Nomogram with insufficient examined lymph node count to help T3N0M0 gastric cancer patients with adjuvant chemotherapy selection–a population-based study combined with external validation

doi:10.21203/rs.3.rs-2958517/v1

Download PDF

Research Article

Nomogram with insufficient examined lymph node count to help T3N0M0 gastric cancer patients with adjuvant chemotherapy selection–a population-based study combined with external validation

https://doi.org/10.21203/rs.3.rs-2958517/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Objective

Whether chemotherapy is required for T3N0M0 gastric cancer patients after surgery is controversial.

Methods

Using the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database, 420 patients with pT3N0M0 gastric cancer diagnosed after radical resection between 2004 and 2016 were screened for analysis. Survival analysis was performed using the Kaplan-Meier method and the log-rank test. Cox proportional hazards regression analysis was used to screen independent prognostic factors and build a nomogram survival prediction model. The patients were divided into three groups of low, moderate, and high risk using X-tile software according to the risk score. A total of 335 patients with pT3N0M0 gastric cancer diagnosed between 2000 and 2013 at our hospital were used for external validation.

Results

Multivariate analysis revealed that age, histology, and examined lymph node count were independent prognostic factors for pT3N0M0 gastric cancer in the group without adjuvant therapy and were therefore included in the nomogram prediction model. The concordance index for the nomogram model was 0.628 (95% confidence interval, 0.542–0.714). All patients were divided into three risk subgroups according to the nomogram prediction score. The analysis results showed that adjuvant chemotherapy did not improve the prognosis of low risk patients, while moderate and high risk patients benefited from it. External validation was consistent with the SEER database results.

Conclusion

The model demonstrated that only moderate and high risk patients were recommended to receive adjuvant chemotherapy, while low risk patients were not.

T3N0M0 gastric cancer

surgery

nomogram

prognosis

adjuvant chemotherapy

Gastric cancer (GC) remains the sixth most common cancer and the third leading cause of cancer death worldwide [1]. Patient prognosis has improved considerably with the progress of early diagnosis, surgery, and adjuvant chemotherapy (ACT). For advanced GC, D2 radical resection plus ACT has a better prognosis than surgery alone [2–4].

In the sixth edition of the NCCN staging of GC, T3N0M0 was included in stage IB, while the latest Japanese GC guidelines did not recommend T3N0M0 GC patients to receive ACT. The patients in stages IIA and III were included in the reference clinical studies [5]. The seventh and eighth editions of TNM staging place T3N0M0 in stage II. The guidelines recommend that stage II and III patients receive ACT after D2 radical surgery [6, 7]. However, it is worth noting that N0 patients did not benefit from ACT (hazard ratio (HR) = 0.79; 95% confidence interval (CI): 0.39–1.60; P = 0.35) [3]. Other studies have found that T3N0M0 patients with high risk factors may benefit from ACT [8]. In this study, insufficient number of lymph nodes is not a high risk factor, as it is known that there is a correlation between the number of examined lymph node (ELN) and number of lymph node metastases. Insufficient number of detected lymph nodes can lead to bias in the pathological stage [9]. Therefore, the role of chemotherapy cannot be completely overlooked for patients with T3N0M0. Individualized treatment might need to be carried out after the risk of prognosis is graded.

In the present study, the Surveillance, Epidemiology, and End Results (SEER) database was used to analyze the risk factors affecting the prognosis of patients with T3N0M0 GC. The patients were further divided into low, moderate, and high risk groups using the nomogram score, and those who could benefit from ACT were selected.

Patient cohort

The SEER*Stat (version 8.3.9) software was used to identify 420 patients with pT3N0M0 GC diagnosed between 2004 and 2016. Inclusion criteria were as follows: (1) pathologically diagnosed GC patients (ICD-O-3: C16.1-16.6, C16.8-16.9), (2) complete follow-up and survival data, (3) not receiving neoadjuvant radiotherapy, (4) D2 radical operation, and (5) primary GC. Patients with pN0 were divided into no ACT (232) and ACT (188) groups according to whether or not ACT was performed. The variables included age, sex, grade, histology, size, primary site, ELN count, patient chemotherapy information, and survival information. Further exclusions were made if information on the above variables was not available.

