PROGNOSTIC SIGNIFICANCE OF MICRO-RNAS IN PAPILLARY THYROID CANCER: A SYSTEMATIC REVIEW

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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES

FACULTY OF MEDICINE

Department of Endocrinology

Arnoldas Kinčius

PROGNOSTIC SIGNIFICANCE OF MICRO-RNAS IN PAPILLARY

THYROID CANCER: A SYSTEMATIC REVIEW

MASTER THESES

of Medicine

Supervisor: Prof. Birutė Žilaitienė

Lithuania, Kaunas, 2018

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SUMMARY

Author: Arnoldas Kinčius

Title: Prognostic significance of micro-RNAs in papillary thyroid cancer: a systematic review

Background/Aims: To systematically assess all papillary thyroid cancer (PTC) micro-RNA (miRNA) studies in relation to recurrence and prognostic factors; evaluate role of miRNAs in the future for PTC.

Methodology: After a search on NCBI PubMed, this review assessed a total of 107 articles with specific inclusion and exclusion criteria. The inclusion criteria consisted of: (i) studies with at least a group of PTC patients comparing PTC prognostic factors with miRNA expression measurements or (ii) PTC miRNA studies which performed quantitative expression measurements on PTC tissues. Overall, 31 articles were included. Studies were further divided into two main groups: one group for the analysis of miRNA in tumour-recurrence patients and another group for analysis of miRNAs and PTC’s clinicopathologic factors. The risk of bias of individual studies was evaluated using a modified Newcastle-Ottawa Scale (NOS) for observational studies.

Results: In all 31 studies, a total of 12 upregulated miRNAs and 18 downregulated miRNAs had statistically significant associations with clinicopathologic factors. This review found 11 and 22 studies which compared PTC’s recurrence and clinicopathologic factors with miRNA expression levels, respectively. In the recurrence group, univariate analyses found miRNAs: -146b,-222, and -221 were consistently and significantly (P<0.05) upregulated in 8, 5, and 3 studies, respectively (n = 378, 174, and 119, respectively). In multi-variate analyses, conflicting results were found for miRNA-146b to act as an independent prognostic factor for recurrence. In the prognostic factor group, miRNA-146b and miRNA-222 expressions levels were found to be consistently upregulated for patients with lymph node metastasis (LNM), extra-thyroidal invasion (ETI), and a higher TNM stage.

Discussion: To the extent of my knowledge, this is the first systematic review to investigate associations between recurrence and miRNAs in PTC. Since many miRNA dysregulational statistical associations exist, this review supports the idea that miRNAs play a key role in PTC development but inconsistent results suggest a non-causal role. Limitations of this study depended on: discrepancies in study and statistical methods, risk of bias in the systematic review, and a lack of meta-analysis.

Conclusions: This systematic review has found miRNAs -146b, -221 and -222 as ideal candidates for further research which is consistent with current literature.

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ACKNOWLEDGMENTS

I would like to express my gratitude to everyone who made this work possible; especially, my sincerest appreciation to my supervisor Prof. Birutė Žilaitienė for all her guidance and recommendations during this research. Additionally, I would like to thank the Department of Endocrinology, Lithuanian University of Health Sciences.

CONFLICT OF INTEREST

The author reports no conflicts of interest.

ETHICS COMMITTEE APPROVAL

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ABBREVIATIONS LIST

TERMS

microRNA dysregulation – The dysregulation of a miRNA means an increase (upregulation) or decrease (downregulation) in the relative expression level of a miRNA when compared to a control.

Clinicopathologic factor – In PTC, the clinicopathologic factors are collected clinically from patients. These consist of all PTC clinically relevant factors obtained during diagnosis, treatment, and follow-up of PTC; for example, age, sex, and tumour size.

miRNA, miR MicroRNA

mRNA Messenger RNA

PTC Papillary thyroid carcinoma

Vs Versus

MNG Multinodular goitre

NG Nodular goitre

PCR Polymerase chain reaction

qRT-PCR Quantitative reverse transcription polymerase chain reaction

TNM Tumour, nodule, metastasis staging

ETI Extra-thyroidal invasion

LN Lymph node

LNM Lymph node metastasis

CLNM Cervical lymph node metastasis

VI Vascular invasion

ROC Receiver operating characteristic

AMES Age, Metastases to distant site, Extra-thyroidal invasion, and tumour Size criteria

AJCC American Joint Committee on Cancer Staging

TCGA The Cancer Genome Atlas

MACIS Metastasis, patient Age, Completeness of resection, local Invasion, and tumour Size.

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INTRODUCTION

Papillary thyroid carcinoma (PTC) remains the most common thyroid carcinoma (85%-90%), let alone the most frequent endocrine cancer[1]_{. The prognosis of PTC is usually excellent with 10 year} survival usually higher than 90% after indicated treatment[2]_{. However, local regional recurrences} occur in up to 35% of patients with PTC and roughly a third of patients with local recurrences result in death[3]_{. To minimise this, the current difficulty is in properly identifying and evaluating a patient’s} prognosis, applying an adequate treatment plan and a life-long screening programme. Due to these difficulties, inadequately managed patients result in potentially higher fatal outcomes. Therefore, the diagnostic tools, prognostic data, and treatments are constantly adapting as seen from the various sets of thyroid guidelines published by different thyroid organisations around the world[4]_.

Clinically, prognostic risk factors do exist, such as: >45years age, large tumour size, extra thyroidal invasion (ETI), lymph node metastasis (LNM), distant metastasis, and vascular invasion (VI), but even these are not able to predict prognostic reoccurrence in many cases or not until the tumour has reached a more advanced stage[5,6]_{. Additionally, half of distant metastases are only} diagnosed during the follow-up period[7]_{. Over the last decades, an increasing incidence of thyroid} cancer has been observed[8]_{, mostly due to an increased sensitivity of diagnostic and follow-up} investigations. These cases are generally attributable to newly diagnosed tumours that are tiny, localised, and asymptomatic but require lifelong follow-up care, and despite low mortality can have persistent low-level disease[4]_{. It is still controversial how much such patients will benefit from} additional therapy and monitoring.

