Outcomes in gestational and non-gestational choriocarcinoma: A retrospective cohort study with nomograms and web tools

Abstract

Background:

Choriocarcinoma (CC), a rare and aggressive form of cancer, is composed of cytotrophoblasts and syncytiotrophoblasts. It is present in two subtypes: gestational choriocarcinoma (GCC) and non-gestational choriocarcinoma (NGCC). Recognizing the disparities between GCC and NGCC is essential for the precise staging, prognosis, and determination of the primary treatment strategy.

Objective:

This study aimed to differentiate clinical outcomes, treatment responses, and prognostic factors between GCC and NGCC and to introduce innovative tools for personalized treatment strategies.

Design:

A retrospective cohort study with Survival Analysis and Nomogram Development.

Methods:

We analyzed data from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database and identified female patients diagnosed with GCC and NGCC between 2000 and 2020. The clinicopathological features of each group were compared using the chi-square test. Kaplan-Meier curves, log-rank tests, and Cox proportional hazard regression were used to assess overall survival and cancer-specific survival and to determine risk factors. The 5-year survival predicting nomogram was constructed, evaluated, and validated.

Results:

The study included 919 patients with 719 CC and 200 patients with NGCC. The NGCC group was characterized by older age, a higher proportion of married individuals, more advanced disease stages, larger tumor sizes, and a higher frequency of surgical interventions than the GCC group. NGCC was associated with worse survival rates than GCC patients.

Conclusions:

This study highlights the critical role of chemotherapy in improving the survival of patients with NGCC, in contrast to its limited effect on GCC. The negative prognosis associated with radiotherapy underscores the urgent need for further investigation to optimize its use. In addition, the introduction of the first web-based survival prediction tool and predictive nomogram marked a significant advancement in personalized treatment strategies, enabling improved clinical outcomes by tailoring therapy to individual patients.

Keywords

chemotherapy precision medicine prognosis survival analysis

Introduction

Choriocarcinoma (CC) is an extremely rare and aggressive trophoblastic neoplasm that predominantly affects women of childbearing age. It is composed of cytotrophoblasts and syncytiotrophoblasts, the latter being responsible for hormone secretion.^1,2 Based on its origin, CC is divided into two subtypes: gestational (GCC) and non-gestational (NGCC).¹ GCC is more common than NGCC, and the occurrence of either CC subtype in postmenopausal women is extremely rare.²

GCC can arise from any gestation, including normal pregnancy, abortion, ectopic pregnancy, and molar pregnancy, with more than 50% of cases being preceded by a complete molar pregnancy.³ Most cases of GCC are present within months of an antecedent pregnancy, and it is uncommon for GCC to present concurrently with pregnancy.⁴

In contrast, NGCC is not associated with any form of pregnancy and arises from primordial germ cells in the gonads and extra-gonadal midline organs, such as the retroperitoneum and mediastinum.⁵ It accounts for <0.6% of all ovarian tumors. Due to its infrequency, its clinical manifestations are not well defined, and its symptoms are often non-specific, including abnormal vaginal bleeding, abdominal pain, and the presence of a pelvic mass.⁶

Recognizing the disparities between GCC and NGCC is essential for the precise staging, prognosis, and determination of the primary treatment strategy (surgery, chemotherapy, and radiotherapy). NGCC has a poor prognosis and requires aggressive treatment.⁷ Effective diagnosis and prompt initiation of chemotherapy are crucial for predicting the prognosis of both subtypes.⁸ However, GCC and NGCC exhibit similar clinical manifestations and histological features, except for a clinical history of pregnancy, which can aid in differentiating GCC from NGCC.^9,10

The diagnosis is confirmed through genetic polymorphism examination by short tandem repeat (STR) analysis, as NGCC possesses the same STR alleles as the patient, whereas GCC is identified by the presence of a paternal chromosome complement.¹¹ GCC demonstrates higher immunogenicity and responds well to chemotherapy, whereas NGCC exhibits lower immunogenicity and is less sensitive to chemotherapy.¹² A combination of surgery and chemotherapy is the standard treatment for NGCC.¹³

Radiation therapy has been reported to be effective in patients with cerebral metastases.⁷ However, several unanswered questions remain, including the choice between conservative and radical surgical procedures in reproductive-aged women and the effect of therapy on survival and fertility.¹⁴ Understanding the major characteristics and differentiating between the two subtypes can significantly improve patient outcomes. This study aimed to investigate the unique characteristics and prognostic factors of GCC and NGCC separately, with the goal of personalizing the prognosis and treatment for each type, as well as incorporating nomogram prognostic models.

