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The simplified depth-predicting score outperforms the depth-predicting score for predicting the depth of invasion in differentiated early gastric cancer patients among nonexpert endoscopists
La puntuación simplificada de predicción de la profundidad supera a la puntuación de predicción de la profundidad para predecir la profundidad de la invasión en pacientes con cáncer gástrico temprano diferenciado entre endoscopistas no expertos
Lulu Zenga, Hui Lia, Tian Huanga, Yuting Henga, Jun Liub,c,
, Xiangpeng Hua,
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Corresponding author
a Department of Gastroenterology, the Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
b Department of Pathophysiology, School of Basic Medical College, Anhui Medical University, Hefei, Anhui Province, China
c Functional Experiment Center, School of Basic Medical College, Anhui Medical University, Hefei, Anhui Province, China
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"referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "Tian" "apellidos" => "Huang" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 3 => array:3 [ "nombre" => "Yuting" "apellidos" => "Heng" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 4 => array:4 [ "nombre" => "Jun" "apellidos" => "Liu" "email" => array:1 [ 0 => "liujun@ahmu.edu.cn" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 5 => array:4 [ "nombre" => "Xiangpeng" "apellidos" => "Hu" "email" => array:1 [ 0 => "huxiangpeng@ahmu.edu.cn" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:3 [ 0 => array:3 [ "entidad" => "Department of Gastroenterology, the Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Department of Pathophysiology, School of Basic Medical College, Anhui Medical University, Hefei, Anhui Province, China" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Functional Experiment Center, School of Basic Medical College, Anhui Medical University, Hefei, Anhui Province, China" "etiqueta" => "c" "identificador" => "aff0015" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding authors." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "La puntuación simplificada de predicción de la profundidad supera a la puntuación de predicción de la profundidad para predecir la profundidad de la invasión en pacientes con cáncer gástrico temprano diferenciado entre endoscopistas no expertos" ] ] "resumenGrafico" => array:2 [ "original" => 1 "multimedia" => array:5 [ "identificador" => "fig0020" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => false "mostrarDisplay" => true "figura" => array:1 [ 0 => array:4 [ "imagen" => "fx1.jpeg" "Alto" => 827 "Ancho" => 1333 "Tamanyo" => 192636 ] ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Gastric cancer (GC) is one of the most prevalent cancers of the digestive tract and one of the most lethal malignant neoplasms worldwide.<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">1–3</span></a> Early gastric cancer (EGC) is defined as an invasive gastric cancer that occurs in the gastric mucosa and invade no more deeply than the submucosa, irrespective of the presence of lymph node metastases.<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">4,5</span></a> Due to advances in early diagnosis and treatment techniques, the overall survival rate of gastric cancer patients has been significantly improved.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">6</span></a> Endoscopic treatment, mainly including endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD), has been widely accepted as the standard treatment for EGC because it is a minimally invasive method and offers a better quality of life over a 5-year period after treatment compared to surgical excision.<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">7–9</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">According to Japanese guidelines, the absolute indication for EMR or ESD is a differentiated EGC without ulcerative findings, for which the diameter is ≤20<span class="elsevierStyleHsp" style=""></span>mm and the depth of invasion must be clinically diagnosed as T1a.<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">10,11</span></a> Therefore, accurate preoperative staging of gastric cancer is essential for selecting optimal treatment methods.<a class="elsevierStyleCrossRefs" href="#bib0190"><span class="elsevierStyleSup">12,13</span></a> In particular, the depth of tumor invasion, namely, the T stage, is a major indicator of accurate preoperative staging.<a class="elsevierStyleCrossRefs" href="#bib0200"><span class="elsevierStyleSup">14,15</span></a> To date, various endoscopic techniques, such as conventional white-light endoscopy (C-WLE), magnifying endoscopy (ME) with narrow-band imaging (NBI), and endoscopic ultrasonography (EUS), have been used to evaluate the depth of tumor invasion.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">16</span></a> In recent years, artificial intelligence (AI) has also been proven to be useful for predicting the invasion depth of EGC, but this approach is not yet widespread.<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">17,18</span></a> C-WLE, as a conventional tool, is still a basic and indispensable method for predicting the invasion depth of EGC.