Stage Cervical Cancer Research Articles

Circulating tumor HPV DNA as a specific biomarker for cervical cancer.

The aim of this study was to determine whether circulating tumor human papillomavirus (HPV) DNA is a potential specific biomarker for cervical cancer (CC). This retrospective matched study included 87 patients with cervical intraepithelial neoplasia (CIN), 29 CC patients (FIGO IA1-IVA) and 29 HPV-negative controls at Yuhuangding Hospital of Qingdao University (from July 2022 to September 2023). The digital droplet PCR (ddPCR) was used to detect and quantify ctHPV DNA in the plasma of patients with HPV16, 18, 33, 52, or 58-associated CC. The ctHPV DNA was exclusively detectable in HPV-positive samples, with no detection in patients across various CIN stages (n = 87) or HPV-negative controls (n = 29). Additionally, ctHPV DNA was identified in nine out of 10 late-stage patients (90%) and six out of 19 early-stage patients (31.6%). The ctHPV DNA serves as a specific biomarker for the diagnosis CC. Additionally, this discovery addresses the knowledge gap in ctHPV DNA research in the early stages of CC and promotes clinical diagnosis and treatment strategies.

Comparative Diagnostic Value of 18F-FDG–PET–CT and Intraoperative Examination in Cervical Cancer Staging

Background and Objectives: The primary objective of this study is to assess the effectiveness of 18F-FDG–PET–CT in preoperative staging of cervical cancer, focusing on determining surgical operability and exploring the correlation between its quantitative parameters and clinicopathological characteristics. Materials and Methods: This retrospective study included 62 cervical cancer patients treated at the Department of Gynecology, Clinic for Operative Oncology at the Institute of Oncology Vojvodina between January 2016 and January 2020, where preoperative clinical examinations and 18F-FDG–PET–CT were performed to assess the extent of cancer, followed by intraoperative and pathohistological examinations of surgically removed specimens to provide a comprehensive evaluation. Results: The mean tumor size measured by 18F-FDG–PET–CT was slightly greater than that obtained through clinical examination (26.4 mm vs. 26.0 mm), with a strong linear correlation (r = 0.678, p < 0.001) observed between the two measurement methods. The overall prediction accuracy of 18F-FDG–PET–CT for primary tumors is 88.7% (55/62) [sensitivity 86.8%, specificity 100.0%, PPV 100.0%, NPV 56.2%] and for intraoperative examination is 88.7% (55/62) [sensitivity 98.1%, specificity 33.3%, PPV 89.7%, NPV 75.0%]. The agreement with histopathological examination was good for 18F-FDG–PET–CT and moderate for intraoperative examination for primary tumors. Regarding lymph nodes, the overall prediction accuracy of 18F-FDG–PET–CT is 82.2% (51/62) [sensitivity 53.8%, specificity 89.8%, PPV 58.3%, NPV 88.8%] and for intraoperative examination 66.1% (41/62) [sensitivity 76.9%, specificity 63.3%, PPV 35.7%, NPV 91.2%]. The agreement with histopathological examination was moderate for 18F-FDG–PET–CT and poor for intraoperative examination for lymph node metastasis, highlighting that the overall accuracy of 18F-FDG–PET–CT (82.1%) was significantly higher than that of intraoperative examination (66.1%) (p = 0.002). Conclusions: In conclusion, 18F-FDG–PET–CT provides high accuracy in detecting primary tumors and superior predictive value for lymph node metastases compared to intraoperative examination, highlighting the importance of incorporating this imaging modality into the preoperative evaluation process to enhance diagnostic precision and inform treatment decisions.

The importance of MRI in determining the stage of cervical cancer

Cervical cancer is one of the most common malignant tumours in women. The treatment of early and locally advanced stages of this cancer typically involves surgery, chemotherapy, and radiotherapy. However, there is no standardised therapy for metastatic cervical cancer due to the diverse manifestations of the disease. Therefore, timely diagnosis and staging of the carcinoma are crucial for maintaining the quality of life of patients. Imaging during the initial diagnostic evaluation is essential for accurately assessing the extent of the tumour and metastases, and for selecting the optimal therapy, with the FIGO system further emphasising this role. Compared to other imaging techniques, MRI provides detailed information on the location and size of the tumour, invasion into surrounding tissues, and the presence of distant metastases. This allows MRI to facilitate a tailored approach in therapy selection, taking into account the specific characteristics of the tumour. The integration of MRI into the diagnostic and therapeutic process improves clinical outcomes for patients with cervical cancer, enabling effective care. MRI is used alongside other imaging modalities in the diagnosis and treatment planning, and without it, precise staging of the disease and establishing a final diagnosis would not be possible.