Materials and methods

Data extraction

In this retrospective cohort study, we extracted the data from “Incidence-SEER 18 Regs Custom Data (with additional treatment fields), Nov 2020 Sub (2000–2020 varying)” database using SEER*Stat software (version 8.4.0.1). The patients who were diagnosed as CC from 2000 to 2020 based on the third edition of the International Classification of Diseases for Oncology (ICD-O-3) were included in this study. Histology code for the disorder was the following: 9100/3 (choriocarcinoma).

Patients with any of the following criteria were excluded: diagnosis not confirmed by histology, CC not the first tumor, or other malignancies present in the body. Finally, 919 eligible patients diagnosed with CC remained. A detailed screening process is shown in the flow diagram (Supplemental Figure S1).

Ethics approval and consent to participate were not required for this study. Authorization and data were obtained through the Surveillance, Epidemiology, and End Results (SEER) website and database, respectively.

Variables

Clinical and demographic data for each patient were organized by age, race, marital status, T component of American Joint Committee on Cancer (AJCC), AJCC stage, metastasis, surgery, chemotherapy, and radiation therapy. Age was reported in two groups (<39 and >39 years). Race was classified into (white, black, and other). Treatment modalities (surgery, chemotherapy, and radiation therapy) were categorized as yes or no.

Statistical analysis

Extracted SEER data of this retrospective cohort study were analyzed by R language (v4.0.0) software, and the elementary packages were “readxl,” “tidyverse,” “Hmisc,” “data. table,” “table1,” “MatchIt,” “survminer,” “survival,” and “broom.” Chi-square analysis was used to analyze different categorical variables and to evaluate distinct clinicopathological characteristics between GCC and NGCC patients. The Kaplan-Meier method was used to estimate survival rates and the Log-rank test was used to analyze the difference between survival curves. Multivariable Cox regression models were performed to reflect and identify independent predictors for overall survival (OS) and cancer-specific survival (CSS). A nomogram predicting 5-year survival was formulated based on the results of multivariable Cox regression using the “rms” package in R software. The performance of the nomogram was evaluated by the receiver operating characteristics. Calibration curves were plotted to assess the calibration of the nomogram. A two-tailed p-value less than 0.05 was considered statistically significant.

Table 1.

Clinicopathological characteristics.

Category characteristics	Gestational (N = 719)	Non-gestational (N = 200)	Overall (N = 919)	p-Value
Age (years)
>39	125 (17.4%)	75 (37.5%)	200 (21.8%)	<0.001
0–39	594 (82.6%)	125 (62.5%)	719 (78.2%)
Race
Black	121 (16.8%)	34 (17.0%)	155 (16.9%)	0.942
Other	119 (16.6%)	28 (14.0%)	147 (16.0%)
White	479 (66.6%)	138 (69.0%)	617 (67.1%)
Year of diagnosis
2000–2009	297 (41.3%)	103 (51.5%)	400 (43.5%)	0.037
2010–2020	422 (58.7%)	97 (48.5%)	519 (56.5%)
Marital status
Married	378 (52.6%)	126 (63.0%)	504 (54.8%)	0.032
Not married	341 (47.4%)	74 (37.0%)	415 (45.2%)
T
T1	541 (75.2%)	66 (33.0%)	607 (66.1%)	<0.001
T2	148 (20.6%)	46 (23.0%)	194 (21.1%)
T3	0 (0%)	24 (12.0%)	24 (2.6%)
T4	30 (4.2%)	64 (32.0%)	94 (10.2%)
Metastasis
M0	422 (58.7%)	91 (45.5%)	513 (55.8%)	0.004
M1	297 (41.3%)	109 (54.5%)	406 (44.2%)
American Joint Committee on Cancer (AJCC)
I	341 (47.4%)	12 (6.0%)	353 (38.4%)	<0.001
II	70 (9.7%)	16 (8.0%)	86 (9.4%)
III	165 (22.9%)	0 (0%)	165 (18.0%)
IV	81 (11.3%)	13 (6.5%)	94 (10.2%)
Missing	62 (8.6%)	159 (79.5%)	221 (24.0%)
Surgery
Not performed	281 (39.1%)	41 (20.5%)	322 (35.0%)	<0.001
Surgery performed	438 (60.9%)	159 (79.5%)	597 (65.0%)
Chemotherapy
No	139 (19.3%)	41 (20.5%)	180 (19.6%)	0.935
Yes	580 (80.7%)	159 (79.5%)	739 (80.4%)
Radiation
No	695 (96.7%)	189 (94.5%)	884 (96.2%)	0.369
Yes	24 (3.3%)	11 (5.5%)	35 (3.8%)

Results

Clinicopathological characteristics of GCC and NGCC patients

A total of 919 patients with CC were identified in the SEER database, divided into 719 patients with GCC and 200 patients with NGCC. Detailed clinicopathological characteristics are summarized in Table 1. There was a statistically significant difference in the age distribution between the GCC and NGCC groups, with younger individuals in the GCC group (p < 0.001). A higher proportion of individuals in the NGCC group were married than those in the GCC group (63.0% versus 52.6%, p = 0.032).

