Identification of High Risk and Low Risk Preterm Neonates in NICU

2020 ◽  
pp. 119-140
Author(s):  
S. Tejaswini ◽  
N. Sriraam ◽  
Pradeep G. C. M.
Keyword(s):  
High Risk ◽  
Neonatal Intensive Care ◽  
Risk Groups ◽  
Clinical Decision ◽  
Biological Indicator ◽  
Low Risk ◽  
Preterm Neonates ◽  
Support Vector ◽  
Svm Classifier ◽  
Sensitivity Specificity

Infant cries are referred as the biological indicator where infant distress is expressed without any external stimulus. One can assess the physiological changes through cry characteristics that help in improving clinical decision. In a typical Neonatal Intensive Care Unit (NICU), recognizing high-risk and low-risk admitted preterm neonates is quite challenging and complex in nature. This chapter attempts to develop pattern recognition-based approach to identify high-risk and low-risk preterm neonates in NICU. Four clinical conditions were considered: two Low Risk (LR) and two High Risk (HR), LR1- Appropriate Gestational Age (AGA), LR2- Intrauterine Growth Restriction (IUGR), HR1-Respiratory Distress Syndrome (RDS), and HR2- Premature Rupture of Membranes (PROM). An overall cry unit of 800 (n=20 per condition) was used for the proposed study. After appropriate pre-processing, Bark Frequency Cepstral Coefficient (BFCC) was estimated using three methods. Schroeder, Zwicker and Terhardt; and Transmiller; and a non-linear Support Vector Machine (SVM) Classifier were employed to discriminate low-risk and high-risk groups. From the simulation results, it was observed that sensitivity specificity and accuracy of 91.47%, 91.42%, and 92.9% respectively were obtained using the BFCC estimated for classifying high risk and low risk with SVM classification.

Artificial Intelligence for the Online Prediction of the Cool-down Time in a Subsea Pipeline After an Unplanned Shutdown

2021 ◽  
Author(s):  
Alberto Gerri ◽  
Ahmed Shokry ◽  
Enrico Zio ◽  
Marco Montini
Keyword(s):  
High Risk ◽  
Operating Conditions ◽  
Low Risk ◽  
Minimum Time ◽  
Computational Time ◽  
Risk Level ◽  
Support Vector ◽  
Svm Classifier ◽  
The Novel ◽  
Subsea Pipelines

Abstract Hydrates formation in subsea pipelines is one of the main reliability concerns for flow assurance engineers. A fast and reliable assessment of the Cool-Down Time (CDT), the period between a shut-down event and possible hydrates formation in the asset, is of key importance for the safety of operations. Existing methods for the CDT prediction are highly dependent on the use of very complex physics-based models that demand large computational time, which hinders their usage in an online environment. Therefore, this work presents a novel methodology for the development of surrogate models that predict, in a fast and accurate way, the CDT in subsea pipelines after unplanned shutdowns. The proposed methodology is, innovatively, tailored on the basis of reliability perspective, by treating the CDT as a risk index, where a critic CDT threshold (i.e. the minimum time needed by the operator to preserve the line from hydrates formation) is considered to distinguish the simulation outputs into high-risk and low-risk domains. The methodology relies on the development of a hybrid Machine Learning (ML) based model using datasets generated through complex physics-based model’ simulations. The hybrid ML-based model consists of a Support Vector Machine (SVM) classifier that assigns a risk level (high or low) to the measured operating condition of the asset, and two Artificial Neural Networks (ANNs) for predicting the CDT at the high-risk (low CDT) or the low-risk (high CDT) operating conditions previously assigned by the classifier. The effectiveness of the proposed methodology is validated by its application to a case study involving a pipeline in an offshore western African asset, modelled by a transient physics-based commercial software. The results show outperformance of the capabilities of the proposed hybrid ML-based model (i.e., SVM + 2 ANNs) compared to the classical approach (i.e. modelling the entire system with one global ANN) in terms of enhancing the prediction of the CDT during the high-risk conditions of the asset. This behaviour is confirmed applying the novel methodology to training datasets of different size. In fact, the high-risk Normalized Root Mean Square Error (NRMSE) is reduced on average of 15% compared to the NRMSE of a global ANN model. Moreover, it’s shown that high-risk CDT are better predicted by the hybrid model even if the critic CDT, which divides the simulation outputs in high-risk and low-risk values (i.e. the minimum time needed by the operator to preserve the line from hydrates formation), changes. The enhancement, in this case, is on average of 14.6%. Eventually, results show how the novel methodology cuts down by more than one hundred seventy-eight times the computational times for online CDT predictions compared to the physics-based model.