The external validation was based on 335 cases of pT3N0M0 GC diagnosed between 1999 and 2015 in the Department of Gastrointestinal Surgery, Second Hospital of Jilin University. The inclusion criteria were the same as above. Among the participants, 219 patients did not receive ACT, and 116 patients did.

Statistical analysis

Chi-square test was used to analyze the relationship between treatment with and without ACT, as well as clinicopathological factors. In order to balance the confounding bias of the included cases, the clinicopathological factors with significant chi-square test results were included for propensity score matching (PSM). The two groups with and without ACT were matched using 1:1 nearest neighbor matching [10]. Survival analysis was performed using the Kaplan-Meier method and the log-rank test.

Establishment of prediction models: (1) Univariate and multivariate Cox analysis was used to evaluate the correlation between variables and overall survival (OS) in the group without ACT. (2) On the basis of Cox multivariate analysis, variables with P < 0.05 were selected to be included in the establishment of a nomogram prediction model and its performance was then tested. Discrimination was measured using the concordance index (C-index) [11]. Nomogram and ELN count C-indexes were compared to evaluate the clinical performance of the model. Consistency: The calibration curve intuitively shows the consistency between the predicted survival rate and the actual survival rate. The decision curve analysis was used to evaluate the net clinical benefit and to compare it to the ELN count. (3) All patients in the ACT and non-ACT groups were artificially divided into three groups of high, moderate, and low risk according to the nomogram risk score using X-tile software. [12]. All statistical analyses were performed using SPSS 24.0 and R language (version 4.0. 0), where P < 0.05 was considered statistically significant.

Patient demographics

Before determining the propensity score, a total of 420 patients with pT3N0M0 who underwent D2 radical surgery were included, of which 232 patients received and 188 did not receive ACT (Fig. 1). The median survival was 23 months (0–155), and the number of deaths was 268 (63.8%). Chi-square test showed that ACT was significantly correlated with age, histology, and ELN count (P < 0.05). After PSM with these variables related to ACT was carried out, the final number was 376, including 188 in the non-ACT group and 188 in the ACT group (Table 1). The median survival was 24 months (0–155), and the number of deaths was 234 (62.2%).

Table 1

Characteristics of patients
Variable	Unmatched Cohort				Matched Cohort
	Total [n(%)]	Non-ACT[n(%)]	ACT[n(%)]	P value	Total [n(%)]	Non-ACT[n(%)]	ACT[n(%)]	P value
Age	420	232	188	< 0.001	376	188	188	< 0.001
< 65	144	48(20.7)	96(51.1)		144	48(25.5)	96(51.1)
≥ 65	276	184(79.3)	92(48.9)		232	140(74.5)	92(48.9)
Sex				0.164				0.255
Male	221	115(49.6)	106(56.4)		201	95(50.5)	106(56.4)
Female	199	117(50.4)	82(43.6)		175	93(49.5)	82(43.6)
Grade				0.762				0.706
Well/Moderately	105	61(26.3)	44(23.4)		95	51(27.1)	44(23.4)
Poorly/undifferentiated	303	164(70.7)	139(73.9)		271	132(70.2)	139(73.9)
Unknown	12	7(3.0)	5(2.7)		10	5(2.7)	5(2.7)
Histology				0.076				0.087
Adenocarcinoma	262	155(66.8)	107(56.9)		233	126(67.0)	107(56.9)
Signet ring cell carcinoma	108	50(21.6)	58(30.9)		98	40(21.3)	58(30.9)
Other	50	27(11.6)	23(12.2)		45	22(11.7)	23(12.2)
Size (cm)				0.626				0.776
≤ 2	44	23(9.9)	21(11.2)		40	19(10.1)	21(11.2)
≤ 3	76	43(18.5)	33(17.6)		74	41(21.8)	33(17.6)
≤ 5	127	65(28.0)	62(33.0)		121	59(31.4)	62(33.0)
> 5	173	101(43.6)	72(38.2)		141	69(36.7)	72(38.2)
Primary site				0.664				0.095
Upper	19	11(4.7)	8(4.3)		19	11(5.9)	8(4.3)
Middle	141	73(31.5)	68(36.2)		141	73(38.8)	68(36.2)
Lower	188	110(47.4)	78(41.5)		166	88(46.8)	78(41.5)
Unknown	72	39(16.4)	33(18.0)		50	17(8.5)	33(18.0)
ELN count				0.015				0.401
< 15	268	160(69.0)	108(57.4)		224	116(61.7)	108(57.4)
≥ 15	152	72(31.0)	80(42.6)		152	72(38.3)	80(42.6)
ACT, adjuvant chemotherapy; ELN, examined lymph node