The GCC group had a higher proportion of T1 stage tumors (75.2%) than the NGCC group (33.0%; p < 0.001). There was also a significant difference in the metastasis status, with a higher proportion of M1 (metastasized) cases in the NGCC group (54.5%) than in the GCC group (41.3%; p < 0.001).

The distribution of AJCC stages showed significant differences, with the GCC group having a higher proportion of stage I cases (47.4%) than the NGCC group (6.0%; p < 0.001). More individuals in the NGCC group underwent surgery (79.5%) than those in the GCC group (60.9%), and this difference was statistically significant (p < 0.001).

Survival rates of GCC and NGCC patients

GCC was associated with better OS and CSS rates than NGCC (95.6% versus 73% and 95.2% versus 71.2%, respectively; Figure 1). In the GCC group, patients who underwent chemotherapy had lower 5-year OS rates than those who did not (91.6% versus 100%; Figure 2). There were significant differences in the 5-year CSS rates between patients who did and did not receive chemotherapy (93.9% and 100%, respectively).

Figure 1.

Kaplan-Meier survival curves. (a) OS stratified by cancer type; (b) CSS stratified by cancer type.

Figure 2.

GCC: Kaplan-Meier survival curves. (a) OS stratified by chemotherapy; (b) CSS stratified by chemotherapy.

In the NGCC group, a significant difference in OS and CSS was observed between patients who received chemotherapy (76.3%) and those who did not (51.1%; Figure 3).

Figure 3.

NGCC: Kaplan-Meier survival curves. (a) OS stratified by chemotherapy; (b) CSS stratified by chemotherapy.

Prognostic factors for OS and CSS in GCC and NGCC patients

To determine possible independent prognostic factors for OS and CSS, we used univariate Cox regression and selected significant variables for multivariate regression. Regarding GCC, marital status, metastasis, and radiation were significantly associated with OS, while metastasis was significantly associated with CSS. The multivariate regression results are shown in Figure. 4.

Figure 4.

GCC: Multivariate Cox regression analyses. (a) OS; (b) CSS.

Regarding NGCC, older age, metastasis, and radiation were significantly poor predictors of OS and CSS. Chemotherapy was a good prognostic factor for OS and CSS. The results of multivariate regression analysis are shown in Figure 5.

Figure 5.

NGCC: Multivariate Cox regression analyses. (a) OS; (b) CSS.

Performance and validation of the nomogram for predicting 5-year survival in GCC and NGCC

A nomogram that integrated all significant factors for gestational trophoblastic neoplasia in the multivariate Cox regression models was developed and is presented in Supplemental Figures S2(a) and S3(a). The calibration curves for both nomograms showed good agreement between predicted and observed probabilities for 5-year survival, with a mean error of 0.01 for the NGCC and 0.015 for the GCC nomogram (Supplemental Figures S2(b) and S3(b)). The area under the curve of the NGCC nomogram was 0.83 (95% CI 0.77–0.9), whereas that of the GCC was 0.71 (95% CI 0.64–0.79; Supplemental Figures S2(c) and S3(c)).

Web-based survival prediction tool for CC patients

A web-based tool was developed using a random forest model that incorporated various clinical variables to predict the survival of patients diagnosed with CC. Clinicians and researchers can input patient-specific data to estimate survival duration.

The interactive tool, designed for ease of use and rapid calculation, is accessible through the following link: https://sakhrshwayyat.shinyapps.io/GCC_NGCC/.

Discussion

Despite the infrequent occurrence of CC, it is a malignant neoplasm that should be considered because of its aggressive nature and metastatic potential. The two subtypes of CC, GCC, and NGCC, display distinct features that require tailored treatment. However, differentiating between these subtypes can be difficult because of their rarity and shared clinical, ultrastructural, and immunohistochemical characteristics. Limited data are available on the clinical course, prognosis, and standard treatment of NGCC, which is less common and has a worse prognosis than GCC.^10,11 To address these challenges, predictive models that have been applied in rare gynecological cancers,^15–18 offer a valuable tool for refining prognosis and optimizing treatment strategies. This study aimed to improve patient outcomes by separately investigating the key characteristics and prognostic factors of GCC and NGCC, with the goal of allowing personalized and optimized therapeutic interventions.