PET Parameters are Useful in Predicting Endometrial Cancer Risk Classes and Prognosis

2020 ◽  
Author(s):  
Adnan Budak ◽  
Emrah Beyan ◽  
Abdurrahman Hamdi Inan ◽  
Ahkam Göksel Kanmaz ◽  
Onur Suleyman Aldemir ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
High Risk ◽  
Myometrial Invasion ◽  
Risk Groups ◽  
Total Sample ◽  
Tumor Stage ◽  
Low Risk ◽  
Tumor Diameter ◽  
Grade 3 ◽  
Fdg Pet Ct

Abstract Aim We investigate the role of preoperative PET parameters to determine risk classes and prognosis of endometrial cancer (EC). Methods We enrolled 81 patients with EC who underwent preoperative F-18 FDG PET/CT. PET parameters (SUVmax, SUVmean, MTV, TLG), grade, histology and size of the primary tumor, stage of the disease, the degree of myometrial invasion (MI), and the presence of lymphovascular invasion (LVI), cervical invasion (CI), distant metastasis (DM) and lymph node metastasis (LNM) were recorded. The relationship between PET parameters, clinicopathological risk factors and overall survival (OS) was evaluated. Results The present study included 81 patients with EC (mean age 60). Of the total sample, 21 patients were considered low risk (endometrioid histology, stage 1A, grade 1 or 2, tumor diameter < 4 cm, and LVI negative) and 60 were deemed high risk. All of the PET parameters were higher in the presence of a high-risk state, greater tumor size, deep MI, LVI and stage 1B-4B. MTV and TLG values were higher in the patients with non-endometrioid histology, CI, grade 3 and LNM. The optimum cut-off levels for differentiating between the high and low risk patients were: 11.1 for SUVmax (AUC = 0.757), 6 for SUVmean (AUC = 0.750), 6.6 for MTV(AUC = 0.838) and 56.2 for TLG(AUC = 0.835). MTV and TLG values were found as independent prognostic factors for OS, whereas SUVmax and SUVmean values were not predictive. Conclusions The PET parameters are useful in noninvasively differentiating between risk groups of EC. Furthermore, volumetric PET parameters can be predictive for OS of EC.

Short-term risk stratification using CADILLAC risk score in patients with ST elevation myocardial infarction

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
T Satou ◽  
H Kitahara ◽  
K Ishikawa ◽  
T Nakayama ◽  
Y Fujimoto ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
High Risk ◽  
Adverse Events ◽  
Risk Score ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Short Term ◽  
Recurrent Myocardial Infarction ◽  
St Elevation

Abstract Background The recent reperfusion therapy for ST-elevation myocardial infarction (STEMI) has made the length of hospital stay shorter without adverse events. CADILLAC risk score is reportedly one of the risk scores predicting the long-term prognosis in STEMI patients. Purpose To invenstigate the usefulness of CADILLAC risk score for predicting short-term outcomes in STEMI patients. Methods Consecutive patients admitted to our university hospital and our medical center with STEMI (excluding shock, arrest case) who underwent primary PCI between January 2012 and April 2018 (n=387) were enrolled in this study. The patients were classified into 3 groups according to the CADILLAC risk score: low risk (n=176), intermediate risk (n=87), and high risk (n=124). Data on adverse events within 30 days after hospitalization, including in-hospital death, sustained ventricular arrhythmia, recurrent myocardial infarction, heart failure requiring intravenous treatment, stroke, or clinical hemorrhage, were collected. Results In the low risk group, adverse events within 30 days were significantly less observed, compared to the intermediate and high risk groups (n=13, 7.4% vs. n=13, 14.9% vs. n=58, 46.8%, p&lt;0.001). In particular, all adverse events occurred within 3 days in the low risk group, although adverse events, such as heart failure (n=4), recurrent myocardial infarction (n=1), stroke (n=1), and gastrointestinal bleeding (n=1), were substantially observed after day 4 of hospitalization in the intermediate and high risk groups. Conclusions In STEMI patients with low CADILLAC risk score, better short-term prognosis was observed compared to the intermediate and high risk groups, and all adverse events occurred within 3 days of hospitalization, suggesting that discharge at day 4 might be safe in this study population. CADILLAC risk score may help stratify patient risk for short-term prognosis and adjust management of STEMI patients. Initial event occurrence timing Funding Acknowledgement Type of funding source: None