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">19</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">The depth-predicting score (DPS) was developed by Abe et al. based on multivariate analysis of the association between endoscopic features and pathologic invasion depth and included four main endoscopic features: margin elevation, lesion size greater than 30<span class="elsevierStyleHsp" style=""></span>mm, uneven surface, and remarkable redness.<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">20,21</span></a> It can be used to objectively predict the depth of invasion of differentiated EGCs in C-WLE patients. Their study showed that the overall diagnostic accuracy of the invasion depth determined by three expert endoscopists using DPS was 82.5–84.8%.<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">21</span></a> Although the diagnostic accuracy of DPS is greater than 80%, this approach appears to be slightly too complex in practice, especially for nonexpert endoscopists. Yoshiki Tsujii et al. proposed simple conventional endoscopy criteria, called the simplified depth-predicting score (S-DPS), which consists of only two dominant features, margin elevation and uneven surface, to predict the depth of invasion of differentiated EGCs. In their study, the overall diagnostic accuracy of the invasion depth of S-DPS determined by three expert endoscopists was 73–82%.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">22</span></a> Expert endoscopists have shown minimal differences in the diagnostic accuracy of invasion depth between DPS and S-DPS. However, the differences between DPS and S-DPS among nonexpert endoscopists remain unclear. In our previous study, the diagnostic accuracy of the DPS for invasion depth was 68.75<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.71% among nonexpert endoscopists.<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">23</span></a> However, the effectiveness of S-DPS for diagnosing invasion depth is unclear among nonexpert endoscopists. Therefore, this study aimed to compare the ability of DPS and S-DPS to predict the depth of invasion of differentiated EGCs among nonexpert endoscopists and to further explore the clinical applications of S-DPS.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Participants and DPS/S-DPS</span><p id="par0020" class="elsevierStylePara elsevierViewall">We collected DPS subitem scores from 19 nonexpert endoscopists for EGC C-WLE images in the EGC dataset. The DPS subitem included four main endoscopic features: margin elevation, uneven surface, lesion size greater than 30<span class="elsevierStyleHsp" style=""></span>mm, and remarkable redness. The DPS scores are the sum of the above four subitem scores. The S-DPS score is the sum of two subitem (margin elevation and uneven surface) scores. The DPS subitems and corresponding scores are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0025" class="elsevierStylePara elsevierViewall">All participants were asked to complete a questionnaire about sex, age, number of gastroscopies performed, and years of experience in C-WLE. Nonexpert endoscopists were defined as those who had undergone fewer than 5000 gastroscopies and had no more than 5 years of operating experience. All expert endoscopists and endoscopists with incomplete data were excluded. This study was approved by the Second Affiliated Hospital of Anhui Medical University Ethics Committee.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Dataset</span><p id="par0030" class="elsevierStylePara elsevierViewall">Eighty-eight cases of C-WLE images of histologically proven differentiated EGC with complete medical records were selected as the EGC dataset of the diagnostic test in our previous DPS training study.<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">23</span></a> According to pathological infiltration depth, all lesions were divided into intramucosal and minute submucosal (M-SM1; <500<span class="elsevierStyleHsp" style=""></span>μm in depth) tumors and deep submucosal invasion (SM2; ≥500<span class="elsevierStyleHsp" style=""></span>μm in depth) tumors. Sixty-six patients were classified as M-SM1, and 22 patients were classified as SM2 based on pathological diagnosis. Close-up and distant images of each lesion were collected in previous clinical work.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Assessment</span><p id="par0035" class="elsevierStylePara elsevierViewall">For the S-DPS, we set 1 or 3 as the cutoff line between M-SM1 and SM2. For the DPS, we used 3 as the cutoff line between M-SM1 and SM2, as described in a previous study. If the S-DPS or DPS was greater than or equal to the cutoff line, the invasion depth of the corresponding lesion was considered to be SM2. Then, we obtained the number of patients diagnosed correctly, the number of overdiagnosed patients, and the number of underdiagnosed patients for each participant by using the histological invasion depth as the gold standard. Based on the above data, we calculated separate evaluation metrics, which included diagnostic accuracy, specificity, overdiagnosis rate and underdiagnosis rate. The cases judged correctly were divided by the total number of cases in the test dataset to obtain diagnostic accuracy. Sixty-six M-SM1 EGC patients were diagnosed correctly and were classified as M-SM1 according to the pathological diagnosis in the test dataset to obtain specificity. The number of overdiagnosed patients was divided by 66 who were classified as M-SM1 on pathological diagnosis in the test dataset to obtain the overdiagnosis rate, and the number of underdiagnosed patients was divided by 22 that were classified as SM-2 on pathological diagnosis in the test dataset to obtain the underdiagnosis rate.