H1||OS||0.005||0.005||3.18 (1.74–5.79)||<0.001||Age, stage, ECOG, smoking|
|Nakanishi et al. ||B7-H1||OS||0.021||NA||NA||NA||OE = worse survival|
|Sharma et al. ||HLA 1||MFS||NA||0.09*||NA||NA||* (HR: 0.57)|
|Levin et al. ||HLA 1||CSS||<0.005||NA||NA||NA||OE = better CSS|
|Kitamura et al. ||HLA 1||Recurrence||0.019||0.04||0.06 (0.01–0.40)||0.003||Stage, grade, HLA, CD4, CD20, CD68, TIA1, S100, FOXP3||Ref. = HLA low|
|Homma et al. ||HLA 1||Rec. after RC||0.03||0.03||2.39 (1.2–4.8)||0.01||pT, pN, and histologic variant||Ref. = HLA high|
|Yu et al. ||HSP70||Recurrence||NA||0.001||1.52 (1.15–2)||<0.001||Multiplicity||OE = more recurrence|
|Sirigos et al. ||HSP70||OS||<0.05||NA||NA||NS||Stage and grade||OE = poor survival|
|Cai et al. ||Infl. Inf||OS||0.0098||NA||NA||0.027||Stage and grade||OE = better survival|
|Samaratunga et al. ||Infl. Inf||MFS||0.56||NA||NA||NS||Age, gender, grade, size, treatments, multifocality||OE = better survival|
|Offersen et al. ||Infl. Inf||CSS||0.004||NA||0.48 (0.24–0.96)||0.04||Stage, nodal status, grade, and vessel density|
|Sanchez et al. ||Infl. Inf||CSS||<0.01||NA||NA||NS||Grade||OE = poor survival|
|Flamm and Havekec ||Infl. Inf||CSS||0.053||NA||NA||0.021||Stage, grade, multiplicity, location, CIS, and adjuvant treatment||OE = better survival|
BCG = bacillus Calmette-Guérin; CI = confidence interval; CIS = carcinoma in situ; CSS = cancer-specific survival; ECOG = Eastern Cooperative Oncology Group; HR = hazard ratio; iBCG = induction bacillus Calmette-Guérin; Infl. inf = Inflammatory infiltrate; LVI = lymphovascular invasion; mBCG = maintenance bacillus Calmette-Guérin; MFS = metastasis-free survival; NA = not applicable; NMIBC = non–muscle-invasive bladder cancer; NS = not significant; OE = overexpression; OS = overall survival; RC = radical cystectomy; Rec = recurrence; S = count in stroma; SS = smoking status; T = count in tumour.
It is difficult to come to a conclusion on the value of CD68 because of the heterogeneity of patient characteristics, tissue location, and methods of quantification. Ayari et al. combined the count in the tumour and in the stroma, whereas Takayama et al. did it separately, , and . A total of three studies showed statistically significant results in multivariate analysis, with strong infiltration by CD68 macrophages associated with adverse outcome, , and . Ayari et al. described that CD68 infiltration in the tumour was associated with a 3.8-fold (95% CI, 1.32–11;p = 0.013) higher risk of recurrence after TURB and maintenance BCG in a series of patients with NMIBC  . This result was not validated by a subsequent publication of the same author in a series of patients not treated with BCG therapy  . Hanada et al. combined NMIBC and MIBC patients and showed that those presenting strong CD68 infiltration in the tumour had a fivefold higher risk of mortality  . However, the study lacked details about patient management and definition of survival end points. Finally, Takayama et al. published a study with 41 patients with carcinoma in situ (CIS) treated with TURB and induction BCG  . The end point was time to recurrence defined by positive cytology. In multivariate analysis adjusted for age and gender, high CD68 count in CIS regions (four or more CD68+cells) was independently associated with recurrence (HR: 1.7). These authors also analysed CD68 counts in the lamina propria but found no association with recurrence. Together with CD68, Ayari et al. explored the impact of dendritic cell infiltration defined by CD83, and high levels of infiltration were associated with adverse outcome—recurrence after maintenance BCG  —and progression to muscle invasion  . Results were statistically significant, but the reliability of the risk estimates by Cox was questionable because of the small number of events (only one tumour recurred in the low CD83 group yielding an upper 95% CI of 85). Altogether these papers pinpoint a possible adverse effect of macrophage infiltration in tumours, but evidence remains weak.
