Prognostic Significance of positive lymph node regression grade to Neoadjuvant Chemoradiation for Esophageal Squamous Cell Carcinoma

doi:10.21203/rs.3.rs-2747434/v1

Download PDF

Research Article

Prognostic Significance of positive lymph node regression grade to Neoadjuvant Chemoradiation for Esophageal Squamous Cell Carcinoma

https://doi.org/10.21203/rs.3.rs-2747434/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background and Purpose

To assess the relationship between metastatic lymph node (LN) responder status and recurrence-free survival (RFS) in patients undergoing neoadjuvant chemoradiotherapy (NCRT).

Materials and Methods

We retrospectively reviewed 304 patients with local advanced esophageal squamous cell carcinoma received NCRT followed by esophagectomy. For 112 patients with positive node, according to the proportion of residual viable tumor cells area within the whole tumor beds of all metastatic LNs, we classified LN-tumor regression grade (LN-TRG) into four categories: grade 1, 0%; 2, < 10%; 3, 10–50%; 4, > 50%. Patients with grade 1 LN-TRG of were considered LN responders, and those with grades 2–4, as LN nonresponders. Univariate and multivariate analyses of recurrence-free survival (RFS) were estimated by a Cox regression model, Kaplan-Meier curve, and log-rank test.

Results

The median follow-up time of a total of 112 patients was 29.6 months. 52 (46.4%) patients have experienced recurrence. In Cox univariate analysis, LN responder status, nerve invasion, and lymphovascular invasion significantly correlated with RFS. Multivariate analysis for RFS revealed that LN responder status (P < 0.05) was an independent prognostic factor. The 3-year RFS rates for patients with LN-TRG of 1 to 4 grades were 72.7%, 76.5%, 37.4%, and 28.5%, respectively, and the median RFS times were not reach, 43.56 months, 28.09 months, 22.77 months, respectively.

Conclusions

LN responder status is an independent prognostic factor for RFS in esophageal cancer patients who received NCRT.

neoadjuvant chemoradiotherapy

lymph node metastasis

tumor regression grade

esophageal squamous cell carcinoma

Esophageal cancer is the fourth leading cause of cancer-related death in China [1], and squamous cell carcinoma is its most common pathological type [2]. Compared to surgery alone, neoadjuvant therapy followed by surgery improves prognosis in most patients with locally advanced disease at the time of diagnosis. Therefore neoadjuvant therapy plays an important role in the treatment of esophageal cancer in middle and late age [3]. In recent years, several studies have shown that NCRT is superior to neoadjuvant chemotherapy (NAC) owing to long-term survival in therapy of locally advanced esophageal cancer, even in the similarly adverse effect, NCRT provides better short-term benefits than those associated with NAC combined with immunotherapy, and it is associated with pathological complete response (pCR) rates of up to 49% [4, 5] and 5-year overall survival (OS) rates of up to 45% [6]. Consequently, NCRT takes an unshakable position in comprehensive anti-tumor therapy. With the addition of adjuvant therapy, pathological TNM stage is seemingly not so reliable in predicting the prognosis of neoadjuvant therapy in contrast with surgery alone [7]. Thus, to help determine prognoses, the imaging and pathological approaches which aim to assess tumor regression were always regarded as important evaluation means [8]. However, pathological criteria are undoubtedly more objective. The commonly used tumor regression grade (TRG) system evaluates the number and proportion of residual tumors, the state of tumor cells, and the number and range of fibrosis after tumor regression induced by treatment, and classifies them by these indicators. However, there are many kinds of TRG [9, 10]. Most evaluation systems are generally regarded as good indicators for predicting the short-term curative effect and estimating recurrence risk, but all grades can only reflect the therapeutic effect on the primary tumor (PT) [11]. In fact, some researchers have found that the response of the primary lesion and lymph nodes (LNs) to the new adjuvant therapy is different [12, 13]. Moreover, previous studies have shown that LN metastasis is more strongly associated with poor prognosis than the invasion of primary lesions is, whether it is after simple surgery or neoadjuvant therapy [14, 15]. Ultimately, LNs must be evaluated individually; however, no internationally recognized standard grading system is available for evaluating the treatment response of LNs.