scholarly journals A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qian Yan ◽  
Wenjiang Zheng ◽  
Boqing Wang ◽  
Baoqian Ye ◽  
Huiyan Luo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Model ◽  
Risk Groups ◽  
Low Risk ◽  
Prognostic Performance ◽  
Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

scholarly journals CanAssist Breast Impacting Clinical Treatment Decisions in Early-Stage HR+ Breast Cancer Patients: Indian Scenario

2019 ◽  
Author(s):  
Satish Sankaran ◽  
Jyoti Bajpai Dikshit ◽  
Chandra Prakash SV ◽  
SE Mallikarjuna ◽  
SP Somashekhar ◽  
...  
Keyword(s):  
High Risk ◽  
Early Stage ◽  
Risk Groups ◽  
Treatment Decisions ◽  
Low Risk ◽  
Not Given ◽  
Breast Cancer Patients ◽  
Number Of Patients ◽  
Risk Of Cancer ◽  
The Impact

AbstractCanAssist Breast (CAB) has thus far been validated on a retrospective cohort of 1123 patients who are mostly Indians. Distant metastasis–free survival (DMFS) of more than 95% was observed with significant separation (P < 0.0001) between low-risk and high-risk groups. In this study, we demonstrate the usefulness of CAB in guiding physicians to assess risk of cancer recurrence and to make informed treatment decisions for patients. Of more than 500 patients who have undergone CAB test, detailed analysis of 455 patients who were treated based on CAB-based risk predictions by more than 140 doctors across India is presented here. Majority of patients tested had node negative, T2, and grade 2 disease. Age and luminal subtypes did not affect the performance of CAB. On comparison with Adjuvant! Online (AOL), CAB categorized twice the number of patients into low risk indicating potential of overtreatment by AOL-based risk categorization. We assessed the impact of CAB testing on treatment decisions for 254 patients and observed that 92% low-risk patients were not given chemotherapy. Overall, we observed that 88% patients were either given or not given chemotherapy based on whether they were stratified as high risk or low risk for distant recurrence respectively. Based on these results, we conclude that CAB has been accepted by physicians to make treatment planning and provides a cost-effective alternative to other similar multigene prognostic tests currently available.

Identification of Molecular Biomarkers and Pathways for Risk Stratification in Human Papilloma Virus-Associated Cancers

2021 ◽  
Author(s):  
Eun Jung Kwon ◽  
Hye Ran Lee ◽  
Ju Ho Lee ◽  
Mihyang Ha ◽  
Yun Hak Kim ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Expression Patterns ◽  
Risk Groups ◽  
Molecular Biomarkers ◽  
Low Risk ◽  
Receptor Interaction ◽  
Prognostic Impact ◽  
Tumor Microenvironments ◽  
Cell Immunity

