Construction and validation of a novel prognostic nomogram for patients with poorly differentiated gastric neuroendocrine neoplasms

Abstract

BACKGROUND

The prognosis of patients with poorly differentiated gastric neuroendocrine neoplasms (PDGNENs) is dismal and related research is limited.

AIM

To investigate the prognostic factors, and validate a novel prognostic nomogram for PDGNEN patients.

METHODS

We conducted a retrospective study using clinical and pathological data from PDGNEN patients treated at the First Medical Center of the Chinese PLA General Hospital from January 2000 to June 2023. Overall survival (OS) differences were assessed with the Log-rank test and Kaplan-Meier survival curves. Cox regression analysis identified independent risk factors for prognosis. Model performance was evaluated using Harrell’s concordance index, receiver operating characteristic analysis, area under the curve, calibration curves, and decision curve analysis (UDC), including the area under the UDC.

RESULTS

The study included 336 patients (227 with neuroendocrine carcinoma and 109 with mixed adenoneuroendocrine carcinoma). The average age was 62.7 years. The cohort comprised 80 (24.7%) patients in stage I, 146 (42.9%) in stage II, 62 (18.1%) in stage III, and 48 (14.3%) in stage IV. Significant differences in OS were observed across tumor-node-metastasis stages (P < 0.001). Multivariate analysis showed age, Ki-67 index, invasion depth, lymph node metastasis, distant metastasis, and platelet-to-lymphocyte ratio as independent risk factors. We developed a nomogram with a concordance index of 0.779 (95% confidence interval: 0.743-0.858). Receiver operating characteristic analysis showed area under the curves for 1-year, 3-year, and 5-year OS predictions of 0.865, 0.850, and 0.890, respectively. The calibration curve demonstrated good agreement with actual outcomes. The area under the UDC for the nomogram vs the 8^th American Joint Committee on Cancer tumor-node-metastasis staging system were 0.047 vs 0.027, 0.291 vs 0.179, and 0.376 vs 0.216 for 1-year, 3-year, and 5-year OS, respectively.

CONCLUSION

PDGNENs are predominantly found in older men, often in advanced stages at diagnosis, resulting in poor prognosis. The established nomogram demonstrates strong predictive capability and clinical utility.

Key Words: Gastric neuroendocrine neoplasms; Poorly differentiated tumor; Nomogram; Prognosis; Overall survival

Core Tip: This single-center retrospective study investigates the clinicopathological characteristics of patients with poorly differentiated gastric neuroendocrine neoplasms and develops a prognostic prediction model. A total of 336 patients were included, making it the largest single-center cohort globally. Key findings indicate that platelet-to-lymphocyte ratio, age, Ki-67 index, invasion depth, lymph node metastasis, and distant metastasis are independent risk factors for survival. The nomogram prediction model demonstrated superior predictive accuracy and clinical usefulness compared to the tumor-node-metastasis staging system.

INTRODUCTION

Neuroendocrine neoplasms (NENs) originate from neuroendocrine cells and neurons, characterized by their secretion of hormones, active peptides, and neuronal amines. These rare and heterogeneous tumors can develop in various tissues and organs, with the gastrointestinal tract being the most common site, accounting for approximately 55% of all NENs[1-4]. Gastric NENs (G-NENs), which occur in the stomach, represent about 7% of all NENs and less than 2% of gastric neoplasms[5]. Recent advancements in medical technology and diagnostic techniques, including the widespread use of gastrointestinal endoscopy, have led to a 15-fold increase in the incidence of NENs[6-8]. A study revealed that the incidence of G-NENs rose from 0.309 per 100000 to 6.149 per 100000 over the past 40 years[8]. Similarly, the Japanese National Cancer Registry reported an incidence rate of 4.82 per 100000 in 2016[9]. This rising prevalence has garnered increasing attention in the medical community.