Therefore, this study aimed to establish a new pathological grading system to grade the degree of pathological LN regression, to determine the prognosis of locally advanced esophageal squamous cell carcinoma after NCRT.

Patients

Between June 2017 and June 2021, all patients with esophageal squamous cell carcinoma (ESCC) undergoing NCRT followed by surgery at the Department of Thoracic Surgery, Sichuan Cancer Hospital were reviewed. The inclusion criteria were (1) primary locally advanced ESCC; (2) no history of concomitant or previous malignancy; (3) concurrent neoadjuvant chemoradiotherapy before surgery; (4) NCRT followed by radical resection of esophageal carcinoma; (5) evidence of LNs metastasis; and (6) no evidence of distant metastasis. Finally, the study included 112 patients who underwent NCRT before esophagectomy(Supplementary Fig. 1).

Methods

Treatment

The chemotherapy regimens comprised combinations of single or double drugs such as paclitaxel-albumin, carboplatin, cisplatin, docetaxel, oxaliplatin, fluorouracil, tegafur, gimeracil, and oteracil potassium capsules, among others. The average number of chemotherapeutic cycles was 1.99 ± 0.52. Concomitant radiotherapy targeting the PT, positive LNs, subclinical lesions, and LN drainage area comprised a total dose of 40–45 Gy delivered in 20–25 fractions. CT scans of the neck, chest, and abdomen, and endoscopic ultrasonography

were used to assess the efficacy of NCRT before esophagectomy, which was performed using either the McKeown or Ivor Lewis approach.

Pathological evaluation

Specimens were fixed with 10% neutral formalin, embedded in paraffin, sectioned routinely and stained with hematoxylin and eosin (HE). The Streptavidin-peroxidase method was used in immunohistochemistry, and the staining steps were carried out on an active immunohistochemistry instrument according to the operating instructions. Primary tumor regression grading (PT-TRG) was based on the standard Becker grading [10], LN-TRG was reassessed by two independent and experienced pathologists, and the tumor bed area of LNs was assessed based on a substantial area of fibrosis, necrosis, and granulomatous changes within the nodal parenchyma. LN-TRG which was determined by calculating the proportion of all viable tumor area within the tumor bed area, within the LNs, was classified into four grades (grade 1, 0%; grade 2, < 10%; grade 3, 10–50%; grade 4, > 50%). When the grading was discordant due to the controversy of assessing whether tumor cells were viable or not, immunohistochemical staining for PCK, and P40 was used for auxiliary interpretation. Only if both of them were positive was the tumor cell regarded as positive (Fig. 1). The ratio of viable tumor area in LNs to the whole tumor bed area was calculated as shown in the schematic diagram (Fig. 1D). Patients with TRG1 were classified as responders, and those with grades 2–4 as nonresponders.

Statistical analysis

Univariate analyses of recurrence-free survival (RFS) was estimated by a Cox regression model, Kaplan-Meier curve, and log-rank test. RFS was defined as the interval from the date of surgery to the date of recurrence or death from any cause. P < 0.05 was considered to indicate statistical significance. All analyses were performed using R Statistical Software (http://www.R-project.org, The R Foundation) and Free Statistics analysis platform.

The median follow-up time of a total of 112 patients was 29.6 months. 76 (67.9%) were younger than 65 years old, 98 (87.5%) were male, 82 (73.2%) and 79 (70.5%) patients had a history of smoking and drinking alcohol, respectively. 99 (88.4%) patients had tumors located in the middle or lower third of the esophagus, and the clinical staging before surgery was predominantly cT3 in 87 patients (77.7%) and cN0 in one (0.9%). Postoperative pathology showed moderate and poor differentiation in 101 (90.2%) patients; further, surgical margin, nerve invasion, lymphvascular invasion (LVI) were positive in 3 (2.7%), 25 (22.3%), and 20 (17.9%) patients respectively. 52 (46.4%) patients have experienced recurrence. The post-neoadjuvant pathological stage was ypT0 in 27 patients (24.1%), ypT1–4 in 85 (75.9%), ypN0 in 20 (17.9%), and ypN1–3 in 92 (82.1%).

