Conceived and designed the experiments: FJ LX. Performed the experiments: LQZ JW FYL. Analyzed the data: LQZ RY. Contributed reagents/materials/analysis tools: LX. Wrote the paper: RY.
The authors have declared that no competing interests exist.
The potential prognostic value of survivin in resected non-small cell lung carcinoma (NSCLC) is variably reported. The objective of this study was to conduct a systematic review of literatures evaluating survivin expression in resected NSCLC as a prognostic indicator.
Relevant literatures were identified using PubMed, EMBASE and Chinese Biomedicine Databases. We present the results of a meta-analysis of the association between survivin expression and overall survival (OS) in NSCLC patients. Studies were pooled and summary hazard ratios (HR) were calculated. Subgroup analyses and publication bias were also conducted.
We performed a final analysis of 2703 patients from 28 evaluable studies. Combined HRs suggested that survivin overexpression had an unfavorable impact on NSCLC patients' survival with no evidence of any significant publication bias (HR = 2.03, 95%CI: 1.78–2.33, Egger's test, P = 0.24) and no severe heterogeneity between studies (I2 = 26.9%). Its effect also appeared significant when stratified according to the studies categorized by histological type, HR estimate, patient race, cutoff point (5%, 10%), detection methods and literature written language except for disease stage. Survivin was identified as a prognostic marker of advanced-stage NSCLC (HR = 1.93, 95%CI: 1.49-2.51), but not early-stage NSCLC (HR = 1.97, 95%CI: 0.76-5.14), in spite of the combined data being relatively small.
This study shows that survivin expression appears to be a pejorative prognostic factor in terms of overall survival in surgically treated NSCLC. Large prospective studies are now needed to confirm the clinical utility of survivin as an independent prognostic marker.
Lung cancer is the leading cause of death from cancer around the world, accounted for an estimated 157,300 deaths in the United States in 2010
Survivin also called baculoviral inhibitor of apoptosis repeat-containing 5 (BIRC5) is a member of the inhibitor of apoptosis (IAP) family, which is one of the most cancer-specific proteins identified to date, being unregulated in almost all human tumors. Biologically, survivin has been shown to inhibit apoptosis, enhance proliferation and promote angiogenesis
The expression of survivin has been reported to be a promising prognostic indicator, associated with a worse overall survival. However, evidence regarding the prognostic value of survivin with respect to overall survival in NSCLC remains controversial. In order to clarify this question, we performed this systematic review of the literatures with methodological assessment and meta-analysis.
A total of 317 potentially relevant citations were retrieved after initial databases search. The title and abstract of relevant articles were read by two authors independently. Two hundred and seventy-three citations were excluded from analysis after the first screening based on abstracts or titles, leaving 44 available for further full text review. After carefully reading the full text articles, 6 were excluded because they were reviews instead of observational studies. Five were excluded because they investigated the correlation with clinicopathological variables not survivals. Meanwhile, another 4 studies were excluded due to lacking of sufficient survival data. Additionally, 2 studies were found by hand search of the reference lists. As a result, 31 eligible studies including 2984 NSCLC cases were included in this meta-analysis
