• Asian Pacific Journal of Cancer Prevention
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• 제15권18호
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• pp.7835-7838
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• 2014

Background: Neuroendocrine tumors have widespread and different clinical presentations and prognoses. This study was conducted to assess their survival time and prognostic factors in Iran. Materials and Methods: In a retrospective cohort study, 189 patients diagnosed of having neuroendocrine carcinoma were chosen. The tumor and clinical characteristics of the patients were modeled with a Cox proportional hazard approach. Survival was assessed using Kaplan-Meyer curves. Results: Crude median survival time was 30 months. Women survived longer than men (the median survival time for women was 40 and for men was 24 months). Age (<60 vs >60 years old with hazard ratio (HR) of 2.43, 95% CI 1.3-4.5), primary pathology report (carcinoid vs. others with HR 5.85 cm, 95% CI 2.4-14.3), tumor size cm (for 5-10, HR of 3.1, 95% CI 1.6 and for >10 HR of 8.2, 95% with 95% CI 3.1-21.9), and chemotherapy with single drug (taking vs. not taking with a HR 2.2, 95% CI 1.1-4.8) had significant effects on overall survival of patients. Conclusions: Survival time in patients with neuroendocrine carcinomas is related to demographics, clinical characteristics, tumor histology, and subtype specific treatment.

• Asian Pacific Journal of Cancer Prevention
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• 제15권1호
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• pp.185-190
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• 2014

Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high-lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness-associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

• 한국환경보건학회지
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• 제37권5호
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• pp.342-347
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• 2011

Healthy worker effect (HWE) refers to the consistent tendency for actively employed individuals to have a more favorable mortality experience than the population at large. Although HWE has been well known since the 1970s, only a few studies in occupational epidemiology have attempted to fully define and evaluate HWE. HWE can be separated into effects on the initial hiring into the workforce (healthy worker hire effect) and those on continuing employment (healthy worker survival effect). In this review, we summarize the methods for minimizingor adjusting for the healthy worker effect available in occupational epidemiology. It is noteworthy that healthy worker survival effect appears complicated, considering that employment status plays simultaneous roles as a counfounding variable and intermediate variable, whereas healthy worker hire effect may be adjusted by incorporating health status at baseline into the statistical model. In addition, two retrospective cohort studies for workers in the semiconductor industry and Vietnam veterans in Korea, respectively, were introduced, and their results were explained in terms of healthy worker effect.

• Asian Pacific Journal of Cancer Prevention
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• 제15권14호
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• pp.5883-5888
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• 2014

Background: Breast cancer is the most common cancers in female populations. The exact cause is not known, but is most likely to be a combination of genetic and environmental factors. Log-logistic model (LLM) is applied as a statistical method for predicting survival and it influencing factors. In recent decades, artificial neural network (ANN) models have been increasingly applied to predict survival data. The present research was conducted to compare log-logistic regression and artificial neural network models in prediction of breast cancer (BC) survival. Materials and Methods: A historical cohort study was established with 104 patients suffering from BC from 1997 to 2005. To compare the ANN and LLM in our setting, we used the estimated areas under the receiver-operating characteristic (ROC) curve (AUC) and integrated AUC (iAUC). The data were analyzed using R statistical software. Results: The AUC for the first, second and third years after diagnosis are 0.918, 0.780 and 0.800 in ANN, and 0.834, 0.733 and 0.616 in LLM, respectively. The mean AUC for ANN was statistically higher than that of the LLM (0.845 vs. 0.744). Hence, this study showed a significant difference between the performance in terms of prediction by ANN and LLM. Conclusions: This study demonstrated that the ability of prediction with ANN was higher than with the LLM model. Thus, the use of ANN method for prediction of survival in field of breast cancer is suggested.

• Journal of Gastric Cancer
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• 제19권4호
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• pp.393-407
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• 2019

Purpose: To identify the potential therapeutic role of postoperative radiotherapy (RT) in patients with locally advanced (stage II and stage III) gastric signet ring cell carcinoma (SRC). Materials and methods: Patients with locally advanced gastric SRC from the Surveillance, Epidemiology, and End Results program database between 2004 and 2012 were included in our study. Univariate and multivariate Cox proportional models were performed, and survival curves were generated to evaluate the prognostic effect of postoperative RT and surgery alone on SRC patients. Propensity score matching (PSM) was used to avoid selection bias among the study cohorts. Results: We found that patients with postoperative RT had better probability of survival compared with those who did not receive RT (overall survival [OS], P<0.001; cancer-specific survival [CSS], P<0.001). After PSM, analysis of both overall and CSS showed that patients who underwent postoperative RT had better prognosis than those receiving surgery alone in the matched cohort (OS, P=0.00079; CSS, P=0.0036). Multivariate Cox proportional model indicated that postoperative RT had better effect on prognosis compared with surgery alone with respect to both overall (hazard ratio [HR], 0.716; 95% confidence interval [95% CI], 0.590-0.87; P=0.001) and CSS (HR, 0.713; 95% CI, 0.570-0.890; P=0.003). Conclusions: Postoperative RT had better prognosis compared with surgery alone for both overall and CSS for patients with locally advanced gastric SRC.

• 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.

• 한국시스템다이내믹스연구
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• 제7권2호
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• pp.97-120
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• 2006

This paper deals with the extension of and discussion on the System Dynamics model (Jeong & Jeon, 2005) of river crabs in Korea. The previous model has been elaborated to empirically search for the optimal restoration and harvest rates of crabs in the Imjin River, on the basis of theoretical models of population dynamics in the field of bio-mathematics and environmental economics. In this paper, the authors tries to couple a series of new feedback loops related to density restrictions and cannibalistic behaviors with a stage-structured model of the crab ecosystem, and also to endogenize the parameter of baby crabs' survival that is caused by water quality improvement and income increase. Through these extensions and relaxations, the authors are able to argue about the strategic decision of the optimal rates additional considerations as well as the properties of the integrated system that was not covered in the previous paper.