The correlation between clinicopathological characteristics and LNs responder status of 112 patients is shown in Table 1. Compared to nonresponders, responders showed significantly lower LVI (P = 0.021), lower proportions of ypT stage (P = 0.015), and ypN stage (P < 0.001) in terms of total LN-TRG. However, there were no significantly differences in age, sex, smoking, drinking, tumor location, differentiation, cT stage, cN stage, surgical margin, and nerve invasion between nonresponders and responders (P > 0.05) (Table 1).

In the univariate Cox regression analysis displayed in Table 2, age, sex, smoking, drinking, tumor location, differentiation, cT stage, cN stage, ypT stage, ypN stage, pCR(ypT0N0M0), pT-TRG, the AJCC pathological staging, and surgical margin were not significant prognostic factors affecting RFS, whereas nerve invasion, LVI, and LNs responder status (P < 0.05) were important predictors of RFS. In the multivariate Cox regression analysis, adjusted for these covariables that exhibited statistical significance in univariate analysis, LNs responder status (P < 0.05) was found to be an independent predictive factor for RFS. LNs non-responder status indicated higher recurrence risk [hazard ratio (HR) = 2.77; 95% confidence interval (CI):1.14–6.71; P = 0.024] (Table 2).

Figure 1 shows that HE was similar in morphology and controversial in interpretation. P40 (nucleus +) and PCK (cytoplasm +) on the left side were used to determine viable tumor cells (Fig. 1, Left side of BC), whereas P40 (nucleus -) and PCK (cytoplasm +) on the right side identified non-viable tumor cells (Fig. 1, Right side of BC).

The 3-year RFS rates for patients with LN-TRG of 1 to 4 grades were 72.7%, 76.5%, 37.4%, and 28.5%, respectively, and the median RFS times were 43.56 months, 28.09 months, 22.77 months, respectively. Notably, LN-TRG 1 was associated with a significant advantage of RFS compared with LN-TRG 3 (HR = 3.85; 95%CI: 1.43–10.41; P = 0.008) and 4 (HR = 3.09; 95%CI 1.23–7.73; P = 0.016). Furthermore, LN-TRG was discordant with PT-TRG in 83 (74.1%) patients, of which 60 (72.3%) had a higher LN-TRG than PT-TRG (Fig. 3A). Conversely, no significant differences were observed between PT-TRG 1–4, ypN0-3, or the AJCC pathological staging in stages 0-IVa (P > 0.05) (Fig. 3B-D).

Subgroup analysis, which divided into the patients into groups according to age, sex, smoking status, drinking status, PT responder status, is displayed in a forest plot. No significant difference was observed in the influence of LNs responder status on RFS in the subgroups (P for interaction > 0.05). LNs nonresponder status was an unfavorable prognostic factor for RFS in all subgroups, and the negative influence was more obvious in patients who were male, smokers, and drinkers (P < 0.05). Nevertheless, we observed that the influence of LNs responder status on RFS was significantly different in different subgroups, depending on whether there was PT response (P for interaction = 0.015). In the PT nonresponder group, LNs nonresponder status was also a significant negative predictive factor for RFS (HR = 5.56; 95% CI: 1.60-19.25; P = 0.007). (Fig. 2).

Figure 4 depicts LNs responder status in patients, the black dotted line indicates the tumor bed area, the red solid line indicates the viable tumor area, and the blue circle in the upper right corner is enlarged by the blue arrow (10X). Case 1: LN-TRG 4, the residual tumor rate was 80.0%, showing extensive residual tumor cells, swelling of cytoplasm, eosinophilia and disappearance of cell boundaries in a few tumors, with no obvious degeneration, interstitial fiber proliferation around the tumor, and disappearance of lymphatic follicles (Fig. 4A). Case 2: LN-TRG 3, the residual rate was 25.0%, showing that partial tumors remained, the tumor cells became eosinophilic, the nuclei were enlarged, lobulated and strangely shaped with apoptosis, and the tumor degeneration was obvious. At the same time, there were more fibrous hyperplasia and lymphoid follicles in the surrounding stroma of the tumor (Fig. 4B). Case 3: LN-TRG 2, the residual rate was 5.0%, showing minimal tumor residue, with eosinophilic and keratotic tumor cells and marked tumor degeneration. There was extensive fibrous proliferation in the peritumoral stroma with calcification, histiocytic response, and keratinization residue (Fig. 4C). Case 4: LN-TRG 1, the residual rate was 0.0%, and no tumor residue was observed except for fibrous hyperplasia, a histiocytic reaction, and keratinization (Fig. 4D).

