• Gut and Liver
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• 제12권6호
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• pp.714-721
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• 2018

Background/Aims: Recently reported prognostic models for primary biliary cholangitis (PBC) have been shown to be effective in Western populations but have not been well-validated in Asian patients. This study aimed to compare the performance of prognostic models in Korean patients and to investigate whether inflammation-based scores can further help in prognosis prediction. Methods: This study included 271 consecutive patients diagnosed with PBC in Korea. The following prognostic models were evaluated: the Barcelona model, the Paris-I/II model, the Rotterdam criteria, the GLOBE score and the UK-PBC score. The neutrophil-to-lymphocyte ratio (NLR) was analyzed with reference to its association with prognosis. Results: For predicting liver transplant or death at the 5-year and 10-year follow-up examinations, the UK-PBC score (areas under the receiver operating characteristic curve [AUCs], 0.88 and 0.82) and GLOBE score (AUCs, 0.85 and 0.83) were significantly more accurate in predicting prognosis than the other scoring systems (all p<0.05). There was no significant difference between the performance of the UK-PBC and GLOBE scores. In addition to the prognostic models, a high NLR (>2.46) at baseline was an independent predictor of reduced transplant-free survival in the multivariate analysis (adjusted hazard ratio, 3.74; p<0.01). When the NLR was applied to the prognostic models, it significantly differentiated the prognosis of patients. Conclusions: The UK-PBC and GLOBE scores showed good prognostic performance in Korean patients with PBC. In addition, a high NLR was associated with a poorer prognosis. Including the NLR in prognostic models may further help to stratify patients with PBC.

• Nuclear Engineering and Technology
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• 제49권5호
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• pp.914-919
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• 2017

While industry understands the importance of keeping equipment operational and well maintained, the importance of tracking maintenance information in reliability models is often overlooked. Prognostic models can be used to predict the failure times of critical equipment, but more often than not, these models assume that all maintenance actions are the same or do not consider maintenance at all. This study investigates the influence of integrating maintenance information on prognostic model prediction accuracy. By incorporating maintenance information to develop maintenance-dependent prognostic models, prediction accuracy was improved by more than 40% compared with traditional maintenance-independent models. This study acts as a proof of concept, showing the importance of utilizing maintenance information in modern prognostics for industrial equipment.

• Asian Pacific Journal of Cancer Prevention
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• 제17권5호
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• pp.2369-2374
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• 2016

Background: Differentiated thyroid cancer (DTC) is a cancer group that shares molecular and cellular origin but shows different clinical courses and prognoses. Several prognostic factors have been reported for predicting recurrence for individual patients. This literature review aimed to evaluate prognostic scores for predicting recurrence of DTC. Materials and Methods: A search of the MEDLINE database for articles published until December 2015 was carried out using the terms "thyroid neoplasms AND (recurrent OR persistent) AND (score OR model OR nomogram)". Studies were eligible for review if they indicated the development of prognostic scoring models, derived from a group of independent prognostic factors, in predicting disease recurrence in DTC patients. Results: Of the 308 articles obtained, five were eligible for evaluation. Two scoring models were developed for DTC including both papillary and follicular carcinoma, one for papillary carcinoma, and the other two for papillary microcarcinoma. The number of patients included in the score development cohort ranged from 59 to 1,669. The number of evaluated potential prognostic factors ranged from 4 to 25. Tumor-related factors were the most common factors included in the final scores, with cervical lymph node metastases being the most common. Only two studies showed internal validation of the derived score. Conclusions: There is a paucity of prognostic scores for predicting disease recurrence in patients with DTC, in particular for follicular thyroid carcinoma. Several limitations of the created scores were found. Performance of the scores has not been adequately studied. Comprehensive validation in multiple cohorts is recommended before widespread use.

