Abstract
Objectives
Lymphovascular invasion (LVI) is a critical risk factor for lymph node metastasis (LNM), which requires additional surgery after endoscopic resection of T1 colorectal cancer (CRC). However, the impact of additional staining on estimating LNM is unclear. This systematic review aimed to evaluate the impact of additional staining on determining LNM in T1 CRC.
Methods
We searched five electronic databases. Outcomes were diagnostic odds ratio (DOR), assessed using hierarchical summary receiver operating characteristic curves, and interobserver agreement among pathologists for positive LVI, assessed using Kappa coefficients (κ). We performed a subgroup analysis of studies that simultaneously included a multivariable analysis for other risk factors (deep submucosal invasion, poor differentiation, and tumor budding).
Results
Among the 64 studies (18,097 patients) identified, hematoxylin–eosin (HE) and additional staining for LVI had pooled sensitivities of 0.45 (95% confidence interval [CI] 0.32–0.58) and 0.68 (95% CI 0.44–0.86), specificities of 0.88 (95% CI 0.78–0.94) and 0.76 (95% CI 0.62–0.86), and DORs of 6.26 (95% CI 3.73–10.53) and 6.47 (95% CI 3.40–12.32) for determining LNM, respectively. In multivariable analysis, the DOR of additional staining for LNM (DOR 5.95; 95% CI 2.87–12.33) was higher than that of HE staining (DOR 1.89; 95% CI 1.13–3.16) (P = 0.01). Pooled κ values were 0.37 (95% CI 0.22–0.52) and 0.62 (95% CI 0.04–0.99) for HE and additional staining for LVI, respectively.
Conclusion
Additional staining for LVI may increase the DOR for LNM and interobserver agreement for positive LVI among pathologists.
Keywords: colorectal cancer, hematoxylin, lymph node metastasis, meta‐analysis, staining
INTRODUCTION
Colorectal cancer (CRC) is the third most common cancer worldwide and the second leading cause of cancer‐related death. 1 , 2 Two main curative treatments for CRC include endoscopic and surgical resections. 3 With the advent of advanced endoscopic techniques such as endoscopic submucosal dissection and endoscopic full‐thickness resection, the number of endoscopically treated patients with T1 CRC is increasing. 4 , 5 Histopathological evaluation of the risk of lymph node metastasis (LNM) is the key to determining the requirement of complete endoscopic resection. 6 , 7 Current treatment guidelines for CRC indicate that T1b (deep submucosal invasion depth [DSI] >1000 μm), lymphovascular invasion (LVI), poorly differentiated adenocarcinoma (PD), indolent cell carcinoma or mucinous carcinoma, and tumor budding (TB) grade 2 or 3 at the site of deepest invasion are risk factors for LNM in CRC. 3 , 6 , 8 Selection of an appropriate treatment, that is, endoscopic versus surgical resection, is critical because surgical resection is associated with the risk of surgery‐related morbidity and mortality, high surgical costs, and reduced patient quality of life, especially in patients with rectal cancer. 3 , 9 , 10
Some previous studies have reported LVI as a strong and reliable predictor of LNM (Table 1). 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 Current guidelines recommend hematoxylin–eosin (HE) staining to diagnose lymphatic and vascular invasion of the tumor. 8 , 12 Conversely, a previous study reported that additional staining had a higher diagnostic odds ratio (DOR) for LNM than HE staining (6.0 vs. 2.7). 19 The use of additional stains, such as D2‐40 for lymphatic invasion (LI) and elastic stains such as Victoria blue (VB) and Elastica van Gieson (EVG) stains for diagnosing vascular invasion (VI), varies among institutions and pathologists. 20 Some previous studies reported that additional staining had higher interobserver agreements among pathologists than HE staining. 21 , 22 However, no large studies or meta‐analyses reported the impact of additional staining for LNM in T1 CRC. The role of additional stains, such as D2‐40 immunostain for LI and elastic stains (VB or EVG stains) for VI, in improving the DOR for LNM and increasing interobserver agreement among pathologists remains unclear.
Table 1.
Overview of definitions of lymphovascular invasion and details of additional stains
| Author, year | Definition of lymphovascular invasion | Additional stains |
|---|---|---|
| JSCCR 2010, 11 2014, 12 2016, 13 2019 8 |
Lymphatic vessel invasion is defined as the invasion of the tumor cells into the lymphatic vessels. Blood vessel invasion is defined as the invasion of tumor cells into the blood vessels. |
When immunostaining is used to examine lymphatic invasion, it should be stated. e.g. Ly1a (D2‐40). When elastic fiber staining is used to examine venous invasion, it should be stated, e.g. V1a (VB) with Victoria blue staining, V1b (EVG) with Elastica van Gieson staining. When a tumor has an elastic plate confirmed at one‐half or more of its circumference, it is considered “V,” and when D2‐40‐positive endothelial cells are confirmed at one‐half or more of its circumference, it is considered “Ly.” Using this method, inconsistencies among individuals judging vascular invasions should be reduced. |
| World Health Organization 14 | Lymphovascular invasion is defined as the invasion of tumor cells into the blood and/or lymphatic vessels. | NA |
| The College of American Pathologists 15 | Lymphovascular invasion is classified as not identified, present, or indeterminate. | NA |
| The Korean Society of Pathologists 16 | Lymphatic or vascular invasion is considered present when tumor cells invade nonmuscle‐walled small vessels or large vessels with a smooth muscle layer and/or an elastic lamina layer. |
Immunohistochemical staining with D2‐40 may be performed additionally to identify the endothelial cells because it may be difficult to differentiate the lymphatic vessel from retraction artifacts with HE staining. Special stains for elastic fiber or immunohistochemical stains for CD31, D2‐40, and smooth muscle actin can be used if necessary. |
HE, hematoxylin–eosin; JCCRS, Japanese Society for Cancer of the Colon and Rectum; NA, not applicable.
Therefore, this systematic review and meta‐analysis aimed to assess the impact of using additional stains, such as D2‐40 and elastic stains, for LVI on estimating LNM in patients with T1 CRC. In addition, we assessed interobserver agreement among pathologists when employing these immunohistochemical staining methods.
METHODS
We followed the methodological standard outlines in the Cochrane Handbook for Systematic Review of Diagnostic Test Accuracy and the Preferred Reporting Items for Systematic Review and Meta‐Analysis of Diagnostic Test Accuracy (PRISMA‐DTA) (Appendix S1). 23 , 24 We registered the study protocol in the International Prospective Register of Systematic Reviews (PROSPERO, registration number: CRD42022382897) and published this protocol in OSF (https://osf.io/6f5qt/) on December 9, 2022 (Appendices S2,S3).
Search strategy
We searched the following databases: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (PubMed), and EMBASE (ProQuest Dialog) from inception until December 10, 2022. Appendix S2 shows the full search strategy. We also searched databases such as the World Health Organization International Clinical Trials Platform Search Portal (ICTRP) and ClinicalTrials.gov for ongoing trials. Our search strategy incorporated keywords associated with CRC, submucosal invasion, and LVI. We included all papers, including published articles, abstracts of conferences, and letters. We did not exclude studies based on the observation period, publication year, language, or country. We reviewed the reference lists of all included studies, international guidelines, 25 , 26 and articles citing eligible studies. We clarified additional data from the respective authors.
