• 보건행정학회지
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• 제19권4호
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• pp.18-32
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• 2009

The goal of this study was to predict the health outcomes of lung cancer surgery based on the Charlson comorbidity index (CCI). An attempt was likewise made to assess the prognostic value of such data for predicting mortality, survival rate, and length of hospital stay. A medical-record review of 389 patients with non-small-cell lung cancer was performed. To evaluate the agreement, the kappa coefficient was tested. Logistic-regression analysis was also conducted within two years after the surgery to determine the association of CCI with death. Survival and multiple-regression analyses were used to evaluate the relationship between CCI and the hospital care outcomes within two-year survival after lung cancer surgery and the length of hospital stay. The results of the study showed that CCI is a valid prognostic indicator of two-year mortality and length of hospital stay, and that it shows the health outcomes, such as death, survival rate, and length of hospital stay, after the surgery, thus enabling the development and application of the methodology using a systematic and objective scale for the results.

• Journal of Gastric Cancer
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• 제21권2호
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• pp.155-168
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• 2021

Purpose: Previous studies have demonstrated the usefulness of the controlling nutritional status (CONUT) score in nutritional assessment and survival prediction of patients with various malignancies. However, its value in advanced gastric cancer (GC) treated with neoadjuvant chemotherapy and curative gastrectomy remains unclear. Materials and Methods: The CONUT score at different time points (pretreatment, preoperative, and postoperative) of 272 patients with advanced GC were retrospectively calculated from August 2004 to October 2015. The χ² test or Mann-Whitney U test was used to estimate the relationships between the CONUT score and clinical characteristics as well as short-term outcomes, while the Cox proportional hazard model was used to estimate long-term outcomes. Survival curves were estimated by using the Kaplan-Meier method and log-rank test. Results: The proportion of moderate or severe malnutrition among all patients was not significantly changed from pretreatment (13.5%) to pre-operation (11.7%) but increased dramatically postoperatively (47.5%). The pretreatment CONUT-high score (≥4) was significantly associated with older age (P=0.010), deeper tumor invasion (P=0.025), and lower pathological complete response rate (CONUT-high vs. CONUT-low: 1.2% vs. 6.6%, P=0.107). Pretreatment CONUT-high score patients had worse progression-free survival (P=0.032) and overall survival (OS) (P=0.026). Adjusted for pathologic node status, the pretreatment CONUT-high score was strongly associated with worse OS in pathologic node-positive patients (P=0.039). Conclusions: The pretreatment CONUT score might be a straightforward index for immune-nutritional status assessment, while being a reliable prognostic indicator in patients with advanced GC receiving neoadjuvant chemotherapy and curative gastrectomy. Moreover, lower pretreatment CONUT scores might indicate better chemotherapy responses.

• Investigative Magnetic Resonance Imaging
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• 제22권3호
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• pp.158-167
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• 2018

Purpose: To investigate the surgical, perfusion, and molecular characteristics of glioblastomas which influence long-term survival after treatment, and to explore the association between MR perfusion parameters and the presence of MGMT methylation and 1p/19q deletions. Materials and Methods: This retrospective study was approved by our institutional review board. A total 43 patients were included, all with pathologic diagnosis of glioblastoma with known MGMT methylation and 1p/19q deletion statuses. We divided these patients into long-term (${\geq}60\;months$, n = 7) and short-term (< 60 months, n = 36) survivors, then compared surgical extent, molecular status, and rCBV parameters between the two groups using Fisher's exact test or Mann-Whitney test. The rCBV parameters were analyzed according to the presence of MGMT methylation and 1p/19q deletions. We investigated the relationship between the mean rCBV and overall survival using linear correlation. Multivariable linear regression was performed in order to find the variables related to overall survival. Results: Long-term survivors (100% [7 of 7]) demonstrated a greater percentage of gross total or near total resection than short-term survivors (54.5% [18 of 33]). A higher prevalence of 1p/19q deletions was also noted among the long-term survivors (42.9% [3 of 7]) than the short-term survivors (0.0% [0 of 36]). The rCBV parameters did not differ between the long-term and short-term survivors. The rCBV values were marginally lower in patients with MGMT methylation and 1p/19q deletions. Despite no correlation found between overall survival and rCBV in the whole group, the short-term survivor group showed negative correlation ($R^2=0.181$, P = 0.025). Multivariable linear regression revealed that surgical extent and 1p/19q deletions, but not rCBV values, were associated with prolonged overall survival. Conclusion: While preoperative rCBV and 1p/19q deletion status are related to each other, only surgical extent and the presence of 1p/19q deletion in GBM patients may predict long-term survival.