The prognosis of patients with ACT before PSM was higher than that of patients without ACT (five-year survival rate of 41.1% vs. 28.7%, P < 0.001, Fig. 2A). The prognosis of patients with ACT after PSM was still higher than that of patients without ACT (five-year survival rate of 41.1% vs. 28.2%, P < 0.001, Fig. 2B).

Nomogram construction

Patients without ACT were included in the Cox proportional hazards model (Table 2). Univariate analysis found that age, histology, size, and ELN count were associated with OS (P < 0.05). A nomogram was constructed to predict the three- and five-year survival rates after D2 radical resection of T3N0M0 GC according to the Cox multivariate analysis (Fig. 3).

Table 2

The univariate and multivariate analyses of factors associated with overall survival
Variable	univariate Cox regression		multivariate Cox regression
Variable	HR (95% CI)	P-value	HR (95% CI)	P-value
Age
< 65	1
≥ 65	1.626 (1.072–2.466)	0.022	1.822(1.151–2.884)	0.010
Sex
Male	1
Female	1.223(0.871–1.717)	0.246
Grade
Well/Moderately	1
Poorly/undifferentiated	1.224(0.832-1.800)	0.305
Unknown	1.243(0.441–3.505)	0.681
Histology
Adenocarcinoma	1
Signet ring cell carcinoma	1.136(0.760–1.699)	0.533	1.620(1.030–2.547)	0.037
Other	0.462(0.240–0.888)	0.020	0.620(0.317–1.213)	0.162
Size (cm)
≤ 2	1
2–3	0.504(0.272–0.935)	0.030	0.530(0.283–0.993)	0.047
3–5	0.450(0.248–0.815)	0.008	0.443(0.243–0.810)	0.008
> 5	0.576(0.327–1.017)	0.057	0.684(0.386–1.214)	0.194
Primary site
Upper	1
Middle	1.065(0.507–2.241)	0.867
Lower	1.070(0.513–2.233)	0.857
Unknown	0.759(0.293–1.969)	0.571
ELN count
< 15	1
≥ 15	0.617(0.429–0.887)	0.009	0.557(0.382–0.812)	0.002
ELN, examined lymph node

Prediction model effectiveness evaluation

The C-index for the nomogram model incorporating the above four risk factors was 0.647 (95% CI, 0.549–0.745), which was significantly higher than that for the ELN count 0.575 (95% CI, 0.491–0.659). The nomogram calibration curve for 3 and 5 year OS showed that the predicted survival probability was in good agreement with the actual survival probability (Fig. 4A, B). Decision curve analysis demonstrated that the net benefits of a nomogram prognostic model for different decision thresholds were greater than those of a prediction line for the ELN count system (Fig. 4C, D).