The current pathological classification of NENs follows the 2019 World Health Organization (WHO) 5^th edition of the classification of tumors of the digestive system[10]. NENs are categorized into neuroendocrine tumors (NETs), neuroendocrine carcinomas (NECs), and mixed neuroendocrine-non-NETs (MiNENs). These tumors are further divided into two subtypes: Poorly differentiated NENs and well-differentiated NENs. These subtypes differ in pathomorphology, molecular pathology, clinical manifestations, epidemiology, therapeutic strategies, and prognostic outcomes. While well-differentiated NENs generally have a favorable prognosis and minimal impact on survival, poorly differentiated NENs are associated with a poorer prognosis. Hence, it is crucial to study poorly differentiated NENs as distinct entities to better understand and address their unique challenges.

Currently, the prognosis of G-NENs is primarily assessed using the WHO/European NET Society grading system and the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control tumor-node-metastasis (TNM) staging system[11,12]. However, these systems focus mainly on anatomical factors and overlook other significant variables such as age, gender, lifestyle habits, and inflammatory markers. Nomogram is a prognostic tool that integrates clinical and laboratory parameters to estimate an individual patient’s survival probability. While several nomogram models have been developed for various malignant tumors and have demonstrated strong predictive capabilities in clinical settings[13-16], none currently exist for poorly differentiated G-NENs (PDGNENs). In this study, we analyzed the clinical data of 336 patients with PDGNENs treated at our hospital from 2000 to the present. As the largest single-center studies worldwide, this research significantly enriches the epidemiological understanding of this rare tumor and provides deeper insights into its clinical and pathological characteristics. More importantly, we have developed a novel nomogram prognostic model, which offers valuable reference and guidance for the individualized prognostic evaluation of patients.

MATERIALS AND METHODS

Patient selection

This study employed a retrospective case-control design. We collected data on patients with PDGNENs who were treated between January 2000 and June 2023 at the Department of General Surgery, Department of Gastroenterology, Department of Medical Oncology, and Department of Thoracic Surgery of the First Medical Center of the Chinese PLA General Hospital. Inclusion criteria were: (1) Diagnosis of NEC or MiNENs containing NEC components according to WHO classification criteria; (2) Tumor located in the stomach; (3) Absence of other malignant tumors; (4) No severe concomitant diseases; and (5) Complete clinical data and follow-up information. Exclusion criteria included: (1) Carcinoma in situ; (2) Presence of other malignant tumors or history of malignancy within the past 5 years, except for treated basal cell carcinoma of the skin or carcinoma in situ of the cervix; and (3) Other serious medical conditions. This study was approved by the Ethics Committee of the Chinese PLA General Hospital under approval number S2022-137-01.

Diagnosis and classification

According to the 2019 5^th edition of the WHO classification of tumors of the digestive system, NENs are categorized as NETs, NECs, and MiNENs. PDGNENs include NECs and MiNENs with NEC components, where the NEC component must constitute more than 30% of the tumor. All cases of MiNENs containing NEC included in this study were reclassified according to the latest criteria and were identified as mixed adeno-NEC (MANEC).

Tumor staging

Tumor staging was based on the 8th edition of the TNM system for gastric cancer from the International Union for Cancer Control/AJCC[17].

Follow-up

Patients were primarily followed up during outpatient clinic visits. For those unable to attend in person, follow-up was conducted via phone or short message service, with intervals not exceeding 6 months. The follow-up period for this study began at the time of diagnosis and continued until July 2023, with the primary endpoint being overall survival (OS).

Cutoff for inflammatory indicators

Fasting peripheral venous blood test results from the patients’ first admissions were retrieved from our hospital’s electronic case system. These results included routine blood metrics such as platelets and lymphocytes, as well as biochemical markers like fibrin. The optimal cut-off values for platelet-to-lymphocyte ratio (PLR) and fibrinogen (FBG) were determined using time-dependent receiver operating characteristic (ROC) curves, with values of 888.48 g/L and 3.91 g/L, respectively. Based on these cut-offs, patients were classified into four groups: Low-PLR (< 888.48), high-PLR (≥ 888.48), low-FBG (< 3.91 g/L), and high-FBG (≥ 3.91 g/L).