• Asian Pacific Journal of Cancer Prevention
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• 제14권7호
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• pp.4157-4160
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• 2013

Objectives: Understanding the situation of cancer awareness which doctors give to patients might lead to prognostic prediction in cases of of colorectal cancer (CRC). Methods: Subsets of 10,779 CRC patients were used to screen the risk factors from the Cancer Registry in Pudong New Area in cancer awareness, age, TNM stage, and gender. Survival of the patients was calculated by the Kaplan-Meier method and assessed by Cox regression analysis. The views of cancer awareness in doctors and patients were surveyed by telephone or household. Results: After a median observation time of 1,616 days (ranging from 0 to 4,083 days) of 10,779 available patients, 2,596 of the 4,561 patients with cancer awareness survived, whereas 2,258 of the 5,469 patients without cancer awareness and 406 of the 749 patients without information on cancer awareness died of the disease. All-cause and cancer-specific survival were poorer for the patients without cancer awareness than those with (P < 0.001 for each, log-rank test). Cox multivariate regression analysis showed that cancer concealment cases had significantly lower cancer-specific survival (hazard ratio (HR) = 1.299; 95 % confidence interval (CI): 1.200-1.407)and all-cause survival (HR = 1.324; 95 % CI: 1.227-1.428). Furthermore, attitudes of cancer awareness between doctors and patients were significantly different (P < 0.001). Conclusion: Cancer concealment, not only late-stage tumor and age, is associated with a poor survival of CRC patients.

• 한국응용곤충학회지
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• 제53권3호
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• pp.311-315
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• 2014

꽃매미는 약충과 성충이 무리지어 식물체 흡즙하거나 그 과정에서 감로를 배출하여 그을음병을 유발시킴으로서 포도 등에 피해를 주는 외래해충이다. 본 연구는 경기도내 주요 포도 재배지에서 꽃매미의 발생특성과 월동기 극저온이 꽃매미 월동난괴의 생존율에 미치는 영향을 분석하기 위해 2010년부터 2013년까지 수행하였다. 경기지역에서 꽃매미 월동난괴는 5월 상순부터 부화하기 시작하여 5월 중순에 가장 높은 약충 밀도를 보이고 있으며 7월 하순부터 출현한 성충은 11월 상순까지 산란하는 특성을 보였다. 동절기 온도가 꽃매미 월동난괴 생존율에 큰 영향을 미쳤으며, 1월 중 극저온 출현일수(x)와 생존율(y) 간 관계를 선형회귀모형으로 분석하였다. 그 결과 예측치와 실측치 간 잔차자승합(residual sum of square) 가장 낮은 모형은 $-11^{\circ}C$를 임계 극저온으로 취급한 y = -1.0486 x + 94.496 ($R^2=0.7067$) 이었다. 본 연구 결과는 월동 중 꽃매미 알의 생존율 예측과 봄철 발생시기 정보를 제공함으로써 꽃매미 관리전략 수립에 유용하게 활용될 수 있을 것으로 판단된다.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.231-243
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• 2021