Study selection
We included studies that assessed the DORs of additional staining, such as D2‐40 immunostaining for LI and elastic staining (VB or EVG) for VI, and HE staining in patients aged over 18 years with T1 CRC who underwent endoscopic or surgical resection. We excluded case reports, case series, reviews, meta‐analyses, and duplicate cases. The reference standard was the presence of LNM in surgical specimens.
The primary outcomes were the sensitivity, specificity, and DOR of HE and additional staining for LVI to identify LNM in patients with T1 CRC. The secondary outcome was interobserver agreement among pathologists for positive LVI, calculated as Cohen's κ of interobserver agreement between two or more pathologists for positive LVI.
Data collection and risk of bias
Two of six reviewers (J.W. and A.M., H.S., M.H., M.T., or T.Y.) independently screened titles and abstracts and then assessed eligibility based on the full texts and extracted data. We contacted the original authors when relevant data were missing. We resolved disagreements between the two reviewers by discussion, and when this failed, a third reviewer acted as an arbiter (K.I. or Y.K.).
Two of four reviewers (J.W. and A.M., H.S., or M.H.) independently evaluated the risk of bias and applicability using the modified Quality Assessment of Diagnostic Accuracy Studies‐2 (QUADAS‐2) tool. 27 We revised the signaling questions in the QUADAS‐2 tool according to our present review questions (Appendix S4). We discussed disagreements between the two reviewers, and when this failed, a third reviewer (K.I. or Y.K.) acted as an arbiter. We did not examine publication bias for the DOR of the stains on identifying LNM due to a lack of appropriate statistical methods. 24
Data synthesis and statistical analysis
We estimated the sensitivities, specificities, and DORs of HE and additional staining for LNM in T1 CRC in each study using 95% confidence intervals (CIs). In the meta‐analysis, we used bivariate models to calculate the pooled estimates of sensitivity and specificity with 95% CI under the assumption that equal thresholds existed among various stains. The model accounted for within‐study and between‐study variabilities in the accuracy of test performance, including random effects. 28
We performed a random‐effect meta‐analysis to compare the adjusted ORs for the diagnostic accuracies of additional and HE staining for LVI (an independent risk factor for LNM). This analysis included only studies that incorporated other risk factors (DSI, PD, and TB) in a multivariable analysis. We calculated the κ value and standard error using the kappaetc, metan, and metareg modules. 29 , 30 , 31 , 32 , 33 We used Review Manager 5.4.1 (RevMan 2020; The Nordic Cochrane Centre, Copenhagen, Denmark) and STATA SE16 software (v. 16.1; StataCorp, College Station, TX, USA) with the midas and metandi packages. 34 , 35
Subgroup and sensitivity analyses
To elucidate the influence of effect modifiers on the results, we performed the following subgroup analyses for the impact of the studied stains for LVI in LNM: (i) EVG vs. VB staining; and (ii) Japan vs. other countries. Subgroup analysis according to additional staining indications (limited cases vs. all cases) was also added. Based on the Cochrane Handbook, we did not use univariate tests for sensitivity and specificity heterogeneity or estimates of the I 2 statistic because they did not account for heterogeneity explained by phenomena such as positive threshold effects. 24 However, to assess whether the results of the review were robust to the decisions made during the review process, we performed sensitivity analyses only for the following studies to identify the impact of the stains for LVI in LNM: (i) studies with patients who fully met our inclusion/exclusion criteria (exclusion of studies in which duplicate cases could not be completely ruled out and studies in which additional staining other than D2‐40 immunostaining for LI and elastic staining [VB or EVG] for VI were performed); (ii) those with patients who underwent primary and additional surgical resection; (iii) those with patients who underwent primary surgical resection; and (iv) those that compared additional staining with HE staining in the same patients or institution. We added sensitivity and specificity analyses of CD31 staining for VI.
RESULTS
Search results and study characteristics
Figure 1 shows the study selection process. We identified 3451 records from various databases until December 10, 2022. After screening for duplicates, we included 64 studies with 18,097 patients, 17 , 18 , 22 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 of them, 59 studies evaluated the diagnostic accuracies of HE and additional staining for LVI in LNM in patients with T1 CRC, four reported the interobserver agreement among pathologists for positive LVI, and one reported both outcomes, with eight studies comprising 4062 patients in multivariable analysis.
Figure 1.

Flowchart of the study selection process.
Table S1 presents the study characteristics of the diagnostic accuracies of HE and additional staining for LVI in LNM in patients with T1 CRC: of the total 60 studies, 48 were from Asia with 13,871 patients, 10 from Europe with 3745 patients, one from Russia with 53 patients, and one with a combined Asian and North American cohort of 428 patients. Patients were treated by primary and/or additional surgery in 52 studies and primary and/or additional surgery and endoscopy in eight studies. The indications for surgery in each study were mainly in accordance with Japanese, American, and European guidelines. 3 , 8 , 11 , 12 , 13 , 25 , 26
Appendix S5 shows the results of the methodological quality assessment of the included studies using the QUADAS‐2 tool. We scored three studies as unclear risks of bias and seven as high applicability concerns for patient selection. We scored 51 studies as unclear risks of bias in the index test, and 11 were scored as high applicability concerns. For reference standard, we scored three studies as high risks of bias and seven as high applicability concerns. For flow and timing, we scored seven studies as high risks of bias and two as unclear risks of bias.
Diagnostic odds ratio of the stains for LI in LNM
Of the 60 studies, the impact of HE and D2‐40 staining for LI was reported in 24 and 16 studies, respectively; HE and elastic staining for VI was reported in 19 and 21 studies, respectively; and HE and additional staining for LVI was reported in 13 and 8 studies, respectively.
Figure 2A shows pooled sensitivities of 0.53 (95% CI 0.42–0.65) and 0.57 (95% CI 0.44–0.69) (P = 0.60), specificities of 0.83 (95% CI 0.75–0.89) and 0.80 (95% CI 0.73–0.86) (P = 0.73), and DORs of 5.48 (95% CI 4.17–7.22) and 5.87 (95% CI 4.27–8.06) of HE and D2‐40 staining, respectively, for detecting LI in LNM. Figure 2B reveals pooled sensitivities of 0.25 (95% CI 0.15–0.39) and 0.44 (95% CI 0.34–0.54) (P = 0.015), specificities of 0.90 (95% CI 0.83–0.94) and 0.76 (95% CI 0.71–0.81) (P = 0.002), and DORs of 3.03 (95% CI 2.32–3.95) and 2.61 (95% CI 2.13–3.20) of HE and elastic staining, respectively, for detecting VI in LNM. Figure 2C indicates pooled sensitivities of 0.45 (95% CI 0.32–0.58) and 0.68 (95% CI 0.44–0.86) (P = 0.17), specificities of 0.88 (95% CI 0.78–0.94) and 0.76 (95% CI 0.62–0.86) (P = 0.14), and DORs of 6.26 (95% CI 3.73–10.53) and 6.47 (95% CI 3.40–12.32) of HE and additional staining, respectively, in identifying LVI in LNM.
Figure 2.

