Cancer Informatics最新文献

{"title":"Cancer Treatment Data in Central Cancer Registries: When Are Supplemental Data Needed?","authors":"Cathy J Bradley, Rifei Liang, Jagar Jasem, Richard C Lindrooth, Lindsay M Sabik, Marcelo C Perraillon","doi":"10.1177/11769351221112457","DOIUrl":"10.1177/11769351221112457","url":null,"abstract":"<p><strong>Background: </strong>We evaluated treatment concordance between the Colorado All Payer Claims Database (APCD) and the Colorado Central Cancer Registry (CCCR) to explore whether APCDs can augment registry data. We compare treatment concordance for breast cancer, an extensively studied site with an inpatient reporting source and select leukemias that are often diagnosed outpatient.</p><p><strong>Methods: </strong>We analyzed concordance by cancer type and treatment, patient demographics, reporting source, and health insurance, calculating the sensitivity, specificity, positive predictive values (PPV) and Kappa statistics. We estimated an adjusted logistic regression model to assess whether the APCD statistically significantly reports additional cancer-directed treatments.</p><p><strong>Results: </strong>Among women with breast cancer, 14% had chemotherapy treatments that were absent from the CCCR. Missing treatments were more common among women younger than age 50 (15%) and patients aged 75 and older (19%), rural residents (17%), and when the reporting source was outpatient (22%). Similar and more pronounced patterns for people with leukemia were observed. Concordance for oral treatments was lower for each cancer. Sensitivity and PPVs were high, with moderate Kappa statistics. The APCD was 5.3 percentage points less likely to identify additional treatments for breast cancer patients and 10 percentage points more likely to identify additional treatments when the reporting source was an outpatient facility.</p><p><strong>Conclusion: </strong>A robust data infrastructure is needed to investigate research questions that require population-level analyses, particularly for questions seeking to reduce health inequity and comparisons across payers, including Medicare Advantage and fee-for-service. APCD data are a step toward creating an infrastructure for cancer, particularly for patients who reside in rural areas and/or receive care from outpatient centers.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"21 ","pages":"11769351221112457"},"PeriodicalIF":2.4,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/69/58/10.1177_11769351221112457.PMC9340909.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9700819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semi-Automated Computational Assessment of Cancer Organoid Viability Using Rapid Live-Cell Microscopy.","authors":"Joseph D Buehler, Cylaina E Bird, Milan R Savani, Lauren C Gattie, William H Hicks, Michael M Levitt, Mohamad El Shami, Kimmo J Hatanpaa, Timothy E Richardson, Samuel K McBrayer, Kalil G Abdullah","doi":"10.1177/11769351221100754","DOIUrl":"10.1177/11769351221100754","url":null,"abstract":"<p><p>The creation of patient-derived cancer organoids represents a key advance in preclinical modeling and has recently been applied to a variety of human solid tumor types. However, conventional methods used to assess in vivo tumor tissue treatment response are poorly suited for the evaluation of cancer organoids because they are time-intensive and involve tissue destruction. To address this issue, we established a suite of 3-dimensional patient-derived glioma organoids, treated them with chemoradiotherapy, stained organoids with non-toxic cell dyes, and imaged them using a rapid laser scanning confocal microscopy method termed \"Apex Imaging.\" We then developed and tested a fragmentation algorithm to quantify heterogeneity in the topography of the organoids as a potential surrogate marker of viability. This algorithm, SSDquant, provides a 3-dimensional visual representation of the organoid surface and a numerical measurement of the sum-squared distance (SSD) from the derived mass center of the organoid. We tested whether SSD scores correlate with traditional immunohistochemistry-derived cell viability markers (cellularity and cleaved caspase 3 expression) and observed statistically significant associations between them using linear regression analysis. Our work describes a quantitative, non-invasive approach for the serial measurement of patient-derived cancer organoid viability, thus opening new avenues for the application of these models to studies of cancer biology and therapy.