The transcription factor FOXP3 is a master regulator of regulatory T cells (Treg)  . Two studies analysed tumour infiltration by FOXP3+lymphocytes and . Both showed better survival in association with strong infiltration, although the findings were statistically significant, after adjustment, in only one of them (HR: 0.17; 95% CI, 0.05–0.6;p = 0.006, for overall survival)  .
22.214.171.124. Tumour inflammatory biomarkers: costimulatory molecules in tumour cells
B7-H1 (PD-L1) is a T-cell coregulatory molecule. All three studies evaluating this marker showed that high B7-H1 expression was associated with decreased cancer-specific or overall survival (two studies after adjustment for classical prognosticators and one in univariable analysis only), , and . In a series of cystectomised patients, Boorjian et al. demonstrated that B7-H1 expression (>5% cells) was associated with a 3.18-fold higher risk of overall mortality compared with those lacking the marker (95% CI, 1.74–5.79;p < 0.001)  .
HLA class I molecules are required for the cytotoxic activity of T cells. Loss of HLA class 1 molecules was associated with adverse outcome. Four studies evaluated the impact of HLA class I expression on survival, , , and . Strong HLA class I expression was associated with decreased recurrence in a series of patients with NMIBC treated with TURB and induction BCG (HR: 0.06; 95% CI, 0.01–0.40;p = 0.003)  . The main limitation of the study was the small sample size (n = 30 patients) and number of events. Homma et al. presented a series of 65 patients treated with RC with similar results  . Patients whose tumour lost HLA class I expression had a 2.39-fold higher risk of recurrence after RC than those who did not, after adjustment for stage and histologic variant. HSP70 participates in pro- or antitumour immunity through its secretion by tumour cells or membrane expression through which it can present antigens to the immune system  . HSP70 has been evaluated twice in UBC and . Yu et al. assessed its association with recurrence and progression in a series of 530 patients with NMIBC treated by TURB  . Strong expression of HSP70 in tumour cells was independently associated with an increased risk of recurrence (HR: 1.52; 95% CI, 1.15–2;p < 0.001), but there was no independent association with progression in a multivariable analysis. By contrast, HSP27 expression was independently inversely associated with progression (HR: 0.49; 95% CI, 0.33–0.73;p < 0.0001).
In spite of their limitations, the major prognosticators for both NMIBC and MIBC at present remain clinical and pathologic factors. The usefulness of several promising molecular prognostic markers, such as Ki-67 overexpression or fibroblast growth factor receptor 3 (FGFR3) mutations, has not been conclusively established. Other markers, such as tumour protein p53 (TP53)mutations or p53 overexpression, have failed to demonstrate clinical usefulness when combined with standard clinical and pathologic parameters  . Molecular profiling has identified new subgroups of UBC, but independent replication is required and . In addition to their prognostic value, such profiles aim at improving patient stratification and outcome prediction through the use of targeted therapies. However, none of these strategies is ready to be used in the clinical setting.
Overall, there is a need to improve methodology to assess prognostic markers in UBC, as in other tumour types  . The field of InfBM discovery is no exception to that rule. The REMARKS guidelines, published in 2005, provide a quality control framework to improve research quality for prognosis biomarker assessment  . From the 34 studies analysed in this review in detail, 28 were published in or after 2005. Most of them did not fulfil the REMARKS criteria. Study and patient characteristics were often poorly described, assay methodology was very heterogeneous, important information was missing, and analysis and presentation of results were irregular. Unsuitable methodology prevents reproducibility and diminishes the impact of the work.