Statistical analysis

Data analysis and visualization were conducted using SPSS 26.0, R 4.2.0, and GraphPad Prism 9.0 software. Survival curves were generated using the Kaplan-Meier method, with differences in OS between groups assessed via the log-rank test. Prognostic risk factors were evaluated through Cox regression analysis, with results expressed as hazard ratios and 95% confidence intervals (CI). A prediction model was constructed based on independent risk factors identified by Cox regression and visualized using a nomogram created in R software. The model’s discriminative and predictive abilities were assessed by calculating the consistency index (C-index), plotting the ROC curve, and determining the area under the curve. Calibration of the model was verified using calibration curves, and decision curve analysis (DCA) was performed with the area under the decision curve to evaluate clinical utility. A P-value of < 0.05 was considered statistically significant.

RESULTS

Population characteristics

A total of 336 patients with PDGNENs met the strict inclusion and exclusion criteria. Among these, 277 (82.4%) were male and 59 (17.6%) were female, with an average age of 62.7 ± 9.35 years. Of these patients, 227 (67.6%) were diagnosed with NEC and 109 (32.4%) with MANEC. The distribution by TNM stage was as follows: 80 patients (24.7%) in stage I, 146 (42.9%) in stage II, 62 (18.1%) in stage III, and 48 (14.3%) in stage IV. Detailed clinicopathologic data are provided in Table 1. Follow-up information was obtained for all 336 patients, with a median follow-up time of 29.0 months (interquartile range: 11.4-40.1). There was a significant difference in OS among patients with PDGNENs at different TNM stages (P < 0.001; Figure 1).

Figure 1 Comparison of overall survival among stage I, stage II, stage III and stage IV patients. OS: Overall survival.

Table 1 Clinicopathological characteristics of 336 patients, n (%).

Clinicopathological characteristics	n (%)
Age (year), mean ± SD	62.7 ± 9.35
BMI (kg/m2), mean ± SD	4.7 ± 2.40
Gender
Male	277 (82.4)
Female	59 (17.6)
Smoking history
Yes	143 (42.6)
No	193 (57.4)
Drinking history
Yes	142 (42.3)
No	194 (57.7)
Pathological grade
NEC	227 (67.6)
MANEC	109 (32.4)
CgA
Positive	230 (68.5)
Negative	106 (31.5)
Syn
Positive	324 (96.4)
Negative	12 (3.6)
CD56
Positive	271 (80.7)
Negative	65 (19.3)
Vascular cancer
Yes	117 (34.8)
No	219 (65.2)
Perineural invasion
Yes	64 (19.0)
No	272 (81.0)
Ki-67 index (%)
< 70	104 (31.0)
≥ 70	232 (69.0)
Tumor diameter (cm)
< 3	45 (13.4)
≥ 3	291 (86.6)
Tumor morphology
Uplift	52 (15.5)
Ulcer	272 (81.0)
Others	12 (3.5)
Tumor location
Upper third	199 (59.2)
Middle third	53 (15.8)
Lower third	78 (23.2)
Others	6 (1.8)
Invasion depth
T1	27 (8.0)
T2	41 (12.3)
T3	111 (33.0)
T4	157 (46.7)
Lymph node metastasis
N0	77 (22.9)
N1	77 (22.9)
N2	86 (25.6)
N3	96 (28.6)
Distant metastasis
M0	275 (81.8)
M1	61 (18.2)
TNM stage
I stage	48 (14.3)
II stage	83 (24.7)
III stage	144 (42.9)
IV stage	61 (18.1)
PLR
Low-PLR	193 (57.4)
High-group	143 (42.6)
FBG
Low-FBG	218 (64.9)
High-FBG	118 (35.1)

BMI: Body mass index; NEC: Neuroendocrine carcinoma; MANEC: Mixed adeno-neuroendocrine carcinoma; CgA: Chromogranin A; Syn: Synuclein; TNM: Tumor-node-metastasis; PLR: Platelet-to-lymphocyte ratio; FBG: Fibrinogen.

Prognostic factors

Univariate log-rank analysis revealed that age, vascular invasion, Ki-67 index, tumor size, tumor location, depth of infiltration, lymph node metastasis, distant metastasis, PLR, and FBG were associated with the prognosis of patients with PDGNENs (P < 0.05). Variables with statistically significant differences in univariate analysis were further evaluated using multivariate Cox regression. This analysis identified age, Ki-67 index, depth of infiltration, lymph node metastasis, distant metastasis, and PLR as independent risk factors affecting prognosis (P < 0.05; Table 2).

