• 제목/요약/키워드: survival curve

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시멘트 복합체 표면의 자기치유 박테리아 생장 곡선 (Bacteria's Survival Curve on the Surface of Cement Composite)

  • 박지윤;장인동;손다솜;이종구
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2021년도 봄 학술논문 발표대회
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    • pp.203-204
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    • 2021
  • Bacteria used in self-healing concrete, which arrest the crack, helps increasing the durability is well known. However, the survival and activity of the bacteria are precisely unknown. In this research, to know the bacteria's survival curve on the surface of the cement composite, bacteria's survival curve has been measured by CFU at different curing days. The survival curve of 3 days and 7 days curing does not show the significant differences in their survival tendency. However, the slope of death phase of 7 days curing was steeper than the 3 days of curing. This research was focused on the death phase but for further research, set of interval time will be reduced and observe the lag phase and exponential phase.

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생존 분석 자료에서 적용되는 시간 가변 ROC 분석에 대한 리뷰 (Review for time-dependent ROC analysis under diverse survival models)

  • 김양진
    • 응용통계연구
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    • 제35권1호
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    • pp.35-47
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    • 2022
  • Receiver operating characteristic (ROC) 곡선은 이항 반응 자료에 대한 마커의 분류 예측력을 측정하기 위해 널리 적용되어왔으며 최근에는 생존 분석에서도 매우 중요한 역할을 하고 있다. 여러 가지 유형의 중도 절단과 원인 불명 등 다양한 종류의 결측 자료를 포함한 생존 자료 분석에서 마커의 사건 발생 여부에 대한 예측력을 판단하기 위해 기존의 통계량을 확장하였다. 생존 분석 자료는 각 시점에서의 사건 발생 여부로 이해할 수 있으며, 따라서 시점마다 ROC 곡선과 AUC를 구할 수 있다. 본 논문에서는 우중도 절단과 경쟁 위험 모형하에서 사용되는 다양한 방법론과 관련 R 패키지를 소개하고 각 방법의 특성을 설명하고 비교하였으며 이를 검토하기 위해 간단한 모의실험을 시행하였다. 또한, 프랑스에서 수집된 치매 자료의 마커 분석을 시행하였다.

Estimation of mortality coefficients and survivorship curves for minke whales (Balaenoptera acutorostrata) in Korean waters

  • Zhang, Chang-Ik;Song, Kyung-Jun;Na, Jong-Hun
    • Animal cells and systems
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    • 제14권4호
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    • pp.291-296
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    • 2010
  • Population ecological characteristics of growth and mortality play an important role in understanding the population dynamics of marine mammals. The instantaneous coefficients of natural and bycatch mortality were estimated for minke whales (Balaenoptera acutorostrata) in Korean waters using a population assessment model composed of bycatch and abundance data. The survivorship curve of this population was fitted to the data, and then the curve was revised using age-specific relative bycatchability coefficients ($q_t$). Instantaneous coefficients of natural and bycatch mortality of minke whales were estimated as 0.024/year and 0.076/year, respectively, and from this the survival rate was estimated as 0.905. This estimated survival rate was comparable to other cetaceans in other regions. The $q_t$ for this population ranged from 0.020 to 0.193. The revised survival rates were higher when the $q_t$ was taken into account. The mortality coefficient, survival rate, $q_t$ and survivorship curves had not previously been determined for minke whale in this area. This estimate could serve as fundamental information to assess the status of this population and for conservation and rational management.