Artificial Intelligence Algorithms in Predictive Factors for Hematologic Toxicities During Concurrent Chemoradiation for Cervical Cancer.

The most recent research conducted for the International Federation of Gynecology and Obstetrics indicates that, depending on the stage of cervical cancer (CC), several therapies can provide similar overall survival and progression-free survival rates. To determine the hematologic toxicities during concurrent chemotherapy for cervical cancer, we evaluated these two therapies (cisplatin or carboplatin). Hematologic markers have been studied using statistical models and descriptive statistics. Artificial intelligence models were built using the treatment data and all the information gathered from each patient after one or more administrations to forecast the CC stage. The information was gathered from stage III cervical cancer patients and provided by Oncohelp Hospital from the West Region of Romania. Many traditional machine learning techniques, such as naïve Bayes (NB), random forest (RF), decision trees (DTs), and a trained transformer called TabPFN, were used in the current study to obtain the tabular data. The algorithms NB, RF, and DTs yielded the greatest classification score of 100% when it came to cervical cancer prediction. On the other hand, TabPFN demonstrated an accuracy of 88%. The effectiveness of the models was evaluated by computing the computational complexity of traditional machine learning methods. Early detection increases the likelihood of a good prognosis during the precancerous and malignant stages. Being aware of any indications and symptoms of cervical cancer can also help to prevent delays in diagnosis. These hematologic toxicities, which have been demonstrated to grow linearly with lowering hematologic markers below their normal expectations, would significantly impair patients' quality of life.

MiR-21 and miR-145 as Prognostic Biomarkers for Radiotherapy Responses in Cervical Cancer Patients: A Preliminary Study.

Radioresistance poses a significant challenge in the effective treatment of cervical cancer, often leading to poor patient outcomes. MicroRNA-21 (miR-21) and MicroRNA-145 (miR-145) are oncogenic micro-RNAs associated with various cancers, including cervical cancer, but their potential as predictive biomarkers for radioresistance remains underexplored. This study aimed to investigate the association between miR-21 and miR-145 expressions and the response to radiation therapy in cervical cancer patients. An analytical cross-sectional study was conducted on 140 subjects with cervical cancer stages IIIB and IVA who received definitive radiotherapy. miR-21 and miR-145 expressions were measured using real-time reverse transcriptase-polymerase chain reaction (RT-qPCR). A total of 102 subjects (72.9%) were classified as having stage III cervical cancer, and 38 subjects (27.1%) were classified as having stage IV cervical cancer. Disease progression occurred in 60.7% of subjects. The cut-off value for miR-21 expression was 0.00088 nmol/(mg/mL) (AUC 0.676, sensitivity 70.8%, specificity 50.8%), and a higher expression was significantly associated with radioresistance (p = 0.010). miR-145, with a cut-off of 0.0239 nmol/(mg/mL) (AUC 0.612, sensitivity 67.5%, specificity 45.5%), showed no significant association with treatment response (p = 0.132). Combining miR-21 and miR-145 (AUC 0.639, sensitivity 68.6%, specificity 46.9%, p = 0.063) did not significantly improve the predictive accuracy. This study suggests that an elevated miR-21 expression is significantly associated with radioresistance in cervical cancer patients, while miR-145 expression shows no significant correlation with treatment response. Additionally, combining miR-21 and miR-145 does not enhance the predictive power.

A precise machine learning model: Detecting cervical cancer using feature selection and explainable AI

Cervical cancer is a cancer that remains a significant global health challenge all over the world. Due to improper screening in the early stages, and healthcare disparities, a large number of women are suffering from this disease, and the mortality rate increases day by day. Hence, in these studies, we presented a precise approach utilizing six different machine learning models (decision tree, logistic regression, naïve bayes, random forest, k nearest neighbors, support vector machine), which can predict the early stage of cervical cancer by analysing 36 risk factor attributes of 858 individuals. In addition, two data balancing techniques—Synthetic Minority Oversampling Technique and Adaptive Synthetic Sampling—were used to mitigate the data imbalance issues. Furthermore, Chi-square and Least Absolute Shrinkage and Selection Operator are two distinct feature selection processes that have been applied to evaluate the feature rank, which are mostly correlated to identify the particular disease, and also integrate an explainable artificial intelligence technique, namely Shapley Additive Explanations, for clarifying the model outcome. The applied machine learning model outcome is evaluated by performance evaluation matrices, namely accuracy, sensitivity, specificity, precision, f1-score, false-positive rate and false-negative rate, and area under the Receiver operating characteristic curve score. The decision tree outperformed in Chi-square feature selection with outstanding accuracy with 97.60%, 98.73% sensitivity, 80% specificity, and 98.73% precision, respectively. During the data imbalance, DT performed 97% accuracy, 99.35% sensitivity, 69.23% specificity, and 97.45% precision. This research is focused on developing diagnostic frameworks with automated tools to improve the detection and management of cervical cancer, as well as on helping healthcare professionals deliver more efficient and personalized care to their patients.