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"21 1","pages":"11769351221100754"},"PeriodicalIF":2.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9150230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44955619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Value of hTERT mRNA and in Combination With AFP, AFP-L3%, Des-γ-carboxyprothrombin for Screening of Hepatocellular Carcinoma in Liver Cirrhosis Patients HBV or HCV-Related","authors":"Hoang Bac Nguyen, Xuan Thi Thanh Le, Huy Huu Nguyen, Thanh Thanh Vo, M. Le, Ngan Nguyen, Thien Minh Do-Nguyen, Cong Minh Truong-Nguyen, Bang Suong Thi Nguyen","doi":"10.1177/11769351221100730","DOIUrl":"https://doi.org/10.1177/11769351221100730","url":null,"abstract":"Diagnosis of hepatocellular carcinoma (HCC) in early-stage, to give an effective treatment option and improve quality of life for cancer patients, is an important medical mission globally. Combination of AFP with some biomarkers may be more supportive in both diagnosis and screening of HCC, but the range value of these markers can be applied as daily markers were unclearly. In some studies, human telomerase reverse transcriptase (hTERT mRNA) was reported as an advantage marker to diagnose cancer. The present study identified serum of 340 patients that were infected chronic hepatitis B virus or hepatitis C virus and divided in 2 groups including Hepatocellular carcinoma (HCC) and liver cirrhosis (LC) to measure their values of hTERT mRNA, AFP, AFP-L3%, and DCP, as well as combination of them. As a result, the concentration of hTERT mRNA, AFP, AFP-L3%, and DCP in HCC groups were significantly higher than that in LC group (P < .01). For detecting HCC, hTERT mRNA had sensitivity of 88% and specificity of 96% (at the cutoff value of 31.5 copies/mL), AFP sensitivity of 73% and specificity of 92% (at the cutoff value of 5.1 ng/mL), AFP-L3% sensitivity of 69% and specificity of 90% (at the cutoff value of 1.05%), DCP sensitivity of 82% and specificity of 92% (at the cutoff value of 29.01 mAU/mL). The largest area under the curve (AUC) of combination hTERT mRNA with DCP was 0.932 (sensitivity of 98.2% and specificity of 88.2%). New combination of DCP with hTERT mRNA gave a useful choice for screening of HCC in chronic HBV or HCV patients associated liver cirrhosis.","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46634427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A 25 Immune-Related Gene Pair Signature Predicts Overall Survival in Cervical Cancer","authors":"Huaqiu Chen, Huanyu Xie, Pengyu Wang, S. Yan, Yuanyuan Zhang, Guangming Wang","doi":"10.1177/11769351221090921","DOIUrl":"https://doi.org/10.1177/11769351221090921","url":null,"abstract":"Mounting evidence suggests that the tumor microenvironment plays an important role in the occurrence and development of cancer, with immune system dysfunction being closely related to malignant cancers. We aimed to screen immune-related genes (IRGs) to generate an IRG pair (IRGP)-based prognostic signature for cervical cancer (CC). Datasets were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases and used as training and validation cohorts, respectively. Using the ImmPort database, IRGs in control and CC samples were compared, and differentially expressed genes were identified to construct an IRGP prognostic signature. Based on this analysis, 25 IRGPs were identified as important factors for the prognosis of CC. Univariate and multivariate Cox regression analyses further showed that the IRGP signature was an independent prognostic factor of overall survival. In summary, we successfully constructed an IRGP prognostic signature of CC, providing insights into immunotherapy for CC.","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47389905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TULIP: An RNA-seq-based Primary Tumor Type Prediction Tool Using Convolutional Neural Networks.","authors":"Sara Jones,&nbsp;Matthew Beyers,&nbsp;Maulik Shukla,&nbsp;Fangfang Xia,&nbsp;Thomas Brettin,&nbsp;Rick Stevens,&nbsp;M Ryan Weil,&nbsp;Satishkumar Ranganathan Ganakammal","doi":"10.1177/11769351221139491","DOIUrl":"https://doi.org/10.1177/11769351221139491","url":null,"abstract":"<p><strong>Background: </strong>With cancer as one of the leading causes of death worldwide, accurate primary tumor type prediction is critical in identifying genetic factors that can inhibit or slow tumor progression. There have been efforts to categorize primary tumor types with gene expression data using machine learning, and more recently with deep learning, in the last several years.