Risk stratification system for overall patient cohort

The risk score for each patient in the two groups was calculated using a nomogram (Table 3). All patients were divided into three risk groups by taking two cut-off values using X-tile software: low (score: ≤129, n = 117), moderate (score: 130–218, n = 215), and high risk (score: ≥223, n = 44) groups (Fig. 5). The 5 year survival rates for low, moderate, and high risk groups were 49.6%, 30.0%, and 18.0%, respectively, and the difference was statistically significant (P < 0.05, Fig. 2C).

Table 3

Point assignment of each component and prognostic score for T3N0 gastric cancer
Group	Score	Estimated 3-y OS (%)	Estimated 5-y OS (%)
Age
< 65	0
≥ 65	62
Histology
Adenocarcinoma	50
Signet ring cell carcinoma	100
Other	0
Size (cm)
≤ 2	84
2–3	18
3–5	0
> 5	45
ELN count
< 15	61
≥ 15	0
Total score
	-10	85
	22	80
	49	75
	71	70
	108	60
	139	50
	-15		80
	12		75
	34		70
	71		60
	102		50
ELN, examined lymph node

Using the existing scoring system, the non-ACT group was divided into low (n = 48), moderate (n = 113), and high risk (n = 27) groups. The 5 year survival rates of the three groups were 58.6%, 20.4%, and 10.0%, respectively (P < 0.05, Fig. 2D). In the ACT group, the 5 year survival rates in the low (n = 69), moderate (n = 102), and high risk (n = 17) groups were 43.7%, 41.3%, and 29.7%, respectively (P > 0.05, Fig. 2E).

Evaluating AT efficiency for patients in different groups

We then further studied whether the three groups of patients benefited from ACT (Table 4). The results showed that patients in the low risk group did not benefit from ACT (HR = 1.32; 95% CI: 0.77–2.26; P > 0.05; Fig. 2F), while patients in the moderate risk (HR = 0.51; 95% CI: 0.36–0.71; P < 0.001; Fig. 2G) and high risk (HR = 0.38; 95% CI: 0.19–0.76; P < 0.01; Fig. 2H) groups did.

Table 4

Risk stratification in non-ACT and ACT group
Survival status	Non-ACT Group				ACT Group
	Low risk[n(%)]	Moderate risk[n(%)]	High risk[n(%)]	P value	Low risk[n(%)]	Moderate risk[n(%)]	High risk[n(%)]	P value
Live	27(56.2)	24(21.2)	2(7.4)	< 0.001	34(49.3)	49(48.0)	6(35.3)	0.573
Death	21(43.8)	89(78.8)	25(92.6)		35(50.7)	53(52.0)	11(64.7)
ACT, adjuvant chemotherapy

ACT for patients in the external validation group

External validation included 335 patients with pT3N0M0 GC who underwent D2 radical surgery, of which 219 did not receive ACT and 116 did. The median survival was 68 months (0–146) and the number of deaths was 193 (57.6%). The prognosis for the ACT group was higher than that for the non-ACT group (5 year survival rate: 71.5% vs. 57.6%, P < 0.01 Fig. 6A).

All patients were divided into three risk groups according to the existing risk scores: low (score: ≤129, n = 213), moderate (score: 130–218, n = 72), and high risk (score: ≥223, n = 50) groups. The 5 year survival rates for the low, moderate, and high risk groups were 68.0%, 49.8%, and 55.6%, respectively (P < 0.05, Fig. 6B). The non-ACT group was divided into three risk groups using the existing scoring system as follows: low (n = 145), moderate (n = 46), and high (n = 28). The 5 year survival rates of the three groups were 66.3%, 36.5%, and 43.0%, respectively (P < 0.05, Fig. 6C). In the ACT group, the 5 year survival rates of the low (n = 68), moderate (n = 26), and high risk (n = 22) groups were 71.7%, 71.5%, and 71.1%, respectively (P > 0.05, Fig. 6D). Patients in the low risk group did not benefit from ACT (HR = 0.71; 95% CI: 0.47–1.07; P > 0.05; Fig. 6E), while patients in the moderate risk (HR = 0.48; 95% CI: 0.26–0.88; P < 0.05; Fig. 6F), and high risk (HR = 0.40; 95% CI: 0.20–0.81; P < 0.05; Fig. 6G) groups did.