Lately, a hot focus has shifted to detecting biomolecular markers of thyroid cancer, for example, gene panel expressions (e.g. BRAF, RAS) and miRNA expression levels. This research is mostly aimed at trying to understand the molecular peculiarities of miRNAs and is driven by the hope it will improve clinical care and management[9]_{. This could be of great benefit to persistent-disease} patients – essentially allowing more specific follow-up screening to be undertaken by patients with low-level disease. However, at the moment, the European Thyroid Association does not currently recommend such biomarkers in routine practice mostly due to inconsistent results and relatively high costs[10]_{. Therefore, critical appraisal of new evidence is paramount to identify and structure effective} novel follow-up strategies.

MicroRNAs are endogenous non-coding RNA molecules (19-25 nucleotides) identified as posttranscriptional negative regulators of gene expression by attaching to the 3’UTP of target mRNAs in the cytoplasm[11]_{. MiRNAs have shown that they are involved in fundamental biological processes,}

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7 including metabolism, cell life cycles, tissue differentiation, embryogenesis, and organogenesis functions such as cell proliferation and apoptosis; proving they act, in principle, as regulators for oncogenes and tumour suppressor genes[11,12]_{. These are key pathogenetic mechanisms in cancer} development thus showing the enormous role miRNAs play in such processes[13]_{. Nowadays, there is} no doubt that the genome’s regulatory potential is largely determined by miRNAs[11]_.

Traditional miRNA expression detection methods are: northern blotting, microarray and quantitative reserve transcription polymerase chain reaction (qRT-PCR) [14]_{. There are more than} 30000 detected miRNAs[15]_{expressed in nature and, using the latest technologies, screening of} miRNAs in normal and cancer tissues has resulted in 100s or even 1000s of abnormally expressed miRNAs[11,16]_{. Out of these, only few may have any clinical relevance. However, multiple study} variations exist within the available research making comparative statistical analysis more difficult. These variations and limitations include: differences in measurement methods, statistical analysis methods, and experiment protocols; small sample sizes; and inconsistent results between studies. In this systematic review, all relevant data on the prognostic value of miRNA expression in PTC will be analysed. As such, the clinical relevance and the prognostic significance of miRNAs in PTC will be reviewed.

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AIM AND OBJECTIVES OF THE THESIS

Aim:

To systematically evaluate the prognostic significance of miRNAs in papillary thyroid carcinoma especially in relation to cancer recurrence.

Objectives:

1. Systematically group and qualitatively assess all miRNA PTC studies with recurrence and follow up groups or relapse-free survival rates.

2. Systematically group and qualitatively assess miRNA PTC studies and their clinicopathologic values and evaluate any prognostic significance.

3. Assess for the possibility of any prognostic implications in clinical practice if miRNA expression measurements were taken into account and assess future implications and current limitations.

Objectives according to participants (P), interventions (I), comparators(C), and outcomes (O)

This research’s aim is to address the significance of miRNA in (P) PTC patient’s prognostic data and tumour-recurrence data by evaluating (I) the patient’s miRNA expression profiles and comparing (C) them with non-recurrent patients and those without poor clinicopathologic factors (controls). The expected outcome (O) is to identify and evaluate potential miRNAs for use in PTC prognostic stratification (e.g. as independent prognostic factors) and judge the relevance of conducting future research on miRNAs for use in the prognostic evaluation of PTC.

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RESEARCH METHODOLOGY AND METHODS

Material and Methods

The study was written in accordance to the PRISMA statement guidelines for reporting articles of systematic reviews and meta-analyses with adaptations to match master thesis requirements.

Search Strategy:

The search was performed by using the following advanced MESH search on NCBI PubMed: (("micrornas"[MeSH Terms] OR "micrornas"[All Fields] OR "mirna"[All Fields]) OR ("micrornas"[MeSH Terms] OR "micrornas"[All Fields] OR "microrna"[All Fields]) OR mir[All Fields]) AND ((papillary[All Fields] AND ("thyroid neoplasms"[MeSH Terms] OR ("thyroid"[All Fields] AND "neoplasms"[All Fields]) OR "thyroid neoplasms"[All Fields] OR ("thyroid"[All Fields] AND "cancer"[All Fields]) OR "thyroid cancer"[All Fields])) OR ("Thyroid cancer, papillary"[All Fields] OR "papillary thyroid carcinoma"[All Fields])) AND (("recurrence"[MeSH Terms] OR "recurrence"[All Fields]) OR ("prognosis"[MeSH Terms] OR "prognosis"[All Fields]) OR prognostic[All Fields] OR ("epidemiology"[Subheading] OR "epidemiology"[All Fields] OR "surveillance"[All Fields] OR "epidemiology"[MeSH Terms] OR "surveillance"[All Fields]) OR follow-up[All Fields])

To summarise, key words used in this search consisted of: „(miRNA OR microRNA OR miR) AND (papillary thyroid cancer OR papillary thyroid carcinoma) AND (recurrence OR prognosis OR prognostic OR surveillance OR follow-up)”, thus using „AND” and „OR” as Boolean operators to narrow down the search. This search yielded 107 results with the final search performed on the 23th of April 2018 at 19:12 o’clock with no lower limit on the year used.

Screening

Initial screening consisted of analysing abstracts with specific inclusion and exclusion criteria. The inclusion criteria consisted of: (i) studies with at least a group of PTC patients comparing prognostic factors with miRNA expression measurements or (ii) PTC miRNA studies which performed quantitative expression measurements on PTC tissues. Exclusion criteria consisted of: (i) non-PTC thyroid cancers studies (ii) in-vitro only studies without patient clinicopathologic data, (iii) single case-reports, (iv) non-English articles, (v) animal only studies, (vi) reviews, letters and abstracts presented in conferences, and (vii) studies without miRNA prognostic or clinicopathologic statistical comparisons. After initial screening 68 such articles were removed. Two studies were found from additional sources and were included because they suited inclusion and exclusion criteria.

