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Year : 2021  |  Volume : 17  |  Issue : 3  |  Page : 630-637

Novel nomogram predicting cancer-specific survival and overall survival in patients with primary esophageal small-cell carcinoma: A surveillance, epidemiology, and end results-based study

1 Department of Medical Oncology, Cheeloo College of Medicine, Qilu Hospital, Shandong University, Jinan, Shandong, China
2 Department of Oncology, Yunyang County People's Hospital, Yunyang, Chongqing, China
3 Department of Respiratory Disease, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang Province, China
4 Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China

Date of Submission01-Nov-2020
Date of Decision29-Dec-2020
Date of Acceptance05-Feb-2021
Date of Web Publication9-Jul-2021

Correspondence Address:
Jing Hao
Department of Medical Oncology, Cheeloo College of Medicine, Qilu Hospital, Shandong University, Jinan, 250012, Shandong Province
Na Shao
Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.JCRT_1612_20

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 > Abstract 

Background: Small-cell carcinoma is a relatively infrequent pathological variety of esophageal cancer. In this study, a novel nomogram model was developed to evaluate the cancer-specific survival (CSS) and overall survival (OS) of patients with primary esophageal small-cell carcinoma (ESmCC).
Materials and Methods: In total, 502 patients with primary ESmCC were identified based on data from 1973 to 2015 retrieved from the surveillance, epidemiology, and end results database. Clinical characteristics such as age at diagnosis, gender, race, site, tumor stage, surgery, radiotherapy, and chemotherapy were included for multivariate logistic analyses to predict CSS and OS. Nomogram models for the prediction of CSS and OS in ESmCC patients were tested with the concordance index (C-index) method and calibration curves.
Results: From our multivariate analyses, race, stage, chemotherapy, and radiotherapy, but not surgery, were significantly associated with the CSS of ESmCC patients, while age at diagnosis, stage, chemotherapy, and radiotherapy were significantly associated with their OS. Nomograms were developed using age at diagnosis, race, gender, stage, surgery, radiotherapy, and chemotherapy to predict the two survival measures; these nomograms were verified as accurate in predicting OS and CSS in ESmCC patients, with C-index values of 0.736 and 0.731, respectively.
Conclusions: By utilizing easily accessible clinicopathological information, we established a simple but useful tool for predicting the CSS and OS of ESmCC patients that could help to make personalized clinical decisions for patients with this rare malignancy.
Cancer-specific survival, esophageal small-cell carcinoma, nomogram, overall survival, surveillance, epidemiology, and end results

How to cite this article:
Li J, Yu H, Peng L, Li L, Wang X, Hao J, Shao N. Novel nomogram predicting cancer-specific survival and overall survival in patients with primary esophageal small-cell carcinoma: A surveillance, epidemiology, and end results-based study. J Can Res Ther 2021;17:630-7

How to cite this URL:
Li J, Yu H, Peng L, Li L, Wang X, Hao J, Shao N. Novel nomogram predicting cancer-specific survival and overall survival in patients with primary esophageal small-cell carcinoma: A surveillance, epidemiology, and end results-based study. J Can Res Ther [serial online] 2021 [cited 2021 Sep 26];17:630-7. Available from: https://www.cancerjournal.net/text.asp?2021/17/3/630/321014

 > Introduction Top

Small-cell carcinomas are a group of aggressive neoplasms that predominantly occur in the lung. Primary esophageal small-cell carcinoma (ESmCC) is a relatively infrequent pathological subtype that accounts for about 0.4%–3.1% of all esophageal cancers but accounts for nearly all the primary neuroendocrine tumors in the esophagus.[1],[2],[3] Patients with ESmCC often present with earlier metastatic disease like other small-cell carcinomas such as small-cell lung cancer and have a much poorer prognosis than patients suffering typical squamous cell carcinoma of the esophagus.[4],[5],[6],[7],[8] Due to the rarity of ESmCC, standardized treatment algorithms and guidelines have yet to be established for patients.[9] Chemotherapy is the most extensively adopted treatment modality for metastatic ESmCC patients.[10] For patients with ESmCC localized to the esophagus, case reports and small series studies suggest that surgery or definitive chemoradiation can improve prognosis.[11],[12] Another accepted approach is to use chemotherapy with or without radiotherapy, similar to the treatment used for small-cell lung cancer.[9],[13]

