Postoperative clinicopathological factors affecting cervical adenocarcinoma

Zhou, Jiansong; Chen, Yuanyuan; Xu, Ximing; Yan, Dingding; Lou, Hanyi

doi:10.1097/md.0000000000009323

Cited by 10 publications

(7 citation statements)

References 31 publications

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“…According to many studies, patients with ADC exhibit worse survival outcomes than patients with SCC [ 17 18 ]. The Japan Society of Obstetrics and Gynecology collected and analyzed data from 15,698 patients with cervical cancer, and found that patients with SCC had a significantly better prognosis than patients with ADC (p=0.004); the 5-year OS rates were 80.4% and 75.7% for patients with SCC and ADC, respectively [ 19 ].…”

Section: Discussionmentioning

confidence: 99%

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

et al. 2020

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Objective To compare survival outcomes between cervical adenocarcinoma (ADC) and squamous cell carcinoma (SCC) using a propensity score matching (PSM) analysis based on the Surveillance, Epidemiology, and End Results (SEER) Program. Methods Patients diagnosed with cervical cancer between 1998 and 2016 were identified from the SEER database. The Kaplan-Meier method and Cox regression analysis were used to analyze survival. A subgroup analysis of overall survival (OS) between patients with ADC and SCC was performed after the 1:1 PSM analysis. Results Of the 33,148 patients, 24,591 (79.19%) had SCC and 8,557 (25.81%) had ADC. In the unmatched cohort, after adjustment in multivariate analysis, patients with ADC had a worse prognosis than patients with SCC (hazard ratio [HR]=1.12; 95% confidence interval [CI]=1.07–1.18; p<0.001). In the propensity matched cohort, Kaplan-Meier analysis and subgroup analysis showed that ADC was associated with a worse prognosis than SCC (p=0.001). An analysis stratified by SEER stage revealed a worse prognosis for patients with ADC patients presenting with a regional disease than patients with SCC (HR=1.24; 95% CI=1.14–1.36 p<0.001), but no statistically significant differences were observed between the localized disease (HR=0.97; 95% CI=0.86–1.10; p=0.664) and distant disease (HR=1.09; 95% CI=0.97–1.22; p=0.162) subgroups. Conclusion The significant differences in survival outcomes between patients with cervical ADC and SCC were only observed in the regional disease subgroup, but not in the localized disease and distant disease subgroups.

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Section: Discussionmentioning

confidence: 99%

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

et al. 2020

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“…These results are consistent with some previously reported research findings. A study has shown that the factors affecting the prognosis of cervical adenocarcinoma include histological grade, lymph node metastasis, and tumor size (7). Another study has pointed out that the prognosis of cervical adenocarcinoma patients with late International Federation of Gynecology and Obstetrics (FIGO) stage, local tumor diameter >4 cm, and poor tumor cell differentiation is poor (20).…”

Section: Discussionmentioning

confidence: 99%

“…Clinical variables cannot accurately predict the prognosis of patients with cervical cancer, and there is controversy among the results of various studies. A study pointed out that the depth of invasion and histological grade are related to prognosis (7). Research also emphasized that the clinical factors of cervical adenocarcinoma lack specificity, and only lymph node metastasis is an independent risk factor for the prognosis of cervical adenocarcinoma (8).…”

Section: Introductionmentioning

confidence: 99%

Screening of prognostic immune genes and establishment of prognostic model of cervical adenocarcinoma based on bioinformatics analysis