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10 Eligibility

41 full-text articles were assessed for eligibility by full-text analysis of each article. Overall, 31 articles were included on the basis that they compared miRNAs with at least one prognostic clinicopathologic valve in univariate and/or multivariate statistical analyses, including Kaplan-Meier survival plots. In-vitro studies were included only if they had a section in which their study also included: retrospectively collected PTC patient data, quantitative miRNA expression level analysis of formalin fixed paraffin embedded (FFPE) tissue and, then, compared the miRNA expression levels to the retrospectively collected clinicopathologic factors. 9 studies were excluded due to the same exclusion criteria above which were unrecognisable from abstract screening. In depth, the excluded studies lacked statistical clinicopathologic comparisons with miRNAs; instead, these studies focused on biomolecular mechanisms of miRNAs, or miRNAs as possible diagnostic biomarkers. Furthermore, one study was excluded due to its statistical comparison of PTCs as a cohort of differential thyroid cancers instead of only PTC tumours. No contact with the authors was required. The key principal summary measures used included the direction of dysregulation, p-values, the number of samples and controls, and, if applicable, hazard ratios/odds ratios.

The data was then extracted with the microRNA, the relative direction of microRNA dysregulation (up or down), p-valve, and sample sizes in relation to their clinicopathologic group and study were collected. Most importantly, only statistically significant associations were included. All the information was then grouped into tables according to recurrence/follow-up data and clinicopathologic data. (Supplementary Tables 1 and 2)

Studies included in analysis (Table 1)

According to the objectives, studies were split into two groups for separate analyses. The two cohorts consisted of: one group for analysis of miRNAs in recurrent and non-recurrent PTC patients (Table 1: studies in green and blue) and another group for analysis of miRNAs and PTC’s clinicopathologic factors (Table 1: studies in black and blue).

Recurrence vs non-recurrence group (Supplemental Table 1)

11 studies were included in the recurrence group. For studies to be included they had to contain PTC patients with either a relapse-free survival analysis or a follow-up period, and include at least a univariate and/or multivariate analysis between both recurrent and non-recurrent patients’ miRNA expression profiles. Also, recurrent patient groups must have contained at least 5 patients (n)

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11 in the statistical analysis. Recurrence was defined as the reappearance of a PTC tumour in local, regional (LNM), and/or distant locations during a follow-up of an initially treated PTC patient.

MiRNAs vs PTC’s clinicopathologic factors group (Supplemental Table 2)

22 studies analysing associations between different clinicopathologic factors and quantitative miRNA expression levels were included in this group. The clinicopathologic factors included were: age, sex, tumour size, bilateral tumours, multifocality (MF), extrathyroidal invasion (ETI), vascular invasion (VI), LNM, distant metastasis, TNM stage, AMES risk, AJCC risk, and MACIS risk. For studies to be included, they had to demonstrate at least one quantitative miRNA expression that had a statistically significant association with any of the above clinicopathologic factors. The direction of miRNA dysregulation, P-value, sample sizes and additional associations were listed (Supplemental

Table 2).

Risk of Bias

The risk of bias of individual studies was evaluated using a modified Newcastle-Ottawa Scale (NOS) for observational studies. The NOS scale uses a ‘star system’ with 8 multiple choice questions to assess the quality of nonrandomised studies on the basis of three broad perspectives: the subject groups, comparability of groups and exposure (in case-control studies) or outcome (in cohort studies). Studies with high quality responses to the set of questions earn a star with a maximum allocation of 9 stars. Briefly, studies were given up to 4 stars for the selection of cases criteria, 2 stars for comparability, and 3 stars for exposure criteria. The results of each criterion for each individual study are listed (Supplementary Table 3). To summarise, almost all studies were of high-quality. In the selection criteria group, 28 studies received all 4 stars, 2 studies received 2 stars, and only 1 study had 1 star. For comparability, 7 studies earned 2 stars, and 24 studies were given 1 star. Finally, for exposure, all 31 studies received 3 stars.

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12 Studies included in systematic review and qualitative analyses

Table 1: miRNA expression profiling studies and methods Author

[Reference]

Year Region Expression Method

Total miRNAs

Total no. of samples n (sample/control) Jahanbani et al. [17] 2018 Kuwait qRT-PCR 9492 113 (101/12) Todorović et al. [18] 2018 Serbia qRT-PCR 84 84 (42/42 NT) Zhang, Yanqing et al. [19] 2017 China qRT-PCR 318 106 (85/21) Rosignolo et al. [20] 2017 Italy qRT-PCR 754 64 (44/20) Dai et al. [21] 2017 China qRT-PCR 624 78 (24/54) Hu et al. [22] 2017 China qRT-PCR 2538 846 (266/ 280 NG, 300 HC) Qiu et al. [23] 2017 China Semi-quantitative PCR 146 146 (73/73) Zhang, M et al. [24] 2017 China qRT-PCR 120 Tissue: 120 (60/60) Serum: 140 (70/70) Sun, Jing et al. [25] 2017 China qRT-PCR 128 128 (64/64) Zhao et al. [26] 2016 China qRT-PCR 120 120 (60/60) Dong et al. [27] 2016 China qRT-PCR 60 60 (30/30) Aragon Han

et al. [28] 2016 USA qRT-PCR 1659 237 (N/A)

Mancikova et al. [29] 2015 Spain qRT-PCR 808 127(110/17 NT) Deng et al. [30] 2015 China Real-time PCR 60 60 (60/0) Sondermann et al. [31]

2015 Brazil Real time PCR 264 66 (19 R/47 NR) Xiong et al. [32] 2015 USA TCGA Dataset 496 496 (N/A) Sun, Mei et al. [33] 2015 China qRT-PCR 736 368 (128/120 NG, 120 HC) Salajegheh et al. [34] 2015 Australia qRT-PCR 121 121 (101/21) Guo et al. [35] 2015 China Microarray, qRT-PCR 386 77 (57PTC/10NT, 10NG) Acibucu et al. [36] 2014 Turkey qRT-PCR 231 77 (57/20) Peng et al. [37] 2014 China Microarray, qRT-PCR 510 102 (36 PTC/15 NG, 51 NT)