SEPT9_i1 and Septin Dynamics in Oncogenesis and Cancer Treatment.

Despite significant advancements in the field of oncology, cancers still pose one of the greatest challenges of modern healthcare. Given the cytoskeleton's pivotal role in regulating mechanisms critical to cancer development, further studies of the cytoskeletal elements could yield new practical applications. Septins represent a group of relatively well-conserved GTP-binding proteins that constitute the fourth component of the cytoskeleton. Septin 9 (SEPT9) has been linked to a diverse spectrum of malignancies and appears to be the most notable septin member in that category. SEPT9 constitutes a biomarker of colorectal cancer (CRC) and has been positively correlated with a high clinical stage in breast cancer, cervical cancer, and head and neck squamous cell carcinoma. SEPT9_i1 represents the most extensively studied isoform of SEPT9, which substantially contributes to carcinogenesis, metastasis, and treatment resistance. Nevertheless, the mechanistic basis of SEPT9_i1 oncogenicity remains to be fully elucidated. In this review, we highlight SEPT9's and SEPT9_i1's structures and interactions with Hypoxia Inducible Factor α (HIF-1 α) and C-Jun N-Terminal Kinase (JNK), as well as discuss SEPT9_i1's contribution to aneuploidy, cell invasiveness, and taxane resistance-key phenomena in the progression of malignancies. Finally, we emphasize forchlorfenuron and other septin inhibitors as potential chemotherapeutics and migrastatics.

Cardiac metastasis in uterine cervical cancer : Asystematic review and case study.

Cardiac metastasis from cervical cancer is rare and only scarcely documented. We aim to present anew case and systematically summarize the available literature. PubMed, Scopus, Web of Science, Central, and ClinicalTrials.gov were systematically searched following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria. Results were screened via title, abstract, and full text. Additionally, the reference lists of all papers chosen for the review were screened. Eighty-one papers were identified, describing 86cases in total. Cardiac metastasis occurred at all stages of cervical cancer and in all age groups. Median time from initial diagnosis to diagnosis of cardiac metastasis was 12months. Patients mainly complained of dyspnea and chest pain, 60.8% had pathologic ECG (electrocardiographic) findings. The cardiac mass was most frequently detected by transthoracic echography. The most common tumor histology was squamous cell carcinoma. Chemotherapy and surgical interventions were the main treatment modalities. Median survival after diagnosis of cardiac metastasis was 3months. This largest review on cardiac metastases from cervical cancer confirmed the heart as avery infrequent site of metastasis. There are < 100 cases described in the literature, with very poor prognosis and undefined clinical management.

Pembrolizumab or placebo with chemoradiotherapy followed by pembrolizumab or placebo for newly diagnosed, high-risk, locally advanced cervical cancer (ENGOT-cx11/GOG-3047/KEYNOTE-A18): overall survival results from a randomised, double-blind, placebo-controlled, phase 3 trial