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">All the statistical analyses were performed using SPSS, version 26.0 (SPSS, Inc.). The normality of the variables was detected by the Shapiro–Wilk test. The variables are expressed appropriately as percentages, medians and ranges, and medians and interquartile ranges (1st quartile, 3rd quartile). Measures that conformed to normal distribution were expressed as mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>standard deviation with 95% confidence intervals (95% CI) calculated, and measures that did not conform to normal distribution were expressed as median (interquartile range) [<span class="elsevierStyleItalic">M</span>(<span class="elsevierStyleItalic">P</span>25,<span class="elsevierStyleItalic">P</span>75)]. The Wilcoxon signed rank test was used to compare the differences between the DPS and S-DPS. A two-sided test with <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05 indicated statistical significance.</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Demographics and operational experience of participants</span><p id="par0045" class="elsevierStylePara elsevierViewall">The 19 nonexpert endoscopists included 11 trainees and 8 junior endoscopists. On average, 19 nonexpert endoscopists were 29 years old (range, 23–36), and the majority were female (89.47%). They have no more than 5 years of operating experience. All participants completed<span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>3500 previous gastroscopies in C-WLE, which met our requirements of less than 5000 gastroscopies in C-WLE. The demographics and operational experience of the participants are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Comparison of the overall diagnostic accuracy and specificity of DPS and S-DPS</span><p id="par0050" class="elsevierStylePara elsevierViewall">The DPS diagnostic accuracy of invasion depth is from 61.36% to 78.41%. The S-DPS diagnostic accuracy of invasion depth is from 64.77% to 77.27% when 3 was set as cutoff value. The S-DPS diagnostic accuracy of invasion depth is from 37.50% to 71.59% when 1 was set as cutoff value. When 1 was set as cut-off value, the S-DPS diagnostic accuracy was significantly lower than that of the other two groups. Therefore, we reserved 3 as the cutoff value of S-DPS in the subsequent study, the same as DPS. When 3 was set as the cutoff value, the overall S-DPS diagnostic accuracy of invasion depth was significantly higher than DPS [73.86% (69.32%, 75.00%) vs. 67.05% (62.50%, 71.60%), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.005] (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). The S-DPS specificity was significantly higher than DPS [92.42% (86.36%, 96.97%) vs. 71.21% (62.12%, 81.82%), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000].</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Comparison of the overdiagnosis rate using DPS and S-DPS</span><p id="par0055" class="elsevierStylePara elsevierViewall">The over-diagnosed cases by S-DPS are from 1 to 22. The cases of over-diagnosed by DPS are from 7 to 31. The over-diagnosed rate of invasion depth by S-DPS is from 1.52% to 33.33%. The over-diagnosed rate of invasion depth by DPS is from 10.61% to 46.97%.</p><p id="par0060" class="elsevierStylePara elsevierViewall">The overall S-DPS over-diagnosed rate of invasion depth was significantly lower compared with DPS [7.58% (3.03%, 13.64%) vs. 28.79% (18.18%, 37.88%), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000] (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>A). For each participant, the over-diagnosed rate using S-DPS was lower than the over-diagnosed rate using DPS (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>B).</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Comparison of the underdiagnosed rate between DPS and S-DPS</span><p id="par0065" class="elsevierStylePara elsevierViewall">The cases of under-diagnosed by S-DPS are from 8 to 21. The cases of under-diagnosed by DPS are from 3 to 14. The under-diagnosed rate of invasion depth by S-DPS is from 36.36% to 95.45%. The under-diagnosed rate of invasion depth by DPS is from 13.64% to 63.64%. The overall S-DPS under-diagnosed rate of invasion depth was significantly higher compared with DPS [86.36% (68.18%, 90.91%) vs. 45.45% (31.82%, 59.09%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000)] (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>A). For each participant, the under-diagnosed rate using S-DPS was higher than the under-diagnosed rate using DPS (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>B).</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Discussion</span><p id="par0070" class="elsevierStylePara elsevierViewall">Previous studies have reported the ability of expert endoscopists to use DPS or S-DPS for depth prediction.