Our study found that LNs responder status was an independent prognostic factor for RFS, we were the first to grade LNs regression and applied it to locally advanced ESCC patients who received NCRT. In addition, we corrected for the observer error of the grading system by using immunohistochemistry for the first time. Finally, our research proved that the classification system had better ability to predict to RFS.

The pCR, PT-TRG, and the AJCC staging system could be regarded as effective indicators to predict long-term survival in neoadjuvant therapy, as previous studies have shown that pCR is an important factor for predicting long-term OS [16, 17]. However, some recent studies have demonstrated that a considerable number of patients with non-pCR can also obtain similar or even longer survival than pCR, which makes the effectiveness of pCR in predicting OS and RFS controversial [18–20]. In this study, pCR was also not the most important indicator in determining RFS. As for PT-TRG, numerous reports have proved that it has significant prognostic implications [21], but some researchers suggest that PT-TRG needs to be combined with pathological TNM staging, which can predict prognosis better in ESCC, this shows that its evaluation function is limited when PT-TRG is associated with LN metastasis [22]. Although in our study not only PT-TRG but also PT responder was not an independent prognostic factor, we could not deny the importance of assessing the responder status of the primary tumor. This may also be related to the confounding factor of metastatic LNs in our group. In addition, this study found that after multivariate analysis eliminated confounding factors, LNs responder status was an independent prognostic factor of RFS, and the expression of this factor was approximately the same in the subgroups. In the forest plot, we analyzed the subgroups which divided the patients into groups according to age, sex, smoking status, and drinking status. The result showed that whether LNs respond or not had no significant effect in most subgroups or influence on RFS. However, in the subgroup about PT responder status, we observed that LNs responder status significantly impacted on RFS. Meanwhile, compared to the PT responder group, LNs nonresponder status still had significant adverse effects on RFS in the group of PT nonresponder. The conclusion was similar to Kadota Tomohiro’s study, in which they suggested that LCER (low ratio of the number of positive metastatic LNs regression) was independently associated with shorter RFS, whereas LCER wasn’t a significant adverse prognostic factor in patients with PT responder status [23]. Conversely, more studies, not only including Groth Shawns’ multi-center analysis of the National Cancer Data Base (2006–2016) but also the Hagi Takaomi’s large sample review, showed that whether PT responder or not, LNs responder status had a great impact on RFS [24, 25]. Notably, there were only 27 patients in PT responder subgroup, thus more data are needed to support the differential presentation of LNs responder status in subgroups, but at least in our sample, LNs responder status was an independent prognostic factor of RFS.

We classified the LN-TRG as previously described. Since no internationally recognized grading criteria have been established for LN-TRG, we derived our criteria from the PT-TRG criteria [11]. Among the many grading systems, the Becker system has a higher consistency among observers due to clear cutoff values; thus, we used the Becker system to evaluate the LN-TRG. On the basis of this system, we are the first to correct for differences between observers using immunohistochemistry. The principle of immunohistochemistry is that an antibody with a color reagent can bind to specific cell antigens; for example, P40 is an antibody specific to the squamous cell, which can specifically bind to the antigen on the nucleus [27], but necrotic cells do not have the above functions. Therefore, when viable tumor cells could not be determined by morphology alone, both PCK (+) and P40 (+) cells were identified as viable tumor cells, which made the classification of LNs regression more objective and accurate. Furthermore, a Kaplan-Meier curve revealed that each curve of LN-TRG had a greater degree of discrimination, compared with PT-TRG, ypN, and the AJCC pathological staging. The patients with LN-TRG 1 were significantly associated with better RFS than those with grade 3 or 4, therefore, LN-TRG can better classify RFS. However, PT-TRG did not significantly affect the RFS (P > 0.05). Therefore, LN-TRG was a more reliable prognostic factor than PT-TRG. Furthermore, two other researches that studied NAC cases with esophageal adenocarcinoma or ESCC came to the same conclusion [28, 29]. Moreover, in our present study, 83 (74.1%) patients showed discordance between the LN-TRG and PT-TRG, 60 (72.3%) of whom exhibited a higher grade in LNs than in the PT, indicating different responses between PT and LNs, and showed a wore response in LNs compare with PT. This might have been associated with tumor heterogeneity, drug delivery, immune microenvironment and the target delineation during radiotherapy [30]. These differences may affect the therapeutic effect of NCRT; therefore, an independent and objective classification of LN-TRG is very valuable for evaluating the prognosis and even guiding the subsequent treatment.