At the first interim analysis of the phase 3 ENGOT-cx11/GOG-3047/KEYNOTE-A18 study, the addition of pembrolizumab to chemoradiotherapy provided a statistically significant and clinically meaningful improvement in progression-free survival in patients with locally advanced cervical cancer. We report the overall survival results from the second interim analysis of this study. Eligible patients with newly diagnosed, high-risk (FIGO 2014 stage IB2-IIB with node-positive disease or stage III-IVA regardless of nodal status), locally advanced, histologically confirmed, squamous cell carcinoma, adenocarcinoma, or adenosquamous cervical cancer were randomly assigned 1:1 to receive five cycles of pembrolizumab (200 mg) or placebo every 3 weeks with concurrent chemoradiotherapy, followed by 15 cycles of pembrolizumab (400 mg) or placebo every 6 weeks. Pembrolizumab or placebo and cisplatin were administered intravenously. Patients were stratified at randomisation by planned external beam radiotherapy type (intensity-modulated radiotherapy [IMRT] or volumetric-modulated arc therapy [VMAT] vs non-IMRT or non-VMAT), cervical cancer stage at screening (FIGO 2014 stage IB2-IIB node positive vs III-IVA), and planned total radiotherapy (external beam radiotherapy plus brachytherapy) dose (<70 Gy vs ≥70 Gy [equivalent dose of 2 Gy]). Primary endpoints were progression-free survival per RECIST 1.1 by investigator or by histopathological confirmation of suspected disease progression and overall survival defined as the time from randomisation to death due to any cause. Safety was a secondary endpoint. Between June 9, 2020, and Dec 15, 2022, 1060 patients at 176 sites in 30 countries across Asia, Australia, Europe, North America, and South America were randomly assigned to treatment, with 529 patients in the pembrolizumab-chemoradiotherapy group and 531 patients in the placebo-chemoradiotherapy group. At the protocol-specified second interim analysis (data cutoff Jan 8, 2024), median follow-up was 29·9 months (IQR 23·3-34·3). Median overall survival was not reached in either group; 36-month overall survival was 82·6% (95% CI 78·4-86·1) in the pembrolizumab-chemoradiotherapy group and 74·8% (70·1-78·8) in the placebo-chemoradiotherapy group. The hazard ratio for death was 0·67 (95% CI 0·50-0·90; p=0·0040), meeting the protocol-specified primary objective. 413 (78%) of 528 patients in the pembrolizumab-chemoradiotherapy group and 371 (70%) of 530 in the placebo-chemoradiotherapy group had a grade 3 or higher adverse event, with anaemia, white blood cell count decreased, and neutrophil count decreased being the most common adverse events. Potentially immune-mediated adverse events occurred in 206 (39%) of 528 patients in the pembrolizumab-chemoradiotherapy group and 90 (17%) of 530 patients in the placebo-chemoradiotherapy group. This study is registered with ClinicalTrials.gov, NCT04221945. Pembrolizumab plus chemoradiotherapy significantly improved overall survival in patients with locally advanced cervical cancer These data, together with results from the first interim analysis, support this immuno-chemoradiotherapy strategy as a new standard of care for this population. Merck Sharp & Dohme, a subsidiary of Merck & Co.

Application of Shear Wave Elastography in the Diagnosis and Evaluation of Cervical Cancer

Background: Our goal was to add an auxiliary examination method for the detection of cervical cancer, and to further explore its application value in clinical staging and treatment. Methods: Shear wave elastography (SWE) technique was used to examine the cervical hardness of patients, and the maximum, mean and minimum values of elastic modulus were recorded, with differences being compared. The area under the receiver operating characreristic (ROC) curve and diagnostic efficacy of elastic modulus were compared with Medcalc software. The differences of elastic modulus values under different parameters were compared in the cervical cancer group. Results: The mean, maximum and minimum values of the cervical cancer group were all the highest, and the differences were statistically significant. The area under the ROC curves were 0.925, 0.909 and 0.873, respectively. For the mean and maximum values, the Youden indexes were 0.79 and 0.72, the positive likelihood ratios were 21.74 and 19.97, and the negative likelihood ratios were 0.18 and 0.25. The optimal cut-off point was 82.2 kilpoascal (kPa) for maximum value and was 66.5 kPa for mean value. Elastic modulus were all significantly different according to International Federation of Gynecology and Obstetrics (FIGO) stages and tumor lesion size. Also, elastic modulus of cervical cancer patients before and after radiotherapy were statistically significant. Conclusions: SWE technology has an application value in the detection of cervical cancer. The mean and maximum values have higher diagnostic accuracy. SWE technology also has potential clinical application value in the clinical staging and treatment of cervical cancer, but further studies with larger sample sizes are needed.

Analysis of Human Papillomavirus-Associated Cervical Cancer Differentially Expressed Genes and Identification of Prognostic Factors using Integrated Bioinformatics Approaches.

Human papillomavirus (HPV)-induced cervical cancer progresses through a series of steps. Despite our limited understanding of the mechanisms driving this progression, identifying the key genes involved could significantly improve early detection and treatment. Two gene expression profiles of GSE9750 and GSE6791, which included cervical cancer HPV-positive and -negative samples, were evaluated using the R limma package with established cut-off criteria of P value < 0.05 and | fold change| ≥ 1. KEGG pathway enrichment was performed to identify potential pathways. Weighted gene co-expression network analysis (WGCNA) was used to discover co-expressed gene modules and trait-module connections. Considering the defined criteria, 115 differentially expressed genes (DEGs) were identified. The DEG's KEGG pathway enrichment analysis revealed enrichment in highly relevant pathways to the HPV infection, including cell cycle, viral carcinogenesis, autophagy-animal, Epstein-Barr virus infection, human T-cell leukemia virus 1 infection, and microRNAs in cancer. WGCNA results in 13 co-expression modules, and the magenta module is identified with significant relations to HPV, cervical cancer stage, and metastasis traits. The survival analysis identified BEX1 and CDC45 as potential prognostic factors in HPV-associated cervical cancer. The innovation of our work lies in identifying essential genes associated with the multi-step process of cervical carcinogenesis. In fact, the current study has the potential to give a distinct viewpoint on the molecular pathways linked to cervical cancer. Considering the potential importance of the hub genes, we recommend conducting in-depth wet lab research to determine their impact on the biological mechanisms of cervical cancer.