Forest plot with the sensitivities and specificities of (A) hematoxylin–eosin (HE) staining and D2‐40 immunostaining for lymphatic invasion, (B) HE and elastic staining for vascular invasion, and (C) HE and additional staining for lymphovascular invasion on estimating; lymph node metastasis. CI, confidence interval; FN, false negative; FP, false positive; TN, true negative; TP, true positive.
In multivariable analysis, the DOR for LVI in LNM differed between the additional (DOR 5.95; 95% CI 2.87–12.33) and HE (DOR 1.89; 95% CI 1.13–3.16) (P = 0.01) staining (Fig. 3).
Figure 3.

Forest plot with the odds ratios of hematoxylin–eosin and additional staining in studies that simultaneously included other risk factors (deep submucosal invasion, poor differentiation, and tumor budding) in multivariable analysis. CI, confidence interval; IV, inverse variance; LNM, lymph node metastasis; SE, standard error.
Additional analysis
Figure S1 displays the subgroup analysis of different staining methods for VI: pooled sensitivities of 0.36 (95% CI 0.22–0.53) and 0.54 (95% CI 0.44–0.64) (P = 0.14), specificities of 0.80 (95% CI 0.73–0.86) and 0.70 (95% CI 0.62–0.78) (P = 0.11), and DORs of 2.36 (95% CI 1.70–3.26) and 2.77 (95% CI 1.89–4.06) of EVG and VB staining, respectively, for VI in LNM.
Figure S2 shows the country‐based subgroup analysis: HE staining for LVI in LNM had pooled sensitivities of 0.57 (95% CI 0.31–0.80) and 0.38 (95% CI 0.25–0.54) (P = 0.15), specificities of 0.78 (95% CI 0.47–0.94) and 0.92 (95% CI 0.87–0.95) (P = 0.10), and DORs of 4.62 (95% CI 2.58–8.30) and 6.54 (95% CI 4.47–9.57) in Japan and other countries, respectively. Additional staining for LVI in LNM showed pooled sensitivities of 0.88 (95% CI 0.69–0.96) and 0.41 (95% CI 0.29–0.55) (P = 0.02), specificities of 0.64 (95% CI 0.43–0.80) and 0.85 (95% CI 0.75–0.92) (P = 0.47), and DORs of 10.27 (95% CI 4.68–22.55) and 3.00 (95% CI 1.15–7.80) in Japan and other countries, respectively.
Figure S3 presents the subgroup analysis of additional staining indications: D2‐40 staining for LI in LNM had pooled sensitivities of 0.59 (95% CI 0.44–0.72) and 0.54 (95% CI 0.28–0.77) (P = 0.73), specificities of 0.81 (95% CI 0.73–0.87) and 0.78 (95% CI 0.59–0.90) (P = 0.72), and DORs of 6.22 (95% CI 4.67–8.28) and 4.09 (95% CI 2.60–6.42) in all and limited cases, respectively. Elastic staining for VI in LNM showed pooled sensitivities of 0.41 (95% CI 0.30–0.55) and 0.55 (95% CI 0.37–0.71) (P = 0.36), specificities of 0.77 (95% CI 0.69–0.83) and 0.74 (95% CI 0.70–0.78) (P = 0.53), and DORs of 2.34 (95% CI 1.70–3.22) and 3.06 (95% CI 1.75–5.37) in all and limited cases, respectively. Additional staining for LVI in LNM showed pooled sensitivities of 0.80 (95% CI 0.58–0.92) and 0.34 (95% CI 0.26–0.43) (P = 0.03), specificities of 0.75 (95% CI 0.56–0.87) and 0.79 (95% CI 0.76–0.82) (P = 0.66), and DORs of 11.66 (95% CI 6.45–21.07) and 2.03 (95% CI 1.10–3.74) in all and limited cases, respectively. Results of the sensitivity analyses were consistent with the main results. Table S2 shows detailed results of the sensitivity analyses.
Interobserver agreement among pathologists for LVI
Five studies reported interobserver agreement among pathologists for positive LVI. For LI, the overall estimate of Cohen's κ was 0.30 (95% CI 0.16–0.44) with HE staining and 0.50 (95% CI 0.37–0.63) with D2‐40 staining (beta‐coefficient 0.20; 95% CI −0.22 to 0.61; P = 0.175). For VI, the overall estimate of Cohen's κ was 0.30 (95% CI 0.16–0.44) with HE staining and 0.50 (95% CI 0.37–0.63) with D2‐40 staining (beta‐coefficient 0.37; 95% CI 0.0057–0.73; P = 0.049). For LVI, the overall estimate of Cohen's κ was 0.37 (95% CI 0.22–0.52) with HE staining and 0.62 (95% CI 0.04–0.99) with additional staining (beta‐coefficient 0.21; 95% CI −0.47 to −0.90; P = 0.433).
DISCUSSION
This systematic review and meta‐analysis of 64 studies with 18,097 patients investigated the impact of additional stains, such as D2‐40 and elastic stains, on estimating LNM in patients with T1 CRC. We found that the DORs of these additional staining methods may be higher than that of the HE staining method in multivariable analysis after adjusting for major risk factors (DSI, PD, and TB). We also demonstrated that additional staining may increase interobserver agreement among pathologists for positive LVI. These findings indicate that the addition of the D2‐40 immunostain for LI and elastic stains for VI, such as VB or EVG, may enhance the DOR of LVI for LNM compared with HE stains alone.
In our meta‐analysis of multivariable studies, the DOR of additional staining for LNM was higher than that of HE stains. In previous systematic reviews, LVI was an independent risk factor for LNM in T1 CRC. However, most of these studies did not provide an exact definition of LVI, and histopathological methods varied among these studies, 17 , 97 , 98 leading to a lack of standardization and bias. 17 , 97 , 98 In the present study, the histopathological methods were also evaluated. We found that, in some studies, the combination of LI and VI into one factor may result in a lack of information and a lower risk of LNM. 17 , 97 Therefore, it is important to evaluate LVI separately from LI and VI. In the present study, LI and VI were also examined separately, suggesting that additional staining, especially for VI, may affect the DOR of LNM. The reason for the difference in improved DOR of additional staining methods for LI and VI is unclear, but since it is often difficult to distinguish small lymph vessels and venous vessels, additional staining for VI may have particularly improved the DOR. The additional staining enables the distinction between LI and VI, which is difficult with HE staining alone.