</p><p><strong>Methods: </strong>In this paper, we developed four 1-dimensional (1D) Convolutional Neural Network (CNN) models to classify RNA-seq count data as one of 17 highly represented primary tumor types or 32 primary tumor types regardless of imbalanced representation. Additionally, we adapted the models to take as input either all Ensembl genes (60,483) or protein coding genes only (19,758). Unlike previous work, we avoided selection bias by not filtering genes based on expression values. RNA-seq count data expressed as FPKM-UQ of 9,025 and 10,940 samples from The Cancer Genome Atlas (TCGA) were downloaded from the Genomic Data Commons (GDC) corresponding to 17 and 32 primary tumor types respectively for training and validating the models.</p><p><strong>Results: </strong>All 4 1D-CNN models had an overall accuracy of 94.7% to 97.6% on the test dataset. Further evaluation indicates that the models with protein coding genes only as features performed with better accuracy compared to the models with all Ensembl genes for both 17 and 32 primary tumor types. For all models, the accuracy by primary tumor type was above 80% for most primary tumor types.</p><p><strong>Conclusions: </strong>We packaged all 4 models as a Python-based deep learning classification tool called TULIP (TUmor CLassIfication Predictor) for performing quality control on primary tumor samples and characterizing cancer samples of unknown tumor type. Further optimization of the models is needed to improve the accuracy of certain primary tumor types.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"21 ","pages":"11769351221139491"},"PeriodicalIF":2.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b1/0b/10.1177_11769351221139491.PMC9729992.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10333449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics Analysis of Differential Gene and MicroRNA Expression in Lung Adenocarcinoma: Genetic Effects on Patient Prognosis, as Indicated by the TCGA Database","authors":"Bingqing Sun, Hongwen Zhao","doi":"10.1177/11769351221082020","DOIUrl":"https://doi.org/10.1177/11769351221082020","url":null,"abstract":"Objective: To investigate the differential expression of genes and microRNAs (miRNAs) in patients with lung adenocarcinoma and the relationship between such changes and patient prognosis. Methods: We analyzed the expression levels of genes and miRNAs in lung adenocarcinoma tissues and adjacent normal tissues using The Cancer Genome Atlas database (TCGA). We analyzed the function of the differentially expressed genes and miRNAs in a co-expression network. Finally, we performed survival analysis of differential genes and miRNAs in the co-expression network using clinical data from the TCGA database. Results: We successfully identified 6064 differentially expressed genes: 5324 upregulated genes and 740 downregulated genes. And we identified 161 differentially expressed miRNAs: 126 upregulated miRNAs and 35 downregulated miRNAs. We identified several genes that were related to each other in the co-expression network. Further analysis revealed that the high expression levels of G6PC, APOB, F2, PAQR9, and PAQR9-AS1 genes were associated with poor prognosis. However, there was no significant correlation between the expression of hsa-mir-122 with regards to patient prognosis. Conclusions: Our data showed that hsa-mir-122 and a number of related genes may affect the prognosis of patients with lung adenocarcinoma by regulating the cytoskeleton, thus promoting tumor angiogenesis and the metastasis of tumor cells. The high expression levels of some differentially expressed genes was associated with the low survival rate in patients with lung adenocarcinoma. However, the levels of hsa-mir-122 were not correlated with patient prognosis.","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44965393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An In Silico Analysis Reveals an EMT-Associated Gene Signature for Predicting Recurrence of Early-Stage Lung Adenocarcinoma","authors":"Yi Han, F. Wong, Di Wang, C. Kahlert","doi":"10.1177/11769351221100727","DOIUrl":"https://doi.org/10.1177/11769351221100727","url":null,"abstract":"Background: The potential micrometastasis tends to cause recurrence of lung adenocarcinoma (LUAD) after surgical resection and consequently