Given the low incidence of ESmCC and the scarcity of established guiding studies, a generally accepted algorithm has yet to be produced for optimal treatment of this malignancy.[9],[14] Case series studies performed retrospectively have intrinsic limitations, and rare malignancy cases such as ESmCC are difficult to be adequately pooled by individual centers or researchers for randomized studies. Nevertheless, population databases with public accessibility offer researchers sufficient data to make a large population-based study practicable. The surveillance, epidemiology, and end results (SEER) database is one such publicly available resource that could be used to explore appropriate treatments for this rare malignancy.[15]

In the current study, we described the clinical characteristics of patients with primary ESmCC identified in the SEER database. Multivariate Cox regression analysis was performed to identify prognostic factors and develop prognostic nomograms for the cancer-specific survival (CSS) and overall survival (OS) of ESmCC patients. The efficacy of the established prognostic nomograms was then examined using the concordance index (C-index) method and calibration curves. Ultimately, we developed a clinically useful tool to predict CSS and OS in ESmCC patients; the tool could help doctors and patients to make optimal and individualized treatment decisions.

 > Materials and Methods Top

Study population

In the present study, data from the SEER-18 Dataset, including 18 cancer registries in the USA, were used. SEER data from 1973 to 2015 were selected to identify the patient population of interest. Data searching with site-specific histology codes (i.e., C150, C151, C152, C153, C154, C155, C158, and C159) identified 84,148 patients diagnosed with esophageal cancer of all pathological types, among which 502 patients were diagnosed with primary small-cell carcinoma (ICD-O-3 codes: 8041, 8043, 8044, and 8045). Patients having undergone surgery, radiation, or chemotherapy were also identified with corresponding codes in the SEER database.

This study was population based without any identifiable information from individual patients being used. The ethics review board of our hospital provided exemption to the study because it was population based and did not involve human subjects.

Study variables

The characteristics analyzed in the current study included age at diagnosis, gender, race, site, histology, tumor stage, treatment modalities (surgery, radiotherapy, and chemotherapy), cause of death, and survival time. The Veterans Administration Lung Study Group staging system was used for tumor staging; patients were divided into groups of limited-stage diseases and extensive-stage diseases, the latter being defined as tumors extended to distant lymph nodes or organs (M1). The CSS and OS of ESmCC patients were the end point outcomes of the study. OS was defined as the time from diagnosis of ESmCC to death for any reason, while CSS was defined as the time from diagnosis to death due to ESmCC.

Statistical analysis

The clinicopathological characteristics of patients with ESmCC and other pathological types were categorized and compared. Multivariate logistic regression analysis was conducted to identify which characteristics were significantly associated with the CSS and OS of ESmCC. Kaplan–Meier survival analysis with a log-rank test was used to show the differences in CSS and OS time between the different patient groups. The hazard ratio and its 95% confidence intervals were calculated to assess the strength of association between different characteristics and CSS or OS. Based on the results of multivariate logistic regression analysis, nomograms for the 2- and 5-year CSS and OS of ESmCC patients were established; they were created as visualizing diagrams to obtain predicted values from the multivariate logistic regression models. The predictive value of the produced nomograms was assessed using the C-index, which is a measure of discriminative ability that quantifies the proportion of all patient pairs. Specifically, a C-index value of 0.5 indicates no predictive power, whereas a C-index value of 1.0 indicates perfect discriminating power. In addition, calibration curves were constructed to assess the performance of the nomogram models based on a logistic regression analysis. Receiver operating characteristic (ROC) curves of 2- and 5-year survival were used to verify the accuracy of the predictions. In these curves, where the area under the curve (AUC) is ≥0.5, the closer the AUC is to 1, the better the prediction accuracy. All data processing was performed in SPSS (version 25.0; IBM Corporation, Armonk, NY, USA) and R software (version 3.6.0). All statistical tests were two sided, and P < 0.05 was considered statistically significant.