With the expanded indication for endoscopic resection as the first‐line treatment in T1 CRC, we recommend additional staining to enhance the DOR for LNM, thereby optimizing patient management. Guidelines recommended considering risk factors, such as DSI, LVI, PD, and TB, when determining the need for a secondary surgical resection after endoscopic resection. 8 , 14 In a previous meta‐analysis, DSI was a poor predictor of LNM, while LVI, PD, and TB had high diagnostic accuracies for LNM. 98 Considering that in the present meta‐analysis, the DORs for LVI in LNM differ between additional (DOR 5.95; 95% CI 2.87–12.33) and HE (DOR 1.89; 95% CI 1.13–3.16) staining, it is possible that additional staining may be more useful than HE staining alone. The identification of LVI using additional staining as one of the most reliable predictors of LNM (i.e. by including it in the training data) will ultimately contribute to improving the DOR of LNM prediction models in combination with other factors such as artificial intelligence and nomograms. 99
The Japanese Society of Colorectal Cancer and the Korean Society of Pathology recommend additional staining methods, but the World Health Organization and the American Society of Pathology do not. 8 , 11 , 12 , 14 , 15 , 16 Differences in the recommendation of additional staining methods by the pathological societies in each country may have affected the difference in the DOR of additional staining between Japan and other countries in the subgroup analysis of this study. In a study showing pathological diagnostic criteria developed using the Delphi method, the histological findings associated with LVI using HE stains were inconsistent. However, the observations of elastic‐stained internal elastic membrane and D2‐40‐stained endothelial cells covering more than half of the circumference surrounding the tumor cluster were highly consistent. 21 The present study revealed a higher interobserver agreement among pathologists with additional staining for LI, VI, and LVI than with HE staining alone in patients with T1 CRC. Although uniform criteria strongly influence the consistency of the diagnosis of LVI, pathologists from different countries may interpret the diagnostic criteria for LVI in CRC differently. 22
The findings of this study may have limited generalizability owing to the inclusion of only surgical cases (both primary and additional surgical cases) as the gold standard for the reference standard for LNM and the exclusion of cases with endoscopic treatment alone. Specifically, patients with T1 CRC can undergo three types of treatment: (i) endoscopic treatment only; (ii) additional surgery after endoscopic treatment; and (iii) primary surgery. In clinical practice, additional staining should be considered for cases of endoscopic resection of T1 CRC (both endoscopic treatment only and additional surgery cases). The risk factors for LNM as indications for additional surgery are PD and LVI according to American guidelines, PD, LVI, and DSI according to European guidelines, and PD, LVI, DSI (greater than 1000 μm since 2005), and TB (since 2009) according to the Japanese guidelines. 3 , 8 , 11 , 12 , 13 , 25 , 26 Notably, when all risk factors are absent, the likelihood of LNM is considered to be low because the guideline indications for LNM have high sensitivity. 100 In the present study, the application of additional staining contributed to an elevated DOR for LNM, based on a multivariable meta‐analysis encompassing all four risk factors of PD, LVI, DSI, and TB. To achieve a comprehensive understanding of LNM in patients with T1 CRC, further studies encompassing cases treated exclusively with endoscopic treatment, which constitute ~30% of all T1 CRC, 20 are essential.
In clinical practice, additional staining of D2‐40 for LI and elastic staining for VI should be performed when other risk factors for LNM are negative, because additional staining increases the sensitivity but does not change the specificity. Routine additional staining increases the detection rate for LI and VI. 101 , 102 In this review, we compared the diagnostic accuracy of different additional staining methods, such as EVG, VB, and CD31 staining, for VI. The additional staining for VI did not show significant differences between EVG and VB staining among elastic staining. However, CD31 staining for VI did not have sufficient data for evaluation because it was often assessed in conjunction with elastic staining, 37 , 76 , 83 and only a few studies evaluated CD31 staining alone for VI. 38 , 42 In a previous study, CD31 staining was found to be less likely to detect VI than elastic staining and was not associated with prognosis. 103 Further studies are needed to elucidate the optimal choice of staining methods and their appropriate utilization.
Our study has a few limitations. First, this review included mostly Asian studies and few European or North American studies, which may limit the generalizability. Further studies may determine the applicability of the present results to regions outside Asia. Second, we could not consider the cost of additional staining in this study. However, the introduction of additional staining into routine practice makes a small difference in cost ($4.97 per case or $44.75 per additional case of VI detection), which is insignificant when compared to the cost of adjuvant therapy, the correct utility of which depends on the accurate detection of LVI. 104 Third, potential heterogeneity may exist in our analysis, although we used a model that accounted for the heterogeneity of within‐study and between‐study variation in the accuracy of study results. 28 Potential sources of heterogeneity are that the evaluated patients differed among studies, resection specimens may be sectioned/handled differently (thereby, for instance, influencing the risk of retraction artifacts), histological assessment may be performed differently by pathologists with different levels of expertise or experience (e.g. general vs. dedicated gastrointestinal pathologist, local vs. centralized assessment), and the LVI criteria may differ. However, we performed sensitivity, subgroup, and meta‐regression analyses to assess as much as possible the potential sources of heterogeneity in this analysis.
In conclusion, the present systematic review and meta‐analysis showed that the DOR of additional staining for LNM may be higher, independent of other major risk factors (DSI, PD, and TB), than that of HE staining. Additional staining also may increase interobserver agreement among pathologists for LVI detection. These findings suggest that additional staining should be recommended to improve the criteria for secondary surgery following endoscopic resection when other risk factors for LNM are negative. Further studies are needed to validate the DOR of additional staining for LNM outside of Asia.
CONFLICT OF INTEREST
Authors declare no conflict of interest for this article.
FUNDING INFORMATION
This study was supported by JSPS KAKENHI (grant numbers JP21K21121 and 23K16289).
Supporting information
Appendix S1 PRISMA‐DTA.
Appendix S2 Search strategy.
Appendix S3 Amendments from the registered protocol.
Appendix S4 The modified Quality Assessment of Diagnostic Accuracy Studies‐2 (QUADAS‐2) tool.
Appendix S5 The risk of bias and applicability using the modified Quality Assessment of Diagnostic Accuracy Studies‐2 (QUADAS‐2) tool.
Table S1 Overview of baseline characteristics.
Table S2 Sensitivity analysis.
Figure S1 Subgroup analysis of the diagnostic accuracy of (A) Elastica van Gieson (EVG) and (B) Victoria blue (VB) staining for vascular invasion on lymph node metastasis.
Figure S2 Subgroup analysis of the diagnostic accuracy of hematoxylin–eosin (HE) and additional staining for lymphovascular invasion on lymph node metastasis in Japan and others.
Figure S3 Subgroup analysis of the diagnostic accuracy of (A) D2‐40 staining for lymphatic invasion, (B) elastic staining for vascular invasion, and (C) additional staining for lymphovascular invasion on lymph node metastasis in (1) all or (2) limited cases.
ACKNOWLEDGMENTS
The authors thank Dr Norikatsu Miyoshi from the Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University; Dr Daisuke Aizawa from the Division of Pathology, Shizuoka Cancer Centre; Dr Tadahiko Masaki from Shimizugaoka Hospital; Dr Satoru Tamura from Tamura Clinic Gastroenterology and Internal Medicine; Dr Yuri Akishima‐Fukasawa from the Department of Pathology, Toho University School of Medicine; Dr Shinsuke Kazama from the Department of Gastroenterological Surgery, Saitama Cancer Center; Dr Atsushi Naito from the Department of Surgery, Osaka Police Hospital; Dr Kazuhiro Yasuda from the Department of Gastroenterological Surgery, Oita Prefectural Hospital; Dr Motohiro Kojima from the Pathology Division, National Cancer Center EPOC; Dr Shinji Tanaka from the Department of Endoscopy, Hiroshima University Hospital; Dr Yoshiki Kajiwara and Dr Hideki Ueno from the Department of Surgery, National Defense Medical College; Dr Young‐Seok Cho from the Division of Gastroenterology, Department of Internal Medicine, Seoul St. Mary's Hospital, The Catholic University of Korea; Dr Scarlet Brockmoeller from Pathology and Data Analytics, University of Leeds; and Dr Kazutomo Togashi from the Department of Coloproctology, Aizu Medical Centre, Fukushima Medical University, for providing us with the detailed information necessary for this study.