First Author | Year | Source of Patients | N. of Patient | Histology | Method | Stage | N. of Positive | Cutoff value | HR Estimate | HR | 95%CIs |
Kim |
2011 | South Korea | 151 | SCC | TMA | I–IV | 116 | 5% | HR | 2.05 | 1.15–3.58 |
93 | ADC | TMA | I–IV | 62 | 5% | HR | 4.51 | 1.71–11.93 | |||
Zhang Q |
2010 | China | 74 | ADC | IHC | I–III | 25 | 10% | HR | 2.16 | 1.37–3.75 |
Zhang JR |
2010 | China | 60 | SCC&ADC | IHC | I–III | 56 | 5% | HR | 2.94 | 1.89–4.57 |
Yang |
2010 | China | 60 | SCC&ADC | TMA | I–IV | 31 | 5% | Sur. Curve | 1.86 | 1.09–3.78 |
Weng |
2010 | China | 50 | NSCLC | IHC | I–III | 39 | NA | HR | 5.22 | 1.20–22.61 |
Porebska |
2010 | Poland | 74 | NSCLC | IHC | I–IV | 39 | 20% | Sur. Curve | 0.98 | 0.28–3.44 |
Nakashima |
2010 | Japan | 122 | NSCLC | IHC | I–IIIB | 64 | 25% | HR | 2.13 | 1.49–3.03 |
Lv |
2010 | China | 70 | SCC&ADC | IHC | I–III | 52 | 30% | HR | 4.02 | 1.73–9.39 |
Grossi |
2010 | USA | 87 | NSCLC | TMA | IIIA–N2 | 62 | 50% | HR | 1.61 | 0.94–2.77 |
Dai |
2010 | China | 66 | NSCLC | RT-PCR | IB–IIIA | 33 | 0.413 | HR | 1.493 | 1.12–2.13 |
Chen |
2010 | China | 72 | NSCLC | RT-PCR | IIIB–IV | 36 | 0.467 | HR | 2.12 | 1.22–3.11 |
Yie |
2009 | China | 78 | SCC&ADC | RT-PCR | I–IV | 33 | 1.02 | HR | 1.51 | 1.06–3.63 |
Yamashita |
2009 | Japan | 47 | NSCLC | RT-PCR | I–III | 28 | NA | HR | 0.62 | 0.22–1.75 |
Mohamed |
2009 | Japan | 78 | NSCLC | IHC | IIIA–N2 | 68 | 10% | HR | 2.21 | 1.26–3.89 |
Hoshil |
2009 | Japan | 100 | SCC&ADC | IHC | I–IIIB | 76 | 10% | HR | 1.73 | 1.04–2.97 |
Chen |
2009 | China | 80 | ADC | IHC | III–IV | 41 | 10% | Sur. Curve | 1.81 | 1.05–3.13 |
Li |
2008 | China | 91 | SCC&ADC | IHC | I–III | 46 | 10% | HR | 1.87 | 1.04–3.34 |
Bria |
2008 | Italy | 116 | NSCLC | IHC | I–IIIA | 82 | 20% | HR | 1.83 | 1.01–3.30 |
Zhu |
2007 | China | 213 | NSCLC | IHC | I–II | 43 | 10% | HR | 0.80 | 0.41–1.55 |
Yoo |
2007 | Korea | 219 | NSCLC | IHC | I–IIIA | 6 | 10% | HR | 1.12 | 0.35–3.54 |
Wang |
2006 | China | 115 | NSCLC | IHC | I–II | 72 | 5% | HR | 3.73 | 1.66–8.39 |
Vischioni |
2006 | Netherlands | 138 | NSCLC | IHC | I–IIIA | 127 | 5% | Logrank +p | 0.78 | 0.49–1.26 |
Atikcan |
2006 | Turkey | 58 | SCC&ADC | IHC | I–IIIA | 28 | 25% | HR | 3.73 | 1.53–9.05 |
Akyurek |
2006 | Turkey | 78 | NSCLC | IHC | I–IV | 50 | 10% | Sur. Curve | 2.28 | 1.17–4.43 |
Zhou |
2005 | China | 43 | SCC&ADC | IHC | I–III | 34 | 5% | Sur. Curve | 3.14 | 1.27–9.78 |
Shinohara |
2005 | USA | 144 | NSCLC | IHC | I–II | 105 | 25% | HR | 2.74 | 1.29–5.79 |
Karczmarek |
2005 | Poland | 60 | NSCLC | FISH | IIB–III | 35 | NA | HR | 4.27 | 3.51–5.03 |
Kren |
2004 | USA | 102 | SCC&ADC | IHC | I–IIIA | 54 | 15% | Sur. Curve | 2.16 | 1.34–3.44 |
Falleni |
2003 | Italy | 83 | NSCLC | RT-PCR | I | 44 | 25n | Sur. Curve | 0.86 | 0.53–1.37 |
Ikehara |
2002 | Japan | 79 | ADC | IHC | I–IV | 41 | 10% | Sur. Curve | 4.16 | 1.60–10.30 |
Monzo |
1999 | Spain | 83 | NSCLC | RT-PCR | I–IIIA | 71 | NA | HR | 2.20 | 1.10–4.50 |
N., number; ADC, adenocarcinoma; SCC, squamous cell carcinoma; NSCLC, non-small cell lung cancer; IHC, immunohistochemistry; TMA, tissue microarray; FISH, fluorescence in situ hybridization; RT-PCR, reverse transcription-polymerase chain reaction; NA, not applicable; HR, hazard ratio; Sur. Curve, survival curve.