<a class="elsevierStyleCrossRefs" href="#bib0235"><span class="elsevierStyleSup">21,22</span></a> The diagnostic ability of the S-DPS was slightly lower than that of the DPS among expert endoscopists, but the S-DPS was simpler and easier to use. However, data from nonexpert endoscopists are scarce. For this purpose, our study explored the ability of DPS and S-DPS to predict depth among nonexpert endoscopists.</p><p id="par0075" class="elsevierStylePara elsevierViewall">The overall DPS diagnostic accuracy in our study did not reach 70%. This finding is lower than that of a previous study in which the accuracy of DPSs determined by three expert endoscopists was 82.5–84.8%.<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">21</span></a> This may be related to the fact that the participants were nonexpert endoscopists who had less professional endoscopy knowledge and experience. Studies indicate that the diagnostic accuracy of invasion depth may depend mainly on the diagnostic expertise and experience of the endoscopist.<a class="elsevierStyleCrossRefs" href="#bib0250"><span class="elsevierStyleSup">24,25</span></a> The diagnostic accuracy of S-DPS by three expert endoscopists was 73–82% in a previous study. The overall diagnostic accuracy of S-DPS by nonexpert endoscopists in our study was 73.86%. This approach achieved an accurate range of results for expert endoscopists.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">22</span></a> This finding suggested that the S-DPS may narrow the impact of lacking experience and expertise in invasion depth diagnostics.</p><p id="par0080" class="elsevierStylePara elsevierViewall">Among nonexpert endoscopists, the overall S-DPS diagnostic accuracy for invasion depth was significantly greater than that of DPS. According to the absolute indication of ESD, M-SM1 EGC patients can be treated with ESD, but SM2 EGC patients should be excluded. The specificity of predicting invasion depth can reflect the ability to correctly diagnose M-SM1 EGC. In clinical practice, we think that specificity may be more important than sensibility. Therefore, we calculated the specificity of S-DPS and found that the specificity of S-DPS was higher than that of DPS. Therefore, the use of S-DPS is more conducive to accurately predicting the invasion depth of EGC by nonexpert endoscopists and is thus more helpful in choosing the correct treatment strategy for EGC.</p><p id="par0085" class="elsevierStylePara elsevierViewall">In this study, we found that the overall rate of invasion depth was significantly lower in S-DPS-overdiagnosed patients than in DPS-overdiagnosed patients, but the overall rate of underdiagnosis was significantly greater. The majority of cases (75%) in the dataset were intramucosal cancers or minute submucosal cancers, which might have a high probability of being overdiagnosed by any method. In this situation, the overdiagnosis of invasion depth using S-DPS was low for most participants. These findings indicated that S-DPS could offer relatively reasonable results to help nonexpert endoscopists avoid overdiagnosis.</p><p id="par0090" class="elsevierStylePara elsevierViewall">Reducing the overdiagnosis rate of invasion depth is very important in clinical practice. Along with the advancements in endoscopic treatment techniques, underdiagnosis may be acceptable because some underdiagnosed patients can be found by expert endoscopists during evaluation before ESD. Even if the lesion is underdiagnosed, it can be remedied by additional surgical excision after ESD, and ESD does not affect subsequent gastrectomy.<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">26</span></a> In contrast, if the lesion is overdiagnosed, direct surgical resection might result in overtreatment. Nonetheless, nonexpert endoscopists play an important role in preliminary judgment. For these patients, a lower overdiagnosis rate is more in line with clinical practice. From this perspective, the S-DPS is more suitable than the DPS.</p><p id="par0095" class="elsevierStylePara elsevierViewall">This study has several limitations, as follows: The dataset used for endoscopic diagnosis included only endoscopic photos without dynamic real-time images; this study was conducted at a single institution, and the sample size was not large. We expect that future studies with more centers will provide stronger evidence.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conclusion</span><p id="par0100" class="elsevierStylePara elsevierViewall">To sum up, we elucidated that the diagnostic ability of S-DPS is higher compared with DPS among nonexpert endoscopists. Compared to the DPS, the S-DPS is simpler and easier to use, making it more conducive to clinical application for nonexpert endoscopists in predicting invasion depth in white-light endoscopy. The S-DPS might be useful for efficiently reducing the overdiagnosis rate to avoid overtreatment among nonexpert endoscopists in clinical practice.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Authors’ contributions</span><p id="par0105" class="elsevierStylePara elsevierViewall">The research initiative and study concept were taken and designed by Xiangpeng Hu and Jun Liu. Lulu Zeng, Hui Li, Tian Huang and Yuting Heng recorded the data and performed the analysis. Lulu Zeng and Hui Li Data interpretation and drafted the manuscript. Xiangpeng Hu finally approval of the article. Lulu Zeng and Hui Li contributed equally as co-first authors.