REFERENCES
- 1. Sung H, Ferlay J, Siegel RL et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021; 71: 209–249. [DOI] [PubMed] [Google Scholar]
- 2. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2021. CA Cancer J Clin 2021; 71: 7–33. [DOI] [PubMed] [Google Scholar]
- 3. Pimentel‐Nunes P, Libânio D, Bastiaansen BAJ et al. Endoscopic submucosal dissection for superficial gastrointestinal lesions: European Society of Gastrointestinal Endoscopy (ESGE) guideline – Update 2022. Endoscopy 2022; 54: 591–622. [DOI] [PubMed] [Google Scholar]
- 4. Ohata K, Kobayashi N, Sakai E et al. Long‐term outcomes after endoscopic submucosal dissection for large colorectal epithelial neoplasms: A prospective, multicenter, cohort trial from Japan. Gastroenterology 2022; 163: 1423–1434.e2. [DOI] [PubMed] [Google Scholar]
- 5. Zwager LW, Bastiaansen BAJ, van der Spek BW et al. Endoscopic full‐thickness resection of T1 colorectal cancers: A retrospective analysis from a multicenter Dutch eFTR registry. Endoscopy 2022; 54: 475–485. [DOI] [PubMed] [Google Scholar]
- 6. Draganov PV, Wang AY, Othman MO, Fukami N. AGA institute clinical practice update: Endoscopic submucosal dissection in the United States. Clin Gastroenterol Hepatol 2019; 17: 16–25.e1. [DOI] [PubMed] [Google Scholar]
- 7. Kudo SE, Ichimasa K, Villard B et al. Artificial intelligence system to determine risk of T1 colorectal cancer metastasis to lymph node. Gastroenterology 2021; 160: 1075–1084.e2. [DOI] [PubMed] [Google Scholar]
- 8. Hashiguchi Y, Muro K, Saito Y et al. Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2019 for the treatment of colorectal cancer. Int J Clin Oncol 2020; 25: 1–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Vermeer NCA, Backes Y, Snijders HS et al. National cohort study on postoperative risks after surgery for submucosal invasive colorectal cancer. BJS Open 2019; 3: 210–217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Vironen JH, Kairaluoma M, Aalto AM, Kellokumpu IH. Impact of functional results on quality of life after rectal cancer surgery. Dis Colon Rectum 2006; 49: 568–578. [DOI] [PubMed] [Google Scholar]
- 11. Watanabe T, Itabashi M, Shimada Y et al. Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2010 for the treatment of colorectal cancer. Int J Clin Oncol 2012; 17: 1–29. [DOI] [PubMed] [Google Scholar]
- 12. Watanabe T, Itabashi M, Shimada Y et al. Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2014 for treatment of colorectal cancer. Int J Clin Oncol 2015; 20: 207–239. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Watanabe T, Muro K, Ajioka Y et al. Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2016 for the treatment of colorectal cancer. Int J Clin Oncol 2018; 23: 1–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Nagtegaal ID, Odze RD, Klimstra D et al. The 2019 WHO classification of tumours of the digestive system. Histopathology 2020; 76: 182–188. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Washington MK, Berlin J, Branton P et al. Protocol for the examination of specimens from patients with primary carcinoma of the colon and rectum. Arch Pathol Lab Med 2009; 133: 1539–1551. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Kim BH, Kim JM, Kang GH et al. Standardized pathology report for colorectal cancer, 2nd edition. J Pathol Transl Med 2020; 54: 1–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Bosch SL, Teerenstra S, de Wilt JHW, Cunningham C, Nagtegaal ID. Predicting lymph node metastasis in pT1 colorectal cancer: A systematic review of risk factors providing rationale for therapy decisions. Endoscopy 2013; 45: 827–834. [DOI] [PubMed] [Google Scholar]
- 18. Yasue C, Chino A, Takamatsu M et al. Pathological risk factors and predictive endoscopic factors for lymph node metastasis of T1 colorectal cancer: A single‐center study of 846 lesions. J Gastroenterol 2019; 54: 708–717. [DOI] [PubMed] [Google Scholar]
- 19. Wada H, Shiozawa M, Sugano N et al. Lymphatic invasion identified with D2‐40 immunostaining as a risk factor of nodal metastasis in T1 colorectal cancer. Int J Clin Oncol 2013; 18: 1025–1031. [DOI] [PubMed] [Google Scholar]
- 20. Ichimasa K, Kudo SE, Miyachi H et al. Current problems and perspectives of pathological risk factors for lymph node metastasis in T1 colorectal cancer: Systematic review. Dig Endosc 2022; 34: 901–912. [DOI] [PubMed] [Google Scholar]
- 21. Kojima M, Shimazaki H, Iwaya K et al. Pathological diagnostic criterion of blood and lymphatic vessel invasion in colorectal cancer: A framework for developing an objective pathological diagnostic system using the Delphi method, from the Pathology Working Group of the Japanese Society for Cancer of the Colon and Rectum. J Clin Pathol 2013; 66: 551–558. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Kojima M, Puppa G, Kirsch R et al. Blood and lymphatic vessel invasion in pT1 colorectal cancer: An international concordance study. J Clin Pathol 2015; 68: 628–632. [DOI] [PubMed] [Google Scholar]
- 23. Salameh JP, Bossuyt PM, McGrath TA et al. Preferred reporting items for systematic review and meta‐analysis of diagnostic test accuracy studies (PRISMA‐DTA): Explanation, elaboration, and checklist. BMJ 2020; 370: m2632. [DOI] [PubMed] [Google Scholar]
- 24. Cochrane Screening and Diagnostic Test Methods Group . Cochrane handbook for systematic reviews of diagnostic test accuracy [Internet] . London: Cochrane; 2022. [cited 2023 Jun 30]. Available from: https://training.cochrane.org/handbook‐diagnostic‐test‐accuracy [Google Scholar]
- 25. ESMO . ESMO clinical practice guidelines: Gastrointestinal cancers [Internet] . Lugano: ESMO; 2020. [cited 2022 Jun 30]. Available from: https://www.esmo.org/guidelines/guidelines‐by‐topic/gastrointestinal‐cancers [Google Scholar]
- 26. Shaukat A, Kahi CJ, Burke CA, Rabeneck L, Sauer BG, Rex DK. ACG clinical guidelines: Colorectal cancer screening 2021. Am J Gastroenterol 2021; 116: 458–479. [DOI] [PubMed] [Google Scholar]
- 27. Whiting PF, Rutjes AWS, Westwood ME et al. QUADAS‐2: A revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011; 155: 529–536. [DOI] [PubMed] [Google Scholar]
- 28. Reitsma JB, Glas AS, Rutjes AWS, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 2005; 58: 982–990. [DOI] [PubMed] [Google Scholar]
- 29. Harbord RM, Higgins JPT. Meta‐regression in Stata. Stata J 2008; 8: 493–519. [Google Scholar]