In our study, we established the LN-TRG classification system and applied it to locally advanced ESCC patients who underwent NCRT, and verified the reliability of the classification system for differentiating RFS, but our study has several limitations. First, the study had a retrospective design and was performed at a single institution. Second, owing to the relatively small sample size, whether this reliable performance could be extended to all neoadjuvant treatment cases requires further verification. Third, although the radiotherapy schedule and dose were relatively standardized and unified, some differences still occurred in the chemotherapeutic drugs and cycles. Lastly, although we corrected for differences in the judgment regarding viable tumor areas between observers by using immunohistochemistry, a difference in tumor bed area as determined by different observers was still obvious.

In conclusion, the classification of LN-TRG performs well in predicting RFS of NCRT patients; however, it requires further verification in a larger prospective study to more accurately determine the prognoses thus optimize treatment strategies for this patient group.

Acknowledgements

The authors acknowledge the help of all the patients who took part in this study. Also, we are very grateful for the hard work of the investigators from Sichuan Cancer Hospital & Institute.

Authors contributions YHZ analyzed the data, performed statistical analysis, and wrote the paper together with YL，QFW. YHZ and PG interpreted the H&E staining. WWH，XFL，CMZ，HY，SQ，JZ，and YW contributed to the data collection. YHZ carried out statistical analyses. PG and ZYH provided laboratory infrastructure. YHZ conceived the project, drafted the paper, and supervised the analyses together with YL and QFW. All authors read and approved the final manuscript.

Funding This work has been supported by the Fund project of Sichuan Medical Association (grant no. S20002).

Availability of data and materials

The datasets generated and/or analysed during the current study are not publicly available for reasons of data protection, but are available from the corresponding author on reasonable request in accordance with relevant guidelines and regulations.

Ethics approval and consent to participate

Ethical approval

The study was conducted in accordance with the guidelines of the declaration of Helsinki. Further, all methods were conducted in accordance with relevant guidelines and regulations. The study was approved by the ethics committee of Sichuan Cancer Hospital which waived the need for informed consent due to the retrospective design of the study. Ethical approval Permission has been obtained from the Regional Ethical Committee (Nos: SCCHEC-02-2017-043 and SCCHEC-02-2023-029).

Conflict of interest

All authors declare that they have no competing interests.

Consent to publish

Not applicable.

Author details

¹ Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

² Chengdu Medical College China

³Department of Radiotherapy, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