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Consent for publication</span><p id="par0110" class="elsevierStylePara elsevierViewall">Not applicable.</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Ethical considerations</span><p id="par0115" class="elsevierStylePara elsevierViewall">This study was approved by the Second Affiliated Hospital of Anhui Medical University Ethics Committee.</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0155">Funding</span><p id="par0120" class="elsevierStylePara elsevierViewall">This work was supported by <span class="elsevierStyleGrantSponsor" id="gs1">Clinical Research Cultivation Project of the Second Affiliated Hospital of Anhui Medical University</span> (<span class="elsevierStyleGrantNumber" refid="gs1">2021LCZD18</span>), <span class="elsevierStyleGrantSponsor" id="gs2">Research Fund of Anhui Institute of Translational Medicine</span> (<span class="elsevierStyleGrantNumber" refid="gs2">2022zhyx-C81</span>) and the <span class="elsevierStyleGrantSponsor" id="gs3">Natural Science Foundation of Anhui Province</span> (<span class="elsevierStyleGrantNumber" refid="gs3">2208085MH284</span>). The funding sources not involved the conduct of the research and/or preparation of the article.</p></span><span id="sec0090" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0160">Conflict of interest</span><p id="par0125" class="elsevierStylePara elsevierViewall">None.</p></span><span id="sec0095" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0165">Availability of data and materials</span><p id="par0130" class="elsevierStylePara elsevierViewall">The data that support the findings of this study are available from the corresponding author, Xiangpeng Hu, and the author, Lulu Zeng, upon reasonable request.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:19 [ 0 => array:3 [ "identificador" => "xres2281062" "titulo" => "Graphical abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0005" ] ] ] 1 => array:3 [ "identificador" => "xres2281063" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0010" "titulo" => "Aim" ] 1 => array:2 [ "identificador" => "abst0015" "titulo" => "Participants and methods" ] 2 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusion" ] ] ] 2 => array:2 [ "identificador" => "xpalclavsec1897492" "titulo" => "Keywords" ] 3 => array:2 [ "identificador" => "xpalclavsec1897493" "titulo" => "Abbreviations" ] 4 => array:3 [ "identificador" => "xres2281064" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Participantes y métodos" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Conclusiones" ] ] ] 5 => array:2 [ "identificador" => "xpalclavsec1897494" "titulo" => "Palabras clave" ] 6 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 7 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Participants and DPS/S-DPS" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Dataset" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Assessment" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analysis" ] ] ] 8 => array:3 [ "identificador" => "sec0035" "titulo" => "Results" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0040" "titulo" => "Demographics and operational experience of participants" ] 1 => array:2 [ "identificador" => "sec0045" "titulo" => "Comparison of the overall diagnostic accuracy and specificity of DPS and S-DPS" ] 2 => array:2 [ "identificador" => "sec0050" "titulo" => "Comparison of the overdiagnosis rate using DPS and S-DPS" ] 3 => array:2 [ "identificador" => "sec0055" "titulo" => "Comparison of the underdiagnosed rate between DPS and S-DPS" ] ] ] 9 => array:2 [ "identificador" => "sec0060" "titulo" => "Discussion" ] 10 => array:2 [ "identificador" => "sec0065" "titulo" => "Conclusion" ] 11 => array:2 [ "identificador" => "sec0070" "titulo" => "Authors’ contributions" ] 12 => array:2 [ "identificador" => "sec0075" "titulo" => "Consent for publication" ] 13 => array:2 [ "identificador" => "sec0080" "titulo" => "Ethical considerations" ] 14 => array:2 [ "identificador" => "sec0085" "titulo" => "Funding" ] 15 => array:2 [ "identificador" => "sec0090" "titulo" => "Conflict of interest" ] 16 => array:2 [ "identificador" => "sec0095" "titulo" => "Availability of data and materials" ] 17 => array:2 [ "identificador" => "xack783587" "titulo" => "Acknowledgments" ] 18 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2024-06-11" "fechaAceptado" => "2024-10-06" "PalabrasClave" => array:2 [ "en" => array:2 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1897492" "palabras" => array:4 [ 0 => "Invasion depth" 1 => "Simplified depth-predicting score" 2 => "Early gastric cancer" 3 => "Endoscopists" ] ] 1 => array:4 [ "clase" => "abr" "titulo" => "Abbreviations" "identificador" => "xpalclavsec1897493" "palabras" => array:11 [ 0 => "DPS" 1 => "S-DPS" 2 => "EGC" 3 => "GC" 4 => "EMR" 5 => "ESD" 6 => "C-WLE" 7 => "ME" 8 => "NBI" 9 => "EUS" 10 => "AI" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1897494" "palabras" => array:4 [ 0 => "Profundidad de invasión" 1 => "Puntuación simplificada de predicción de profundidad" 2 => "Cáncer gástrico temprano" 3 => "Endoscopistas" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Aim</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Endoscopists utilize depth-predicting score (DPS) and simplified depth-predicting score (S-DPS) to predict the invasion depth of early gastric cancer based on conventional white-light endoscopic features. The effectiveness of these scores has not been fully elucidated among nonexpert endoscopists. This study aimed to compare the ability of DPS and S-DPS to predict invasion depth of differentiated early gastric cancers by nonexpert endoscopists.