- 30. Harris RJ, Deeks JJ, Altman DG, Bradburn MJ, Harbord RM, Sterne JAC. Metan: Fixed‐ and random‐effects meta‐analysis. Stata J 2008; 8: 3–28. [Google Scholar]
- 31. Sun S. Meta‐analysis of Cohen's kappa. Health Serv Outcomes Res Methodol 2011; 11: 145–163. [Google Scholar]
- 32. Arbyn M, Castle PE, Schiffman M, Wentzensen N, Heckman‐Stoddard B, Sahasrabuddhe VV. Meta‐analysis of agreement/concordance statistics in studies comparing self‐ vs clinician‐collected samples for HPV testing in cervical cancer screening. Int J Cancer 2022; 151: 308–312. [DOI] [PubMed] [Google Scholar]
- 33. Klein D. KAPPAETC: Stata module to evaluate interrater agreement [Internet] . Örebro: EconPapers; 2022. [cited 2023 Jun 30]. Available from: https://econpapers.repec.org/software/bocbocode/S458283.htm [Google Scholar]
- 34. Harbord RM, Metandi WP. Meta‐analysis of diagnostic accuracy using hierarchical logistic regression. Stata J 2009; 9: 211–229. [Google Scholar]
- 35. Dwamena B. MIDAS: Stata module for meta‐analytical integration of diagnostic test accuracy studies [Internet] . Örebro: EconPapers; 2009. [cited 2023 Jun 30]. Available from: https://EconPapers.repec.org/RePEc:boc:bocode:s456880 [Google Scholar]
- 36. Ebbehøj AL, Smith HG, Jørgensen LN, Krarup PM. Prognostic factors for lymph node metastases in pT1 colorectal cancer differ according to tumor morphology: A nationwide cohort study. Ann Surg 2023; 277: 127–135. [DOI] [PubMed] [Google Scholar]
- 37. Bae HJ, Ju H, Lee HH et al. Long‐term outcomes after endoscopic versus surgical resection of T1 colorectal carcinoma. Surg Endosc 2023; 37: 1231–1241. [DOI] [PubMed] [Google Scholar]
- 38. Cho SH, Park BS, Son GM et al. Differences in factors predicting lymph node metastasis between pT1 rectal cancer and pT1 colon cancer: A retrospective study. Am Surg Published online: 29 Jun 2022; DOI: 10.1177/00031348221111517. [DOI] [PubMed] [Google Scholar]
- 39. Gambella A, Falco EC, Benazzo G et al. The importance of being “that” colorectal pT1: A combined clinico‐pathological predictive score to improve nodal risk stratification. Front Med (Lausanne) 2022; 9: 837876. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Kim JK, Rhee YY, Bae JM et al. Composite scoring system and optimal tumor budding cut‐off number for estimating lymph node metastasis in submucosal colorectal cancer. BMC Cancer 2022; 22: 861. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Morini A, Annicchiarico A, De Giorgi F et al. Local excision of T1 colorectal cancer: Good differentiation, absence of lymphovascular invasion, and limited tumor radial infiltration (≤4.25 mm) may allow avoiding radical surgery. Int J Colorectal Dis 2022; 37: 2525–2533. [DOI] [PubMed] [Google Scholar]
- 42. Ozeki T, Shimura T, Ozeki T et al. The risk analyses of lymph node metastasis and recurrence for submucosal invasive colorectal cancer: Novel criteria to skip completion surgery. Cancer 2022; 14: 822. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. Rönnow CF, Arthursson V, Toth E, Krarup PM, Syk I, Thorlacius H. Lymphovascular infiltration, not depth of invasion, is the critical risk factor of metastases in early colorectal cancer: Retrospective population‐based cohort study on prospectively collected data, including validation. Ann Surg 2022; 275: e148–e154. [DOI] [PubMed] [Google Scholar]
- 44. Song JH, Hong Y, Kim ER, Kim SH, Sohn I. Utility of artificial intelligence with deep learning of hematoxylin and eosin‐stained whole slide images to predict lymph node metastasis in T1 colorectal cancer using endoscopically resected specimens; prediction of lymph node metastasis in T1 colorectal cancer. J Gastroenterol 2022; 57: 654–666. [DOI] [PubMed] [Google Scholar]
- 45. Cheng P, Lu Z, Zhang M et al. Is additional surgery necessary after non‐curative endoscopic submucosal dissection for early colorectal cancer? J Invest Surg 2021; 34: 889–894. [DOI] [PubMed] [Google Scholar]
- 46. Kang J, Choi YJ, Kim IK et al. Lasso‐based machine learning algorithm for prediction of lymph node metastasis in T1 colorectal cancer. Cancer Res Treat 2021; 53: 773–783. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Naito A, Iwamoto K, Ohtsuka M et al. Risk factors for lymph node metastasis in pathological T1b colorectal cancer. In Vivo 2021; 35: 987–991. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Nishimura T, Oka S, Tanaka S et al. Clinical significance of immunohistochemical lymphovascular evaluation to determine additional surgery after endoscopic submucosal dissection for colorectal T1 carcinoma. Int J Colorectal Dis 2021; 36: 949–958. [DOI] [PubMed] [Google Scholar]
- 49. Sugai T, Yamada N, Osakabe M et al. Microenvironmental markers are correlated with lymph node metastasis in invasive submucosal colorectal cancer. Histopathology 2021; 79: 584–598. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Takashina Y, Kudo SE, Ichimasa K et al. Clinicopathological features of small T1 colorectal cancers. World J Clin Cases 2021; 9: 10088–10097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Dou LZ, Zhang YM, He S et al. Long‐term outcome after endoscopic resection for early colorectal carcinoma. Zhonghua Zhong Liu Za Zhi 2020; 42: 758–764. Chinese. [DOI] [PubMed] [Google Scholar]
- 52. Mochizuki K, Kudo SE, Ichimasa K et al. Left‐sided location is a risk factor for lymph node metastasis of T1 colorectal cancer: A single‐center retrospective study. Int J Colorectal Dis 2020; 35: 1911–1919. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53. Haasnoot KJC, Backes Y, Moons LMG et al. Associations of non‐pedunculated T1 colorectal adenocarcinoma outcome with consensus molecular subtypes, immunoscore, and microsatellite status: A multicenter case‐cohort study. Mod Pathol 2020; 33: 2626–2636. [DOI] [PubMed] [Google Scholar]
- 54. Yamaoka Y, Imai K, Shiomi A et al. Endoscopic resection of T1 colorectal cancer prior to surgery does not affect surgical adverse events and recurrence. Surg Endosc 2020; 34: 5006–5016. [DOI] [PubMed] [Google Scholar]
- 55. Barel F, Auffret A, Cariou M et al. High reproducibility is attainable in assessing histoprognostic parameters of pT1 colorectal cancer using routine histopathology slides and immunohistochemistry analyses. Pathology 2019; 51: 46–54. [DOI] [PubMed] [Google Scholar]