In Recent years the way we analyze the breast cancer has changed dramatically. Breast cancer is the most common and complex disease diagnosed among women. There are several subtypes of breast cancer and many options are there for the treatment. The most important is to educate the patients. As the research continues to expand, the understanding of the disease and its current treatments types, the researchers are constantly being updated with new researching techniques. Breast cancer survival rates have been increased with the use of new advanced treatments, largely due to the factors such as earlier detection, a new personalized approach to treatment and a better understanding of the disease. Many machine learning classification models have been adopted and modified to diagnose the breast cancer disease. In order to enhance the performance of classification model, our research proposes a model using A Hybrid Modified K-Means Clustering with Modified SVM (Support Vector Machine) Machine learning algorithm to create a new method which can highly improve the performance and prediction. The proposed Machine Learning model is to improve the performance of machine learning classifier. The Proposed Model rectifies the irregularity in the dataset and they can create a new high quality dataset with high accuracy performance and prediction. The recognized datasets Wisconsin Diagnostic Breast Cancer (WDBC) Dataset have been used to perform our research. Using the Wisconsin Diagnostic Breast Cancer (WDBC) Dataset, We have created our Model that can help to diagnose the patients and predict the probability of the breast cancer. A few machine learning classifiers will be explored in this research and compared with our Proposed Model "A Hybrid Modified K-Means with Modified SVM Machine Learning Algorithm to Enhance the Cancer Prediction" to implement and evaluated. Our research results show that our Proposed Model has a significant performance compared to other previous research and with high accuracy level of 99% which will enhance the Cancer Prediction.

• Korean Journal of Radiology
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• 제24권7호
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• pp.626-639
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• 2023

Objective: To investigate the association of clinical, pathologic, and magnetic resonance imaging (MRI) variables with progressive disease (PD) during neoadjuvant chemotherapy (NAC) and distant metastasis-free survival (DMFS) in patients with triple-negative breast cancer (TNBC). Materials and Methods: This single-center retrospective study included 252 women with TNBC who underwent NAC between 2010 and 2019. Clinical, pathologic, and treatment data were collected. Two radiologists analyzed the pre-NAC MRI. After random allocation to the development and validation sets in a 2:1 ratio, we developed models to predict PD and DMFS using logistic regression and Cox proportional hazard regression, respectively, and validated them. Results: Among the 252 patients (age, 48.3 ± 10.7 years; 168 in the development set; 84 in the validation set), PD was occurred in 17 patients and 9 patients in the development and validation sets, respectively. In the clinical-pathologic-MRI model, the metaplastic histology (odds ratio [OR], 8.0; P = 0.032), Ki-67 index (OR, 1.02; P = 0.044), and subcutaneous edema (OR, 30.6; P = 0.004) were independently associated with PD in the development set. The clinical-pathologic-MRI model showed a higher area under the receiver-operating characteristic curve (AUC) than the clinical-pathologic model (AUC: 0.69 vs. 0.54; P = 0.017) for predicting PD in the validation set. Distant metastases occurred in 49 patients and 18 patients in the development and validation sets, respectively. Residual disease in both the breast and lymph nodes (hazard ratio [HR], 6.0; P = 0.005) and the presence of lymphovascular invasion (HR, 3.3; P < 0.001) were independently associated with DMFS. The model consisting of these pathologic variables showed a Harrell's C-index of 0.86 in the validation set. Conclusion: The clinical-pathologic-MRI model, which considered subcutaneous edema observed using MRI, performed better than the clinical-pathologic model for predicting PD. However, MRI did not independently contribute to the prediction of DMFS.

• Radiation Oncology Journal
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• 제30권2호
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• pp.70-77
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• 2012