The lack of rigor in conducting and reporting studies renders validation of the results less likely. In this review, none of the studies included provided internal or external validation. Statistical significance from Cox multivariable analysis does not mean that a marker is worth translation into clinics. Studies should provide evidence of the marker's analytical validity (robustness of the test method) and discriminative ability (ie, c-index)  . Finally, the ideal biomarker should allow identification of patients at risk of a certain outcome with acceptable cost  . None of the studies included in this review provided any of those estimates. Consequently, translation into the clinics is inefficient, and much effort is wasted in the replication of poor quality studies. Despite these methodological limitations, we provide evidence that some InfBMs merit additional study as markers of UBC prognosis ( Fig. 3 ).
SNPs in inflammatory pathways possibly play a role in UBC prognosis, although their individual value will probably be too small to be useful in the clinical setting. It is, however, likely that the combined effect of multiple polymorphisms may be more important and more robust as a marker. The multi-inflammatory SNP approach has already been applied to UBC risk studies  , and similar approaches should be applied to prognosis.
The prognostic significance of IL-6 and CRP has been demonstrated in other cancers including lung, breast, ovary, colon, prostate, and upper urinary tract. Our review suggests that CRP may be the first InfBM approaching translation into clinics. All studies reviewed consistently provide evidence that patients with a high CRP level have a poorer prognosis in MIBC, independently of standard clinical or pathologic factors. However, these results need to be interpreted cautiously because of the heterogeneous methodology applied. The prognostic significance of CRP in patients with NMIBC is unknown and also merits study.
NLR has recently attracted interest and is a promising marker for patients undergoing radical surgery. Since we performed this search, two additional studies have shown that high NLR is associated with adverse outcome in UBC and in upper tract urothelial carcinoma and . A recent meta-analysis exploring the impact of NLR in all urologic malignancies confirmed its significance in urothelial carcinoma and showed comparable results for renal cell carcinoma  .
There is also an increasing interest in inflammatory infiltrates of tumours. Galon et al. reported that the type, location, and density of inflammatory infiltrating cells in colorectal carcinoma were better predictors of survival than the commonly used clinical and histopathologic factors  . An Immunoscore based on the assessment of CD3+and CD8+cells in the centre of the tumour and at the invasion front was established for clinical translation  , and a worldwide task force has been organised to “initiate the incorporation of Immunoscore as a component of cancer classification”  . We show that CD3 and CD8 infiltration in the tumour are directly associated with a better UBC prognosis, as in colon cancer. One of the main limitations, however, is the lack of standardised methods of immunostaining and scoring: Variation of the cut-off chosen for positivity and lack of normalisation of the results (ie, per square millimetre) reduces the robustness of the results. The relevance of these markers is also supported by gene expression profiling of UBC showing the existence of an “infiltrated” subtype characterised by a strong “immune signature.” Sjodahl et al. reported high levels of CD3d molecule, delta (CD3-TCR complex) (CD3D), CD3 g molecule, gamma (CD3-TCR complex) (CD3G), and CD8a molecule (CD8A) transcripts in UBC with preliminary data suggesting an association with a better prognosis  .
The interplay between inflammatory and tumour cells should also be assessed. PD-L1 is important as a marker and as a therapeutic target  . Interaction between PD-L1 and its receptor PD1 transmits an inhibitory signal to CD8+lymphocytes, reducing their proliferation  . The three studies reviewed in this paper showed that PD-L1 tumour cell expression was associated with adverse outcome. Anti–PD-L1 antibodies have shown remarkable antitumour activity and safety in recent clinical trials in patients with advanced cancers  . In melanoma, anti-PD1 and anti–PD-L1 antibodies induced high rates of durable responses  . Clinical trials are now being conducted in metastatic UBC.
To translate knowledge into the management of patients with UBC, several specific challenges need to be addressed: Tumours are highly heterogeneous; the TURB generally disrupts the morphology of the tumour mass, which is fragmented; the natural history of the disease is long and subject to medical intervention, for example with nonsteroidal anti-inflammatory drugs; and chronic cystitis, associated with lymphocytic and lymphofollicular infiltrates, can occur in the setting of UBC. Immune editing secondary to BCG immunotherapy may be particularly relevant. Regarding MIBC, it will be important to assess incident tumours separately from those that progress from NMIBC  . These issues will require well-designed prospective multicentre studies of appropriate sample size.