• Annals of Laboratory Medicine
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• 제38권6호
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• pp.495-502
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• 2018

Background: Molecular genetic abnormalities are observed in over 90% of chronic myelomonocytic leukemia (CMML) cases. Recently, several studies have demonstrated the negative prognostic impact of ASXL1 mutations in CMML patients. We evaluated the prognostic impact of ASXL1 mutations and compared five CMML prognostic models in Korean patients with CMML. Methods: We analyzed data from 36 of 57 patients diagnosed as having CMML from January 2000 to March 2016. ASXL1 mutation analysis was performed by direct sequencing, and the clinical and laboratory features of patients were compared according to ASXL1 mutation status. Results: ASXL1 mutations were detected in 18 patients (50%). There were no significant differences between the clinical and laboratory characteristics of ASXL1-mutated ($ASXL1^+$) CMML and ASXL1-nonmutated ($ASXL1^-$) CMML patients (all P >0.05). During the median follow-up of 14 months (range, 0-111 months), the overall survival (OS) of $ASXL1^+$ CMML patients was significantly inferior to that of $ASXL1^-$ CMML patients with a median survival of 11 months and 19 months, respectively (log-rank P =0.049). An evaluation of OS according to the prognostic models demonstrated inferior survival in patients with a higher risk category according to the Mayo molecular model (log-rank P =0.001); the other scoring systems did not demonstrate a significant association with survival. Conclusions: We demonstrated that ASXL1 mutations, occurring in half of the Korean CMML patients examined, were associated with inferior survival. ASXL1 mutation status needs to be determined for risk stratification in CMML.

• Journal of Gastric Cancer
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• 제21권3호
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• pp.268-278
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• 2021

Purpose: While several prognostic models for the stratification of death risk have been developed for patients with advanced gastric cancer receiving first-line chemotherapy, they have seldom been tested in the Chinese population. This study investigated the performance of these models and identified the optimal tools for Chinese patients. Materials and Methods: Patients diagnosed with metastatic or recurrent gastric adenocarcinoma who received first-line chemotherapy were eligible for inclusion in the validation cohort. Their clinical data and survival outcomes were retrieved and documented. Time-dependent receiver operating characteristic (ROC) and calibration curves were used to evaluate the predictive ability of the models. Kaplan-Meier curves were plotted for patients in different risk groups divided by 7 published stratification tools. Log-rank tests with pairwise comparisons were used to compare survival differences. Results: The analysis included a total of 346 patients with metastatic or recurrent disease. The median overall survival time was 11.9 months. The patients were different into different risk groups according to the prognostic stratification models, which showed variability in distinguishing mortality risk in these patients. The model proposed by Kim et al. showed relative higher predicting abilities compared to the other models, with the highest χ² (25.8) value in log-rank tests across subgroups, and areas under the curve values at 6, 12, and 24 months of 0.65 (95% confidence interval [CI]: 0.59-0.72), 0.60 (0.54-0.65), and 0.63 (0.56-0.69), respectively. Conclusions: Among existing prognostic tools, the models constructed by Kim et al., which incorporated performance status score, neutrophil-to-lymphocyte ratio, alkaline phosphatase, albumin, and tumor differentiation, were more effective in stratifying Chinese patients with gastric cancer receiving first-line chemotherapy.

• Journal of Gastric Cancer
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• 제17권2호
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• pp.132-144
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• 2017