Changes in the molecular nodes of the Notch and NRF2 pathways in cervical cancer tissues from the precursor stages to invasive carcinoma.

Cancer is a multifactorial disease characterized by the loss of control in the expression of genes known as cancer driver genes. Cancer driver genes trigger uncontrolled cell replication, which leads to the development of malignant tumors. A cluster of signal transduction pathways that contain cancer driver genes involved in cellular processes, such as cell proliferation, differentiation, apoptosis and dysregulated organ growth, are associated with cancer initiation and progression. In the present study, three signal transduction pathways involved in cervical cancer (CC) development were analyzed: The Hippo pathway (FAT atypical cadherin, yes-associated protein 1, SMAD4 and TEA domain family member 2), the Notch pathway [cellular-MYC, cAMP response element-binding binding protein (CREBBP), E1A-associated cellular p300 transcriptional co-activator protein and F-Box and WD repeat domain containing 7] and the nuclear factor erythroid 2-related factor 2 (NRF2) pathway [NRF2, kelch-like ECH-associated protein 1 (KEAP1), AKT and PIK3-catalytic subunit α]. Tumor samples from patients diagnosed with various stages of CC, including cervical intraepithelial neoplasia (CIN) 1, CIN 2, CIN 3, in situ CC and invasive CC, were analyzed. The mRNA expression levels were analyzed using reverse transcription-quantitative PCR assays, whereas protein expression levels were assessed through immunohistochemical tissue microarrays. High mRNA expression levels of c-MYC and AKT and low expression levels of NRF2 and KEAP1 were associated with a decreased survival time of patients with CC. Additionally, increased expression levels of c-MYC were detected in the invasive CC stage. At the protein level, increased NRF2 expression levels were observed in all five stages of CC samples compared with those in the cancer-free control samples. AKT1 was found to be dysregulated in the CIN 1 and CIN 2 stages, PI3K in the in situ and invasive stages, and CREBBP in the CIN 3 and in situ stages. In summary, the present study demonstrated significant changes in proteins of the Notch and NRF2 pathways in CC. NRF2 was overexpressed in all cervical cancer stages (cervical intraepithelial neoplasia, in situ CC and invasive CC). The present study makes an important contribution to the possible biomarker proteins to be analyzed for the presence of premalignant and malignant lesions in the cervix.

1928: Disparities in cervical cancer stage and outcomes: does place matter?

1928: Disparities in cervical cancer stage and outcomes: does place matter?

The Value of Human Epididymal Protein 4, Carcinoembryonic Antigen and Alpha-Fetoprotein in the Early Diagnosis of Cervical Cancer

Objectives: This research aimed to unveil the value of human epididymal protein 4 (HE4), carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP) in the early diagnosis of cervical cancer. Design: This was a clinical study. Participants: Sixty patients with cervical cancer stage IA-IIA (early stage cervical cancer group), 60 patients with cervical intraepithelial neoplasia (CIN) (disease control group), and 60 healthy women who had passed the physical examination (healthy control group) were selected. Setting: The review was conducted in a Jiaxing First Hospital. Methods: Sixty patients with cervical cancer stage IA-IIA (early stage cervical cancer group), 60 patients with CIN (disease control group), and 60 healthy women who had passed the physical examination (healthy control group) were selected. The expression levels of serum HE4, CEA, and AFP in the three groups were detected, and the correlation between the levels of serum HE4, CEA, and AFP and the clinicopathological characteristics of patients with early stage cervical cancer were analyzed, and the receiver operating characteristic (ROC) curves were plotted to identify the value of the single and triple tests of serum HE4, CEA, and AFP for the early stage diagnosis of cervical cancer. Results: The levels of serum HE4, CEA, and AFP in the early stage cervical cancer group were higher than those in the disease control and the healthy control groups (p < 0.05). The levels of serum HE4, CEA, and AFP were related to the FIGO stage as well as the histological grading of patients with early stage cervical cancer (p < 0.05). The results of the ROC curves revealed that the AUC areas of HE4, CEA, and AFP for single as well as triple diagnosis of patients with early stage cervical cancer were 0.725, 0.679, 0.663, and 0.811, respectively, and the AUC of the three combined tests was markedly higher than that of HE4, CEA, AFP single test (p < 0.05). Limitations: There is a lack of larger sample sizes to test whether the combined HE4, CEA, and AFP detection has sufficient validity at the individual level and there are not enough serum samples in this study to perform circulating HPV-DNA detection and compare it with the levels of serum markers. Conclusion: The combination of HE4, CEA, and AFP has good clinical reference value analysis in the auxiliary diagnosis of early stage cervical cancer, and it is worthy of further validation and popularization.