Prognostic Value of Preoperative Serum CA 242 in Esophageal Squamous Cell Carcinoma Cases

  • Feng, Ji-Feng;Huang, Ying;Chen, Qi-Xun
    • Asian Pacific Journal of Cancer Prevention
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    • 제14권3호
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    • pp.1803-1806
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    • 2013
  • Purpose: Carbohydrate antigen (CA) 242 is inversely related to prognosis in many cancers. However, few data regarding CA 242 in esophageal cancer (EC) are available. The aim of this study was to determine the prognostic value of CA 242 and propose an optimum cut-off point in predicting survival difference in patients with esophageal squamous cell carcinoma (ESCC). Methods: A retrospective analysis was conducted of 192 cases. A receiver operating characteristic (ROC) curve for survival prediction was plotted to verify the optimum cuf-off point. Univariate and multivariate analyses were performed to evaluate prognostic parameters for survival. Results: The positive rate for CA 242 was 7.3% (14/192). The ROC curve for survival prediction gave an optimum cut-off of 2.15 (U/ml). Patients with CA 242 ${\leq}$ 2.15 U/ml had significantly better 5-year survival than patients with CA 242 >2.15 U/ml (45.4% versus 22.6%; P=0.003). Multivariate analysis showed that differentiation (P=0.033), CA 242 (P=0.017), T grade (P=0.004) and N staging (P<0.001) were independent prognostic factors. Conclusions: Preoperative CA 242 is a predictive factor for long-term survival in ESCC, especially in nodal-negative patients. We conclude that 2.15 U/ml may be the optimum cuf-off point for CA 242 in predicting survival in ESCC.

Development of Program for Relative Biological Effectiveness (RBE) Analysis of Particle Beam Therapy

  • Chung, Yoonsun;Ahn, Sang Hee;Choi, Changhoon;Park, Sohee
    • 한국의학물리학회지:의학물리
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    • 제28권1호
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    • pp.11-15
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    • 2017
  • Relative biological effectiveness (RBE) of particle beam needs to be evaluated at particle beam therapy centers before the clinical application of the particle beam. However, since RBE analysis is implemented manually, it is useful to have a tool that can easily and effectively handle the data of experiments to generate cell survival curve and to analyze RBE simultaneously. In this work, the development of a program for RBE analysis of particle beam therapy was presented. This RBE analysis program was developed to include two parts; fitting the cell survival curves to linear-quadratic model and calculating the RBE values at a certain endpoint using fitting results. This program was also developed to simultaneously compare and analyze the template results that stored experiment data with photon and particle beam irradiations. The results of the cell survival curve obtained by each irradiation can be analyzed by the user on a desired data after reading the template stored in the easy-to-use excel file. The analysis results include the cell survival curves with error range, which are appeared in the screen and the ${\alpha}$ and ${\beta}$ parameters of linear-quadratic model with 95% confidence intervals, RBE values, and $R^2$ values to evaluate goodness-of-fit of survival curves to model, which are stored in a text cvs file. This software can generate cell survival curve, fit to model, and calculate RBE all at once with raw experiment data, so it helps users to save time for data handling and to reduce the possibility of making error on analysis. As a coming plan, we will create a user-friendly graphical user interface to present the results more intuitively.

ROC Curve for Multivariate Random Variables

  • Hong, Chong Sun
    • Communications for Statistical Applications and Methods
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    • 제20권3호
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    • pp.169-174
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    • 2013
  • The ROC curve is drawn with two conditional cumulative distribution functions (or survival functions) of the univariate random variable. In this work, we consider joint cumulative distribution functions of k random variables, and suggest a ROC curve for multivariate random variables. With regard to the values on the line, which passes through two mean vectors of dichotomous states, a joint cumulative distribution function can be regarded as a function of the univariate variable. After this function is modified to satisfy the properties of the cumulative distribution function, a ROC curve might be derived; moreover, some illustrative examples are demonstrated.

Optimization of Predictors of Ewing Sarcoma Cause-specific Survival: A Population Study

  • Cheung, Min Rex
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권10호
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    • pp.4143-4145
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    • 2014
  • Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) Ewing sarcoma (ES) outcome data. The aim of this study was to identify and optimize ES-specific survival prediction models and sources of survival disparities. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ES. 1844 patients diagnosed between 1973-2009 were used for this study. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome (bone and joint specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: The mean follow up time (S.D.) was 74.48 (89.66) months. 36% of the patients were female. The mean (S.D.) age was 18.7 (12) years. The SEER staging has the highest ROC (S.D.) area of 0.616 (0.032) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged) to a simpler non-metastatic (I and II) versus metastatic (III) versus un-staged model. The ROC area (S.D.) of the 3-tiered model was 0.612 (0.008). Several other biologic factors were also predictive of ES-specific survival, but not the socio-economic factors tested here. Conclusions: ROC analysis measured and optimized the performance of ES survival prediction models. Optimized models will provide a more efficient way to stratify patients for clinical trials.