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13 Dettmer et al. [38] 2014 Switzerland qRT-PCR 768 80 (72/8) Chou et al. [39] 2013 Taiwan Real-time PCR 71 71 (R:30/NR:41) Lee et al. [40] 2013 Australia Microarray and qRT-PRC 872 Tissue: 31(9 R/17 NR, 5 NC) Serum: 78 (42PTC/36 NG) Yang et al. [41] 2013 China qRT-PCR, 480 40 (20/20) Wang et al. [42] 2013 China Microarray, qRT-PCR 455 91 (25/66) Wang et al. [43] 2013 China Microarray, qRT-PCR 348 87 (51/36) Dettmer et al. [44] 2013 Switzerland qRT-PCR 748 52 (44/ 8 NT) Huang et al. [45] 2013 China Microarray, qRT-PCR 276 138 (69/69) Linwah (Yip) et al. [46] 2011 USA Microarray and qRT-PCR 319 32 (17 R/ 15 NR) Chou et al. [47] 2010 China qRT-PCR 348 116 (100/16)

NT: normal thyroid tissue, NG: nodular goitre, R: recurrence group, NR: non-recurrence group, HC: healthy controls, PTC: papillary thyroid cancer, qRT-PCR: Quantitative real-time reverse transcription polymerase chain reaction, TCGA: The National Cancer Institute’s Cancer Genome Atlas, N/A: not available. Studies in green and blue were part of the recurrence vs non-recurrence miRNA analysis. Studies in black and blue were part of the clinicopathologic features vs miRNA analysis.

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SYSTEMIZATION AND ANALYSIS OF DATA

Fig. 1. Flowchart of the study selection Notes:

1. All criteria can be found under the screening section of the study (pg. 9), 2. Reasons are found under the eligibility section of the study (pg. 10).

Records identified through PubMed database search

(n = 107)

Additional records identified through other sources

(n = 2)

Records after duplicates removed (n = 109) Records screened (n = 109) Records excluded according inclusion/exclusion criteria1 (n = 68) Full-text articles assessed for eligibility

(n = 41)

Full-text articles excluded with reasons 2 (n = 10) Studies included in qualitative synthesis (n = 31) Ide nt if ic at ion Inc lude d E li gi bi li ty S cr ee ni ng Recurrence vs non-recurrence group (n = 11) MiRNAs vs PTC’s clinicopathologic factors group (n = 22)

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ANALYSIS OF DATA

Recurrence vs non-recurrence group (Supplemental Table 1)

Table 2: miRNA directions in recurrence-included group showing statistical association in at least two studies

miRNAs in the same direction

Reference of study Expression

upregulated (↑) or downregulated (↓) Total Sample Size (n) 146b [19]†_{, [20]}†_{, [46], [40], [23],} [21], [35], [39]* Up (↑) 378 222 [19]†_,_{[46], [40],}_{[21], [44]} _{Up (↑)} ₁₇₄ 221 [19]†_{, [20]}†_,_[21] _{Up (↑)} ₁₁₉ 21 [31]*, [21] Down (↓) 144 9 [31]*, [21] Down (↓) 144 Conflicting miRNAs 21 [35] Up (↑) 57 [31]*, [21], Down (↓) 144

†: measured from serum sample, *: multivariate analysis statistically significant (p value <0.05)

The 11 studies included in recurrence analysis, found 3 miRNAs that demonstrated consistent upregulation in at least two studies and 2 miRNAs with consistent downregulation in at least two studies. The upregulated miRNA were: firstly, miRNA-146b which was upregulated in 8 studies with a total sample size of 321 (n). Secondly, miRNA-222 showed upregulation in 5 studies with a total sample size of 174 (n). Finally, miRNA-221 was upregulated in 3 studies with a total sample size of 119 (n). The downregulated miRNA were: miRNA-21 and miRNA-9 that were both downregulated in two studies and both had a total sample size of 144 (n) each. In addition, two studies for miRNA-146b and miRNA-221, and one study for miRNA-222 found statistically significant upregulation of miRNAs in peripheral serum samples. In two studies, using multivariate analysis, Cox proportional hazard models of miRNA-21, miRNA-9, and miRNA-146b were found to have significant expression levels as independent prognostic factors for recurrence in PTC.

Conflicting miRNAs were miRNAs in which studies demonstrated opposite dysregulation in separate studies. As seen above, 1 study found miRNA-21 to be upregulated with total sample size of 57 (n) and two studies found miRNA-21 to be downregulated with a total sample size of 144 (n).

Overall, this study has found miRNA-146b as the most consistently upregulated miRNA associated with recurrence and/or a poorer relapse-free survival.

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16 Multivariate analyses – independent prognostic factors for recurrence or relapse-free survival rate

Table 3: miRNAs included in multivariate analyses

Author [Reference] miRNA HR (95% CI) or OR P-valve

Dai et al. [21] 221 1.41(1.14–1.95) 0.007 222 1.86(0.76–5.65) 0.226 Chou et al. [39] 146b 3.92(1.73-8.86) <0.05 Sondermann et al. [31] 9 1.48(1.24-1.77) <0.001 10b 1.24(0.84-1.81) 0.276 21 1.52(1.18-1.94) 0.001 146b 0.94(0.74-1.19) 0.599

Guo et al. [35] 146b N/A 0.769

21 N/A 0.975

Dettmer et al. [44] 181a-2-3p OR: 0.136 <0.05

99b OR: 0.170 <0.05

MiRNAs in bold are statistically significant (P<0.05) HR: hazard ratio, CI: confidence interval, OR: odds ratio, N/A: not available.

Of the 11 studies included, 5 performed multivariate Cox regression analysis on their selected miRNAs which initially showed univariate statistical significance. After correcting for clinicopathologic and other factors, miRNAs: -221, -146b, -9, -21, -181a-2, -99b all demonstrated significant associations as independent prognostic markers of recurrence or poor relapse-free survival rates (Table 3). However, miRNA-146b did not reach statistical significance in two studies (P=0.599 and 0.769, respectively) and miRNA-21 did not reach multivariate statistical significance in one study (P=0.975). Then again, miRNA-21 was an independent prognostic marker for recurrence but not for poorer relapse-free survival rates.

Overall, this results in no two studies demonstrating a reliable and reproducible multivariate statistical association for the same miRNA as an independent prognostic marker for recurrence in this systematic review. The limited amount of studies available that are performing similar multivariate analysis is a limitation in these results. Nonetheless, these miRNAs show great promise for further research as independent prognostic biomarkers.

