• 제목/요약/키워드: Prediction of survival

검색결과 212건 처리시간 0.033초

Prediction Role of Seven SNPs of DNA Repair Genes for Survival of Gastric Cancer Patients Receiving Chemotherapy

  • Zou, Hong-Zhi;Yang, Shu-Juan
    • Asian Pacific Journal of Cancer Prevention
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    • 제13권12호
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    • pp.6187-6190
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    • 2012
  • We aimed to investigate DNA repair gene expression of response to chemotherapy among gastric patients, and roles in the prognosis of gastric cancer. A total of 209 gastric cancer patients were included in this study between January 2007 and December 2008, all treated with chemotherapy. Polymorphisms were detected by real time PCR with TaqMan probes, and genomic DNA was extracted from peripheral blood samples. The overall response rate was 61.2%. The median progression and overall survivals were 8.5 and 18.7 months, respectively. A significant increased treatment response was found among patients with XPG C/T+T/T or XRCC1 399G/A+A/A genotypes, with the OR (95% CI) of 2.14 (1.15-4.01) and 1.75 (1.04-3.35) respectively. We found XPG C/T+T/T and XRCC1 399 G/A+A/A were associated with a longer survival among gastric cancer patients when compared with their wide type genotypes, with HRs and 95% CIs of 0.49 (0.27-0.89) and 0.56 (0.29-0.98) respectively. Selecting specific chemotherapy based on pretreatment genotyping may be an innovative strategy for further studies.

A semiparametric method to measure predictive accuracy of covariates for doubly censored survival outcomes

  • Han, Seungbong;Lee, JungBok
    • Communications for Statistical Applications and Methods
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    • 제23권4호
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    • pp.343-353
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    • 2016
  • In doubly-censored data, an originating event time and a terminating event time are interval-censored. In certain analyses of such data, a researcher might be interested in the elapsed time between the originating and terminating events as well as regression modeling with risk factors. Therefore, in this study, we introduce a model evaluation method to measure the predictive ability of a model based on negative predictive values. We use a semiparametric estimate of the predictive accuracy to provide a simple and flexible method for model evaluation of doubly-censored survival outcomes. Additionally, we used simulation studies and tested data from a prostate cancer trial to illustrate the practical advantages of our approach. We believe that this method could be widely used to build prediction models or nomograms.

Support Vector Machine을 이용한 고객구매예측모형 (Purchase Prediction Model using the Support Vector Machine)

  • 안현철;한인구;김경재
    • 지능정보연구
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    • 제11권3호
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    • pp.69-81
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    • 2005
  • 고객관계관리는 치열한 경쟁환경에서 각 기업이 생존하기 위해 반드시 필요한 하나의 기업전략이 되었다. 고객관계관리의 방법은 다양하지만 가장 기본적인 방법은 특정 고객이 어떤 상품 혹은 상품군을 구매할 것인지를 정확히 예측하는 것이다. 이미 국내외 실무현장에서 전통적인 데이터마이닝 기법을 활용한 고객구매예측모형이 널리 적용되고 있다. 하지만 전통적인 기법의 경우, 정확도가 상대적으로 떨어지거나 혹은 모형의 구축 및 유지관리가 어렵다는 문제가 종종 제기되어 왔다. 이에 본 연구에서는 기존 모형의 문제점을 개선하기 위한 대안으로, 매우 높은 예측력을 나타내면서 동시에 일반화 능력이 우수한 것으로 알려진 Support Vector Machine(SVM)을 이용하여 고객구매예측모형을 구축하고자 한다. 본 연구에서는 고객구매예측의 도구로써 SVM의 적합성을 판단하기 위하여 전통적인 기법인 로지스틱 회귀분석, 인공신경망과 그 성과를 비교하였다. 그 결과, SVM이 다른 기법들에 비해 상대적으로 우수한 성과를 나타냄을 확인할 수 있었다.

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The Application of Machine Learning Algorithm In The Analysis of Tissue Microarray; for the Prediction of Clinical Status

  • Cho, Sung-Bum;Kim, Woo-Ho;Kim, Ju-Han
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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    • pp.366-370
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    • 2005
  • Tissue microarry is one of the high throughput technologies in the post-genomic era. Using tissue microarray, the researchers are able to investigate large amount of gene expressions at the level of DNA, RNA, and protein The important aspect of tissue microarry is its ability to assess a lot of biomarkers which have been used in clinical practice. To manipulate the categorical data of tissue microarray, we applied Bayesian network classifier algorithm. We identified that Bayesian network classifier algorithm could analyze tissue microarray data and integrating prior knowledge about gastric cancer could achieve better performance result. The results showed that relevant integration of prior knowledge promote the prediction accuracy of survival status of the immunohistochemical tissue microarray data of 18 tumor suppressor genes. In conclusion, the application of Bayesian network classifier seemed appropriate for the analysis of the tissue microarray data with clinical information.