The age distribution differs between patients with GCC and NGCC. In our study, 82.6% of patients with GCC were below 39, while 17.4% were above 39. In comparison, NGCCs age distribution was 37.5% above 39 and 62.5% below 39. In a retrospective study done on 13 patients with GCC, the median age was found to be 36.¹⁹ While GCC is typically seen in women of childbearing age, some cases have been reported in postmenopausal women.²⁰ NGCC mainly affects adolescents and younger women, with a median age of 13.²¹

While the placenta is the primary site for GCC, NGCC mainly emerges from reproductive organs. In our study, the ovary was the most common primary site (48/200), followed by the endometrium (42/200), then the fundus of the uterus (15/200). In addition, several NGCC cases have emerged from outside the reproductive organs, including the colon, bladder, anterior mediastinum, and stomach. A case of primary gastric CC was reported by Santiago Casiano et al. in a 24-year-old female,²² and other studies have also showcased NGCC outside the reproductive organs.^23,24

Our analysis also showed an increase in the prevalence of GCC from 41.3 to 58.7 in the last decade. This could be attributed to histopathological advancement in diagnosing GCC, allowing earlier and more precise detection of even small lesions.^25–27 Our research indicated that GCC exhibited an OS of 91.4%, while NGCC demonstrated an OS of 64.9%. This is consistent with the widely held belief that GCC typically has a more favorable prognosis than NGCC.²⁸ In a study of 21 NGCC patients by Jiao et al., the 5-year survival rate was 79.4%.²⁹ This difference may be due to several factors, including NGCCs decreased sensitivity to chemotherapy compared to GCC,³⁰ its greater tendency to invade adjacent organs, and its higher likelihood of metastasizing to distant organs.¹³

Multivariate analysis revealed that metastatic GCC is a poor prognostic factor, as distant metastasis indicates a higher tumor stage and increased mortality risk.²⁸ In addition, the model showed that non-married females had a statistically significant negative impact on prognosis.

Our study revealed that NGCC patients under the age of 39 had a better prognosis, as per a study by Liu et al. on 39 patients with ovarian NGCC. This study showed that older age has a negative impact on OS.⁵

Our analysis found that chemotherapy for GCC has limited benefit; this could be attributed to the earlier stages of GCC at presentation compared to NGCC, which limits the benefit of chemotherapy. This challenges the current standard management of patients with GCC, which includes either single or polychemotherapy based on the FIGO staging and classification system.^31,32 A study by Braga et al. showed that patients with nonmetastatic GCC and normal hCG levels sustained complete remission without chemotherapy.³³ Other studies of patients with nonmetastatic GCC also showed complete remission without chemotherapy in most patients.^27,34,35 This suggests that nonmetastatic patients may benefit from expectant management, avoiding the use of chemotherapy and its potential side effects. This may warrant a revision of the FIGO system treatment approach. Several studies have also called for a revision of the FIGO system’s approach to chemoresistance with higher scores.^36,37

In our study, chemotherapy showed a strong association with a good prognosis for NGCC. A study by Goswami et al. supported our findings by comparing the 2-year survival of patients who underwent surgery combined with chemotherapy to those who underwent surgery alone, with 2-year survival rates of 81% and 28%, respectively.³⁸ A case report of a patient who achieved complete remission with polychemotherapy for NGCC also supports its use.³⁹ Currently, there is no standard therapy for NGCC, but treatment generally follows that for GCC, with different chemotherapeutic regimens being used.⁴⁰

Our research demonstrated that radiation therapy was associated with poor prognosis. Currently, the use of radiotherapy in combination with chemotherapy is primarily reserved for the management of patients with brain metastasis, isolated metastases at other sites, or to minimize hemorrhagic complications, with resulting survival rates of 50%–75%.⁴¹

In a case series involving four patients with brain metastasis, chemotherapy combined with radiosurgery was used for stabilization without the need for whole-brain radiation.⁴² This finding, in addition to our previous findings, suggests that chemotherapy without radiation therapy may be more effective in the management of CC.

In addition to the prognostic efficacy of radiation therapy, adverse effects should also be considered, particularly in patients with gynecological cancers. Given that CC primarily affects women of childbearing age, radiation therapy can affect fertility.⁴³ In addition, radiation may result in gestational complications following radiation exposure, such as miscarriage and preterm labor.⁴⁴ Furthermore, radiation can cause damage and toxicity to the abdominopelvic organs, leading to bowel discomfort, rectal bleeding, and bladder irritation.⁴³ Several studies are currently being conducted to evaluate the psychological effects of radiation therapy, with findings indicating an increased incidence of psychological symptoms in patients receiving radiation.^45,46 Considering the already existing impact of cancer on the mental health of patients,⁴⁷ radiation therapy may exacerbate their psychological state, especially when combined with chemotherapy.