Abstract Background: Human papillomavirus (HPV) is the major cause of cervical cancer (CC) etiology; its contribution to head and neck cancer (HNC) incidence is steadily increasing. As individual patients’ response to the treatment of HPV-associated cancer is variable, there is a pressing need for the identification of biomarkers for risk stratification that can help determine the intensity of treatment. Methods: We have previously reported a novel prognostic and predictive indicator (HPPI) scoring system in HPV-associated cancers regardless of the anatomical locations by analyzing the TCGA and GEO databases. In this study, we comprehensively investigated the association of group-specific expression patterns of common differentially expressed genes (DEGs) between high-risk and low-risk groups in HPV-associated CC and HNC, identifying a molecular biomarkers and pathways for the risk stratification. Results: Among the identified 174 DEGs, expression of the genes associated with extracellular matrix (ECM)-receptor interaction pathway (ITGA5, ITGB1, LAMB1, LAMC1) were increased in high-risk groups in both HPV-associated CC and HNC while expression of the genes associated with the T-cell immunity (CD3D, CD3E, CD8B, LCK, and ZAP70) were decreased vise versa. The individual genes showed statistically significant prognostic impact on HPV-associated cancers but not on HPV-negative cancers. The expression levels of identified genes were similar between HPV-negative and HPV-associated high-risk groups with distinct expression patterns only in HPV-associated low-risk groups. Each group of genes showed negative correlations, and distinct patterns of immune cell infiltration in tumor microenvironments. Conclusion: These results identify molecular biomarkers and pathways for risk stratification in HPV-associated cancers regardless of anatomical locations. The identified targets are selectively working in only HPV-associated cancers, but not in HPV-negative cancers indicating possibility of the selective targets governing HPV-infective tumor microenvironments.

The national impact of the COVID-19 pandemic on U.S. prostate cancer community care.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 5061-5061
Author(s):  
Matthew R. Cooperberg ◽  
Paul Brendel ◽  
Daniel J. Lee ◽  
Rahul Doraiswami ◽  
Hariesh Rajasekar ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Language Processing ◽  
Care Delivery ◽  
Specific Antigen ◽  
Risk Groups ◽  
Low Risk ◽  
T Stage ◽  
Risk Stratum ◽  
The Impact

5061 Background: We used data from a specialty-wide, community-based urology registry to determine trends in outpatient prostate cancer (PCa) care during the COVID-19 pandemic. Methods: 3,165 (̃ 25%) of US urology providers, representing 48 states and territories, participate in the American Urological Association Quality (AQUA) Registry, which collects data via automated extraction from electronic health record systems. We analyzed trends in PCa care delivery from 156 practices contributing data in 2019 and 2020. Risk stratification was based on prostate-specific antigen (PSA) at diagnosis, biopsy Gleason, and clinical T-stage, and we used a natural language processing algorithm to determine Gleason and T-stage from unstructured clinical notes. The primary outcome was mean weekly visit volume by PCa patients per practice (visits defined as all MD and mid-level visits, telehealth and face-to-face), and we compared each week in 2020 through week 44 (November 1) to the corresponding week in 2019. Results: There were 267,691 PCa patients in AQUA who received care between 2019 and 2020. From mid-March to early November, 2020 (week 10 – week 44) the magnitude of the decline and recovery varied by risk stratum, with the steepest drops for low-risk PCa (Table). For 2020, overall mean visits per day (averaged weekly) were similar to 2019 for the first 9 weeks (̃25). Visits declined to week 14 (18.19; a 31% drop from 2019), recovered to 2019 levels by week 23, and declined steadily to 11.89 (a 58% drop from 2019) as of week 44, the cut off of this analysis. Conclusions: Access to care for men with PCa was sharply curtailed by the COVID-19 pandemic, and while the impact was less for men with high-risk disease compared to those with low-risk disease, visits even for high-risk individuals were down nearly one-third and continued to fall through November. This study provides real-world evidence on the magnitude of decline in PCa care across risk groups. The impact of this decline on cancer outcomes should be followed closely.[Table: see text]

scholarly journals Prelabor rupture of membranes at term: A possible hematological triage in addition to vagino-rectal beta-hemolytic streptococcus screening for early labor induction

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0261906
Author(s):  
Francesco D’Ambrosi ◽  
Nicola Cesano ◽  
Enrico Iurlaro ◽  
Alice Ronchi ◽  
Ilaria Giuditta Ramezzana ◽  
...  
Keyword(s):  
High Risk ◽  
Cesarean Section ◽  
Neonatal Intensive Care ◽  
Perinatal Outcomes ◽  
Expectant Management ◽  
Low Risk ◽  
Clinical Protocol ◽  
Hemolytic Streptococcus ◽  
Beta Hemolytic Streptococcus ◽  
Prelabor Rupture Of Membranes