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Gene signature for prediction of radiosensitivity in human papillomavirus-negative head and neck squamous cell carcinoma

  • Kim, Su Il;Kang, Jeong Wook;Noh, Joo Kyung;Jung, Hae Rim;Lee, Young Chan;Lee, Jung Woo;Kong, Moonkyoo;Eun, Young-Gyu
    • Radiation Oncology Journal
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    • 제38권2호
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    • pp.99-108
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    • 2020
  • Purpose: The probability of recurrence of cancer after adjuvant or definitive radiotherapy in patients with human papillomavirus-negative (HPV(-)) head and neck squamous cell carcinoma (HNSCC) varies for each patient. This study aimed to identify and validate radiation sensitivity signature (RSS) of patients with HPV(-) HNSCC to predict the recurrence of cancer after radiotherapy. Materials and Methods: Clonogenic survival assays were performed to assess radiosensitivity in 14 HNSCC cell lines. We identified genes closely correlated with radiosensitivity and validated them in The Cancer Genome Atlas (TCGA) cohort. The validated RSS were analyzed by ingenuity pathway analysis (IPA) to identify canonical pathways, upstream regulators, diseases and functions, and gene networks related to radiosensitive genes in HPV(-) HNSCC. Results: The survival fraction of 14 HNSCC cell lines after exposure to 2 Gy of radiation ranged from 48% to 72%. Six genes were positively correlated and 35 genes were negatively correlated with radioresistance, respectively. RSS was validated in the HPV(-) TCGA HNSCC cohort (n = 203), and recurrence-free survival (RFS) rate was found to be significantly lower in the radioresistant group than in the radiosensitive group (p = 0.035). Cell death and survival, cell-to-cell signaling, and cellular movement were significantly enriched in RSS, and RSSs were highly correlated with each other. Conclusion: We derived a HPV(-) HNSCC-specific RSS and validated it in an independent cohort. The outcome of adjuvant or definitive radiotherapy in HPV(-) patients with HNSCC can be predicted by analyzing their RSS, which might help in establishing a personalized therapeutic plan.

P.S.C 철도교량의 잔존수명 예측 (Lifetime Prediction of a P.S.C Rail Road Bridge)

  • 양승이
    • 한국철도학회논문집
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    • 제8권5호
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    • pp.439-443
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    • 2005
  • The biggest challenge bridge agencies face is the maintenance of bridges, keeping them safe and serviceable, with limited funds. To maintain the bridges effectively, there is and urgent need to predict their remaining life from a system reliability viewpoint. In this paper, a model using lifetime functions to evaluate the overall system probability of survival of a rail road bridge is proposed. In this model, the rail load bridge is modeled as a system. Using the model, the lifetime of the rail road bridge is predicted.

비례위험모형에서 비례성 가정에 대한 검정: 도산모형에의 응용

  • 남재우;김동석;이회경
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2004년도 추계학술대회 및 정기총회
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    • pp.615-618
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    • 2004
  • The previous quantitative bankruptcy prediction models cannot include time dimension. To overcome this limit, various dynamic models using survival analysis are developed recently. This paper emphasizes that the proportionality assumption must be adapted with caution when the Cox's proportional hazard model is used to explain bankruptcy. It is shown that a non-proportional hazard model including a change point model is a proper alternative, when the proportionality assumption is violated by the change of macroeconomic environment, such as the financial crisis in 1997.

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Functional annotation of uncharacterized proteins from Fusobacterium nucleatum: identification of virulence factors