Presentation of a Locally Advanced Cervical Cancer with Hydrometrocolpos: A Case Report

Introduction: Early stages of cervical cancer remain asymptomatic. Its common symptoms are postcoital bleeding, postmenopausal bleeding, heavy menstrual flow and foul smelling blood stained discharge. Presentation of locally advanced cervical cancer with hydrometrocolpos is unusual. Case report: An 83-year-old woman who presented with a large abdomino-pelvic mass was diagnosed as benign bilateral ovarian tumour with left sided hydroureteronephrosis. During laparotomy, the mass was confirmed to be a hydrometrocolpos with left hydroureteronephrosis secondary to a locally advanced cervical cancer (FIGO IIIB). Histology confirmed the diagnosis of invasive squamous cell carcinoma of the cervix. Conclusion: Besides thorough evaluation via symptoms and signs, radiologists have an important role in guiding surgeons to the most probable diagnosis. In an elderly woman with a stenosed vagina and a pelvic mass with hydroureteronephrosis, gynecologists need to be aware of the possibility of locally advanced cervical cancer, and perform relevant preoperative assessments and plan management.

Validation of FIGO 2018 staging for cervical cancer: Insights from a Japanese multicenter cohort.

126 Background: The International Federation of Gynecology and Obstetrics (FIGO) updated its staging system for cervical cancer in 2018, introducing major changes such as the establishment of stage IIIC based on lymph node metastasis (LNM), which has been reported to provide a better reflection of prognosis. However, stage IIIC has been reported to be heterogeneous, with prognoses varying depending on LNM extent and local tumor factors. In Japan, where various imaging tests are extensively performed, this revision is expected to lead to numerous cases of stage migration due to LNM. However, there have been few reports on the impact of this revision in Japan. Therefore, this multicenter study aims to assess the validity of FIGO 2018 in a Japanese cohort, focusing on LNM, local tumor factors, and histological types. Methods: Using a unified registry for gynecological malignancies developed by The Japanese Society of Obstetrics and Gynecology, this study involved 1,468 cervical cancer patients treated between 2011 and 2019 across eight designated cancer treatment hospitals. The registry used the FIGO 2009 staging system, and patients with stage IA to IIIB disease were restaged according to the FIGO 2018. Stage IIIC cases were further classified into substages IIIC-T1, IIIC-T2, and IIIC-T3AB based on local tumor factors. Results: After restaging process, A total of 347 cases (27.6%) were upstaged to stage IIIC according to LNM. Survival analysis showed that stage IIIC had a poorer prognosis than stage II (HR, 2.09; 95% CI, 1.27-3.44; p=0.004), but a significantly better prognosis than stage IIIAB (HR, 0.46; 95% CI, 0.27-0.77; p=0.004). There was also a clear difference between subclasses stage IIIC1 and IIIC2, with IIIC2 having a worse prognosis (HR, 2.13; 95% CI, 1.23-3.67; p=0.007). A survival analysis focusing on stageIIIC1 subdivisions (T1, T2, and T3AB) showed varied prognosis among them. Furthermore, IIIC1-T1 and IIIC1-T2 had significantly worse prognoses compared to stages I and II (I vs IIIC1-T1, HR, 3.21; 95% CI, 1.64-6.30; p&lt;0.001. II vs IIIC1-T2, HR, 1.82; 95% CI, 1.03-3.21; p=0.04), while the prognosis of IIIC1-T3AB was similar to stage IIIAB. In the analysis by histological type, there was little difference between IIIC1-T1 and IIIC1-T2 in squamous cell carcinoma, but there was significant difference between IIIC1-T1 and IIIC1-T2 in adenocarcinoma (HR, 5.12; 95% CI, 1.10-23.74; p=0.04). On the other hand, for IIIC2, prognosis was similar across T1, T2, and T3AB, all showing uniformly poor outcomes. Conclusions: We were able to concretely clarify the current situation in Japan and validate the usefulness of FIGO 2018. The comprehensive examination of LNM, local tumor factors, and histological type may further reinforce and complement FIGO 2018.