Table 2 Univariate and multivariate analysis of survival time of gastric cancer patients.

Clinicopathological characteristics	Univariate analysis			Multivariate analysis
	HR	95%CI	P value	HR	95%CI	P value
Age (year)	1.030	1.012-1.048	0.001	1.040	1.019-1.061	< 0.001
BMI (kg/m2)	0.959	0.916-1.004	0.071	-	-	-
Gender
Female vs male	0.938	0.612-1.437	0.767	-	-	-
Smoking history
Yes vs no	1.120	0.821-1.528	0.474	-	-	-
Drinking history
Yes vs no	1.006	0.738-1.373	0.968	-	-	-
Pathological grade
MANEC vs NEC	0.770	0.546-1.087	0.137	-	-	-
CgA
Positive vs negative	0.768	0.556-1.061	0.109	-	-	-
Syn
Positive vs negative	1.745	0.646-4.710	0.272	-	-	-
CD56
Positive vs negative	1.073	0.734-1.568	0.717	-	-	-
Vascular cancer
Yes vs no	1.461	1.062-2.010	0.020	0.897	0.634-1.268	0.538
perineural invasion
Yes vs no	1.398	0.964-2.029	0.078	-	-	-
Ki-67 index (%)
≥ 70 vs < 70	1.786	1.240-2.571	0.002	1.504	1.022-2.214	0.038
Tumor diameter (cm)
≥ 3 vs < 3	2.713	1.470-5.006	0.001	0.775	0.369-1.628	0.502
Tumor morphology	-	-	0.107	-	-	-
Ulcer vs uplift	1.466	0.933-2.303	0.097	-	-	-
Others vs uplift	0.645	0.193-2.157	0.477	-	-	-
Tumor location	-	-	0.042	-	-	0.082
Middle third vs upper third	1.097	0.715-1.684	0.671	1.388	0.880-2.189	0.159
Lower third vs upper third	0.769	0.519-1.139	0.190	0.756	0.501-1.142	0.184
Others vs upper third	2.655	1.157-6.093	0.021	1.784	0.761-4.183	0.183
Invasion depth	-	-	< 0.001	-	-	0.040
T2 vs T1	3.003	0.846-10.874	0.089	2.224	0.582-8.490	0.242
T3 vs T1	4.824	1.493-15.590	0.009	2.288	0.594-8.819	0.229
T4 vs T1	11.766	3.728-37.133	< 0.001	3.764	0.972-14.575	0.055
Lymph node metastasis	-	-	< 0.001	-	-	< 0.001
N1 vs N0	1.534	0.853-2.759	0.153	1.229	0.654-2.308	0.522
N2 vs N0	3.335	1.966-6.658	< 0.001	2.746	1.518-4.968	0.001
N3 vs N0	8.491	5.117	< 0.001	4.534	2.416-8.355	< 0.001
Distant metastasis
M1 vs M0	4.808	3.396-6.808	< 0.001	2.513	1.666-3.792	< 0.001
TNM stage	-	-	< 0.001	-	-	-
II stage vs I stage	2.012	0.899-4.500	0.089	-	-
III stage vs I stage	5.502	2.649-11.428	< 0.001	-	-	-
IV stage vs I stage	16.746	7.837-35.784	< 0.001	-	-	-
PLR
High-group vs low-PLR	1.840	1.350-2.509	< 0.001	1.424	1.020-1.988	0.038
FBG
High-FBG vs low-FBG	2.386	1.746-3.260	< 0.001	1.153	0.821-1.620	0.410

HR: Hazard ratios; CI: Confidence interval; BMI: Body mass index; NEC: Neuroendocrine carcinoma; MANEC: Mixed adeno-neuroendocrine carcinoma; CgA: Chromogranin A; Syn: Synuclein; TNM: Tumor-node-metastasis; PLR: Platelet-to-lymphocyte ratio; FBG: Fibrinogen.