This review has some limitations. Reporting and publication bias may result from the lack of information or unpublished negative studies. The reduced number of studies for each marker did not allow us to provide a quantitative assessment of the presence of bias. In addition, the power of meta-analyses is limited due to the small number of studies included, making assessment of heterogeneity and the interpretation of results difficult. The search, using very general keywords, demonstrated problems in the referencing of inflammatory-related articles in Medline. A hand search of reference lists of retrieved publications was necessary to identify most of the studies regarding CRP. This also outlines the difficulties of defining an inflammatory marker. Undoubtedly, some markers are directly implicated in immune response, such as CD3, CD8, HLA, or CRP. Others, such as HSP70, have more pleiotropic functions. Finally, markers included in Supplementary Table 1 are not necessarily devoid of interest: They just require more attention. A major emphasis should be placed on building partnerships to conduct larger and better studies. The study of the tumour inflammatory microenvironment promises novel insight into cancer biology and raises new opportunities for therapeutic intervention. The urologic community should contribute so that progress in the management of patients with UBC does not get “lost in translation.”
InfBMs show promising usefulness in the management of patients with UBC, both for improved assessment of prognosis and to guide therapy. Serum CRP is one of the most promising InfBMs and independently associated with mortality in advanced UBC. However, these findings need to be interpreted with caution because of many methodological drawbacks. In the translational process of these markers into the clinical milieu, rigorous efforts should be placed in proper study design. Progress will be faster if researchers unite their efforts.
Author contributions:Núria Malats had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design:Masson-Lecomte, Allory, Malats.
Acquisition of data:Masson-Lecomte.
Analysis and interpretation of data:Masson-Lecomte, Rava, Real, Allory, Malats.
Drafting of the manuscript:Masson-Lecomte, Allory, Malats.
Critical revision of the manuscript for important intellectual content:Masson-Lecomte, Rava, Hartmann, Real, Allory, Malats.
Statistical analysis:Masson-Lecomte, Rava.
Obtaining funding:Masson-Lecomte, Allory, Malats.
Administrative, technical, or material support:None.
Financial disclosures:Núria Malats certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: None.
Funding/Support and role of the sponsor:This work was partially funded by a fellowship of the European Urological Scholarship Program for Research given to Alexandra Masson-Lecomte (EUSP Scholarship S-01-2013); Red Temática de Investigación Cooperativa en Cáncer (#RD12/0036/0050) for supporting the two groups at CNIO and Fondo de Investigaciones Sanitarias (FIS), Instituto de Salud Carlos III, Spain (Grant numbers #PI00-0745, #PI05-1436, and #PI06-1614); and EU-7FP-HEALTH-TransBioBC #601933 for all the background provided by these studies that is exploited here.
Appendix A. Supplementary data
Supplementary Fig. 1 Forest plot from the meta-analysis of the three studies on serum C-reactive protein (CRP), considered as a dichotomous variable, and overall survival or cancer-specific survival. The diamond indicates overall hazard ratio (HR) (meta-HR) and 95% confidence interval for mortality associated with values of CRP over the cut-off value.
Supplementary Fig. 2 Forest plot from the meta-analysis of the two studies on serum C-reactive protein (CRP), considered as a continuous variable, and overall survival or cancer-specific survival. The diamond indicates overall hazard ratio (HR) (meta-HR) and 95% confidence interval for mortality associated with per unit increase in CRP level. Note that for the work of Saito et al., HR was transformed because CRP was assessed using different units (milligrams per liter instead of milligrams per deciliter).
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a Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
b Urology Department, Henri Mondor Academic Hospital, INSERM U955Eq7, Créteil, France
c Epithelial Carcinogenesis Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
d Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain
e Department of Pathology, University Erlangen-Nürnberg, Erlangen, Germany
f Pathology Department, Henri Mondor Academic Hospital, INSERM U955Eq7, Créteil, France
Corresponding author. Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernández Almagro, 3, 28029 Madrid, Spain. Tel. +34 912 246 900 ext. 3330; Fax: +34 912 246 911.
© 2014 European Association of Urology, Published by Elsevier B.V.