- 56. Barel F, Cariou M, Saliou P et al. Histopathological factors help to predict lymph node metastases more efficiently than extra‐nodal recurrences in submucosa invading pT1 colorectal cancer. Sci Rep 2019; 9: 8342. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57. Kishida Y, Oishi T, Sugino T et al. Associations between loss of ARID1A expression and clinicopathologic and genetic variables in T1 early colorectal cancer. Am J Clin Pathol 2019; 152: 463–470. [DOI] [PubMed] [Google Scholar]
- 58. Makimoto S, Takami T, Hatano K et al. Additional surgery after endoscopic submucosal dissection for colorectal cancer: A review of 53 cases. Int J Colorectal Dis 2019; 34: 1723–1729. [DOI] [PubMed] [Google Scholar]
- 59. Rampioni Vinciguerra GL, Antonelli G, Citron F et al. Pathologist second opinion significantly alters clinical management of pT1 endoscopically resected colorectal cancer. Virchows Arch 2019; 475: 665–668. [DOI] [PubMed] [Google Scholar]
- 60. Takamatsu M, Kawachi H, Yamamoto N et al. Immunohistochemical evaluation of tumor budding for stratifying T1 colorectal cancer: Optimal cut‐off value and a novel computer‐assisted semiautomatic method. Mod Pathol 2019; 32: 675–683. [DOI] [PubMed] [Google Scholar]
- 61. Yoshizumi A, Uno H, Shida T et al. The influence of endoscopic resection prior to surgical operation on the prognosis of patients with submucosal invasive colorectal cancer. Gastroenterol Endosc 2019; 61: 2337–2345. Japanese. [Google Scholar]
- 62. Zhang Q, Wang L, Huang D et al. Pathological risk factors for lymph node metastasis in patients with submucosal invasive colorectal carcinoma. Cancer Manag Res 2019; 11: 1107–1114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63. Chernyshov SV, Shelygin YA, Kashnikov VN, Maynovskaya OA, Rybakov EG. Risk factors of regional lymph node metastases in pT1 colorectal cancer. Khirurgiia (Mosk) 2018; 8: 4–9. Russian. [DOI] [PubMed] [Google Scholar]
- 64. Han J, Hur H, Min BS, Lee KY, Kim NK. Predictive factors for lymph node metastasis in submucosal invasive colorectal carcinoma: A new proposal of depth of invasion for radical surgery. World J Surg 2018; 42: 2635–2641. [DOI] [PubMed] [Google Scholar]
- 65. Lee SJ, Kim A, Kim YK et al. The significance of tumor budding in T1 colorectal carcinoma: The most reliable predictor of lymph node metastasis especially in endoscopically resected T1 colorectal carcinoma. Hum Pathol 2018; 78: 8–17. [DOI] [PubMed] [Google Scholar]
- 66. Yim K, Won DD, Lee IK, Oh ST, Jung ES, Lee SH. Novel predictors for lymph node metastasis in submucosal invasive colorectal carcinoma. World J Gastroenterol 2017; 23: 5936–5944. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67. Machado I, Valera‐Alberni M, Martínez de Juan F et al. Histological factors predicting loco‐regional lymph node metastasis in early invasive colorectal adenocarcinoma pT1. Gastroenterol Hepatol 2016; 39: 1–8. [DOI] [PubMed] [Google Scholar]
- 68. Kawachi H, Eishi Y, Ueno H et al. A three‐tier classification system based on the depth of submucosal invasion and budding/sprouting can improve the treatment strategy for T1 colorectal cancer: A retrospective multicenter study. Mod Pathol 2015; 28: 872–879. [DOI] [PubMed] [Google Scholar]
- 69. Toh EW, Brown P, Morris E, Botterill I, Quirke P. Area of submucosal invasion and width of invasion predicts lymph node metastasis in pT1 colorectal cancers. Dis Colon Rectum 2015; 58: 393–400. [DOI] [PubMed] [Google Scholar]
- 70. Barresi V, Branca G, Ieni A et al. Poorly differentiated clusters (PDCs) as a novel histological predictor of nodal metastases in pT1 colorectal cancer. Virchows Arch 2014; 464: 655–662. [DOI] [PubMed] [Google Scholar]
- 71. Lee SH, Cho HD, Park DI et al. Pathological predictors for defining a therapeutic strategy for early colon cancer after endoscopic resection: Multicenter retrospective analysis from surgically resected specimens. Hepatogastroenterology 2014; 61: 642–646. [PubMed] [Google Scholar]
- 72. Nishida T, Egashira Y, Akutagawa H et al. Predictors of lymph node metastasis in T1 colorectal carcinoma: An immunophenotypic analysis of 265 patients. Dis Colon Rectum 2014; 57: 905–915. [DOI] [PubMed] [Google Scholar]
- 73. Suh JP, Youk EG, Lee EJ et al. Endoscopic submucosal dissection for nonpedunculated submucosal invasive colorectal cancer: Is it feasible? Eur J Gastroenterol Hepatol 2013; 25: 1051–1059. [DOI] [PubMed] [Google Scholar]
- 74. Nakadoi K, Tanaka S, Kanao H et al. Management of T1 colorectal carcinoma with special reference to criteria for curative endoscopic resection. J Gastroenterol Hepatol 2012; 27: 1057–1062. [DOI] [PubMed] [Google Scholar]
- 75. Akishima‐Fukasawa Y, Ishikawa Y, Akasaka Y et al. Histopathological predictors of regional lymph node metastasis at the invasive front in early colorectal cancer. Histopathology 2011; 59: 470–481. [DOI] [PubMed] [Google Scholar]
- 76. Ishii H, Ikegami M, Kobayashi H et al. Risk factors for lymph node metastasis in submucosal invasive colon cancer: Emphasis on comparison between vessel permeation and budding. Tokyo Jikeikai Ika Daigaku Zasshi 2010; 125: 19–32. Japanese. [Google Scholar]
- 77. Komori K, Hirai T, Kanemitsu Y et al. Is “depth of submucosal invasion ≥1000 μm” an important predictive factor for lymph node metastases in early invasive colorectal cancer? Hepatogastroenterology 2010; 57: 1123–1127. [PubMed] [Google Scholar]
- 78. Tateishi Y, Nakanishi Y, Taniguchi H, Shimoda T, Umemura S. Pathological prognostic factors predicting lymph node metastasis in submucosal invasive (T1) colorectal carcinoma. Mod Pathol 2010; 23: 1068–1072. [DOI] [PubMed] [Google Scholar]
- 79. Suzuki A, Togashi K, Nokubi M et al. Evaluation of venous invasion by Elastica van Gieson stain and tumor budding predicts local and distant metastases in patients with T1 stage colorectal cancer. Am J Surg Pathol 2009; 33: 1601–1607. [DOI] [PubMed] [Google Scholar]
- 80. Harris EI, Lewin DN, Wang HL et al. Lymphovascular invasion in colorectal cancer: An interobserver variability study. Am J Surg Pathol 2008; 32: 1816–1821. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81. Kawaura K, Fujii S, Murata Y et al. The lymphatic infiltration identified by D2‐40 monoclonal antibody predicts lymph node metastasis in submucosal invasive colorectal cancer. Pathobiology 2007; 74: 328–335. [DOI] [PubMed] [Google Scholar]
- 82. Nakajo K, Tamura S, Hiroi M, Onishi S, Yasuda N. Evaluation of the risk factors of lymph node metastasis in pT1 stage colorectal carcinoma: Indication for an endoscopic mucosal resection. Dig Endosc 2007; 19: 174–179. [Google Scholar]
