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1.
Article in Chinese | WPRIM | ID: wpr-961942

ABSTRACT

ObjectiveTo investigate the distribution and trend of rehabilitation personnel of China Disabled Persons' Federation (CDPF) system and the people with disabilities (PWDs) using geographical gravity model. MethodsBased on ArcGIS and statistical data, the distribution of geographical center of gravity of the rehabilitation personnel of the CDPF system from 2011 to 2021 was analyzed. According to the economic development, the areas were divided into three regions, and the eastern region included eleven provincial units, the central region includes eight provincial units, and the western region included twelve provincial units. ResultsCompared with 2011, rehabilitation staffs per thousand PWDs increased at 107.5% in 2021, 81.1%, 114.2% and 174.1% for the eastern, central, and western regions, respectively; professional staffs increased at 190.5%, 148.8%, 284.6% and 280.6% for the eastern, central, and western regions, respectively; managerial staff increased at 80.0%, 46.8%, 554.3% and 128.1% for the eastern, central, and western regions, respectively. Compared with 2011, the geographical center of gravity of the rehabilitation personnel moved about 330.9 km in 2021, while the geographical center of gravity of the PWDs moved about 169.64 km. ConclusionThe rehabilitation personnel in the CDPF system is the most in the eastern region and least in the western region. The tracks of the geographical center of gravity of the three kind of rehabilitation personnel in the CDPF system are relatively consistent. The rehabilitation personnel in the eastern region are more concentrated than those in the western region, and the density of the PWDs is more westward than that of the rehabilitation personnel, and coordination is not a perfect match yet. It is necessary to strengthen the rehabilitation personnel allocation in the western region, to balance distribution of human resources for rehabilitation of PWDs among regions.

2.
Article in Chinese | WPRIM | ID: wpr-868916

ABSTRACT

Objective:To investigate the definition and influencing factors of early recurrence after resection for synchronous colorectal cancer liver metastases (sCRLM).Methods:Patients with sCRLM in Department of Hepatobiliary Surgery, Cancer Hospital, Chinese Academy of Medical Sciences from December 2008 to December 2016 were included. Restricted cubic spline was used to determine the correlations between the time of recurrence and the long-term prognosis. The univariable and multivariable Cox was performed to measure the feasibility of recurrence within 6 months as the early recurrence. Then apply logistic regression, support vector machine, decision tree, random forest, artificial neural network and XGBoost, these machine learning algorithm to comprehensively rank the importance of every clinicopathological variable to early recurrence, and according to the comprehensively ranks, we introduced variables into the multivariable logistic regression model and observed the receiver operating characteristic curve (ROC) of the logistic regression model, based on the ROC area under curve, Akaike information criterion, and Bayesian information criterion, we identified the best performed variable combination and introduced them into the multivariate logistic regression analysis to confirm the independent risk factors for early recurrence. Subsequently, inverse probability weighting (IPTW) was performed on the therapy-associated independent risk factor to evaluate and validate its influence on the early recurrence of sCRLM patients after reducing the standardized mean difference of all covariates.Results:A total of 228 sCRLM patients who received resection were enrolled and followed up from 2.10 to 108.57 months. There were 142 males and 86 females, aged (55.89±0.67) years old. In 170 (74.6%) patients with recurrence, restricted cube analysis determined that the hazard ratio (HR) of disease free survival (DFS) and overall survival (OS) satisfies a linear relationship ( P<0.05), and Cox analysis indicated that 6 months as the time cutoff for defining early recurrence was feasible ( HR=3.405, 95% CI: 2.098-5.526, P<0.05). Early recurrence was occurred in 93 (40.79%) patients. The survival rate of patients in early recurrence group was significantly lower than that in the late recurrence group ( HR=3.405, 95% CI: 2.098-5.526, P<0.05, and the 5-year survival rate was 14.0% vs 52.0%). Comprehensive analysis of 6 machine learning algorithms identified that the total number of lymph node dissection >22 ( OR=0.258, 95% CI: 0.132-0.506, P<0.05) is an independent protective factor for early recurrence, while the number of liver metastases>3 ( OR=4.715, 95% CI: 2.467-9.011, P<0.05) and postoperative complications ( OR=2.334, 95% CI: 1.269-4.291, P<0.05) are independent risk factors. Finally, the IPTW analysis fully reduced the influence of covariate confounding influence via causal inference to prove lymph node dissection associated with early recurrence (IPTW OR=0.29, P<0.05), benefiting the DFS (IPTW HR=0.4887, P<0.05), but without influence on OS (IPTW HR=0.6951, P>0.05). Conclusion:Six months after sCRLM as the definition of early recurrence, it has significant feasibility. The long-term survival of patients with early recurrence is poor. The independent influencing factors of early recurrence after sCRLM are the total number of lymph node dissection, the number of liver metastases and postoperative complications disease.