산화철 나노입자의 U373MG 세포 독성평가 및 방사선 세포생존 곡선에 미치는 영향에 대한 연구 (A Research on Superparamagnetic Iron Oxide Nanoparticles' Toxicity to U373MG Cell and its Effect on the Radiation Survival Curve)

  • 강성희;김정환;김도경;강보선
    • 한국방사선학회논문지
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    • 제6권6호
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    • pp.507-513
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    • 2012
  • 본 연구는 초상자성 산화철 나노입자 (SPIONs)의 세포독성평가 및 SPIONs를 uptake한 뇌신경교종 (glioblastoma multiforme, GBM) 세포의 방사선 세포생존곡선을 구하기 위해 수행되었으며, 본 연구의 결과는 양성자선과 SPIONs 이용한 GBM의 양성자선 치료선량 정보 등 양성자선 치료효과를 개선하기 위한 기초자료로 활용될 수 있을 것이다. SPIONs의 세포독성을 평가는 in vitro 실험 후 MTT 분석법을 이용하여 수행하였다. 독성평가 결과 $1{\sim}100{\mu}g/ml$의 농도에서는 세포생존율의 유의한 차이가 나타나지 않았다. 하지만 $200{\mu}g/ml$의 농도에서는 세포생존율이 74.2%로 감소하며 세포독성을 나타냈다. SPIONs가 uptake 된 U373MG세포와 uptake 되지 않은 U373MG세포에 0~5 Gy의 양성자선을 조사하여 각각에 대한 세포생존곡선을 측정한 결과를 분석하여 SPIONs가 uptake된 U373MG세포의 세포생존율이 더 급격히 감소함을 알 수 있었다. 결론적으로 SPIONs가 uptake 된 세포에서는 보다 적은 선량으로도 세포사멸을 유도할 수 있음을 알 수 있었다. 따라서 GBM에 SPIONs를 타겟팅하면 양성자선을 이용한 뇌신경교종 치료효과를 개선할 수 있음을 보였다.

Confidence bands for survival curve under the additive risk model

  • Song, Myung-Unn;Jeong, Dong-Myung;Song, Jae-Kee
    • Journal of the Korean Statistical Society
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    • 제26권4호
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    • pp.429-443
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    • 1997
  • We consider the problem of obtaining several types of simultaneous confidence bands for the survival curve under the additive risk model. The derivation uses the weak convergence of normalized cumulative hazard estimator to a mean zero Gaussian process whose distribution can be easily approxomated through simulation. The bands are illustrated by applying them from two well-known clinicla studies. Finally, simulation studies are carried outo to compare the performance of the proposed bands for the survival function under the additive risk model.

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Bezier curve smoothing of cumulative hazard function estimators

  • Cha, Yongseb;Kim, Choongrak
    • Communications for Statistical Applications and Methods
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    • 제23권3호
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    • pp.189-201
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    • 2016
  • In survival analysis, the Nelson-Aalen estimator and Peterson estimator are often used to estimate a cumulative hazard function in randomly right censored data. In this paper, we suggested the smoothing version of the cumulative hazard function estimators using a Bezier curve. We compare them with the existing estimators including a kernel smooth version of the Nelson-Aalen estimator and the Peterson estimator in the sense of mean integrated square error to show through numerical studies that the proposed estimators are better than existing ones. Further, we applied our method to the Cox regression where covariates are used as predictors and suggested a survival function estimation at a given covariate.