Establishment and validation of nomogram

The Cox proportional hazards model identified six independent risk factors affecting survival in patients with PDGNENs. Using these factors, we developed a nomogram to predict the risk of patient mortality. Individual scores are assigned based on age, Ki-67 index, depth of infiltration, lymph node metastasis, distant metastasis, and PLR. The nomogram estimates OS rates at 1 year, 3 years, and 5 years based on the total score (Figure 2A). Resampling validation of the nomogram showed a C-index of 0.779 (95%CI: 0.743-0.858), indicating strong predictive value. The area under the ROC curve for predicting 1-year, 3-year, and 5-year survival rates was 0.865, 0.850, and 0.890, respectively, demonstrating the model’s robust predictive ability (Figure 2B). The calibration curve, which compares predicted and actual death probabilities, closely aligns with the 45° line, indicating good agreement and consistency between predicted and actual outcomes (Figure 3). DCA was used to assess the clinical utility of the model, with the area under the decision curve for the nomogram and AJCC 8^th edition TNM staging system being 0.047 vs 0.027, 0.291 vs 0.179, and 0.376 vs 0.216 at 1 year, 3 years, and 5 years, respectively. Both models offer significant positive net benefits, but the nomogram shows higher net benefits and better clinical utility (Figure 4).

Figure 2 Nomogram prediction model. A: Nomogram prediction model for 1-year, 3-year, and 5-year overall survival in patients; B: Receiver operating characteristic for the nomogram prediction model. PLR: Platelet-to-lymphocyte ratio; OS: Overall survival; AUC: Area under the curve.

Figure 3 Calibration curve for the nomogram prediction model. OS: Overall survival.

Figure 4 Decision curve analysis of nomogram prediction model and American Joint Committee on Cancer (8^th edition) tumor-node-metastasis staging system. A: 1-year overall survival (OS); B: 3-year OS; C: 5-year OS. TNM: Tumor-node-metastasis.

DISCUSSION

Gastric cancer (GC) is a malignant tumor originating from gastric mucosal cells, with an incidence rate of approximately 17 per 10000, making it the fifth most common cancer globally and the fourth leading cause of cancer-related mortality[18]. GC is highly heterogeneous, with varying histological types exhibiting distinct clinical and pathological characteristics and prognoses[19]. Adenocarcinoma is the most prevalent subtype, accounting for about 95% of all GCs[20]. PDGNENs, which include gastric NEC and MiNENs with NEC components, predominantly consist of MANEC. PDGNENs are rare, representing only 0.1% to 0.6% of GCs[21], and there is a lack of comprehensive epidemiological and clinical research on this tumor type, resulting in unsatisfactory prognostic outcomes[22]. This study reviews 336 patients treated at our hospital over the past 23 years, representing the largest single-center sample size for research on PDGNENs to date. We have summarized the clinical and pathological characteristics, conducted a prognostic analysis, and developed a nomogram prognostic prediction model. This work contributes to a better understanding of these rare tumors and provides valuable guidance for clinical practice.

To minimize bias from insufficient sample sizes, this study retrospectively analyzed clinical and pathological data of patients with PDGNENs treated at our hospital from 2000 to 2023. The cohort included 227 patients with NEC (67.6%) and 109 patients with MANEC (32.4%), with a male-to-female ratio of 4.7:1 and an average age of 62.7 years. Tumors were predominantly located in the upper part of the stomach (199 cases, 59.2%), with an average size of 4.7 cm. Most patients (226 cases, 85.7%) were diagnosed at advanced stages (II, III, and IV). These findings align with similar studies, such as Chen et al’s research[23] from a single center in China, which reported a male-to-female ratio of 5.9:1, an average age of 61.7 years, and 59.8% of tumors originating from the upper stomach, with 74.4% of patients in progressive or advanced stages. Another Chinese report reflects similar epidemiological features[24]. In contrast, Li et al’s study[25], utilizing data from the SEER database, found a male-to-female ratio of 1.2:1, with 31.4% of tumors originating from the upper stomach and 53.3% of patients in advanced stages. These differences may be attributed to ethnic variations and differences in early screening practices, highlighting the need for improved awareness and diagnostic techniques to detect GC at earlier stages and improve overall patient outcomes.