Overall, the global quality score of the included studies ranged from 44.6 to 62.0% with a mean of 55.2% (as
Number of studies | Global Score (%) | Design(/10) | Laboratory methodology(/10) | Generalizability(/10) | ||
All studies | 31 | 55.2 | 5.4 | 5.7 | 5.3 | 5.2 |
Positive | 24 | 54.4 | 5.3 | 5.4 | 5.5 | 5.0 |
Negative | 7 | 55.2 | 5.4 | 6.1 | 5.2 | 5.4 |
|
0.67 | 0.76 | 0.42 | 0.12 | 0.66 | |
Asian | 22 | 51.6 | 4.9 | 4.8 | 5.0 | 4.9 |
Non-Asian | 9 | 54.5 | 5.6 | 5.3 | 5.2 | 5.5 |
|
0.25 | 0.09 | 0.32 | 0.26 | 0.34 | |
HR | 22 | 54.0 | 5.6 | 5.6 | 5.4 | 5.3 |
Sur. curve | 8 | 52.6 | 4.8 | 5.3 | 5.2 | 4.8 |
|
0.39 | 0.028 | 0.65 | 0.14 | 0.08 |
Score distributions are summarized by the median values; Negative, no significant prognostic factor for survival; Positive, as significant poor prognostic factor for survival; HR, Hazard ratio.
Highly significant heterogeneity was detected when all studies were pooled (chi-squared = 110.45, I2 = 71.9%, p<0.001), then the source of heterogeneity was explored using meta-regression analysis. One study investigated survivin expression by FISH
After excluding the 3 studies, the meta-analysis was performed on the 28 remaining studies. The main results of this meta-analysis are presented in
N. of studies | Number of patients | Random effects HR(95%CIs) | Heterogeneity test | |||
chi-squared | I2 | P-value | ||||
Overall | 28 | 2703 |
|
38.32 | 26.9% | 0.092 |
Written Language | ||||||
English written | 19 | 1929 |
|
20.18 | 5.8% | 0.384 |
Non English written | 9 | 776 |
|
16.57 | 51.7% | 0.035 |
HR Estimate | ||||||
HR | 21 | 2207 |
|
33.49 | 37.3% | 0.041 |
Sur. Curve | 7 | 516 |
|
4.58 | 0.00% | 0.599 |
Histological type | ||||||
ADC | 4 | 326 |
|
4.16 | 27.9% | 0.247 |
ADC&SCC | 9 | 662 |
|
8.24 | 2.90% | 0.410 |
NSCLC | 15 | 1565 |
|
21.84 | 35.9% | 0.082 |
Methods | ||||||
IHC | 23 | 2297 |
|
28.06 | 18.0% | 0.214 |
RT-PCR | 5 | 346 |
|
5.59 | 28.5% | 0.232 |
Ethnicity | ||||||
Asian | 22 | 2097 |
|
35.51 | 38.1% | 0.034 |
Non-Asian | 6 | 606 |
|
2.76 | 0.00% | 0.736 |
Tumor stage | ||||||
I–II | 3 | 472 | 1.97 (0.76–5.14) | 10.08 | 80.2% | 0.006 |
I–III | 15 | 1301 |
|
19.73 | 29.0% | 0.139 |
I–IV | 6 | 613 |
|
7.18 | 16.5% | 0.304 |
III–IV | 4 | 317 |
|
0.86 | 0.00% | 0.836 |
Cutoff value | ||||||
5% | 6 | 522 |
|
4.17 | 0.00% | 0.525 |
10% | 9 | 1012 |
|
11.01 | 27.3% | 0.201 |
N., number; HR, hazard ratio; NSCLC, non-small cell lung cancer. ADC, adenocarcinoma; SCC, squamous cell carcinoma;
When grouped according to the ethnicity, the combined HRs of Asian studies and non-Asian studies were 2.07 (95%CI: 1.75–2.44) and 1.95 (95% CI: 1.51–2.53), respectively. In the subgroup analysis according to the method of survivin detection used, the combined HR was 2.16 (95%CI: 1.87–2.49) for IHC and 1.62 (95%CI: 1.21–2.16) for RT-PCR. When stratified according to literature written language, the combined HRs of both English and non-English literatures showed an inverse effects on survival (HR = 1.93 and 2.31, separately). Although we also observed statistically significant effects of survivin expression on survival from studies reported all stages with an HR of 2.13 (95% CI: 1.57–2.89) and from 15 studies reported stage I–III with an HR of 2.07 (95% CI: 1.72–2.48), when we aggregated the studies that reported results for early-stage and advanced-stage NSCLC, the combined HR were 1.97 (95% CI: 0.76–5.14) and 1.93 (95% CI:1.49–2.51) with 3 and 4 studies in each arms, respectively (
The summary HR and 95% CIs were shown (according to the random effect estimations).