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17 MiRNAs vs PTC’s clinicopathologic factors group (Supplemental Table 2)

Table 4 – miRNAs with statistical associations correlated to prognostic factors in at least two studies Prognostic

feature

miRNA Reference of study Expression

upregulated (↑) or downregulated (↓) Total Sample size (n) Extra-thyroidal invasion 146b [19]†_,_[33]†_{, [36], [41], [42], [47]} _{Up (↑)} ₄₉₈ 221 [19]†_,_{[36], [41], [42],}_[47] _{Up (↑)} ₃₇₀ 222 [19]†_,_[36]_,_{[41], [42]}_,_[47] _{Up (↑)} ₃₇₀ Metastatic lymph node 146b [19] †_,_{[23], [28]*, [30],}_[36] _{Up (↑)} ₅₁₂ 222 [19]†_,_{[28]*, [36]} _{Up (↑)} ₃₇₉ 221 [19]†_,_[36] _{Up (↑)} ₁₄₂ 146a [23], [33] Up (↑) 201 TNM Stage I/II vs III/IV 146b [19]†_,_[42] _{Up (↑)} ₁₇₆ 222 [19]†_,_[42] _{Up (↑)} ₁₇₆

†: measured from serum sample, *: multivariate analysis statistically significant (P-value <0.05)

In this systematic review, 22 studies were included in the clinicopathologic factor group comparing miRNA expression levels with specific clinicopathologic features (Supplemental Table 2). Univariate analysis compared miRNA expression differences between PTC patients with a specific cliniopathologic feature against those without it. Extra-thyroidal invasion, metastatic lymph node, and TNM stage I/II vs III/IV were the prognostic factors which featured statistically significant associations correlated to miRNAs in at least two studies (Table 4).

Patients with extra-thyroidal invasion presented with 3 upregulated miRNAs which were miRNA-146b, miRNA-221, and miRNA-222. MiRNA-146b showed significant upregulation (P<0.05) in 6 studies with a total sample size of 498 (n). MiRNA-221 and miRNA-222 showed significant upregulation (P<0.05) in 5 studies with a total sample size of 370 (n) each. MiRNA-146b had statistical associations (P<0.05) for LNM in 2 studies which measured miRNA expression levels from peripheral blood. Meanwhile, miRNA-221 and miRNA-222 both demonstrated significance (P<0.05) for LNM in one study with samples collected from peripheral blood.

Studies comparing PTC patients with LNM showed 4 upregulated miRNAs (miRNA-146b, miRNA-222, miRNA-221, and miRNA-146a) that established statistical associations (P<0.05) in at least two studies. The miRNA with the most studies was miRNA-146b with 5 studies establishing statistical significance between LNM positive and LNM negative patients (P<0.05) with a total sample size of 512 (n). Additionally, miRNA-222 demonstrated 3 studies which had statistical significance

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18 with LNM (P<0.05); it had a sample size of 379 (n). Finally, miRNA-221 and miRNA-146b both had 2 studies demonstrating statistical significance (P<0.05) for LNM with a sample size of 146 and 201 (n), respectively.

Lastly, there was 2 miRNAs (miR-146b and miR-222) which both displayed statistical significance (P<0.05) in two studies correlated for TNM stage I/II against III/IV stage patients. One of these studies used samples from peripheral blood.

In one study[28]_{, multivariable logistic regression analysis with adjusting variables for} molecular markers (BRAF mutation and miRNAs), tumour size, age, sex, multifocality, vascular invasion, positive surgical margins, ETI, and histological subtypes displayed miRNA-146b-3p to be an independent prognostic marker of cervical LNM (P= 0.03). Furthermore, in the same study, a separate multivariable logistic regression analysis was done using patient’s data that is only available preoperatively (molecular markers, sex, age, and tumour size). This demonstrated miRNA-146b-3p (P = 0.01), miRNA-146b-5p (P = 0.01), and miRNA-222 (P=0.01) to have a significant ability to act as independent prognostic markers for cervical LNM.

Overall, in this systematic review, miRNA-146b expressions levels were the most consistently upregulated for all 3 prognostic factors and it also demonstrated its ability to act as an independent prognostic marker for cervical LNM.

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DISCUSSION

This systematic review has revealed miRNAs that show strong statistically significant associations with prognostic factors of PTC. To the extent of my knowledge, this is the first systematic review to investigate associations between recurrence and miRNAs in PTC.

To summarise, miRNAs-146b, -221, and -222 expression levels were identified as consistently upregulated in several clinical features related to poor prognosis in PTC. This does not necessarily support a causative role of miRNA but it could indicate that miRNA dysregulation is a key molecular event in PTC development. It is well-known that many dysregulated miRNAs play a role in tumour initiation and progression of tumours[48]_{. Especially, in in-vitro studies, where miRNA} molecular mechanism studies have shown they induce migration and invasion of PTC cells[30,49]_. Therefore, according to our findings, one could hypothesize that these upregulated miRNAs (146b, -221 and -222) predispose cells to aggressive molecular features leading them to sequentially develop worse prognostic features, such as: ETI, LNM, large tumour size, and a higher risk of recurrence. These prognostic features can be seen in Table 2 and Supplemental Table 2 revealing the upregulated miRNAs.

In all 31 included studies, a total of 12 upregulated miRNAs (miRNA21, 182, 203, 221, 222, 451, 2861, 135b, 146a, 146b, 199b, and 92a) and 18 downregulated miRNAs (miRNA16, -32, -101, -126, -137, -139, -142, -143, -144, -205, -222, -451, -613, -940, -15a, -193a, -20a, and -20b) had statistically significant associations with prognostic factors (Supplemental Table 2). This extensive list is possible because many studies searched for novel miRNAs related to PTC. However, those studies which compared similar PTC-associated miRNAs found both consistent and conflicting results. A large high-quality multi-analysis study is required to validate and consolidate this research. For clinical relevance, further additional factors must be considered such as genetic variations within different populations.