leads to an increase in the mortality risk. Compelling evidence has suggested the underlying mechanisms of tumor metastasis could involve the activation of an epithelial-mesenchymal transition (EMT) program. Hence, the objective of this study was to develop an EMT-associated gene signature for predicting the recurrence of early-stage LUAD. Methods: The mRNA expression data of patients with early-stage LUAD were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) available databases. Gene Set Variation Analysis (GSVA) was first performed to provide an assessment of EMT phenotype, whereas Weighted Gene Co-expression Network Analysis (WGCNA) was constructed to determine EMT-associated key modules and genes. Based on the genes, a novel EMT-associated signature for predicting the recurrence of early-stage LUAD was identified using a least absolute shrinkage and selection operator (LASSO) algorithm and a stepwise Cox proportional hazards regression model. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves and Cox regression analyses were used to estimate the performance of the identified gene signature. Results: GSVA revealed diverse EMT states in the early-stage LUAD. Further correlation analyses showed that the EMT states presented high correlations with several hallmarks of cancers, tumor purity, tumor microenvironment cells, and immune checkpoint genes. More importantly, Kaplan-Meier survival analyses indicated that patients with high EMT scores had worse recurrence-free survival (RFS) and overall survival (OS) than those with low EMT scores. A novel 5-gene signature (AGL, ECM1, ENPP1, SNX7, and TSPAN12) was established based on the EMT-associated genes from WGCNA and this signature successfully predicted that the high-risk patients had a higher recurrence rate compared with the low-risk patients. In further analyses, the signature represented robust prognostic values in 2 independent validation cohorts (GEO and TCGA datasets) and a combined GEO cohort as evaluated by Kaplan-Meier survival (P-value &lt; .0001) and ROC analysis (AUC = 0.781). Moreover, the signature was corroborated to be independent of clinical factors by univariate and multivariate Cox regression analyses. Interestingly, the combination of the signature-based recurrence risk and tumor-node-metastasis (TNM) stage showed a superior predictive ability on the recurrence of patients with early-stage LUAD. Conclusion: Our study suggests that patients with early-stage LUAD exhibit diverse EMT states that play a vital role in tumor recurrence. The novel and promising EMT-associated 5-gene signature identified and validated in this study may be applied to predict the recurrence of early-stage LUAD, facilitating risk stratification, recurrence monitoring, and individualized management for the patient","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49035005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deciphering the Increased Prevalence of TP53 Mutations in Metastatic Prostate Cancer","authors":"Wensheng Zhang, Yan Dong, O. Sartor, Kun Zhang","doi":"10.1177/11769351221087046","DOIUrl":"https://doi.org/10.1177/11769351221087046","url":null,"abstract":"The prevalence of TP53 mutations in advanced prostate cancers (PCa) is 3 to 5 times of the quantity in primary PCa. By an integrative analysis of the Cancer Genome Atlas and Catalogue of Somatic Mutations in Cancer data, we revealed the supporting evidence for 2 complementary hypotheses: H1 - TP53 abnormalities promote metastasis or therapy-resistance of PCa cells, and H2—part of TP53 mutations in PCa metastases occur after the diagnosis of original cancers. The plausibility of these hypotheses can explain the increased prevalence of TP53 mutations in PCa metastases. With H1 and H2 as the general assumptions, we developed mathematical models to decipher the change of the percentage frequency (prevalence) of TP53 mutations from primary tumors to metastases. The following results were obtained. Compared to TP53-normal patients, TP53-mutated patients had poorer biochemical relapse-free survival, higher Gleason scores, and more advanced t-stages (P < .01). Single-nucleotide variants in metastases more frequently occurred on G bases of the coding sequence than those in primary cancers (P = .03). The profile of TP53 hotspot mutations was significantly different between primary and metastatic PCa as demonstrated in a set of statistical tests (P < .05). By the derived formulae, we estimated that about 