- 83. Yasuda K, Inomata M, Shiromizu A, Shiraishi N, Higashi H, Kitano S. Risk factors for occult lymph node metastasis of colorectal cancer invading the submucosa and indications for endoscopic mucosal resection. Dis Colon Rectum 2007; 50: 1370–1376. [DOI] [PubMed] [Google Scholar]
- 84. Wang HS, Liang WY, Lin TC et al. Curative resection of T1 colorectal carcinoma: Risk of lymph node metastasis and long‐term prognosis. Dis Colon Rectum 2005; 48: 1182–1192. [DOI] [PubMed] [Google Scholar]
- 85. Kazama S, Watanabe T, Ajioka Y, Kanazawa T, Nagawa H. Tumour budding at the deepest invasive margin correlates with lymph node metastasis in submucosal colorectal cancer detected by anticytokeratin antibody CAM5.2. Br J Cancer 2006; 94: 293–298. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86. Watanabe T, Kasamaki S, Kawai K et al. Clinical significance of tumor surface desmoplastic reaction as a predictor of lymph node metastasis in colorectal cancer with submucosal invasion. The Japanese Journal of Gastroenterological Surgery 2005; 38: 1675–1683. Japanese. [Google Scholar]
- 87. Kitajima K, Fujimori T, Fujii S et al. Correlations between lymph node metastasis and depth of submucosal invasion in submucosal invasive colorectal carcinoma: A Japanese collaborative study. J Gastroenterol 2004; 39: 534–543. [DOI] [PubMed] [Google Scholar]
- 88. Okabe S, Shia J, Nash G et al. Lymph node metastasis in T1 adenocarcinoma of the colon and rectum. J Gastrointest Surg 2004; 8: 1032–1039. [DOI] [PubMed] [Google Scholar]
- 89. Taira S, Miyaoka M, Moriyasu F. New criteria for endoscopic resection of submucosally invasive colorectal cancer. J Tokyo Med Univ 2004; 62: 280–290. [Google Scholar]
- 90. Ueno H, Mochizuki H, Hashiguchi Y et al. Risk factors for an adverse outcome in early invasive colorectal carcinoma. Gastroenterology 2004; 127: 385–394. [DOI] [PubMed] [Google Scholar]
- 91. Asai K, Igarashi S, Matsui T, Horiguchi J, Kotake K. Risk factors of lymph node metastasis in colorectal cancer, invading to submucosal layer. The Japanese Journal of Gastroenterological Surgery 2003; 36: 1365–1369. Japanese. [Google Scholar]
- 92. Sakuragi M, Togashi K, Konishi F et al. Predictive factors for lymph node metastasis in T1 stage colorectal carcinomas. Dis Colon Rectum 2003; 46: 1626–1632. [DOI] [PubMed] [Google Scholar]
- 93. Suzuki T, Sadahiro S, Mukoyama S et al. Risk of lymph node and distant metastases in patients with early invasive colorectal cancer classified as Haggitt's level 4 invasion: Image analysis of submucosal layer invasion. Dis Colon Rectum 2003; 46: 203–208. [DOI] [PubMed] [Google Scholar]
- 94. Tsuruta O, Tsuji Y, Kawano H et al. Indication for endoscopic resection of submucosal colorectal carcinoma: Special reference to lymph node metastasis. Diagn Ther Endosc 2000; 6: 101–109. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95. Inoue Y, Suzuki M, Yoshida K, Tezuka T, Takasaki K. Study on submucosal invasion of submucosal carcinoma of colon and rectum – comparison with absolute valuation and relative valuation of depth of submucosal cancer invasion. J Jpn Soc Coloproctol 1999; 52: 1–7. [Google Scholar]
- 96. Coverlizza S, Risio M, Ferrari A, Fenoglio‐Preiser CM, Rossini FP. Colorectal adenomas containing invasive carcinoma. Pathologic assessment of lymph node metastatic potential. Cancer 1989; 64: 1937–1947. [DOI] [PubMed] [Google Scholar]
- 97. Choi JY, Jung SA, Shim KN et al. Meta‐analysis of predictive clinicopathologic factors for lymph node metastasis in patients with early colorectal carcinoma. J Korean Med Sci 2015; 30: 398–406. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98. Zwager LW, Bastiaansen BAJ, Montazeri NSM et al. Deep submucosal invasion is not an independent risk factor for lymph node metastasis in T1 colorectal cancer: A meta‐analysis. Gastroenterology 2022; 163: 174–189. [DOI] [PubMed] [Google Scholar]
- 99. Kajiwara Y, Oka S, Tanaka S et al. Nomogram as a novel predictive tool for lymph node metastasis in T1 colorectal cancer treated with endoscopic resection: A nationwide, multicenter study. Gastrointest Endosc 2023; 97: 1119–1128.e5. [DOI] [PubMed] [Google Scholar]
- 100. Ichimasa K, Kudo SE, Mori Y et al. Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer. Endoscopy 2018; 50: 230–240. [DOI] [PubMed] [Google Scholar]
- 101. Sari A, Cyr DP, Brar A et al. Routine elastin staining in surgically resected colorectal cancer: Impact on venous invasion detection and its association with oncologic outcomes. Am J Surg Pathol 2022; 46: 200–212. [DOI] [PubMed] [Google Scholar]
- 102. Ervine AJ, McBride HA, Kelly PJ, Loughrey MB. Double immunohistochemistry enhances detection of lymphatic and venous invasion in early‐stage colorectal cancer. Virchows Arch 2015; 467: 265–271. [DOI] [PubMed] [Google Scholar]
- 103. Van Wyk HC, Foulis AK, Roxburgh CS, Orange C, Horgan PG, McMillan DC. Comparison of methods to identify lymphatic and blood vessel invasion and their prognostic value in patients with primary operable colorectal cancer. Anticancer Res 2015; 35: 6457–6463. [PubMed] [Google Scholar]
- 104. Abdulkader M, Abdulla K, Rakha E, Kaye P. Routine elastic staining assists detection of vascular invasion in colorectal cancer. Histopathology 2006; 49: 487–492. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Appendix S1 PRISMA‐DTA.
Appendix S2 Search strategy.
Appendix S3 Amendments from the registered protocol.
Appendix S4 The modified Quality Assessment of Diagnostic Accuracy Studies‐2 (QUADAS‐2) tool.
Appendix S5 The risk of bias and applicability using the modified Quality Assessment of Diagnostic Accuracy Studies‐2 (QUADAS‐2) tool.
Table S1 Overview of baseline characteristics.
Table S2 Sensitivity analysis.
Figure S1 Subgroup analysis of the diagnostic accuracy of (A) Elastica van Gieson (EVG) and (B) Victoria blue (VB) staining for vascular invasion on lymph node metastasis.
Figure S2 Subgroup analysis of the diagnostic accuracy of hematoxylin–eosin (HE) and additional staining for lymphovascular invasion on lymph node metastasis in Japan and others.
Figure S3 Subgroup analysis of the diagnostic accuracy of (A) D2‐40 staining for lymphatic invasion, (B) elastic staining for vascular invasion, and (C) additional staining for lymphovascular invasion on lymph node metastasis in (1) all or (2) limited cases.