  • Kanchan Rauthan;Saranya Joshi;Lokesh Kumar;Divya Goel;Sudhir Kumar
    • Genomics & Informatics
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    • 제21권2호
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    • pp.21.1-21.14
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    • 2023
  • Fusobacterium nucleatum is a gram-negative bacteria associated with diverse infections like appendicitis and colorectal cancer. It mainly attacks the epithelial cells in the oral cavity and throat of the infected individual. It has a single circular genome of 2.7 Mb. Many proteins in F. nucleatum genome are listed as "Uncharacterized." Annotation of these proteins is crucial for obtaining new facts about the pathogen and deciphering the gene regulation, functions, and pathways along with discovery of novel target proteins. In the light of new genomic information, an armoury of bioinformatic tools were used for predicting the physicochemical parameters, domain and motif search, pattern search, and localization of the uncharacterized proteins. The programs such as receiver operating characteristics determine the efficacy of the databases that have been employed for prediction of different parameters at 83.6%. Functions were successfully assigned to 46 uncharacterized proteins which included enzymes, transporter proteins, membrane proteins, binding proteins, etc. Apart from the function prediction, the proteins were also subjected to string analysis to reveal the interacting partners. The annotated proteins were also put through homology-based structure prediction and modeling using Swiss PDB and Phyre2 servers. Two probable virulent factors were also identified which could be investigated further for potential drug-related studies. The assigning of functions to uncharacterized proteins has shown that some of these proteins are important for cell survival inside the host and can act as effective drug targets.

Survival-Related Factors of Spinal Metastasis with Hepatocellular Carcinoma in Current Surgical Treatment Modalities : A Single Institute Experience

  • Lee, Min Ho;Lee, Sun-Ho;Kim, Eun-Sang;Eoh, Whan;Chung, Sung-Soo;Lee, Chong-Suh
    • Journal of Korean Neurosurgical Society
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    • 제58권5호
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    • pp.448-453
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    • 2015
  • Objective : Recently, the survival of patients with hepatocellular carcinoma (HCC) has been prolonged with improvements in various diagnostic tools and medical treatment modalities. Consequently, spine metastases from HCC are being diagnosed more frequently. The accurate prediction of prognosis plays a critical role in determining a patient's treatment plan, including surgery for patients with spinal metastases of HCC. We investigated the clinical features, surgical outcomes, and prognostic factors of HCC presenting with spine metastases, in patients who underwent surgery. Methods : A retrospective review was conducted on 33 HCC patients who underwent 36 operations (three patients underwent surgical treatment twice) from February 2006 to December 2013. The median age of the patients was 56 years old (range, 28 to 71; male : female=30 : 3). Results : Overall survival was not correlated with age, sex, level of metastases, preoperative Child-Pugh classification, preoperative ambulatory function, preoperative radiotherapy, type of operation, administration of Sorafenib, or the Tokuhashi scoring system. Only the Tomita scoring system was shown to be an independent prognostic factor for overall survival. Comparing the Child-Pugh classification and ambulatory ability, there were no statistically differences between patients pre- and post-operatively. Conclusion : The Tomita scoring system represents a practicable and highly predictive prognostic tool. Even though surgical intervention may not restore ambulatory function, it should be considered to prevent deterioration of the patient's overall condition. Additionally, aggressive management may be needed if there is any ambulatory ability remaining.

Providing Reliable Prognosis to Patients with Gastric Cancer in the Era of Neoadjuvant Therapies: Comparison of AJCC Staging Schemata

  • Kim, Gina;Friedmann, Patricia;Solsky, Ian;Muscarella, Peter;McAuliffe, John;In, Haejin
    • Journal of Gastric Cancer
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    • 제20권4호
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    • pp.385-394
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    • 2020
  • Purpose: Patients with gastric cancer who receive neoadjuvant therapy are staged before treatment (cStage) and after treatment (ypStage). We aimed to compare the prognostic reliability of cStage and ypStage, alone and in combination. Materials and Methods: Data for all patients who received neoadjuvant therapy followed by surgery for gastric adenocarcinoma from 2004 to 2015 were extracted from the National Cancer Database. Kaplan-Meier (KM)curves were used to model overall survival based on cStage alone, ypStage alone, cStage stratified by ypStage, and ypStage stratified by cStage. P-values were generated to summarize the differences in KM curves. The discriminatory power of survival prediction was examined using Harrell's C-statistics. Results: We included 8,977 patients in the analysis. As expected, increasing cStage and ypStage were associated with worse survival. The discriminatory prognostic power provided by cStage was poor (C-statistic 0.548), while that provided by ypStage was moderate (C-statistic 0.634). Within each cStage, the addition of ypStage information significantly altered the prognosis (P<0.0001 within cStages I-IV). However, for each ypStage, the addition of cStage information generally did not alter the prognosis (P=0.2874, 0.027, 0.061, 0.049, and 0.007 within ypStages 0-IV, respectively). The discriminatory prognostic power provided by the combination of cStage and ypStage was similar to that of ypStage alone (C-statistic 0.636 vs. 0.634). Conclusions: The cStage is unreliable for prognosis, and ypStage is moderately reliable. Combining cStage and ypStage does not improve the discriminatory prognostic power provided by ypStage alone. A ypStage-based prognosis is minimally affected by the initial cStage.