40% TP53 mutation records collected from metastases occurred after the diagnosis of the original cancers. Our study provided significant insight into PCa progression. The proposed models can also be applied to decipher the prevalence of mutations on TP53 (or other driver genes) in other cancer types.","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"21 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42356781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-Cell Transcriptome Analysis Reveals Paraspeckles Expression in Osteosarcoma Tissues.","authors":"Emel Rothzerg,&nbsp;Wenyu Feng,&nbsp;Dezhi Song,&nbsp;Hengyuan Li,&nbsp;Qingjun Wei,&nbsp;Archa Fox,&nbsp;David Wood,&nbsp;Jiake Xu,&nbsp;Yun Liu","doi":"10.1177/11769351221140101","DOIUrl":"https://doi.org/10.1177/11769351221140101","url":null,"abstract":"<p><p>Nuclear paraspeckles are subnuclear bodies contracted by nuclear-enriched abundant transcript 1 (NEAT1) long non-coding RNA, localised in the interchromatin space of mammalian cell nuclei. Paraspeckles have been critically involved in tumour progression, metastasis and chemoresistance. To this date, there are limited findings to suggest that paraspeckles, NEAT1 and heterogeneous nuclear ribonucleoproteins (hnRNPs) directly or indirectly play roles in osteosarcoma progression. Herein, we analysed NEAT1, paraspeckle proteins (SFPQ, PSPC1 and NONO) and hnRNP members (HNRNPK, HNRNPM, HNRNPR and HNRNPD) gene expression in 6 osteosarcoma tumour tissues using the single-cell RNA-sequencing method. The normalised data highlighted that the paraspeckles transcripts were highly abundant in osteoblastic OS cells, except NEAT1, which was highly expressed in myeloid cell 1 and 2 subpopulations.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"21 ","pages":"11769351221140101"},"PeriodicalIF":2.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/4d/17/10.1177_11769351221140101.PMC9730017.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10333451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge, Attitude, and Practice Toward Cervical Cancer Screening and Associated Factors Among College and University Female Students in Dire Dawa City, Eastern Ethiopia","authors":"H. Bekele, A. Nuri, Legesse Abera","doi":"10.1177/11769351221084808","DOIUrl":"https://doi.org/10.1177/11769351221084808","url":null,"abstract":"Introduction: Cervical cancer is preventable and, in most cases, curable if identified at an early stage. Cervical cancer is the second leading cause of cancer-related mortality Ethiopia with screening accounting for only 0.8%. Furthermore, female students and young adults in colleges and universities’ have a high prevalence of genital HPV infection because of their risky sexual behavior, lack of knowledge on screening and very few students receive screening services. This study aimed to assess the Knowledge, attitudes, and practice toward cervical cancer screening and its associated factors among female college students in Dire Dawa City, Ethiopia. Methods: An institutional-based cross-sectional study was conducted using a multistage sampling technique from November to December 2020, among 730 female college students in Dire Dawa. Descriptive statistics and binary logistic regression were used to describe each variable and identify associations between the dependent and independent variables respectively. Adjusted odds ratio with 95% confidence interval and P-value <.05 used to determine the association. Results: The results showed, only 64 (9.3%) participants were knowledgeable, 413 (60.1%) had positive attitudes and 17 (2.5%) were screened in their lifetime. Age group, years of study, and history of cervical cancer practice were significantly associated with knowledge of cervical cancer screening. The year of study was based on cervical cancer smears and the number of screenings was significantly associated with attitude. Conclusion: This study showed that students’ knowledge of cervical cancer screening is low. Overall attitudes toward cervical cancer screening among female students were good, but only a small proportion of students had undergone cervical cancer screening. The most common reasons for the low screening practice were lack of information and undecided. There is a need to promote different campaigns for cervical cancer screening programs, in order to increase awareness.","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44368152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}