 > Results Top

Patient characteristics

Among the 84,148 esophageal cancer patients retrieved from the SEER database, 502 (0.6%) were diagnosed with small-cell cancer histology. The demographic, clinical, and pathological characteristics of this “ESmCC cohort” are listed in [Table 1]. It consisted of 300 (59.8%) male and 202 (40.2%) female patients. There were a higher proportion of female patients with ESmCC histology compared with other esophageal cancer patients (40.2% vs. 24.0%; P < 0.001). However, there was no significant difference in age at diagnosis or race between the two histological groups. The primary tumor of most patients with other esophageal cancer types was located in the lower part of the esophagus (52.4%); this was also true of ESmCC patients but with a lower percentage (42.0%). As expected, the ESmCC cohort had higher metastatic disease stage at diagnosis (P < 0.001). Significantly, fewer ESmCC patients received surgery compared with patients of other histologies (8.6% vs. 26.3%, P < 0.001). Furthermore, they were less likely to undergo radiotherapy (45.6% vs. 54.3%, P < 0.001) but more likely to undergo chemotherapy (62.5% vs. 52.9%, P < 0.001). Given an interval of 5 years, we found no significant change in the diagnosis rate of ESmCC in all esophageal cancers from 1973 to 2015 [0.5%–0.9%; [Figure 1]]; however, there was a tendency toward a decreasing diagnosis rate of ESmCC after 2007.
Table 1: The demographic, clinical, and treatment characteristics of esophageal small-cell carcinoma patients in different pathological groups

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Figure 1: Broken line graph showing the proportion of primary small-cell carcinoma subtype in all esophageal cancers in the past decades

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Independent prognostic factors in the study population

Multivariate cox proportional hazard analysis of the 502 patients with ESmCC demonstrated that those with a diagnosis age of 0–64, limited-stage disease, and having undergone radiotherapy or chemotherapy had significantly better OS [all P < 0.05; [Table 2]]. For CSS, patients with white or other ethnicities had significantly better CSS than patients with African ethnicity [P < 0.05; [Table 2]]. In addition, ESmCC patients with limited-staged disease and those that had undergone radiation or chemotherapy had significantly better CSS [all P < 0.0001; [Table 2]]. The hazard ratios for undergoing surgery in ESmCC patients were 0.69 and 0.75 for CSS and OS, respectively, neither of which were statistically significant (P > 0.05). However, there was a tendency for surgery to improve the survival of ESmCC patients, especially for CSS.
Table 2: Multivariate cox proportional hazard analyses of cancer-specific survival and overall survival in patients with esophageal small-cell carcinoma

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Kaplan–Meier survival curves

The CSS and OS Kaplan–Meier survival curves of ESmCC patients with different clinical and treatment characteristics are shown in [Figure 2]. ESmCC patients with limited-stage disease had significantly better CSS and OS (P < 0.05) relative to patients with extensive-stage disease [Figure 2]a and [Figure 2]b. Interestingly, surgery at the primary site also improved OS and CSS according to univariate Kaplan–Meier survival analysis that did not include the influence of staging on survival [P < 0.05; [Figure 2]c and [Figure 2]d]. This might be explained by the tendency for patients undergoing surgery to have early-stage tumors with better prognoses. CSS and OS were both improved in patients who had received radiation or chemotherapy relative to patients who had not [P < 0.05; [Figure 2]e, [Figure 2]f, [Figure 2]g, [Figure 2]h].
Figure 2: Kaplan–Meier survival curves for esophageal small-cell carcinoma overall survival time (a, c, e, and g) and cancer-specific survival time (b, d, f, and h) with various clinical and treatment characteristics

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Nomogram development

The prognostic nomograms of OS and CSS were developed to predict the 2- and 5-year survival rate in the study cohort based on age at diagnosis, gender, race, stage, surgery, radiation, and chemotherapy. Each prognostic parameter was assigned a score on the point scale shown in [Figure 3] and [Figure 4]. The 2- and 5-year OS and CSS rates of ESmCC patient were evaluated by determining the score of each prognostic parameter and calculating the total score. The prognostic nomogram of OS suggested that chemotherapy contributed most to the prediction, followed by stage, race, radiation, age at diagnosis, and surgery [Figure 3]. For the CSS nomogram, chemotherapy and stage shared the largest contribution toward the prediction, followed by race, radiation, and surgery [Figure 4].
Figure 3: Nomogram predicting the overall survival rate at 2 and 5 years in patients with primary esophageal small-cell carcinoma

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Figure 4: Nomogram predicting the cancer-specific survival rate at 2 and 5 years in patients with primary esophageal small-cell carcinoma

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Internal validation of the nomograms