Purpose: To evaluate the patterns of tumor shape and to compare tumor volume derived from simple diameter-based ellipsoid measurement with that derived from tracing the entire tumor contour using region of interest (ROI)-based 3D volumetry with respect to the prediction outcome in cervical cancer patients treated with concurrent chemotherapy and radiotherapy. Materials and Methods: Magnetic resonance imaging was performed in 98 patients with cervical cancer (stage IB-IIIB). The tumor shape was classified into two categories: ellipsoid and non-ellipsoid shape. ROI-based volumetry was derived from each magnetic resonance slice on the work station. For the diameter-based surrogate "ellipsoid volume," the three orthogonal diameters were measured to calculate volume as an ellipsoid. Results: The more than half of tumor (55.1%) had a non-ellipsoid configuration. The predictions for outcome were consistent between two volume groups, with overall survival of 93.6% and 87.7% for small tumor (<20 mL), 62.9% and 69.1% for intermediate-size tumor (20-39 mL), and 14.5% and 16.7% for large tumors (${\geq}$40 mL) using ROI and diameter based measurement, respectively. Disease-free survival was 93.8% and 90.6% for small tumor, 54.3% and 62.7% for intermediate-size tumor, and 13.7% and 10.3% for large tumor using ROI and diameter based method, respectively. Differences in outcome between size groups were statistically significant, and the differences in outcome predicted by the tumor volume by two different methods. Conclusion: Our data suggested that large numbers of cervical cancers are not ellipsoid. However, simple diameter-based tumor volume measurement appears to be useful in comparison with ROI-based volumetry for predicting outcome in cervical cancer patients.

• 대한토목학회논문집
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• 제32권5D호
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• pp.453-461
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• 2012

장비나 설비의 경제성 분석을 위해 실시되는 수명분석의 목적은 현 자산의 미래 폐기 지표를 예측하여, 예측자료에 의거한 여러 경영전략을 수립하여 활용하는 데 있다. 본 연구에서는 1) 생존곡선을 사용하여 건설장비의 평균수명, 기대수명, 예측수명을 구하는 방법과 생존곡선에 의한 수명결정방법을 분석하여 제시하였고 2) 수익과 비용에 의한 수명결정 모델을 제안하고 이를 검증해 보았다. 연구 결과, 동일한 장비라고 하더라도 비용, 수익, 초기투자비에 따라 경제수명이 다르게 나타날 수 있음을 알게 되었다. 본 연구에서 제안한 건설장비 수명결정 모델은, 장비의 개별적 경영상황을 반영할 수 있는 수명 결정 모델로서, 회사경영합리화를 위해 활용될 수 있을 것이다.

• Korean Journal of Radiology
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• 제22권9호
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• pp.1514-1524
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• 2021

Objective: To develop a radiomics risk score based on dynamic contrast-enhanced (DCE) MRI for prognosis prediction in patients with glioblastoma. Materials and Methods: One hundred and fifty patients (92 male [61.3%]; mean age ± standard deviation, 60.5 ± 13.5 years) with glioblastoma who underwent preoperative MRI were enrolled in the study. Six hundred and forty-two radiomic features were extracted from volume transfer constant (K^trans), fractional volume of vascular plasma space (V_p), and fractional volume of extravascular extracellular space (V_e) maps of DCE MRI, wherein the regions of interest were based on both T1-weighted contrast-enhancing areas and non-enhancing T2 hyperintense areas. Using feature selection algorithms, salient radiomic features were selected from the 642 features. Next, a radiomics risk score was developed using a weighted combination of the selected features in the discovery set (n = 105); the risk score was validated in the validation set (n = 45) by investigating the difference in prognosis between the "radiomics risk score" groups. Finally, multivariable Cox regression analysis for progression-free survival was performed using the radiomics risk score and clinical variables as covariates. Results: 16 radiomic features obtained from non-enhancing T2 hyperintense areas were selected among the 642 features identified. The radiomics risk score was used to stratify high- and low-risk groups in both the discovery and validation sets (both p < 0.001 by the log-rank test). The radiomics risk score and presence of isocitrate dehydrogenase (IDH) mutation showed independent associations with progression-free survival in opposite directions (hazard ratio, 3.56; p = 0.004 and hazard ratio, 0.34; p = 0.022, respectively). Conclusion: We developed and validated the "radiomics risk score" from the features of DCE MRI based on non-enhancing T2 hyperintense areas for risk stratification of patients with glioblastoma. It was associated with progression-free survival independently of IDH mutation status.