scholarly journals Selective screening: theory and practice based on high-risk groups of cervical cancer.

1979 ◽  
Vol 33 (4) ◽  
pp. 257-261 ◽  
Author(s):  
M Hakama ◽  
E Pukkala ◽  
P Saastamoinen
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Risk Groups ◽  
Theory And Practice ◽  
Selective Screening

scholarly journals Immune‐related Long Noncoding RNA Signature for Patients with Cervical Cancer

2020 ◽  
Author(s):  
Jianfeng Zheng ◽  
Jinyi Tong ◽  
Benben Cao ◽  
Xia Zhang ◽  
Zheng Niu
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Risk Score ◽  
Immune Cell ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Training Set ◽  
Score Model

Abstract Background: Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune‐related lncRNAs(IRLs) of CC has never been reported. This study aimed to establish an IRL signature for patients with CC.Methods: The RNA-seq dataset was obtained from the TCGA, GEO, and GTEx database. The immune scores（IS）based on single-sample gene set enrichment analysis (ssGSEA) were calculated to identify the IRLs, which were then analyzed using univariate Cox regression analysis to identify significant prognostic IRLs. A risk score model was established to divide patients into low-risk and high-risk groups based on the median risk score of these IRLs. This was then validated by splitting TCGA dataset(n=304) into a training-set(n=152) and a valid-set(n=152). The fraction of 22 immune cell subpopulations was evaluated in each sample to identify the differences between low-risk and high-risk groups. Additionally, a ceRNA network associated with the IRLs was constructed.Results: A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson’s correlation analysis between immune score and lncRNA expression (P < 0.01). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values (P < 0.05) were identified which demonstrated an ability to stratify patients into low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low‐risk group showed longer overall survival (OS) than those in the high‐risk group in the training-set, valid-set, and total-set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four IRLs signature in predicting the one-, two-, and three-year survival rates were larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Conclusions: Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four-IRLs in the development of CC were ascertained preliminarily.

scholarly journals Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Jianfeng Zheng ◽  
Benben Cao ◽  
Xia Zhang ◽  
Zheng Niu ◽  
Jinyi Tong
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Immune Cell ◽  
Risk Group ◽  
Pearson Correlation ◽  
Characteristic Curve ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Gynecological Malignancy

Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune-related lncRNAs (IRLs) of CC has never been reported. This study is aimed at establishing an IRL signature for patients with CC. A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson correlation analysis between the immune score and lncRNA expression ( p < 0.01 ). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values ( p < 0.05 ) were identified which demonstrated an ability to stratify patients into the low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group in the training set, valid set, and total set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four-IRL signature in predicting the one-, two-, and three-year survival rates was larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four IRLs in the development of CC were ascertained preliminarily.

High-risk groups and cervical cancer

BMJ ◽  
1980 ◽  
Vol 281 (6251) ◽  
pp. 1352-1352
Author(s):  
J E. Macgregor
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Risk Groups

Selective screening for depression in 3 high risk groups in primary care is not effective

2008 ◽  
Vol 107 ◽  
pp. S118-S119
Author(s):  
K.D. Baas⁎ ◽  
K.A. Wittkampf ◽  
H.C. van Weert ◽  
P. Lucassen ◽  
J. Huyser ◽  
...  
Keyword(s):  
Primary Care ◽  
High Risk ◽  
Risk Groups ◽  
Selective Screening

scholarly journals Perioperative treatments for stage IB–IIB uterine cervical cancer

2019 ◽  
Vol 50 (2) ◽  
pp. 99-103
Author(s):  
Muneaki Shimada ◽  
Hideki Tokunaga ◽  
Hiroaki Kobayashi ◽  
Mitsuya Ishikawa ◽  
Nobuo Yaegashi
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Neoadjuvant Chemotherapy ◽  
Radical Hysterectomy ◽  
Adjuvant Radiotherapy ◽  
Concurrent Chemoradiotherapy ◽  
Risk Groups ◽  
Perioperative Chemotherapy ◽  
Stage Ib ◽  
Risk Patients

Abstract Japan Society of Gynecologic Oncology guidelines recommended either radical hysterectomy-based approach or the definitive radiotherapy including concurrent chemoradiotherapy as primary treatment for patients with not only stage IB1/IIA1, but also stages IB2, IIA2 and IIB. Based on pathological findings of surgical specimens, patients who underwent radical hysterectomy are divided into three recurrent-risk groups, low-risk, intermediate, and high-risk groups. Although some authors reported the usefulness of adjuvant chemotherapy for intermediate/high-risk patients, radiotherapy was standard adjuvant treatment for pathological-risk patients after radical hysterectomy. It has been uncertain whether neoadjuvant chemotherapy followed by radical hysterectomy is beneficial for stage IB2–IIB patients. Recently, the randomized phase III study revealed that neoadjuvant chemotherapy followed by radical hysterectomy failed to improve survival of stage IB2–IIB patients compared to concurrent chemoradiotherapy. Majority of stage IB2–IIB patients are required adjuvant radiotherapy after radical hysterectomy. The multimodality strategy consisting of radical hysterectomy followed by adjuvant radiotherapy is associated with not only impaired quality of life, but also conflicting of cost-effectiveness. Thereby, some authors investigated the significance of multimodality strategy consisting of chemotherapy before/after radical hysterectomy for stage IB2–IIB cervical cancer. Multimodality strategy consisting of radical hysterectomy/perioperative chemotherapy needs higher curability of radical hysterectomy, higher response to perioperative chemotherapy and less perioperative complications. Consequently, gynecologic oncologists have to examine the patients strictly before treatment and judge whether radical hysterectomy-based approach or definitive irradiation is appropriate for the patient with stage IB–IIB cervical cancer.