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Participants and methods</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">We collected subitem scores of DPS and S-DPS from 19 nonexpert endoscopists for early gastric cancer conventional white-light endoscopy images in the test dataset to predict the invasion depth of the early gastric cancer conventional white-light endoscopy images. Accuracy, specificity, overdiagnosis rate, and underdiagnosis rate were subsequently calculated using the histological invasion depth as the gold standard.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Using 3 as the cutoff line, the overall S-DPS diagnostic accuracy for invasion depth was significantly greater than that of DPS [73.86% (69.32%, 75.00%) vs. 67.05% (62.50%, 71.60%), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.005]. The overall S-DPS overdiagnosis rate was significantly lower than that of DPS [7.58% (3.03%, 13.64%) vs. 28.79% (18.18%, 37.88%), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000]. The overall S-DPS under-diagnosed rate was significantly higher than that of DPS [86.36% (68.18%, 90.91%) vs. 45.45% (31.82%, 59.09%), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000]. The specificity of the S-DPS was significantly greater than that of DPS [92.42% (86.36%, 96.97%) vs. 71.21% (62.12%, 81.82%), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000].</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusion</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">The diagnostic accuracy of the S-DPS was greater than that of the DPS among nonexpert endoscopists. Furthermore, S-DPS is simpler than other methods, making it more conducive to clinical application for nonexpert endoscopists.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0010" "titulo" => "Aim" ] 1 => array:2 [ "identificador" => "abst0015" "titulo" => "Participants and methods" ] 2 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Objetivo</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Los endoscopistas utilizan la puntuación de predicción de profundidad (<span class="elsevierStyleItalic">depth-predicting score</span> [DPS]) y la puntuación simplificada de predicción de profundidad (S-DPS) para predecir la profundidad de invasión del cáncer gástrico temprano basándose en las características endoscópicas convencionales con luz blanca. La eficacia de estas puntuaciones no se ha dilucidado del todo entre endoscopistas no expertos. El objetivo de este estudio fue comparar la capacidad de la DPS y de la S-DPS para predecir la profundidad de invasión de los cánceres gástricos tempranos diferenciados por endoscopistas no expertos.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Participantes y métodos</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Recopilamos las puntuaciones de subelementos de la DPS y la S-DPS de 19 endoscopistas no expertos para imágenes de endoscopia convencional de luz blanca de cáncer gástrico temprano en el conjunto de datos de prueba para predecir la profundidad de invasión de las imágenes de endoscopia convencional de luz blanca de cáncer gástrico temprano. Posteriormente se calcularon la precisión, la especificidad, la tasa de sobrediagnóstico y la tasa de infradiagnóstico utilizando la profundidad de invasión histológica como patrón de referencia.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Resultados</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Utilizando 3 como línea de corte, la precisión diagnóstica global de la S-DPS para la profundidad de invasión fue significativamente mayor que la de la DPS (73,86% [69,32%-75,00%] frente al 67,05% [62,50%-71,60%], p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,005). La tasa global de sobrediagnóstico de S-DPS fue significativamente inferior a la de DPS (7,58% [3,03%-13,64%] frente al 28,79% [18,18%-37,88%], p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,000). La tasa global de infradiagnóstico de la S-DPS fue significativamente superior a la de la DPS (86,36% [68,18%-90,91%] frente al 45,45% [31,82%-59,09%], p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,000). La especificidad de la S-DPS fue significativamente mayor que la de la DPS (92,42% [86,36%, 96,97%] frente al 71,21% [62,12%-81,82%], p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,000).</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Conclusiones</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">La precisión diagnóstica de la S-DPS fue mayor que la de la DPS entre los endoscopistas no expertos. Además, la S-DPS es más sencilla que otros métodos, lo que la hace más propicia para la aplicación clínica por parte de endoscopistas no expertos.