Staging of Cervical Cancer: What has Changed?

In India, cervical cancer is the second most common cause of cancer-related fatalities and the fourth most common malignancy worldwide affecting women. India accounts for 25% of all cervical cancer-related deaths worldwide each year. The main drawbacks of clinical staging were the imprecise estimation of tumor size and the challenge of determining the involvement of pelvic and para-aortic lymph nodes with the few studies that FIGO allowed to be done for staging of cancer cervix. The use of 2009 staging approach showed that when many cases were operated based only on clinical findings, they subsequently required adjuvant therapy; hence, treatment-related morbidity was negatively impacted by these errors. Changes have been made to the staging of cervical cancer according to the 2018 revised International Federation of Gynecology and Obstetrics (FIGO) guidelines. Correction to cancer of the cervix staging was published recently in 2024. The horizontal extent (lateral extent) of the disease is not taken into consideration for staging in cases of microinvasive disease. Three subgroups have been identified based on the stratification of tumor size: IB1 ≤ 2cm, IB2 > 2- ≤ 4cm, and IB3 > 4cm. Pathology and imaging modalities are added to clinical diagnosis for staging of cancer cervix. The involvement of lymph nodes (LNs) is now classified based on pathology (p) or imaging (r) which specifies that lymph node involvement is diagnosed using pathology (p) or imaging (r). Stage IIIC has been added [IIIC1 (involvement of pelvic nodes) and IIIC2 (involvement of para-aortic nodes)] is assigned to the case in the event of lymph node positive status. Pathological assessment takes precedence over radiological and clinical findings. The involvement of vascular/lymphatic spaces should not change the staging. The lower staging should be assigned when there is doubt about stage. Overall, the revised FIGO staging of cancer cervix (2024) has a number of advantages, including the inclusion of imaging and pathology, tumor size and LN-based categorization. More studies on staging of cancer cervix in different populations using revised staging of cancer cervix will help to prognosticate use of this staging.

Cervical cancer disparities in stage at presentation for disaggregated Asian Americans, Native Hawaiians, and Pacific Islanders

Over 20 million people in the United States identified as Asian American, Native Hawaiian, or Pacific Islander (AANHPI) in 2022. Despite the diversity of immigration histories, lived experiences, and health needs within the AANHPI community, prior studies in cervical cancer have considered this group in aggregate. We sought to analyze disparities in cervical cancer stage at presentation in the United States, focusing on disaggregated AANHPI groups. Data from the United States National Cancer Database from 2004 to 2020 of 122,926 patients newly diagnosed with cervical cancer was retrospectively analyzed. AANHPI patients were disaggregated by country of origin. Logistic regression, adjusted for clinical and sociodemographic factors, was used to calculate adjusted odds ratios. Higher adjusted odds ratios indicate an increased likelihood of metastatic versus non-metastatic disease at diagnosis. Out of 122,926 patients with cervical cancer, 5,142 (4.2%) identified as AANHPI. Compared to non-Hispanic White (NHW) patients, pooled AANHPI patients presented at lower stages of cancer (NHW: 58.7% diagnosed local/regional, AANHPI: 85.6% at local/regional, χ2 P<0.001). The largest AANHPI subgroups included Filipino Americans (n=1051, 20.4% of AANHPI), Chinese Americans (n=995, 19.4%), Asian Indian/Pakistani Americans (n=711, 13.8%), Vietnamese Americans (n=627, 12.2%), and Korean Americans (n=550, 10.7%) respectively. AANHPI disaggregation revealed that Pacific Islander American patients had higher odds of presenting with metastatic disease (aOR 1.58, 95% CI 1.21-2.06, p = 0.001) relative to non-Hispanic White patients. Conversely, Chinese American (aOR 0.47, 95% CI 0.37-0.59, p < 0.001), Vietnamese American (aOR 0.54, 95% CI 0.41-0.70, p < 0.001), Hmong American (aOR 0.46, 95% CI 0.22-0.97, p = 0.040), and Indian/Pakistani American (aOR 0.76, 95% CI 0.61-0.94, p = 0.013) patients were less likely to present with metastatic disease. Compared to the largest AANHPI group (Chinese American), nine other subgroups were more likely to present with metastatic disease. The largest differences were observed in Pacific Islander American (aOR 3.44, 95% CI 2.41-4.91, p < 0.001), Thai American (aOR 2.79, 95% CI 1.41-5.53, p = 0.003), Kampuchean American (aOR 2.39, 95% CI 1.29-4.42, p = 0.006), Native Hawaiian American (aOR 2.23, 95% CI 1.37-3.63, p = 0.001), and Laotian American (aOR 2.02, 95% CI 1.13-3.61, p = 0.017). In contrast, Vietnamese American (aOR 1.20, 95% CI 0.85-1.71, p = 0.303) and Hmong American (aOR 1.09, 95% CI 0.50-2.37, p = 0.828) patients did not show a statistically significant difference in presenting with metastatic disease compared to Chinese American patients. Aggregated evaluation of the Asian American, Native Hawaiian, or Pacific Islander monolith masks disparities in outcomes for distinct populations at risk for equity gaps. This disaggregation study shows that marginalized groups within the larger AANHPI population - including Pacific Islander American and Thai American patients - may face different exposures and larger structural barriers to cancer screening and early-stage diagnosis. A future focus on community based disaggregated research and tailored interventions is necessary to close these gaps.