Introduction A potential complication of term prelabor rupture of membranes (term PROM) is chorioamnionitis with an increased burden on neonatal outcomes of chronic lung disease and cerebral palsy. The purpose of the study was to analyze the efficacy of a standing clinical protocol designed to identify women with term PROM at low risk for chorioamnionitis, who may benefit from expectant management, and those at a higher risk for chorioamnionitis, who may benefit from early induction. Material and methods This retrospective study enrolled all consecutive singleton pregnant women with term PROM. Subjects included women with at least one of the following factors: white blood cell count ≥ 15×100/μL, C-reactive protein ≥ 1.5 mg/dL, or positive vaginal swab for beta-hemolytic streptococcus. These women comprised the high risk (HR) group and underwent immediate induction of labor by the administration of intravaginal dinoprostone. Women with none of the above factors and those with a low risk for chorioamnionitis waited for up to 24 hours for spontaneous onset of labor and comprised the low-risk (LR) group. Results Of the 884 consecutive patients recruited, 65 fulfilled the criteria for HR chorioamnionitis and underwent immediate induction, while 819 were admitted for expectant management. Chorioamnionitis and Cesarean section rates were not significantly different between the HR and LR groups. However, the prevalence of maternal fever (7.7% vs. 2.9%; p = 0.04) and meconium-stained amniotic fluid was significantly higher in the HR group than in LR group (6.1% vs. 2.2%; p = 0.04). This study found an overall incidence of 4.2% for chorioamnionitis, 10.9% for Cesarean section, 0.5% for umbilical artery blood pH < 7.10, and 1.9% for admission to the neonatal intensive care unit. Furthermore, no confirmed cases of neonatal sepsis were encountered. Conclusions A clinical protocol designed to manage, by immediate induction, only those women with term PROM who presented with High Risk factors for infection/inflammation achieved similar maternal and perinatal outcomes between such women and women without any risks who received expectant management. This reduced the need for universal induction of term PROM patients, thereby reducing the incidence of maternal and fetal complications without increasing the rate of Cesarean sections.

scholarly journals Development and Verification of the Hypoxia- and Immune-Associated Prognostic Signature for Pancreatic Ductal Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Dongjie Chen ◽  
Hui Huang ◽  
Longjun Zang ◽  
Wenzhe Gao ◽  
Hongwei Zhu ◽  
...  
Keyword(s):  
High Risk ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Pearson Correlation ◽  
Risk Groups ◽  
Low Risk ◽  
Ductal Adenocarcinoma ◽  
Prognostic Signature ◽  
Score Model

We aim to construct a hypoxia- and immune-associated risk score model to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). By unsupervised consensus clustering algorithms, we generate two different hypoxia clusters. Then, we screened out 682 hypoxia-associated and 528 immune-associated PDAC differentially expressed genes (DEGs) of PDAC using Pearson correlation analysis based on the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression project (GTEx) dataset. Seven hypoxia and immune-associated signature genes (S100A16, PPP3CA, SEMA3C, PLAU, IL18, GDF11, and NR0B1) were identified to construct a risk score model using the Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, which stratified patients into high- and low-risk groups and were further validated in the GEO and ICGC cohort. Patients in the low-risk group showed superior overall survival (OS) to their high-risk counterparts (p &lt; 0.05). Moreover, it was suggested by multivariate Cox regression that our constructed hypoxia-associated and immune-associated prognosis signature might be used as the independent factor for prognosis prediction (p &lt; 0.001). By CIBERSORT and ESTIMATE algorithms, we discovered that patients in high-risk groups had lower immune score, stromal score, and immune checkpoint expression such as PD-L1, and different immunocyte infiltration states compared with those low-risk patients. The mutation spectrum also differs between high- and low-risk groups. To sum up, our hypoxia- and immune-associated prognostic signature can be used as an approach to stratify the risk of PDAC.

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.

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