To fully utilise miRNAs in a clinical setting further academic work is required in both theory and clinical practice. In theory, a more detailed and scientifically proven understanding of miRNA molecular biology around tumorigenesis and progression of PTC is required. Understanding such complex processes would allow further ideas in targeting key areas of tumorigenesis with the goal of understanding, epigenetically, why certain patients develop such poor prognosis. Practically, the aim is for epigenetic directed treatments and biomarkers to spur from such theory. In clinical practice, the significance of such research would depend on how miRNA processes vary between different populations and the reliability of the research. Additionally, practical issues may limit their use in

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20 clinical practice, for instance, difficulties in applying complex treatments or problems in the complexity of measuring epigenetic molecules in routine practice.

This study also noted that while miRNA expression levels had statistically significant dysregulations, many quantitative expression levels of miRNA and their interquartile ranges overlap between sample and control groups. This may limit miRNA use as a prognostic biomarker because extrapolating a meaningful cut-off point for reference ranges in clinical practice would lead to poor sensitivities. This could render the biomarker test equivocal for clinical practice.

Limitations of this systematic review consisted of discrepancies in individual study methods, risk of bias in the systematic review, lack of meta-analysis, and a wide-range of different statistical models in the studies. While most studies were of high-quality, many individual differences between studies increase the chance of systematic reporting bias. These differences consisted of: (i) differences of control groups. For example, many studies used adjacent normal thyroid tissue as control, meanwhile, others used PTC tissue from healthy volunteers, and others even added multinodular goitre groups to analyse their significance. (ii) Different methods of performing qRT-PCR and different types of microarrays can skew results and make them incomparable. (iii) Slight differences within comparisons groups (e.g. one study included prophylactic LN dissection patients, meanwhile, others who only included therapeutic LN dissection patients). (iv) Lack of multi-variate analyses in most studies. The risk of bias pitfalls, in this systemic review, includes an increased chance of reporting bias because this study focused only on statistically significant results and non-significant results were not included in the interpretation of results, also only a single author was involved in conducting the systematic search.

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CONCLUSION/RECOMMENDATIONS

Recurrence vs non-recurrence miRNA significance

To conclude, this study has found miRNA-146b, -221 and -222 as the most consistently upregulated miRNAs associated with recurrence and/or a poorer relapse-free survival rate. Further high-quality prospective studies are needed to validate its significance as a specific recurrence miRNA prognostic marker and provide insights as a possible target for prevention, risk stratification and treatment of PTC.

Prognostic clinical factors and miRNAs

Overall, in this systematic review, miRNA-146b, -221 and -222 expressions levels were the most consistency upregulated for patients with LNM, EVI, and a higher TNM stage. MiRNA-146b also demonstrated its ability to act as an independent prognostic marker for cervical LNM (P<0.05). Further large sample, high-quality prospective studies are needed to validate these results.

Clinical relevance and future implications

It is well known that accurate stratification and clinical evaluation of PTC patients play crucial roles in determining the prognosis of PTC. Recently, miRNAs show great promise in aiding such processes. If not directly as a biomarker, than indirectly once miRNA’s biological role in oncogenesis is further understood.

Directly, large well-designed future prospective studies are needed to evaluate the prognostic significance of miRNAs. Ideally, candidate miRNA biomarkers need to be evaluated with the utilisation of ROC curves to determine sensitivity and specificity for clinical practice. Most importantly, the valve of miRNA and time-to-recurrence should be evaluated in a prospective high-quality multi-variate analysis. If significant time-to-recurrence miRNAs were found and were used with individualised patient details, this could allow the effective screening of PTC recurrence and allow PTC tumours to be caught at an earlier-asymptomatic stage, and, therefore, allow earlier radical treatment.

Indirectly, in-vitro studies must continue building and studying the complex epigenetic genome of miRNA and their relationship with biologic processes (such as oncogenesis). This allows for the advancement of molecular biology and may be of use by unseen future biomedical technologies.

Most importantly, this systematic review has found miRNAs -146b, -221 and -222 as ideal candidates for further research which is consistent with current literature.

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27

ANNEX

Supplemental Table 1.1: miRNA statistical associations between recurrence and nonrecurrent PTC Author [Study Reference] Dysregulated microRNA p-value and/or HR Follow-up: Median months (range) Re cu rr en t sam p le s iz e (n ) N on re cu rr en t sam p le s iz e (n ) M axi m u m N on re cu rr en ce ti m e p er iod ( yr s) A d d it ion al S tat is ti cal A ss oc iat ion s Zhang, Yanqing [19] †_{↑: 146b, 222,} 221 0.001, <0.001, <0.001 N/A (TTR: 52(10-124)) 12 9 1 ETI, advanced (III/IV) TNM stage, LNM, bilateral tumours Rosignolo [20] ↑: 146a†_{, 221}† _<0.05, <0.05. 14.4 (12-24) 5 15 1-2 Tg-negative tumours Yip, Linwah [46] ↑: 146b, 222, ↓: 130b, 34b 0.0031, 0.0177, 0.0197, 0.0172 102 (0.48-312) 17 15 Mean: 6.1 miR: 34b, 1: possible MET gene target. 146b: BRAF+ Lee [40] ↑: 146b, 222, 0.038, 0.014, RC: 72 (15-216), NR: 24 (12-60) 9 17 Median: 2(1-5) BRAF+ (miRNA: +221), Qiu [23] †_{↑: 146a, 146b 0.0086,} 0.0176 12 (12-12) 17 56 1 LN metastasis, sig. lower survival time Sondermann [31] ↓: 9*, 21* <0.001, 0.001 120 (N/A) 19 47 10 Tumour size, ETI, higher risk ATA, advanced TNM stages. Dai [21] ↑: 146b, 220, 221, 222 ↓: 9, 21 0.015, 0.005, <0.001, <0.001, <0.001, <0.001. 68 (8-158)

24 54 10 High ATA risk

class, larger primary tumour, higher TMN stages, ETI, CLNM Mancikova [29] ↑: Let-7a-3p*, ↓:192-3p* KM RFS: 0.0321, 0.0357 72 (41-96), 24 (10-36) 25 25 11.7

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28 Cont. Supplemental Table 1.2