Predictive models for personalized precision medical intervention in spontaneous regression stages of cervical precancerous lesions

BackgroundDuring the prolonged period from Human Papillomavirus (HPV) infection to cervical cancer development, Low-Grade Squamous Intraepithelial Lesion (LSIL) stage provides a critical opportunity for cervical cancer prevention, giving the high potential for reversal in this stage. However, there is few research and a lack of clear guidelines on appropriate intervention strategies at this stage, underscoring the need for real-time prognostic predictions and personalized treatments to promote lesion reversal.MethodsWe have established a prospective cohort. Since 2018, we have been collecting clinical data and pathological images of HPV-infected patients, followed by tracking the progression of their cervical lesions. In constructing our predictive models, we applied logistic regression and six machine learning models, evaluating each model’s predictive performance using metrics such as the Area Under the Curve (AUC). We also employed the SHAP method for interpretative analysis of the prediction results. Additionally, the model identifies key factors influencing the progression of the lesions.ResultsModel comparisons highlighted the superior performance of Random Forests (RF) and Support Vector Machines (SVM), both in clinical parameter and pathological image-based predictions. Notably, the RF model, which integrates pathological images and clinical multi-parameters, achieved the highest AUC of 0.866. Another significant finding was the substantial impact of sleep quality on the spontaneous clearance of HPV and regression of LSIL.ConclusionsIn contrast to current cervical cancer prediction models, our model’s prognostic capabilities extend to the spontaneous regression stage of cervical cancer. This model aids clinicians in real-time monitoring of lesions and in developing personalized treatment or follow-up plans by assessing individual risk factors, thus fostering lesion spontaneous reversal and aiding in cervical cancer prevention and reduction.Graphical

The Polish Society of Gynecological Oncology Guidelines for the Diagnosis and Treatment of Cervical Cancer (v2024.0).

Background: Recent publications underscore the need for updated recommendations addressing less radical surgery for <2 cm tumors, induction chemotherapy, or immunotherapy for locally advanced stages of cervical cancer, as well as for the systemic therapy for recurrent or metastatic cervical cancer. Aim: To summarize the current evidence for the diagnosis, treatment, and follow-up of cervical cancer and provide evidence-based clinical practice recommendations. Methods: Developed according to AGREE II standards, the guidelines classify scientific evidence based on the Agency for Health Technology Assessment and Tariff System criteria. Recommendations are graded by evidence strength and consensus level from the development group. Key Results: (1) Early-Stage Cancer: Stromal invasion and lymphovascular space involvement (LVSI) from pretreatment biopsy identify candidates for surgery, particularly for simple hysterectomy. (2) Surgical Approach: Minimally invasive surgery is not recommended, except for T1A, LVSI-negative tumors, due to a reduction in life expectancy. (3) Locally Advanced Cancer: concurrent chemoradiation (CCRT) followed by brachytherapy (BRT) is the cornerstone treatment. Low-risk patients (fewer than two metastatic nodes or FIGO IB2-II) may consider induction chemotherapy (ICT) followed by CCRT and BRT after 7 days. High-risk patients (two or more metastatic nodes or FIGO IIIA, IIIB, and IVA) benefit from pembrolizumab with CCRT and maintenance therapy. (4) Metastatic, Persistent, and Recurrent Cancer: A PD-L1 status from pretreatment biopsy identifies candidates for Pembrolizumab with available systemic treatment, while triplet therapy (Atezolizumab/Bevacizumab/chemotherapy) becomes a PD-L1-independent option. Conclusions: These evidence-based guidelines aim to improve clinical outcomes through precise treatment strategies based on individual risk factors, predictors, and disease stages.