Purpose: To identify baseline prognostic factors for survival in patients with disease progression, during or after chemotherapy for the treatment of advanced gastric or gastroesophageal junction (GEJ) cancer. Materials and Methods: We pooled data from patients randomized between 2009 and 2012 in 2 phase III, global double-blind studies of ramucirumab for the treatment of advanced gastric or GEJ adenocarcinoma following disease progression on first-line platinum- and/or fluoropyrimidine-containing therapy (REGARD and RAINBOW). Forty-one key baseline clinical and laboratory factors common in both studies were examined. Model building started with covariate screening using univariate Cox models (significance level=0.05). A stepwise multivariable Cox model identified the final prognostic factors (entry+exit significance level=0.01). Cox models were stratified by treatment and geographic region. The process was repeated to identify baseline prognostic quality of life (QoL) parameters. Results: Of 1,020 randomized patients, 953 (93%) patients without any missing covariates were included in the analysis. We identified 12 independent prognostic factors of poor survival: 1) peritoneal metastases; 2) Eastern Cooperative Oncology Group (ECOG) performance score 1; 3) the presence of a primary tumor; 4) time to progression since prior therapy <6 months; 5) poor/unknown tumor differentiation; abnormally low blood levels of 6) albumin, 7) sodium, and/or 8) lymphocytes; and abnormally high blood levels of 9) neutrophils, 10) aspartate aminotransferase (AST), 11) alkaline phosphatase (ALP), and/or 12) lactate dehydrogenase (LDH). Factors were used to devise a 4-tier prognostic index (median overall survival [OS] by risk [months]: high=3.4, moderate=6.4, medium=9.9, and low=14.5; Harrell's C-index=0.66; 95% confidence interval [CI], 0.64-0.68). Addition of QoL to the model identified patient-reported appetite loss as an independent prognostic factor. Conclusions: The identified prognostic factors and the reported prognostic index may help clinical decision-making, patient stratification, and planning of future clinical studies.

• 대기
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• 제29권2호
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• pp.227-239
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• 2019

This paper reviews various bulk-type cloud microphysics parameterizations (BCMPs). BCMP, predicting the moments of size distribution of hydrometeors, parameterizes the grid-resolved cloud and precipitation processes in atmospheric models. The generalized gamma distribution is mainly applied to represent the hydrometeors size distribution in BCMPs. BCMP can be divided in three different methods such as single-moment, double-moment, and triple-moment approaches depending on the number of prognostic variables. Single-moment approach only predicts the hydrometeors mixing ratio. Double-moment approach predicts not only the hydrometeors mixing ratio but also the hydrometeors number concentration. Triple-moment approach predicts the dispersion parameter of hydrometeors size distribution through the prognostic reflectivity, together with the number concentrations and mixing ratios of hydrometeors. Triple-moment approach is the most time expensive method because it has the most number of prognostic variables. However, this approach can allow more flexibility in representing hydrometeors size distribution relative to single-moment and double-moment approaches. At the early stage of the development of BMCPs, warm rain processes were only included. Ice-phase categories such as cloud ice, snow, graupel, and hail were included in BCMPs with prescribed properties for densities and sedimentation velocities of ice-phase hydrometeors since 1980s. Recently, to avoid fixed properties for ice-phase hydrometeors and ad-hoc category conversion, the new approach was proposed in which rimed ice and deposition ice mixing ratios are predicted with total ice number concentration and volume.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제8권10호
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• pp.397-402
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• 2019

암 환자에게 적절한 치료계획을 제공하기 위해 암의 진행양상 또는 환자의 생존 기간 등에 해당하는 환자의 예후를 정확히 예측하는 것은 생물정보학 분야에서 다루는 중요한 도전 과제 중 하나이다. 많은 연구에서 암 환자의 유전자 발현량 데이터를 이용하여 환자의 예후를 예측하는 기계학습 모델들이 많이 제안되어 오고 있다. 유전자 발현량 데이터는 약 17,000개의 유전자에 대한 수치값을 갖는 고차원의 수치형 자료이기에, 기존의 연구들은 특징 선택 또는 차원 축소 전략을 이용하여 예측 모델의 성능 향상을 도모하였다. 그러나 이러한 접근법은 특징 선택과 예측 모델의 훈련이 분리되어 있어서, 기계학습 모델은 선별된 유전자들이 생물학적으로 어떤 관계가 있는지 알기가 어렵다. 본 연구에서는 유전자 발현량 데이터를 이미지 형태로 변환하여 예후 예측이 효과적으로 특징 선택 및 예후 예측을 수행할 수 있는 기법을 제안한다. 유전자들 사이의 생물학적 상호작용 관계를 유전자 발현량 데이터에 통합하기 위해 Node2Vec을 활용하였으며, 2차원 이미지로 표현된 발현량 데이터를 효과적으로 학습할 수 있도록 합성곱 신경망 모델을 사용하였다. 제안하는 모델의 성능은 이중 교차검증을 통해 평가되었고, 유전자 발현량 데이터를 그대로 이용하는 기계학습모델보다 우월한 예후 예측 정확도를 가지는 것이 확인되었다. Node2Vec을 이용한 유전자 발현량의 새로운 이미지 표현법은 특징 선택으로 인한 정보의 손실이 없어 예측 모델의 성능을 높일 수 있으며, 이러한 접근법이 개인 맞춤형 의학의 발전에 이바지할 것으로 기대한다.