Postoperative ACT is generally recommended for stage II and III advanced GC. While ACT can significantly reduce the recurrence rate of GC patients and increase their five-year OS by 10.6% [13], chemotherapy itself will cause related adverse reactions, which may lead to the death of patients in severe cases [14–17]. A classic study has previously demonstrated that ACT can improve DFS (HR = 0.56; 95% CI: 0.45–0.70; P < 0.001) and OS (HR = 0.64; 95% CI: 0.49–0.82; P < 0.001) in patients with stage II and III GC, although these results were based on the sixth edition TNM stages, where T3N0M0 belongs to stage IB [3]. The effect of ACT in patients with T3N0M0 has not been described in large-scale studies. The Japanese guidelines do not recommend ACT for T3N0M0 patients, which did not improve their OS in a study by Lee et al. (P = 0.731) [18]. Kang et al. have also found that T3N0M0 patients did not benefit from ACT (HR = 1.160; 95% CI: 0.644–2.089; P = 0.622) [19]. Currently, the issue of whether T3N0M0 patients with GC should receive ACT remains controversial. The purpose of the present study was to screen the high-risk factors affecting the prognosis of T3N0M0 patients using the SEER database and to classify patients via a nomogram in order to provide specific and personalized ACT treatment.

Significant guidance can be provided for ACT in T3N0M0 patients by studying the high-risk factors of postoperative recurrence. The present study found that age of ≥ 65 years was a high risk factor for patients (HR = 1.822; 95%CI: 1.151–2.884; P = 0.01). The elderly were typically in the middle and late stages of diagnosis due to the insidious disease onset before surgery. The incidence of postoperative complications is relatively high in cardiopulmonary diseases, and the prognosis is poor [20, 21]. The elderly also have a high rate of Helicobacter pylori infection and are prone to developing resistance to antibiotics. H. pylori infection is also associated with increased morbidity and mortality from GC [22, 23].

The incidence of gastric signet ring cell carcinoma is increasing every year, accounting for 35–45% of adenocarcinomas [24]. Signet ring cell carcinoma is usually accompanied by mutation of CDH1 and decreased expression of E-cadherin, which promotes the invasion and metastasis of GC, leading to its poor prognosis. Some studies have also found that the prognosis of early gastric signet ring cell carcinoma is better [25, 26], showing that the influence of gastric signet ring cell carcinoma on the prognosis of GC is controversial. The present study found that the prognosis of gastric signet ring cell carcinoma was relatively poor (HR = 1.620; 95%CI: 1.030–2.547; P = 0.037).

Whether tumor size is an independent prognostic factor of GC remains under debate. Yokota et al. believe that tumor size is not an independent prognostic factor for patients [27]. Bilici et al. [28] have found that the proportion of tumors with a size of > 8 cm in T3 GC patients was 44%. The prognosis of tumors with a size of ≤ 8 cm was better than that of those with a size of > 8 cm (HR = 0.33; 95% CI: 0.17–0.62; P = 0.001), where the tumor size was an independent prognostic factor. The larger the tumor, the longer the tumor growth cycle, and the larger the direct contact area with its surrounding normal tissues, the greater the possibility of invading blood vessels and lymph nodes leading to tumor micrometastases and worse prognosis. The present study found that tumor size was an independent prognostic factor for patients, but the relative prognosis of tumors with a size of < 2 cm and > 5 cm was poor. The larger the tumor, the higher the risk of lymph node metastasis and the worse the prognosis [29, 30]. However, the poor prognosis in tumors with a size of < 2 cm in T3N0M0 patients may be related to the 32% of signet ring cell carcinomas and 65% of patients with poorly differentiated or undifferentiated. Therefore, there was no absolute negative correlation between tumor size and prognosis in T3N0M0 patients.