⁴ Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Sung H, Ferlay J, Siegel R et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 2021; 71: 209-249.
Lagergren J, Smyth E, Cunningham D, Lagergren P. Oesophageal cancer. Lancet 2017; 390: 2383-2396.
Hirohata R, Hamai Y, Hihara J et al. Evaluation of Neoadjuvant Chemoradiotherapy Followed by Surgery for Borderline Resectable Esophageal Squamous Cell Carcinoma. World j surg 2022; 46: 1934-1943.
Yang H, Liu H, Chen Y et al. Neoadjuvant Chemoradiotherapy Followed by Surgery Versus Surgery Alone for Locally Advanced Squamous Cell Carcinoma of the Esophagus (NEOCRTEC5010): A Phase III Multicenter, Randomized, Open-Label Clinical Trial. J clin oncol 2018; 36: 2796-2803.
Yang H, Liu H, Chen Y et al. Long-term Efficacy of Neoadjuvant Chemoradiotherapy Plus Surgery for the Treatment of Locally Advanced Esophageal Squamous Cell Carcinoma: The NEOCRTEC5010 Randomized Clinical Trial. Jama surg 2021; 156: 721-729.
Shapiro J, van Lanschot JJB, Hulshof M et al. Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): long-term results of a randomised controlled trial. Lancet oncol 2015; 16: 1090-1098.
Ding T, Liu C, Huang B et al. A Survival Prediction Nomogram for Esophageal Squamous Cell Carcinoma Treated with Neoadjuvant Chemoradiotherapy Followed by Surgery. Cancer Manag Res 2021; 13: 7771-7782.
Makino T, Miyata H, Yamasaki M et al. Utility of response evaluation to neo-adjuvant chemotherapy by (18)F-fluorodeoxyglucose-positron emission tomography in locally advanced esophageal squamous cell carcinoma. Surgery 2010; 148: 908-918.
Mandard AM, Dalibard F, Mandard JC et al. Pathologic assessment of tumor regression after preoperative chemoradiotherapy of esophageal carcinoma. Clinicopathologic correlations. Cancer-am cancer soc 1994; 73: 2680-2686.
Becker K, Mueller JD, Schulmacher C et al. Histomorphology and grading of regression in gastric carcinoma treated with neoadjuvant chemotherapy. Cancer-am cancer soc 2003; 98: 1521-1530.
Klevebro F, Tsekrekos A, Low D et al. Relevant issues in tumor regression grading of histopathological response to neoadjuvant treatment in adenocarcinomas of the esophagus and gastroesophageal junction. Dis esophagus 2020; 33: null.
Yasuda T, Yano M, Miyata H et al. Prognostic Significance of (18)F-fluorodeoxyglucose Positron Emission Tomography (FDG-PET)-Positive Lymph Nodes Following Neoadjuvant Chemotherapy and Surgery for Resectable Thoracic Esophageal Squamous Cell Carcinoma. Ann surg oncol 2015; 22: 2599-2607.
Makino T, Doki Y, Miyata H et al. Use of (18)F-fluorodeoxyglucose-positron emission tomography to evaluate responses to neo-adjuvant chemotherapy for primary tumor and lymph node metastasis in esophageal squamous cell carcinoma. Surgery 2008; 144: 793-802.
Doki Y, Ishikawa O, Takachi K et al. Association of the primary tumor location with the site of tumor recurrence after curative resection of thoracic esophageal carcinoma. World j surg 2005; 29: 700-707.
Matsuyama J, Doki Y, Yasuda T et al. The effect of neoadjuvant chemotherapy on lymph node micrometastases in squamous cell carcinomas of the thoracic esophagus. Surgery 2007; 141: 570-580.
Saeed SM, Naffouje S, Mehta R et al. Impact of histology classification on pathologic treatment response and overall survival in distal esophageal cancer patients: a propensity matched analysis. Dis esophagus 2021; 34: null.
Zheng Y, Liu XB, Sun HB et al. A phase III study on neoadjuvant chemotherapy versus neoadjuvant toripalimab plus chemotherapy for locally advanced esophageal squamous cell carcinoma: Henan Cancer Hospital Thoracic Oncology Group 1909 (HCHTOG1909). Ann transl med 2021; 9: 73.
Qian D, Chen X, Shang X et al. Definitive chemoradiotherapy versus neoadjuvant chemoradiotherapy followed by surgery in patients with locally advanced esophageal squamous cell carcinoma who achieved clinical complete response when induction chemoradiation finished: A phase II random. Radiother oncol 2022; 174: 1-7.
Zhang G, Zhang C, Sun N et al. Neoadjuvant chemoradiotherapy versus neoadjuvant chemotherapy for the treatment of esophageal squamous cell carcinoma: a propensity score-matched study from the National Cancer Center in China. J cancer res clin 2022; 148: 943-954.
Leng X, He W, Yang H et al. Prognostic Impact of Postoperative Lymph Node Metastases After Neoadjuvant Chemoradiotherapy for Locally Advanced Squamous Cell Carcinoma of Esophagus: From the Results of NEOCRTEC5010, a Randomized Multicenter Study. Ann surg 2021; 274: e1022-e1029.
Nasierowska-Guttmejer A, Szawłowski A. How to standardize the evaluation of tumor regression grading of gastrointestinal cancers after neoadjuvant therapy? Virchows arch 2018; 473: 255-256.
Yun JK, Kim Y, Lee GD et al. Tumor regression grade combined with lymph node status in esophageal squamous cell carcinoma after neoadjuvant chemoradiotherapy. Cancer Med 2022; null: null.
Kadota T, Hatogai K, Yano T et al. Pathological tumor regression grade of metastatic tumors in lymph node predicts prognosis in esophageal cancer patients. Cancer sci 2018; 109: 2046-2055.
Groth SS, Burt BM, Farjah F et al. Prognostic value of neoadjuvant treatment response in locally advanced esophageal adenocarcinoma. J thorac cardiov sur 2019; 157: 1682-1693.e1681.
Hagi T, Makino T, Yamasaki M et al. Pathological Regression of Lymph Nodes Better Predicts Long-term Survival in Esophageal Cancer Patients Undergoing Neoadjuvant Chemotherapy Followed by Surgery. Ann surg 2022; 275: 1121-1129.
Ozawa H. [Principles and basics of immunohistochemistry]. Nihon Yakurigaku Zasshi 2019; 154: 156-164.
Urakawa S, Makino T, Yamasaki M et al. Lymph Node Response to Neoadjuvant Chemotherapy as an Independent Prognostic Factor in Metastatic Esophageal Cancer. Ann surg 2021; 273: 1141-1149.
Davies AR, Myoteri D, Zylstra J et al. Lymph node regression and survival following neoadjuvant chemotherapy in oesophageal adenocarcinoma. Brit j surg 2018; 105: 1639-1649.
Wen J, Luo KJ, Liu QW et al. The epithelial-mesenchymal transition phenotype of metastatic lymph nodes impacts the prognosis of esophageal squamous cell carcinoma patients. Oncotarget 2016; 7: 37581-37588.