• Asian Pacific Journal of Cancer Prevention
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• 제15권23호
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• pp.10231-10236
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• 2015

This study aimed to evaluate the prevalence of preoperative thrombocytosis and its prognostic significance in Thai patients with endometrial cancer. We retrospectively reviewed the medical records of 238 cases who had undergone surgical staging procedures between January 2005 and December 2008. Associations between clinicopathological variables and preoperative platelet counts were analyzed using Pearson's chi square or two-tailed Fisher's exact tests. Survival analysis was performed with Kaplan-Meier estimates. Univariate and Cox-regression models were used to evaluate the prognostic impact of various factors including platelet count in terms of disease-free survival and overall survival. The mean preoperative platelet count was $315,437/{\mu}L$ (SD $100,167/{\mu}L$). Patients who had advanced stage, adnexal involvement, lymph node metastasis, and positive peritoneal cytology had significantly higher mean preoperative platelet counts when compared with those who had not. We found thrombocytosis (platelet count greater than $400,000/{\mu}L$) in 18.1% of our patients with endometrial cancer. These had significant higher rates of advanced stage, cervical involvement, adnexal involvement, positive peritoneal cytology, and lymph node involvement than patients with a normal pretreatment platelet count. The 5-year disease-free survival and overall survival were significantly lower in patients who had thrombocytosis compared with those who had not (67.4% vs. 85.1%, p=0.001 and 86.0% vs. 94.9%, p=0.034, respectively). Thrombocytosis was shown to be a prognostic factor in the univariate but not the multivariate analysis. In conclusion, presence of thrombocytosis is not uncommon in endometrial cancer and may reflect unfavorable prognostic factors but its prognostic impact on survival needs to be clarified in further studies.

• Asian Pacific Journal of Cancer Prevention
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• 제13권7호
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• pp.3187-3190
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• 2012

This study evaluated the relationship between pretreatment hemoglobin (Hb) and prognostic factors in Thai patients with endometrial cancer. Medical records of 228 patients who had undergone surgery between January 2005 and December 2007 were retrospectively reviewed. Associations between clinicopathological variables and pretreatment Hb levels were described using Pearson's chi square test or two-tailed Fisher's exact test. Survival analysis was performed with Kaplan-Meier estimates. Univariate and Cox-regression models were used to evaluate the prognostic impact of various factors, including Hb levels, in term of disease-free survival. The median duration of follow-up was 38.2 months. Eighty-nine patients (39%) had a preoperative Hb level of <12 g/dL, these having significantly higher rates of non-endometrioid histology, advanced FIGO stage, lymphovascular space invasion, cervical involvement, adnexal involvement, positive peritoneal cytology, and lymph node involvement than patients with Hb ${\geq}12$ g/dL. The 5-year disease-free and overall survival were significantly lower in patients with pretreatment Hb levels <12 g/dL compared with those with Hb ${\geq}12$ g/dL (79.3% vs. 89.2%, p=0.044 and 87.6% vs. 99.3%, p<0.001, respectively). In the multivariate analysis only histology, myometrial invasion, and lymphovascular invasion proved to be independent prognostic factors, whereas tumor grading, stage, cervical involvement, adnexal involvement, positive peritoneal cytology, lymph node involvement, and low Hb were not. In conclusion, presence of anemia before treatment may reflect poor prognostic factors in patients with endometrial cancer and low pretreatment hemoglobin level may have a prognostic impact on clinical outcome.