The summary HR and 95% CIs were shown (according to the random effect estimations).
The Egger's test and Begg's funnel plot were applied for detecting publication bias in the meta-analysis. In all included studies, no funnel plot asymmetry was found, with p = 0.24 in the Egger's test (
Studies are distributed symmetrically above and below the horizontal line, and suggest that the meta-analysis is absence of publication bias.
Survivin, as a biomarker of prognosis in malignancies, has generated much interest. But the conclusions for its prognostic value are controversial. Survivin expression is an unfavorable prognostic indicator in esophageal, hepatocellular, and ovarian cancers, cholangiocarcinoma, and endometrial cancers. In contrast, favorable outcome associated with nuclear survivin has been reported for gastric, bladder, and breast cancers, ependymoma, osteosarcoma and pancreatic ductal adenocarcinoma
The level of evidence provided by retrospective studies regarding prognostic indicators is lower than provided by randomized controlled trials. Our study used data from published trials rather than individual patient data. Although no evidence for significant heterogeneity was found, it is possible that the results of the meta-analysis could have been influenced by differences between the 28 studies. Studies may have differed with regard to the baseline characteristics of the patients included (age, histological type, differentiation or disease stage), the adjuvant treatment they might have received, the duration of follow-up and adjustments for other cofactors. Therefore, we attempted to perform a stratified subgroup analysis. As a result, the meta-analysis based on 31 literatures shows that the expression of the survivin protein is a poor prognostic factor for the survival of NSCLC who underwent surgical resection. However, when stratified analysis was conducted about different stages of NSCLC, the association was also found in stage III–IV, but not stage I–II, indicating that survivin could probably predict worse prognosis in advanced-stage NSCLC. In particular, an important issue that we need to take into account is the type of adjuvant therapy that each patient received after resection because chemotherapy and/or therapies that target the epidermal growth factor receptor, such as gefitinib or erlotinib, can change the outcome for NSCLC patients
We also performed a methodological assessment of the studies to avoid some selection biases (more detailed reports of significant trials) according to ELCWP scale. The absence of a detectable difference in quality score between significant and non-significant studies encourages us to perform a quantitative aggregation of the results of the individual trials. But this meta-analysis had to deal with heterogeneity problems. There was a highly significant heterogeneity among the 31 evaluable studies. Meta-regression analysis according to the type of patients, the disease characteristics, and the diversity in the techniques used to identify survivin status detected 3 studies accounting for the heterogeneity.