Sufficient number of detected lymph nodes must be ensured in GC surgery to provide the optimal accuracy of N staging. The number of positive lymph nodes may also increase with the increase in the number of detected lymph nodes. Insufficient number of detected lymph nodes will lead to staging migration, eventually affecting patient prognosis and providing wrong guidance for postoperative diagnosis and treatment [31]. In order to ensure the accuracy of N staging, the total number of lymph nodes cleaned in patients with GC should reach at least 15 before it has the value of predicting postoperative survival. Otherwise, it is also prone to staging bias [32]. Therefore, there are many new methods of lymph node staging, such as metastatic lymph node ratio, log odds of positive lymph nodes, negative lymph node count, and lymph node micrometastasis. Their purpose is to reduce stage migration [33, 34]. Gu et al. have found that the prognosis of T3N0M0 GC patients with the number of lymph nodes of < 15 and T3N1 with the number of lymph nodes of ≥ 16 was the same, with stage migration and poor prognosis, which is consistent with the present results [35]. These results also showed that patients with sufficient lymph node detection had a good prognosis (HR = 0.557; 95% CI: 0.382–0.812; P = 0.002).

Compared to the number of lymph nodes detected (C-index: 0.581), the current nomogram (C-index: 0.725) can better predict the 3 and 5 year survival rate of T3N0M0 GC. It was further confirmed that the nomogram was superior to the number of detected lymph nodes in predicting the overall survival of patients with T3N0M0 GC. In addition, it was demonstrated that chemotherapy can benefit T3N0M0 patients, which may be because chemotherapy is mostly used in clinical patients with poor prognostic factors, resulting in postoperative ACT improving the prognosis. This does not mean that all patients need adjuvant treatment, which therefore requires to select patients who can truly benefit from chemotherapy with precise and individualized treatment. The pathological factors affecting the prognosis were scored using a nomogram, and the patients were divided into low, medium, and high risk groups. The present study found that patients in the low risk group did not benefit from ACT, which was consequently not recommended for them. Chemotherapy was recommended for medium and high risk patients because they did benefit from it. The present study did not simply evaluate whether patients should receive ACT. Each individual is different and each patient prognosis may vary. Therefore, by evaluating the prognosis of each patient, chemotherapy is recommended if the risk is high in order to guide the patient's treatment more accurately, avoid excessive medical treatment, and eliminate unnecessary physical and economic burden to the patient. The included data from our hospital also validated the conclusion that only moderate and high risk patients should receive ACT.

The present investigation had several limitations. The study was retrospective, which may lead to bias. The chemotherapy regimen and implementation cycle were not unified, which may have an impact on the results. At present, there has been no prospective study proving that T3N0M0 patients need chemotherapy or investigating a survival model that incorporates patient's pathological factors. Patient classification using such a model is of great significance for individualized guidance of clinical ACT, which highlights the importance of the present study.

Age, histology, size, and ELN count were independent prognostic factors for patients with T3N0M0 GC. After stratification using nomogram scores, patients at moderate and high risk are recommended to receive ACT, while low risk patients are not.

Acknowledgements

None.

Data Availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Author contributions

DCW designed the research. CZ collected the data, analyzed the date. STZ analyzed the date and wrote the manuscript. All the authors approved the final manuscript.

Funding

This work was supported by Department of Finance of Jilin Province (No.2021LC033;2020SCZT063;2019SCZT051).

Ethics approval and consent to participate

The study was conducted according to the Declaration of Helsinki’s ethical standards for medical research involving human people. The protocol was reviewed and approved by the Institutional Research Ethical Committee of Second Hospital of Jilin University. Written informed consent was obtained from the patients.

Consent for publication

Not applicable.

Competing interests

No potential conflicts of interest were disclosed.