KM RFS: Kaplan-Meier relapse-free-survival analysis p value, HR: hazard ratio, *: multivariate adjusted p value, †: measured from serum sample. ↑: upregulated miRNA, ↓: downregulated miRNA, TTR (range): time-to-recurrence (range), ~: roughly, RC: recurrence group, NR: non-recurrence group. Sig.: significant. (C)LNM: (cervical) lymph node metastasis, ETI: extra-thyroidal invasion, N/A: not-available. Tg: thyroglobulin Author [Study Reference] Dysregulated microRNA p-value and/or HR Follow-up: Median months (range) Re cu rr en t sam p le s iz e (n ) N on re cu rr en t sam p le s iz e (n ) M axi m u m N on re cu rr en ce ti m e p er iod ( yr s) A d d it ion al S tat is ti cal A ss oc iat ion s Dettmer [44] ↓: 181a-2-3p*, 99b-3p* ↑: 222 (univariate) KM RFS <0.002, <0.018, <0.05 55.9 (±54) 9 8 9.2 Guo [35] ↑: 146b, 21 KM RFS: <0.05, <0.05 N/A (~1-250) 57 N/A Chou (2013) [39] ↑ 146b*, KM RFS:<0.05 ,HR: 3.92 (1.73-8.86) 127 (±29.8) 30 4 1 10.8 (±1.86) BRAF, CLNM, advanced tumour stage <0.005, 0.02*

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29 Supplemental Table 2.1: miRNA associated with PTC’s clinicopathologic factors

Clinicopathologic feature comparisons (n1) vs (n2) Author [Reference] D ys re gu lat ed m ic roR N A P-value S am p le s iz e n o. (n1 ) S am p le s iz e n o. (n2 ) T ot al s am p le s A d d it ion al A ss oc iat ion s

Age: <45y vs ≥ 45y Wang [42] ↓: 222 0.048 51 40 91 Sex: Female vs male Wang [42] ↓: 222 0.002 61 30 91 Sun, M [33] ↑146a, ↑146b 0.009, 0.008 98 30 128 Tumour size: <2cm vs >2cm Zhang, Yanqing [19] ↑:222 † _0.024 ₆₄ ₂₁ ₈₅ >2cm <4cm vs >4cm or outside thyroid Xiong [32] ↓: 126-3p <0.001 79 68 147 <2cm vs >4cm or outside thyroid ↓:126-3p <0.001 79 66 145 <3cm vs ≥3cm Wang [42] ↑: 146b, 222, 135b 0.018, 0.008, 0.024 56 35 91 Unilateral vs bilateral tumour Zhang, Yanqing [19] †_↑:146b, 221, 222 0.008, 0.032, 0.041 46 39 85 Hu [22] ↓: 940, 15a <0.05, <0.05 184 82 266 IL-23 Multifocal tumour vs non-multifocal tumour Zhang, Yanqing [19] †_{↑: 221} _0.031 ₂₀ Yes 65 85 Acibucu [36] ↑: 146b 0.014 22 35 57 Sun [33] ↑: 146a 0.002 77 51 128 Extra-thyroidal invasion vs no-extra-thyroidal invasion Zhang, Yanqing [19] †_↑146b, 221, 222 0.012, 0.010, <0.001 17 68 85 Acibucu [36] ↑: 146b, 221, 222 0.001, 0.001, 0.001 19 38 57 Chou (2010) [47] ↑: 146b, 221, 222 0.003, 0.013, 0.050 46 54 100 Yang [41] ↑: 146b-5p, 221, 222 ↓: 16, 613 <0.05, <0.05, <0.05, <0.05, <0.05 17 20 37

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30 Cont. Supplemental Table 2.2: miRNA associated with PTC’s clinicopathologic factors Clinicopathologic feature comparisons (n1) vs (n2) Author [Reference] D ys re gu lat ed m ic roR N A P-value S am p le s iz e n o. (n1 ) S am p le s iz e n o. (n2 ) T ot al s am p le s A d d it ion al A ss oc iat ion s Cont. extrathyroidal invasion vs no-extrathyroidal invasion Wang [42] ↑: 135b, 146b, 221, 222 0.006, 0.001, 0.019, 0.004 25 66 91 Jahanbani [17] ↓: 144-3p, 15a-5p, 32-5p, 20a-5p 0.016, 0.015, 0.045, 0.049 27 12 39 Xiong [32] ↓:126-3p <0.001 72 134 206 Peng [37] ↑: 199b-5p 0.047 9 27 36 Sun [33] ↑: 146a, 146b, 146b† 0.011,0._001, 0.021 59 69 128 Hu [22] ↓: 940, 15a, 16 <0.05, <0.05, <0.05 111 155 266 IL-23 Vascular invasion vs no vascular invasion Acibucu [36] ↑: 146b, 221, 222 0.001, 0.001, 0.001 13 44 57 Metastatic lymph node (e.g. cervical) vs no LN metastasis Zhang, Yanqing [19] †_{↑: 146b,} 221, 222 0.007, 0.001, 0.008 59 26 85 Acibucu [36] ↑: 146b, 221, 222 0.001, 0.001, 0.001 16 41 57 Hu [22] ↓: 940, 15a, 16 90 176 266 IL-23 Qiu [23] ↑: 146a, 146b 0.0078, 0.0097 36 37 73 Wang [43] ↑: 2861, 451 0.004, 0.026 51 36 87 Deng [30] ↑: 146b-5p <0.05 30 30 60 ↓: ZNRF3 Zhao [26] ↓: 101 0.03 10 68 78 USP22 Dong [27] ↓: 137 <0.01 8 22 30 CXCL12 Salajegheh [34] ↓: 205 <0.05 25 26 51 Peng [37] ↑: 199b-5p 0.010 21 15 36 Sun [33] ↑: 146a 0.006 39 89 128 Huang [45] ↑: 21 0.005 0