The heterogeneity could be explained by the fact that the technique of detecting survivin is not comparable among the studies. Most studies (77.4%) in the meta-analysis used IHC staining to study expressions of survivin. Although IHC staining is simple and cost-effective to perform, results are highly dependent on a variety of methodological factors, such as storage time, fixation method of paraffin-embedded tissues, different primary antibodies, the revelation protocols and different levels of positive (0, 10, 50%, different scores combining intensity and percentage, intensity only)
Finally, the pooled HRs calculated in our meta-analysis may be overestimated due to publication and reporting bias. We attempted to minimize publication bias by performing the literature search as complete as possible, using PubMed, EMBASE and Chinese Biomedicine databases. However, we did not take unpublished papers and abstracts into account because the required data was unavailable. Positive results tend to be more acceptable by journals, whereas negative results often are rejected or are not even submitted for review. Of the studies investigating survivin expression in patients with NSCLC, 4 were not included in the meta-analysis due a lack of available, or calculated, survival statistics. Another potential source of bias is related to the method used to extrapolate the HR. If the HR was not reported in a study, it was calculated from the data included in the article or extrapolated from the survival curves. In fact, the method of extrapolating HR from survival curves did seem to be less reliable than when it was obtained from published statistics because this strategy did not completely eliminate inaccuracy in the extracted survival rates. In addition, each study adjusted for different covariates and only the studies that found significant results in univariate analysis performed multivariate analysis, thus pooling of results may produce bias. Language also introduces bias, and positive results tend to be published in English-language journals. Although our search was conducted without language restriction, only one study written in a Japanese language was included except for Chinese and English articles in the meta-analysis
In conclusion, survivin expression was associated with a poor prognosis in patients with NSCLC in the present systematic review with meta-analysis. Interestingly, our meta-analysis suggests that survivin has a detrimental effect on survival in stage III–IV NSCLC. Survivin expression as a prognostic tool at the advanced stage of NSCLC may help clinicians to make difficult therapeutic decisions. Our conclusions need to be confirmed by an adequately designed prospective study and the exact role of survivin expression needs to be determined by an appropriate multivariate analysis taking into account the classical well-defined prognostic factors for lung cancer.
Studies were identified via an electronic search of PubMed, EMBASE and Chinese Biomedicine Databases using the following keywords: non-small cell lung carcinoma, NSCLC, BIRC5, baculoviral inhibitor of apoptosis repeat-containing 5, survivin, prognostic, prognosis and survival. The search ended on June 2011. The meta-analysis gathered complete databases from published studies dealing with the prognostic value of survivin in patients with NSCLC who underwent surgical resection of tumor. No language of published papers was restricted. To be eligible for inclusion, studies had to meet the following criteria: (i)they measured survivin expression in NSCLC with immunohistochemistry (IHC), reverse transcription- polymerase chain reaction (RT-PCR) or fluorescence in situ hybridization (FISH); (ii) compared of overall survival between different expressions of survivin in NSCLC; (iii) hazard ratios (HRs) for overall survival according to survivin status either had to be reported or could be computed from the data presented; (iv) when the same author or group reported results obtained from the same patient population in more than one article, the most recent report or the most informative one was included. We also used a manual reference search for relevant articles, including original articles and reviews, to identify additional studies. Abstracts were excluded because of insufficient data for use. To avoid duplication of data, we carefully noted the author names and the different research centers involved.
Data were extracted independently by two investigators (Zhang L.Q. and Jiang F.) by means of a predefined form. Topics in this form were first author's surname, year of publication, patient race, number of patients, histological type, disease stage, assay method, scoring protocol used, positive ratio, and survival data. In addition, discrepancies were resolved by a meeting called by Xu L.
Study quality was assessed independently by two investigators (Zhang L.Q. and Xu L.) by means of reading and scoring each study according to the European Lung Cancer Working Party (ELCWP) scale established by Steels et al
The primary outcomes were the overall survival in all population and then stratified by histological type, ethnicity, stage, test method, cutoff value, hazard ratio estimate and literature written language. The effective value of overall survival was determined by the combination of HR and 95% confidence interval (CI). If a direct report of HR and 95% CI was not available, estimated value was derived indirectly from other presented data using the methods described by Tierney et al
The correlation between two continuous variables was measured by the Spearman rank correlation coefficient. Non-parametric tests were used to compare the distribution of quality scores according to the value of a discrete variable.
The combination of the estimated risk was obtained by calculating the log (hazard ratio) and its variance estimates. A combined HR>1 implied a worse survival for the group with survivin overexpression. This pejorative impact of survivin on survival was considered as statistically significant if the 95% CI for the combined HR did not overlap 1. To assess heterogeneity among the studies, we used the Cochran Q and I2 statistics: for the Q statistic, a P value<0.10 was considered statistically significant for heterogeneity