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: a cancer journal for clinicians. 2021;71(3):209-249.
Bang YJ, Kim YW, Yang HK, et al. Adjuvant capecitabine and oxaliplatin for gastric cancer after D2 gastrectomy (CLASSIC): a phase 3 open-label, randomised controlled trial. Lancet (London, England). 2012;379(9813):315-321.
Noh SH, Park SR, Yang HK, et al. Adjuvant capecitabine plus oxaliplatin for gastric cancer after D2 gastrectomy (CLASSIC): 5-year follow-up of an open-label, randomised phase 3 trial. The Lancet Oncology. 2014;15(12):1389-1396.
Sasako M, Sakuramoto S, Katai H, et al. Five-year outcomes of a randomized phase III trial comparing adjuvant chemotherapy with S-1 versus surgery alone in stage II or III gastric cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2011;29(33):4387-4393.
Japanese gastric cancer treatment guidelines 2010 (ver. 3). Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2011;14(2):113-123.
Korean Practice Guideline for Gastric Cancer 2018: an Evidence-based, Multi-disciplinary Approach. Journal of gastric cancer. 2019;19(1):1-48.
Wang FH, Zhang XT, Li YF, et al. The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021. Cancer communications (London, England). 2021;41(8):747-795.
Imamura T, Komatsu S, Ichikawa D, et al. Poor prognostic subgroup in T3N0 stage IIA gastric cancer, suggesting an indication for adjuvant chemotherapy. Journal of surgical oncology. 2015;111(2):221-225.
Dong Y, Qiu Y, Deng J, et al. Insufficient examined lymph node count underestimates staging in pN3a patients after curative gastrectomy: a multicenter study with external validation. Journal of cancer research and clinical oncology. 2020;146(2):515-528.
Austin PC. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate behavioral research. 2011;46(3):399-424.
Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology. 1983;148(3):839-843.
Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clinical cancer research : an official journal of the American Association for Cancer Research. 2004;10(21):7252-7259.
Smyth EC, Nilsson M, Grabsch HI, van Grieken NC, Lordick F. Gastric cancer. Lancet (London, England). 2020;396(10251):635-648.
Lordick F, Nilsson M, Leong T. Adjuvant radiotherapy for gastric cancer-end of the road? Annals of oncology : official journal of the European Society for Medical Oncology. 2021;32(3):287-289.
Park SH, Lim DH, Sohn TS, et al. A randomized phase III trial comparing adjuvant single-agent S1, S-1 with oxaliplatin, and postoperative chemoradiation with S-1 and oxaliplatin in patients with node-positive gastric cancer after D2 resection: the ARTIST 2 trial(☆). Annals of oncology : official journal of the European Society for Medical Oncology. 2021;32(3):368-374.
Yoshikawa T, Terashima M, Mizusawa J, et al. Four courses versus eight courses of adjuvant S-1 for patients with stage II gastric cancer (JCOG1104 [OPAS-1]): an open-label, phase 3, non-inferiority, randomised trial. The lancet Gastroenterology & hepatology. 2019;4(3):208-216.
Cheong JH, Yang HK, Kim H, et al. Predictive test for chemotherapy response in resectable gastric cancer: a multi-cohort, retrospective analysis. The Lancet Oncology. 2018;19(5):629-638.
Lee KG, Lee HJ, Oh SY, et al. Is There Any Role of Adjuvant Chemotherapy for T3N0M0 or T1N2M0 Gastric Cancer Patients in Stage II in the 7th TNM but Stage I in the 6th TNM System? Annals of surgical oncology. 2016;23(4):1234-1243.
Kang M, Youn HG, An JY, et al. Adjuvant Chemotherapy vs. Surgery Alone for pT3N0M0 Gastric Cancer. Annals of surgical oncology. 2021;28(3):1437-1444.
Makiyama A, Kunieda K, Noguchi M, et al. First-line chemotherapy with S-1 alone or S-1 plus cisplatin for elderly patients with advanced gastric cancer: a multicenter propensity score matched study. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2018;21(5):792-801.