The two nomogram models for survival prediction were internally validated by assessing their performance in discrimination and calibration. Discrimination was evaluated using the C-index, which was 0.731 and 0.736 for the models predicting OS and CSS, respectively. The calibration curves for 2- and 5-year OS and CSS are shown in [Figure 5]; there was agreement between the 2- and 5-year CSS and OS estimated from the nomograms, and the corresponding survival times derived from Kaplan–Meier estimation. Finally, ROC curves were used to estimate the predictive accuracy of the entire study [Figure 6]; the AUC values of the 2-year and 5-year survival rate curves in the current cohort were 0.704 and 0.736, respectively.
Figure 5: Calibration curves verifying the nomograms predicting 2-year overall survival (a), 2-year cancer-specific survival (b), 5-year overall survival (c), and 5-year cancer-specific survival (d) in primary esophageal small-cell carcinoma patients

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Figure 6: Receiver operating characteristic curves estimating the accuracy of 2-year (a) and 5-year (b) survival predictions in primary esophageal small-cell carcinoma patients

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 > Discussion Top

Clinical prediction models such as nomograms act as useful decision aids in predicting cancer risk, prevention, and prognosis.[16] Although these prediction models cannot compete with evidence derived from randomized prospective clinical trials with large sample sizes, they do aid clinical decision-making when clinical trial data are unavailable or an appropriate therapeutic algorithm has yet to be determined.[17] Primary ESmCC is a rare and typically aggressive malignancy with poor prognosis. A predictive model has not yet been designed that facilitates the prediction of ESmCC prognosis; hence, different treatment decisions in different individual cases have led to varying patient survival outcomes.[5],[18] In the current study, we established novel nomogram models that were able to accurately estimate the CSS and the OS of ESmCC patients.

In our study, data on 84,148 esophageal cancer patients were available, and 0.6% of these patients (502) were diagnosed with small-cell carcinoma histology. This percentage was in agreement with previous studies, which showed that ESmCC accounted for 0.4%–3.1% of primary esophageal cancers.[1],[2],[3] In addition, a SEER-based study also reported an ESmCC incidence of 0.6% in the USA between 1973 and 2009.[19] Although we observed a decreasing ESmCC diagnosis rate since 2007, incidence of ESmCC tended to be increasing in East Asia including Japan and China.[5],[20] For example, Chen et al. reported that the incidence of ESmCC in the same center rose from 0.94% to 1.15% in 2019 and proposed that this increase may have been due to improved diagnostic pathology.[21],[22] However, increased incidence might also be attributable to these studies being based on single institutes.

ESmCC is more likely to occur in male patients, with a previously reported male-to-female ratio being 1.66.[4] Similarly, the male-to-female ESmCC patient ratio in the present study was 1.49; however, a significantly higher proportion of patients with ESmCC histology were female compared with the proportion in other esophageal cancer patients. In addition, black patients with ESmCC tended to have worse CSS, although not to a significant extent, which was consistent with findings in other cancer types, suggesting either a lack of access to appropriate care or genetic differences in patients with African ethnicity.[23],[24]

For rare diseases such as ESmCC, it is difficult to perform randomized and controlled studies to identify appropriate treatment modalities. Therefore, recruiting data from the SEER database, as in the present study, provides the advantage of a large ESmCC patient sample size, which enables comprehensive analysis (e.g., multivariate analyses) of real-world treatment modalities and treatment optimization. In our analyses, significantly fewer ESmCC patients received surgery and radiation compared with those with other histologies; however, more ESmCC patients received chemotherapy compared with patients with other esophageal cancer types. Although surgery is considered the primary treatment modality for ESmCC, its advantage might only be seen in patients with localized disease in combination with chemotherapy.[25] We found that surgery did not significantly influence the OS or CSS of ESmCC patients, although most patients that underwent surgery had localized disease. In a retrospective study of 211 ESmCC patients, Chen et al.[26] demonstrated that surgery alone was primarily indicated for Stage I and IIA patients, whereas chemotherapy should be the primary treatment approach for those with ESmCC at Stage IIB or above; a combination of chemotherapy and radiotherapy tended to improve survival in the latter group of patients. In another retrospective study, Wong et al.[27] found that esophagectomy was associated with improved OS within ESmCC patients with node-negative localized disease when compared with chemoradiation; esophagectomy or chemoradiation was recommended as a part of multimodal treatments to improve survival for selected patients with nonmetastatic ESmCC. Multicenter studies with large sample sizes are required to confirm the value of surgery in ESmCC. In addition, translational research could help to select ESmCC patients who would benefit the most from surgery.[28]