scholarly journals Bioinformatic identification of genomic instability-associated lncRNAs signatures for improving the clinical outcome of cervical cancer by a prognostic model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jian Zhang ◽  
Nan Ding ◽  
Yongxing He ◽  
Chengbin Tao ◽  
Zhongzhen Liang ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Overall Survival ◽  
High Risk ◽  
Cancer Patients ◽  
Genomic Instability ◽  
Prognostic Model ◽  
Risk Group ◽  
Expression Profiles ◽  
Risk Groups ◽  
Training Set

AbstractThe research is executed to analyze the connection between genomic instability-associated long non-coding RNAs (lncRNAs) and the prognosis of cervical cancer patients. We set a prognostic model up and explored different risk groups' features. The clinical datasets and gene expression profiles of 307 patients have been downloaded from The Cancer Genome Atlas database. We established a prognostic model that combined somatic mutation profiles and lncRNA expression profiles in a tumor genome and identified 35 genomic instability-associated lncRNAs in cervical cancer as a case study. We then stratified patients into low-risk and high-risk groups and were further checked in multiple independent patient cohorts. Patients were separated into two sets: the testing set and the training set. The prognostic model was built using three genomic instability-associated lncRNAs (AC107464.2, MIR100HG, and AP001527.2). Patients in the training set were divided into the high-risk group with shorter overall survival and the low-risk group with longer overall survival (p < 0.001); in the meantime, similar comparable results were found in the testing set (p = 0.046), whole set (p < 0.001). There are also significant differences in patients with histological grades, FIGO stages, and different ages (p < 0.05). The prognostic model focused on genomic instability-associated lncRNAs could predict the prognosis of cervical cancer patients, paving the way for further research into the function and resource of lncRNAs, as well as a key approach to customizing individual care decision-making.

scholarly journals Improvement of selective screening strategy for gestational diabetes through a more accurate definition of high-risk groups

2014 ◽  
Vol 170 (1) ◽  
pp. 87-93 ◽  
Author(s):  
Basilio Pintaudi ◽  
Giacoma Di Vieste ◽  
Francesco Corrado ◽  
Giuseppe Lucisano ◽  
Fabio Pellegrini ◽  
...  
Keyword(s):  
High Risk ◽  
Gestational Diabetes ◽  
International Association ◽  
Risk Groups ◽  
Study Groups ◽  
Oral Glucose ◽  
Selective Screening ◽  
Family History Of Diabetes ◽  
Screening Approach ◽  
Increased Risk

ObjectiveThis study aimed to assess the predictive value of risk factors (RFs) for gestational diabetes mellitus (GDM) established by selective screening (SS) and to identify subgroups of women at a higher risk of developing GDM.DesignA retrospective, single-center study design was employed.MethodsData of 1015 women screened for GDM at 24–28 weeks of gestation and diagnosed according to the International Association of Diabetes and Pregnancy Study Groups criteria were evaluated. Information on RFs established by SS was also collected and their association with GDM was determined. To identify distinct and homogeneous subgroups of patients at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used.ResultsOverall, 113 (11.1%) women were diagnosed as having GDM. The application of the SS criteria would result in the execution of an oral glucose tolerance test (OGTT) in 58.3% of women and 26 (23.0%) cases of GDM would not be detected due to the absence of any RF. The RECPAM analysis identified high-risk subgroups characterized by fasting plasma glucose values >5.1 mmol/l (odds ratio (OR)=26.5; 95% CI 14.3–49.0) and pre-pregnancy BMI (OR=7.0; 95% CI 3.9–12.8 for overweight women). In a final logistic model including RECPAM classes, previous macrosomia (OR=3.6; 95% CI 1.1–11.6), and family history of diabetes (OR=1.8; 95% CI 1.1–2.8), but not maternal age, were also found to be associated with an increased risk of developing GDM. A screening approach based on the RECPAM model would reduce by over 50% (23.0 vs 10.6%) the number of undiagnosed GDM cases when compared with the current SS approach, at the expense of 50 additional OGTTs required.ConclusionsA screening approach based on our RECPAM model results in a significant reduction in the number of undetected GDM cases compared with the current SS procedure.

High-risk groups and cervical cancer

BMJ ◽  
1980 ◽  
Vol 281 (6244) ◽  
pp. 869-870
Author(s):  
S. W Davies
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Risk Groups
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