Nelen SD, Verhoeven RHA, Lemmens V, de Wilt JHW, Bosscha K. Increasing survival gap between young and elderly gastric cancer patients. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2017;20(6):919-928.
Holleczek B, Schöttker B, Brenner H. Helicobacter pylori infection, chronic atrophic gastritis and risk of stomach and esophagus cancer: Results from the prospective population-based ESTHER cohort study. International journal of cancer. 2020;146(10):2773-2783.
Huang Q, Jia X, Chu Y, Zhang X, Ye H. Helicobacter pylori Infection in Geriatric Patients: Current Situation and Treatment Regimens. Frontiers in medicine. 2021;8:713908.
Pernot S, Voron T, Perkins G, Lagorce-Pages C, Berger A, Taieb J. Signet-ring cell carcinoma of the stomach: Impact on prognosis and specific therapeutic challenge. World journal of gastroenterology. 2015;21(40):11428-11438.
Chon HJ, Hyung WJ, Kim C, et al. Differential Prognostic Implications of Gastric Signet Ring Cell Carcinoma: Stage Adjusted Analysis From a Single High-volume Center in Asia. Annals of surgery. 2017;265(5):946-953.
Kao YC, Fang WL, Wang RF, et al. Clinicopathological differences in signet ring cell adenocarcinoma between early and advanced gastric cancer. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2019;22(2):255-263.
Yokota T, Ishiyama S, Saito T, et al. Is tumor size a prognostic indicator for gastric carcinoma? Anticancer research. 2002;22(6b):3673-3677.
Bilici A, Uygun K, Seker M, et al. The effect of tumor size on overall survival in patients with pT3 gastric cancer: experiences from 3 centers. Onkologie. 2010;33(12):676-682.
Pokala SK, Zhang C, Chen Z, et al. Lymph node metastasis in early gastric adenocarcinoma in the United States of America. Endoscopy. 2018;50(5):479-486.
Liu X, Xu Y, Long Z, Zhu H, Wang Y. Prognostic significance of tumor size in T3 gastric cancer. Annals of surgical oncology. 2009;16(7):1875-1882.
Bunt AM, Hermans J, Smit VT, van de Velde CJ, Fleuren GJ, Bruijn JA. Surgical/pathologic-stage migration confounds comparisons of gastric cancer survival rates between Japan and Western countries. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 1995;13(1):19-25.
Deng J, Liang H, Sun D, Wang D, Pan Y. Suitability of 7th UICC N stage for predicting the overall survival of gastric cancer patients after curative resection in China. Annals of surgical oncology. 2010;17(5):1259-1266.
Lee SY, Hwang I, Park YS, Gardner J, Ro JY. Metastatic lymph node ratio in advanced gastric carcinoma: a better prognostic factor than number of metastatic lymph nodes? International journal of oncology. 2010;36(6):1461-1467.
Deng J, Zhang R, Wu L, et al. Superiority of the ratio between negative and positive lymph nodes for predicting the prognosis for patients with gastric cancer. Annals of surgical oncology. 2015;22(4):1258-1266.
Gu P, Deng J, Wang W, et al. Impact of the number of examined lymph nodes on stage migration in node-negative gastric cancer patients: a Chinese multi-institutional analysis with propensity score matching. Annals of translational medicine. 2020;8(15):938.

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Nomogram with insufficient examined lymph node count to help T3N0M0 gastric cancer patients with adjuvant chemotherapy selection–a population-based study combined with external validation

Status:

Version 1

Abstract

Objective

Methods

Results

Conclusion

Figures

Introduction

Materials and methods

Patient cohort

Statistical analysis

Results

Patient demographics

Nomogram construction

Prediction model effectiveness evaluation

Risk stratification system for overall patient cohort

Evaluating AT efficiency for patients in different groups

ACT for patients in the external validation group

Discussion

Declarations

References

Additional Declarations

Status:

Version 1