Table.1 Clinicopathological Characteristics According to Total Lymph Node Regression Status

Variables	Total (n = 112)	Responders (n = 19)	Nonresponders (n = 93)	p
Age, n (%)				0.551
≤65	76 (67.9)	14 (73.7)	62 (66.7)
＞65	36 (32.1)	5 (26.3)	31 (33.3)
Sex, n (%)				0.458
Male	98 (87.5)	18 (94.7)	80 (86.0)
Female	14 (12.5)	1 (5.3)	13 (14.0)
Smoke, n (%)				0.079
No	30 (26.8)	2 (10.5)	28 (30.1)
Yes	82 (73.2)	17 (89.5)	65 (69.9)
Drinking, n (%)				0.741
No	33 (29.5)	5 (26.3)	28 (30.1)
Yes	79 (70.5)	14 (73.7)	65 (69.9)
Location, n (%)				0.560
Up	13 (11.6)	3 (15.8)	10 (10.8)
Middle	46 (41.1)	6 (31.6)	40 (43.0)
Low	53 (47.3)	10 (52.6)	43 (46.2)
Differentiation, n (%)				0.074
Well	10 ( 8.9)	4 (21.1)	6 (6.5)
Middle	65 (58.0)	8 (42.1)	57 (61.3)
Poor	37 (33.0)	7 (36.8)	30 (32.3)
cT, n (%)				0.373
2	10 ( 8.9)	1 (5.3)	9 (9.7)
3	87 (77.7)	18 (94.7)	69 (74.2)
4	9 ( 8.0)	0 (0)	9 (9.7)
5	6 ( 5.4)	0 (0)	6 (6.5)
cN, n (%)				0.743
0	1 ( 0.9)	0 (0)	1 (1.1)
1	32 (28.6)	5 (26.3)	27 (29.0)
2	60 (53.6)	12 (63.2)	48 (51.6)
3	19 (17.0)	2 (10.5)	17 (18.3)
Surgical Margin, n (%)				0.999
Negative	109 (97.3)	19 (100)	90 (96.8)
Positive	3 ( 2.7)	0 (0)	3 (3.2)
Nerve Invasion, n (%)				0.235
Negative	87 (77.7)	17 (89.5)	70 (75.3)
Positive	25 (22.3)	2 (10.5)	23 (24.7)
Lymph Vascular Invasion, n (%)				0.022
Negative	92 (82.1)	19 (100)	73 (78.5)
Positive	20 (17.9)	0 (0)	20 (21.5)
ypT, n (%)				0.044
0	28 (25.0)	6 (31.6)	22 (23.7)
1	14 (12.5)	6 (31.6)	8 (8.6)
2	23 (20.5)	3 (15.8)	20 (21.5)
3	46 (41.1)	4 (21.1)	42 (45.2)
4	1 ( 0.9)	0 (0)	1 (1.1)
ypN, n (%)				< 0.001
0	19 (17.0)	17 (89.5)	2 (2.2)
1	67 (59.8)	2 (10.5)	65 (69.9)
2	24 (21.4)	0 (0)	24 (25.8)
3	2 ( 1.8)	0 (0)	2 (2.2)