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Participantes y métodos" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Conclusiones" ] ] ] ] "multimedia" => array:6 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 933 "Ancho" => 981 "Tamanyo" => 49491 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Compare the overall diagnostic accuracy using DPS, S-DPS (1 or 3 as the cutoff line). Diagnostic accuracy was compared using the Wilcoxon signed rank test. The overall S-DPS (3 as the cutoff line) diagnostic accuracy of invasion depth was significantly higher compared with DPS. *<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05. The overall S-DPS (3 as the cutoff line) diagnostic accuracy of invasion depth was significantly higher compared with S-DPS (1 as the cutoff line). *<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05. DPS, depth-predicting score. S-DPS, simplified depth-predicting.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 841 "Ancho" => 1650 "Tamanyo" => 90401 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Compare the over-diagnosed rate using DPS and S-DPS. (A) The overall over-diagnosed rate of invasion depth was significantly lower using S-DPS compared with DPS. (B) Every participant of the over-diagnosed rate was reduced using S-DPS to diagnose compared with DPS. *<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05.</p>" ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1110 "Ancho" => 2167 "Tamanyo" => 129289 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Compare the under-diagnosed rate using DPS and S-DPS. (A) The overall under-diagnosed rate of invasion depth was significantly higher using S-DPS compared with DPS. (B) Every participant of the under-diagnosed rate was risen using S-DPS to diagnose compared with DPS. *<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Endoscopic features \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Definitions \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">DPS \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">S-DPS \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Margin elevation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">A protruding edge surrounding the tumors \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 points \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 points \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Uneven surface \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Nodulations in the tumor's surface \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 point \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 point \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Remarkable redness \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">A reddish area similar to regenerative epithelium \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 point \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor size<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>30<span class="elsevierStyleHsp" style=""></span>mm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Lesion size more than 30<span class="elsevierStyleHsp" style=""></span>mm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 points \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3698163.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Comparison of endoscopic features and scores methods used in the DPS and S-DPS.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Characteristic \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sub-characteristic and measurement \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Value \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (y) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (range), years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 (23–36) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Gender \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Female, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 (89.47%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Operating year \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Less than 1, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (57.89%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2–5, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (42.11%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">C-WLE performed in career \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (range), case \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">350 (300–3500) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3698164.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Demographics and operational experience of participants (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>19).</p>" ] ] 5 => array:5 [ "identificador" => "fig0020" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => false "mostrarDisplay" => true "figura" => array:1 [ 0 => array:4 [ "imagen" => "fx1.jpeg" "Alto" => 827 "Ancho" => 1333 "Tamanyo" => 192636 ] ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:26 [ 0 => array:3 [ "identificador" => "bib0135" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Epidemiology of stomach cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "M. 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