Strengths and limitations

This study has several strengths. First, it utilized a large population-based dataset, allowing for a comprehensive analysis of clinical outcomes and prognostic factors in patients with GCC and NGCC. The development of a nomogram and web-based survival prediction tool represents a significant advancement in personalized treatment strategies, providing clinicians with accessible and data-driven decision-making support. However, this study had some limitations. As a retrospective analysis, it is inherently subject to selection bias and missing data, which may affect the generalizability of the results. The database lacks detailed treatment protocols, including chemotherapy regimens and response rates. Moreover, the absence of genetic and molecular data limits our ability to assess the underlying biological differences between GCC and NGCC. In NGCC, older age, advanced stage, and possible comorbidities may have biased chemotherapy and survival analyses. Finally, external validation using independent cohorts is necessary to validate our results. Future prospective studies are needed to further refine the risk stratification and optimize treatment approaches for these rare malignancies.

Conclusions

In this study, the NGCC group was characterized by older age, a higher proportion of married individuals, more advanced disease stages, larger tumor sizes, and a higher frequency of surgical interventions. Chemotherapy was found to be critical for improving survival in NGCC, in contrast to GCC, in which chemotherapy had limited benefit in prognosis due to the earlier stage at presentation. The negative prognosis associated with radiotherapy emphasizes the need for further research to determine its optimal use. This study also introduced the first known web-based survival prediction tool and predictive nomogram, which represent groundbreaking advancements in personalized treatment plans. These tools enable healthcare providers to tailor therapy according to individual patient profiles, leading to improved clinical outcomes.

Supplemental Material

sj-docx-1-whe-10.1177_17455057251344386 – Supplemental material for Outcomes in gestational and non-gestational choriocarcinoma: A retrospective cohort study with nomograms and web tools

Supplemental material, sj-docx-1-whe-10.1177_17455057251344386 for Outcomes in gestational and non-gestational choriocarcinoma: A retrospective cohort study with nomograms and web tools by Sakhr Alshwayyat, Mahmoud Bashar Abu Al Hawa, Karam Maraqa, Tala Abdulsalam Alshwayyat, Mustafa Alshwayyat, Hamdah Hanifa and Tala Alsaghir in Women’s Health

Supplemental Material

sj-docx-2-whe-10.1177_17455057251344386 – Supplemental material for Outcomes in gestational and non-gestational choriocarcinoma: A retrospective cohort study with nomograms and web tools

Supplemental material, sj-docx-2-whe-10.1177_17455057251344386 for Outcomes in gestational and non-gestational choriocarcinoma: A retrospective cohort study with nomograms and web tools by Sakhr Alshwayyat, Mahmoud Bashar Abu Al Hawa, Karam Maraqa, Tala Abdulsalam Alshwayyat, Mustafa Alshwayyat, Hamdah Hanifa and Tala Alsaghir in Women’s Health

Supplemental Material

sj-docx-3-whe-10.1177_17455057251344386 – Supplemental material for Outcomes in gestational and non-gestational choriocarcinoma: A retrospective cohort study with nomograms and web tools

Supplemental material, sj-docx-3-whe-10.1177_17455057251344386 for Outcomes in gestational and non-gestational choriocarcinoma: A retrospective cohort study with nomograms and web tools by Sakhr Alshwayyat, Mahmoud Bashar Abu Al Hawa, Karam Maraqa, Tala Abdulsalam Alshwayyat, Mustafa Alshwayyat, Hamdah Hanifa and Tala Alsaghir in Women’s Health

Footnotes

ORCID iDs

Sakhr Alshwayyat

Karam Maraqa

Hamdah Hanifa

Ethical considerations

Ethics approval is not required for this study. Authorization and data were obtained through the SEER website and database, respectively.

Consent for participate

Consent to participate is not required for this study.

Consent for publication

Not applicable.

Author contributions

Sakhr Alshwayyat: Conceptualization; Formal analysis; Writing – original draft.

Mahmoud Bashar Abu Al Hawa: Visualization; Writing – original draft.

Karam Maraqa: Methodology; Writing – original draft.

Tala Abdulsalam Alshwayyat: Visualization; Methodology.

Mustafa Alshwayyat: Formal analysis; Software.

Hamdah Hanifa: Writing – review & editing.

Tala Alsaghir: Writing – review & editing; Supervision.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

Supplemental material

Supplemental material for this article is available online.

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