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31 Cont. Supplemental Table 2.3: miRNA associated with PTC’s clinicopathologic factors Clinicopathologic feature comparisons (n1) vs (n2) Author [Reference] D ys re gu lat ed m ic roR N A P-value S am p le s iz e n o. (n1 ) S am p le s iz e n o. (n2 ) T ot al s am p le s A d d it ion al A ss oc iat ion s Cont. metastatic lymph node (e.g. cervical) vs no LN metastasis Todorović [18] ↑: 92a, 92a* 0.012, 0.036 (OR: 4.703) 10 26 36 Zhang M [24] ↓: 451 0.006, 9 45 54 Zhang M [24] ↓: 451 (serum cohort) 0.017 18 52 70 Aragon Han [28] 146b-3p, 146b-5p, 221, 222. Postop cohort: 146b-3p*, 146b-5p*. Preop cohort: 146b-3p*, 146b-5p*, 222*. 0.01, <0.01, 0.04, <0.01. 0.03, 0.02. 0.01, 0.01, 0.01. 101 136 237 BRAF mutation, tumour size, multi-focality*, lymph vascular invasion*, ETE*, advanced AJCC stage Distant metastatis vs none Acibucu [36] ↑: 146b, 221 0.028, 0.011 4 53 57 Hu [22] ↓: 940, 15a, 16 <0.05, <0.05, <0.05 21 245 266 IL-23 Jahanbani [17] ↓: 144-3p, 15a-5p, 32-5p, 20a-32-5p, 143-3p, 20b-5p, 142-5p 0.011, 0.002, 0.001, 0.013, 0.010, 0.002, 0.013 25 14 39 ACO – PTC vs

none-ACO Dettmer [38] ↓: 139-5p, 193a-5p, 451. ↑: 182, 222 0.0066, 0.0066, 0.0292, 20 8 28

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32 Cont. Supplemental Table 2.4: miRNA associated with PTC’s clinicopathologic factors

↑: upregulated miRNA, ↓: downregulated miRNA, *: multivariate analysis statistically significant, †: sample taken from peripheral blood, ETE: extrathyroid extension, CLNM: cervical lymph node metastatis, LN: lymph node, MS: metastasis, Preop: preoperative, Postop: postoperative, AJCC: American Joint Committee on Cancer Staging; RFS: relapse free survival, ACO: Adverse clinical outcome group is defined when a patient had at least one of outcomes: local relapse after first radioiodine therapy, distant metastases or tumour associated death. MACIS is a prognostic scoring

Clinicopathologic feature comparisons (n1) vs (n2) Author [Reference] D ys re gu lat ed m ic roR N A P-value S am p le s iz e n o. (n1 ) S am p le s iz e n o. (n2 ) T ot al s am p le s A d d it ion al A ss oc iat ion s TNM Stage

I/II vs III/IV Zhang, Yanqing [19] †_{↑: 146b,} 221, 222 0.001, <0.001, <0.001 56 29 85 Wang [42] ↑: 146b, 222 0.004, 0.0001 56 35 91 Dong [27] ↓: 137 <0.01 9 21 30 CXCL12 I/II vs III Hu [22] ↓: 940, 15a, 16 <0.05, <0.05, <0.05 42 202 244 IL-23 I/II vs IV Hu [22] ↓: 940, 15a, 16 <0.05, <0.05, <0.05 22 202 224 IL-23

I, II, III, IV Acibucu [36] ↑: 221 0.016 29 5 46 9 89

III/IV Sun [33] ↑: 146a,

146b, 146b (blood) 0.014, 0.008, 0.029 27 51 78

II vs III/IV Sun [33] ↑: 146a, 146b, 146b (blood) 0.028,0. 017, 0.047 27 51 78

AMES high vs low risk Zhang, Yanqing [19] †_{↑: 146b,} 221, 222 0.001, 0.002, <0.001 13 72 85

AJCC high risk vs

low risk Chou (2010)[35] ↑: 146b, 221 0.042, 0.013 38 62 100 BRAF mutation mutant vs wild type Chou (2010) [35] ↑: 146b <0.001 46 54 100 Huang [45] ↑: 21, 203 0.009, 0.013 33 36 69

MACIS risk high vs low

Xiong [32] ↓: 126-3p <0.01 16 83 99 MACIS risk

moderate vs low

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33 system used in the TCGA database which is based on the presence of Metastasis, patient Age, Completeness of resection, local Invasion, and tumour Size.

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34 Supplemental Table 3.1 – Risk of bias of individual studies

Author Jah an b an i T od or ovi ć Z h an g, Y an q in g R os ign ol o D ai Hu Qiu Z h an g, M S u n , Ji n g Z h ao D on g A ragon H an M an ci k ova D en g S on d er m an n Year 2018 2018 2017 2017 2017 2017 2017 2017 2017 2016 2016 2016 2015 2015 2015 Criteria Selection Bias Adequate Case Definition * * * * * * * * * * * * * * * Representativeness of the cases * * * * * * * * * * * * * * * Selections of controls * * * * * * * * * * * * * * Definition of Controls * * * * * * * * * * * * * * Comparability * * * * * ** * ** * * * ** * * * Exposure Ascertainment of exposure * * * * * * * * * * * * * * * Same method of ascertainment for cases

and controls

* * * * * * * * * * * * * * *

Non-response rate * * * * * * * * * * * * * * *

Newcastle-Ottawa Scale (NOS) for observational scale was used. *: high quality answers earn a star. Studies were given up to 4 starts for the selection of cases criteria, 2 stars for comparability, and 3 stars for exposure criteria. A maximum of 9 stars per study is possible.

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35 Cont. Supplemental Table 3.2 –Risk of bias of individual studies

Author X ion g Sun, M ei S al aj egh eh G u o Ac ib u cu P en g De tt m er C h ou Le e Y an g Wan g Wan g De tt m er H u an g L in w ah (Y ip ) C h ou Year 2015 2015 2015 2015 2014 2014 2014 2013 2013 2013 2013 2013 2013 2013 2011 2010 Criteria Selection Bias Adequate Case Definition * * * * * * * * * * * * * * * * Representativeness of the cases * * * * * * * * * * * * * * Selections of controls * * * * * * * * * * * * * * Definition of Controls * * * * * * * * * * * * * * * Comparability * ** * * * * ** ** * * * * ** * * * Exposure Ascertainment of exposure * * * * * * * * * * * * * * * * Same method of ascertainment for cases