FBG is a key glycoprotein involved in the acute phase response to trauma, playing crucial roles in wound healing, thrombosis regulation, and inflammation[26]. Elevated FBG levels have been associated with increased local infiltration and distant metastasis in various malignant tumors, often indicating a poor prognosis[27,28]. Cancer progression is closely linked to systemic inflammatory responses, which disrupt the balance of circulating leukocytes. Lymphocytes, essential for tumor immunity, are particularly significant; low lymphocyte counts generally reflect weakened tumor defenses[29]. Additionally, platelets contribute to tumor metastasis by protecting tumor cells from cytolysis and facilitating their spread via glycoprotein bridging[30]. Thus, the PLR serves as a marker of systemic inflammation and has been recognized as important in various malignancies[31]. Our study explores the relationship between FBG, PLR, and prognosis in patients with PDGNENs. We identified PLR as an independent prognostic factor (hazard ratios: 1.424, 95%CI: 1.020-1.988) and included it as a predictor in our nomogram. Additionally, age, depth of tumor infiltration, lymph node metastasis, distant metastasis, and Ki-67 index were also found to be independent prognostic factors, consistent with previous findings[32,33]. To improve prognosis for PDGNEN patients, enhancing diagnostic capabilities is crucial for early detection and intervention. Special attention should be given to older patients with high Ki-67 indexes and advanced TNM stages.

The study by Song et al[34] utilized the SEER database to develop a nomogram predicting the 1-year, 3-year, and 5-year cancer-specific survival of patients with G-NENs treated between 2010 and 2015. The SEER database offers the advantage of a large patient population, but it has limitations, such as lacking comprehensive data on imaging and blood tests, and providing ambiguous information on rare tumor types. For instance, the SEER database categorizes only “NET” and “NEC”, omitting “MANEC”. Additionally, it predominantly represents the American population, which differs significantly from the Chinese population in terms of ethnicity and treatment approaches. Consequently, the models derived from SEER may not fully apply to Chinese patients and should be considered complementary. Fang et al[35] developed a nomogram for 1183 patients with gastrointestinal and pancreatic NENs, including six predictors (age, tumor size, degree of differentiation, N-stage, M-stage, and tumor location). However, the C-index of this model was only 0.760. Its limitations include a broad scope covering multiple organ types and a limited range of observational indicators, reducing its specificity. Wang et al[36] proposed a nomogram for 276 G-NEN patients using four predictors (Ki-67 index, T stage, M stage), with a C-index of 0.806. This study’s limitations include treating NETs and NECs as a single group, resulting in reduced specificity. Additionally, it only provided predictions for 3-year OS, lacking predictions for 1-year and 5-year OS. In contrast, our study systematically reviewed 21 basic clinical parameters using the latest grading standards. We identified six independent risk factors for PDGNENs - age, depth of infiltration, lymph node metastasis, distant metastasis, PLR, and Ki-67 index - using Cox proportional hazards model analysis. These factors, readily available in clinical practice, were used to develop a nomogram predictive model. Our model demonstrated a C-index of 0.779 (95%CI: 0.743-0.858), indicating robust predictive value. The ROC analysis showed area under the curves of 0.865, 0.850, and 0.890 for 1-year, 3-year, and 5-year OS predictions, respectively, reflecting excellent predictive discrimination. The DCA confirmed that our nomogram offers strong clinical utility with higher net benefits compared to the AJCC 8th edition TNM staging system.

We acknowledge several limitations in this study. First, despite including 336 patients - the largest sample size reported from a single center - our results are subject to selection bias inherent in retrospective studies from a single center. Second, while we performed internal validation of the prediction model, there is a need for external validation using large, multi-center datasets. Lastly, due to database constraints, we lacked some patient clinical information, including details on preoperative neoadjuvant and postoperative adjuvant chemotherapy. Consequently, we could not assess the impact of adjuvant chemotherapy on patient outcomes. Additionally, our study focused solely on OS, without incorporating other prognostic metrics such as Disease-Free Survival.

CONCLUSION

PDGNENs are more prevalent in older men and are typically found in the upper stomach. Most patients are diagnosed at an advanced stage, leading to a poor prognosis. Independent risk factors for OS include age, Ki-67 index, invasion depth, lymph node metastasis, distant metastasis, and PLR. The nomogram we developed demonstrates strong predictive accuracy and clinical utility.

ACKNOWLEDGEMENTS

The authors would like to extend their heartfelt gratitude to each patient and their family who participated in this study.