Sheng

Nie

2022

Ann Transl Med

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Background: There is currently a lack of clinical models to accurately predict the prognosis of cervical adenocarcinoma. This study aimed to explore the correlation between immune genes and the prognosis of cervical adenocarcinoma patients, and establish a prognostic model. Methods:Transcriptome sequencing data sets and clinical data sets of cervical adenocarcinoma samples were downloaded from the Gene Expression Omnibus (GEO) database. Information about the immune gene was obtained from the ImmPort database. Differentially expressed genes and differentially expressed immune genes were screened in cervical adenocarcinoma tissue and normal cervical group by edgeR package.Differentially expressed immune genes were screened for prognosis-related immune genes by Cox analysis. Taking the immune genes related to prognosis as variables, a prognosis prediction model was established by multivariate Cox regression analysis. Kaplan-Meier analysis and a receiver operating characteristic (ROC) curve were used to test the effectiveness of the model. According to the clinical information and risk score, univariate multivariate Cox analyses were used to screen the independent prognostic risk factors of cervical adenocarcinoma. Results: CXCL9 was an independent prognostic factor of cervical adenocarcinoma [hazard ratio (HR) =0.63; P=0.025]. CGB5 (HR =1.22; P=0.034), CXCL12 (HR =1.33; P=0.023), PTX3 (HR =1.53; P=0.024), and CXCL10 (HR =2.31; P=0.031) were prognostic risk factors for cervical adenocarcinoma. The risk score was calculated as follows: risk score = (0.005 × CXCL10) + (0.076 × CGB5) + (0.061 × CXCL12) + (0.034 × PTX3)+ (−0.004 × CXCL9). The prognosis of the low-risk score group was better than that of the high-risk score group (P=0.035). The area under the ROC curve (AUC) of the risk score was 0.713, and the predictive power was good. Multivariate Cox analysis showed that N stage (HR =1.34; P=0.035) and risk score (HR =1.37; P<0.001) were independent risk factors for the prognosis of cervical adenocarcinoma (HR >1; P<0.001).Conclusions: In this study, an immune gene prognosis prediction model for cervical adenocarcinoma was established based on the GEO and ImmPort databases. The prediction performance of the model is good, and the prognosis of patients can be evaluated according to the gene expression, which has clinical practicability.

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“…Although the incidence rate of cervical cancer has shown an overall decrease [21], the incidence rate of UAC has increased [22]. At present, the main treatment of UAC remains radical surgery or CCRT, but the sensitivity of UAC to radiotherapy is lower than that of SCC [23], and the survival outcomes of UAC patients are worse than SCC patients [24,25]. Therefore, more patients with UAC undergo surgery.…”

Section: Discussionmentioning

confidence: 99%

Nomograms for predicting the survival rate of stage T1−T2 uterine cervical adenocarcinoma patients after hysterectomy

2022

European Journal of Gynaecological Oncology

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To explore factors associated with the overall survival (OS) and cancer-specific survival (CSS) of patients with stage T1–T2 uterine cervical adenocarcinoma (UAC) after hysterectomy and develop nomogram models to predict their prognosis. The data of stage T1–T2 UAC patients after hysterectomy, diagnosed from 2004 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database, were retrieved and divided into a training cohort (n = 2103) and internal validation cohort (n = 1052). Another dataset of eligible patients (n = 107) diagnosed from 2013 to 2019 at the Fujian Maternal and Child Health Hospital was retrieved as the external validation set. Nomograms were developed by the results of univariate and multivariate Cox regression models of OS and CSS. C-index, calibration curve, receiver operating characteristic (ROC) curve and area under the curve (AUC) value were used to assess the prediction model. Age, race, marital status, tumor grade, T stage, tumor size and number of positive lymph nodes were identified as independent prognostic factors for OS and CSS. The number of primary tumors was a specific influencing factor for OS, and postoperative radiotherapy was a beneficial factor for CSS. The C-indexes of OS and CSS nomograms constructed in this study in the training cohort were 0.825 (0800–0.850) and 0.820 (0.789–0.851), higher than the 0.701 (0.671–0.731) and 0.735 (0.702–0.768) of the International Federation of Gynecology and Obstetrics (FIGO) stage, p < 0.001. The prediction ability of the nomogram models was successfully validated in both the internal and external validation cohorts. The established nomogram models had high prediction accuracy for predicting the OS and CSS of stage T1–T2 UAC patients after hysterectomy and were superior to the FIGO stage. They could help clinicians accurately predict patients’ prognoses and select the best treatment plan.

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Postoperative clinicopathological factors affecting cervical adenocarcinoma

Cited by 10 publications

References 31 publications

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

Screening of prognostic immune genes and establishment of prognostic model of cervical adenocarcinoma based on bioinformatics analysis

Nomograms for predicting the survival rate of stage T1−T2 uterine cervical adenocarcinoma patients after hysterectomy

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