Table.2 Univariate and Multivariate Analysis of Recurrence-free Survival

Item	Univariate Analysis		Multivariate Analysis
	HR(95%CI)	P(Wald's test)	HR(95%CI)	P(Wald's test)
Age: ＞65 vs ≤65	1.02 (0.57,1.83)	0.944
Sex: Male vs Female	0.63 (0.25,1.59)	0.331
Smoke: Yes vs No	1.11 (0.58,2.12)	0.756
Drinking: Yes vs No	1.3 (0.68,2.48)	0.425
Location: ref.=UP
Middle	1.13 (0.43,2.99)	0.8
Low	1.1 (0.42,2.91)	0.844
Differentiation: ref.=well
Middle	9.24 (1.24,68.64)	0.03	7.42 (0.99-55.71)	0.051
Poor	8.61 (1.15,64.29)	0.036	6.68 (0.88-50.62)	0.066
cT: ref.=2
3	0.79 (0.33,1.89)	0.589
4	0.9 (0.27,2.97)	0.863
5	2.07 (0.66,6.46)	0.212
cN: ref.=0
1	0.37 (0.05,2.86)	0.344
2	0.31 (0.04,2.34)	0.258
3	0.41 (0.05,3.24)	0.395
Surgical Margin: Positive vs Negative	2.21 (0.53,9.17)	0.276
Nerve Invasion: Positive vs Negative	2.64 (1.49,4.66)	< 0.001	1.96 (0.83-4.59)	0.124
Lymph Vascular Invasion: Positive vs Negative	2.56 (1.4,4.69)	0.002	1.44 (0.61-3.40)	0.407
PT.TRG: ref.=0
1	0.73 (0.32,1.68)	0.464
2	1.47 (0.71,3.06)	0.299
3	2.06 (0.83,5.13)	0.122
ypT: ref.=0
1	0.83 (0.31,2.18)	0.699
1	0.83 (0.32,2.14)	0.697
3	1.62 (0.8,3.27)	0.178
ypN: ref.=0
1	1.7 (0.73,3.96)	0.218
2	2.5 (0.98,6.36)	0.054
3	4.87 (0.58,40.86)	0.145
pCR: Yes vs No	0.6 (0.19,1.93)	0.39
Stage.AJCC（8th）: ref.=0
Ⅰ	0.16 (0.03,0.99)	0.049	0.08 (0.01-0.73)	0.025
Ⅱ	0.39 (0.06,2.34)	0.3	0.16 (0.02-1.25)	0.08
ⅢA	0.46 (0.13,1.61)	0.225	0.02 (0.00-0.26)	0.002
ⅢB	0.9 (0.27,2.98)	0.867	0.03 (0.00-0.29)	0.003
PT. Responder: Yes vs No	1.2 (0.62,2.34)	0.589
LN. Responder: Yes vs No	3.31 (1.27,8.64)	0.015	23.01 (2.92-181.22)	0.003

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Prognostic Significance of positive lymph node regression grade to Neoadjuvant Chemoradiation for Esophageal Squamous Cell Carcinoma

Status:

Version 1

Abstract

Figures

Introduction

Patients And Methods

Statistical analysis

Results

Discussion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1