• Asian Pacific Journal of Cancer Prevention
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• 제15권23호
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• pp.10505-10508
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• 2015

Background: Breast cancer is an important cause of death among women. One way of classifying different forms of breast cancer is by molecular features, usually in terms of the four subtypes: luminal A, luminal B, HER2-enriched, and triple negative. Objectives: This study aimed to investigate the association between molecular subtypes and survival among breast cancer patients treated with radiotherapy. Materials and Methods: A retrospective cohort study was conducted. The subjects were 272 breast cancer patients who had received treatment in the radiotherapy unit at Srinagarind Hospital, Thailand, between 1 January, 1999, and 31 May, 2009. The end of the study was 1 June, 2014. Overall survival was defined as the time elapsing between initial registration at the radiotherapy unit and death or the end of the study. Survival curves were estimated by the Kaplan-Meier method, and a multivariate analysis was performed using Cox's proportional hazard regression model. Results: The patient mean age was $47.5{\pm}10.4$ at the time of diagnosis. Of the 272 patients, 146 (53.7%) were classified as luminal A, 12 (4.4%) as luminal B, 30 (11.0%) as HER2-enriched, and 84 (30.9%) as triple negative. The overall survival rates at 1, 3 and 5 years were 87.1%, 68.4% and 59.2%, respectively. According to molecular subtypes, HER2-enriched patients had the lowest 5-year survival rate (30.0 %, 95%CI: 15.02-46.55). The median follow-up time was 8.37 years. In the Cox model analysis a higher risk of death was found for patients with HER2-enriched ($HR_{adj}=3.34$, 95%CI:1.96-5.67), triple negative ($HR_{adj}=2.17$, 95%CI: 1.44-3.27), and stage IIlB ($HR_{adj}=2.20$, 95%CI: 1.16-4.17) cancers. Conclusions: The worst survival rates were among patients classified as HER2-enriched, triple negative and at stage IIIB. Early detection and an advanced treatment modality are needed to help these patients.

• 한국간담췌외과학회지
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• 제27권1호
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• pp.28-39
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• 2023

We aimed to compare resection and survival outcomes of neoadjuvant chemoradiotherapy (CRT) and immediate surgery in patients with resectable pancreatic cancer (RPC) or borderline resectable pancreatic cancer (BRPC). In compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement standards, a systematic review of randomized controlled trials (RCTs) was conducted. Random effects modeling was applied to calculate pooled outcome data. Likelihood of type 1 or 2 errors in the meta-analysis model was assessed by trial sequential analysis. A total of 400 patients from four RCTs were included. When RPC and BRPC were analyzed together, neoadjuvant CRT resulted in a higher R0 resection rate (risk ratio [RR]: 1.55, p = 0.004), longer overall survival (mean difference [MD]: 3.75 years, p = 0.009) but lower overall resection rate (RR: 0.83, p = 0.008) compared with immediate surgery. When RPC and BRPC were analyzed separately, neoadjuvant CRT improved R0 resection rate (RR: 3.72, p = 0.004) and overall survival (MD: 6.64, p = 0.004) of patients with BRPC. However, it did not improve R0 resection rate (RR: 1.18, p = 0.13) or overall survival (MD: 0.94, p = 0.57) of patients with RPC. Neoadjuvant CRT might be beneficial for patients with BRPC, but not for patients with RPC. Nevertheless, the best available evidence does not include contemporary chemotherapy regimens. Patients with RPC and those with BRPC should not be combined in the same cohort in future studies.

• Korean Journal of Radiology
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• 제22권2호
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• pp.213-224
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• 2021

Objective: Clinical outcomes of patients who undergo transarterial chemoembolization (TACE) for single small hepatocellular carcinoma (HCC) are not consistent, and may differ based on certain imaging findings. This retrospective study was aimed at determining the efficacy of pre-TACE CT or MR imaging findings in predicting survival outcomes in patients with small HCC upon being treated with TACE. Besides, the study proposed to build a risk prediction model for these patients. Materials and Methods: Altogether, 750 patients with functionally good hepatic reserve who received TACE as the first-line treatment for single small HCC between 2004 and 2014 were included in the study. These patients were randomly assigned into training (n = 525) and validation (n = 225) sets. Results: According to the results of a multivariable Cox analysis, three pre-TACE imaging findings (tumor margin, tumor location, enhancement pattern) and two clinical factors (age, serum albumin level) were selected and scored to create predictive models for overall, local tumor progression (LTP)-free, and progression-free survival in the training set. The median overall survival time in the validation set were 137.5 months, 76.1 months, and 44.0 months for low-, intermediate-, and high-risk groups, respectively (p < 0.001). Time-dependent receiver operating characteristic curves of the predictive models for overall, LTP-free, and progression-free survival applied to the validation cohort showed acceptable areas under the curve values (0.734, 0.802, and 0.775 for overall survival; 0.738, 0.789, and 0.791 for LTP-free survival; and 0.671, 0.733, and 0.694 for progression-free survival at 3, 5, and 10 years, respectively). Conclusion: Pre-TACE CT or MR imaging findings could predict survival outcomes in patients with small HCC upon treatment with TACE. Our predictive models including three imaging predictors could be helpful in prognostication, identification, and selection of suitable candidates for TACE in patients with single small HCC.