Currently, chemotherapy is typically considered part of ESmCC treatment, although there remains a lack of conclusive evidence-based support for this approach.[2],[29] While the use of palliative chemotherapy as an optimal treatment for extensive-stage ESmCC is not debated, the use of chemotherapy in localized disease is controversial. There have been recommendations supporting the use of chemotherapy even in early ESmCC;[30] however, Chen et al.[26] concluded that Stage I and IIA ESmCC could be treated by surgery alone and that chemotherapy did not further improve survival. Radiotherapy is frequently used for local control in esophageal cancers including ESmCC. The overall response rate to radiotherapy in ESmCC can reach 60% and contribute to the long-term survival of patients, suggesting that radiotherapy alone or in combination with chemotherapy is an effective treatment mode for localized disease control.[22] In the current study, 62.5% and 45.6% of ESmCC patients underwent chemotherapy and radiation therapy during the disease course, respectively. Moreover, in our multivariate analysis, both chemotherapy and radiotherapy improved CSS and OS for ESmCC patients, further highlighting their importance as treatment modalities.

Among the patient factors included in our novel nomogram, chemotherapy and stage shared the largest contribution for predicting survival. For such an aggressive malignancy with a small cell histology, extensive ESmCC stage was always likely to predict poor survival. As previously discussed, chemotherapy is recommended as both a neoadjuvant or adjuvant therapy in early-stage ESmCC and as palliative therapy in metastatic disease. According to our novel nomogram, chemotherapy was the most potent prognostic factor of CSS, which supports its crucial role in the ESmCC treatment algorithm. However, radiotherapy ranked only fourth, behind chemotherapy, stage, and race, in terms of discriminating power for survival prediction in our nomogram. Our results therefore strengthen the predicting role of race in ESmCC, particularly in relation to patients with African ethnicity. As discussed previously, the role of surgery in ESmCC remains ambiguous and might only be an advantage in patients with localized disease in combination with chemotherapy. In our analyses, surgery did not significantly influence the CSS or OS of ESmCC patients.

The novel nomograms developed here performed well in predicting CSS and OS in ESmCC patients: the C-index values were 0.736 and 0.731, respectively, and the predicted CSS and OS at 2 and 5 years were highly proximate to actual survival data according to calibration curves. Thus, these nomograms could potentially be applied more universally in clinical practice. Furthermore, nomograms that incorporate parameters associated with disease prognosis could act as convenient tools for assessing individual risk and thereby assisting doctors in more accurately predicting prognosis and making decisions related to personalized treatment.

As a population-based study, there are some innate limitations in the current research. First, the study was performed retrospectively using data from the SEER database, which creates intrinsic biases and limits analysis to those predictive factors specifically available in this database. For example, the SEER database did not include data on performance status score, radiotherapy dosages, or chemotherapy regimens. Moreover, potential combined treatment modalities such as surgery plus radiotherapy and chemotherapy as well as detailed surgery types were also not included for analysis. Thus, some important prognostic factors were not included in our analysis. It is also important to recognize that the prediction models were constructed based on limited data in the SEER database that might not represent the actual ESmCC patient population. In addition, although our nomograms and risk classification system were established based on data from a large ESmCC cohort, and the models were internally validated for accuracy, further validation with an external patient cohort is required.

 > Conclusion Top

In summary, we have established a set of nomograms and a relevant risk classification system to predict the cancer specific survival and overall survival of patients with primary esophageal small cell carcinoma using four clinicopathologic parameters and three treatment related parameters. The internal validation of the nomogram models demonstrated its great accuracy. Although further external validation is still needed, this set of tools can be useful in helping clinicians and patients to make treatment decisions in areas including prognostic evaluation, personalized medicine as well as clinical trial designing.

Financial support and sponsorship

This work was funded by the Clinical Research Center of Shandong University (No. 2020SDUCRCC010), Shandong Province Key Research Program (2015GGH318025), and Beijing Medical and Health Foundation Grant (YWJKJJHKYJJ-F1121A).

Conflicts of interest

There are no conflicts of interest.

 > References Top

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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]

  [Table 1], [Table 2]


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