3.
Article in Chinese | WPRIM | ID: wpr-865030

ABSTRACT

Objective:To investigate the application value of machine learning algorithms and COX nomogram in the survival prediction of hepatocellular carcinoma (HCC) after resection.Methods:The retrospective and descriptive study was conducted. The clinicopathological data of 375 patients with HCC who underwent radical resection in the Cancer Hospital of Chinese Academy of Medical Sciences and Peking Union Medical College from January 2012 to January 2017 were collected. There were 304 males and 71 females, aged from 21 to 79 years, with a median age of 57 years. According to the random numbers showed in the computer, 375 patients were divided into training dataset consisting of 300 patients and validation dataset consisting of 75 patients, with a ratio of 8∶2. Machine learning algorithms including logistic regression (LR), supporting vector machine (SVM), decision tree (DT), random forest (RF), and artificial neural network (ANN) were used to construct survival prediction models for HCC after resection, so as to identify the optimal machine learning algorithm prediction model. A COX nomogram prediction model for predicting postoperative survival in patients with HCC was also constructed. Comparison of performance for predicting postoperative survival of HCC patients was conducted between the optimal machine learning algorithm prediction model and the COX nomogram prediction model. Observation indicators: (1) analysis of clinicopathological data of patients in the training dataset and validation dataset; (2) follow-up and survival of patients in the training dataset and validation dataset; (3) construction and evaluation of machine learning algorithm prediction models; (4) construction and evaluation of COX nomogram prediction model; (5) evaluation of prediction performance between RF machine learning algorithm prediction model and COX nomogram prediction model. Follow-up was performed using outpatient examination or telephone interview to detect survival of patients up to December 2019 or death. Measurement data with normal distribution were expressed as Mean± SD, and comparison between groups was analyzed by the paired t test. Measurement data with skewed distribution were expressed as M ( P25, P75) or M (range), and comparison between groups was analyzed by the Mann-Whitney U test. Count data were represented as absolute numbers. Comparison between groups was performed using the chi-square test when Tmin ≥5 and N ≥40, using the calibration chi-square test when 1≤ Tmin ≤5 and N ≥40, and using Fisher exact probability when Tmin <1 or N <40. The Kaplan-Meier method was used to calculate survival rate and draw survival curve. The COX proportional hazard model was used for univariate analysis, and variables with P<0.2 were included for the Lasso regression analysis. According to the lambda value, variables affecting prognosis were screened for COX proportional hazard model to perform multivariate analysis. Results:(1) Analysis of clinicopathological data of patients in the training dataset and validation dataset: cases without microvascular invasion or with microvascular invasion, cases without liver cirrhosis or with liver cirrhosis of the training dataset were 292, 8, 105, 195, respectively, versus 69, 6, 37, 38 of the validation dataset, showing significant differences between the two groups ( χ2=4.749, 5.239, P<0.05). (2) Follow-up and survival of patients in the training dataset and validation dataset: all the 375 patients received follow-up. The 300 patients in the training dataset were followed up for 1.1-85.5 months, with a median follow-up time of 50.3 months. Seventy-five patients in the validation dataset were followed up for 1.0-85.7 months, with a median follow-up time of 46.7 months. The postoperative 1-, 3-year overall survival rates of the 375 patients were 91.7%, 79.5%. The postoperative 1-, 3-year overall survival rates of the training dataset were 92.0%, 79.7%, versus 90.7%, 81.9% of the validation dataset, showing no significant difference in postoperative survival between the two groups ( χ2=0.113, P>0.05). (3) Construction and evaluation of machine learning algorithm prediction models. ① Selection of the optimal machine learning algorithm prediction model: according to information divergence of variables for prediction of 3 years postoperative survival of HCC, five machine learning algorithms were used to comprehensively rank the variables of clinicopathological factors of HCC, including LR, SVM, DT, RF, and ANN. The main predictive factors were screened out, as hepatitis B e antigen (HBeAg), surgical procedure, maximum tumor diameter, perioperative blood transfusion, liver capsule invasion, and liver segment Ⅳ invasion. The rank sequence 3, 6, 9, 12, 15, 18, 21, 24, 27, 29 variables of predictive factors were introduced into 5 machine learning algorithms in turn. The results showed that the area under curve (AUC) of the receiver operating charateristic curve of LR, SVM, DT, and RF machine learning algorithm prediction models tended to be stable when 9 variables are introduced. When more than 12 variables were introduced, the AUC of ANN machine learning algorithm prediction model fluctuated significantly, the stability of AUC of LR and SVM machine learning algorithm prediction models continued to improve, and the AUC of RF machine learning algorithm prediction model was nearly 0.990, suggesting RF machine learning algorithm prediction model as the optimal machine learning algorithm prediction model. ② Optimization and evaluation of RF machine learning algorithm prediction model: 29 variables of predictive factors were sequentially introduced into the RF machine learning algorithm to construct the optimal RF machine learning algorithm prediction model in the training dataset. The results showed that when 10 variables were introduced, results of grid search method showed 4 as the optimal number of nodes in DT, and 1 000 as the optimal number of DT. When the number of introduced variables were not less than 10, the AUC of RF machine learning algorithm prediction model was about 0.990. When 10 variables were introduced, the RF machine learning algorithm prediction model had an AUC of 0.992 for postoperative overall survival of 3 years, a sensitivity of 0.629, a specificity of 0.996 in the training dataset, an AUC of 0.723 for postoperative overall survival of 3 years, a sensitivity of 0.177, a specificity of 0.948 in the validation dataset. (4) Construction and evaluation of COX nomogram prediction model. ① Analysis of postoperative survival factors of HCC patients in the training dataset. Results of univariate analysis showed that HBeAg, alpha fetoprotein (AFP), preoperative blood transfusion, maximum tumor diameter, liver capsule invasion, and degree of tumor differentiation were related factors for postoperative survival of HCC patients [ hazard ratio ( HR)=1.958, 1.878, 2.170, 1.188, 2.052, 0.222, 95% confidence interval ( CI): 1.185-3.235, 1.147-3.076, 1.389-3.393, 1.092-1.291, 1.240-3.395, 0.070-0.703, P<0.05]. Clinico-pathological data with P<0.2 were included for Lasso regression analysis, and the results showed that age, HBeAg, AFP, surgical procedure, perioperative blood transfusion, maximum tumor diameter, tumor located at liver segment Ⅴ or Ⅷ, liver capsule invasion, and degree of tumor differentiation as high differentiation, moderate-high differentiation, moderate differentiation, moderate-low differentiation were related factors for postoperative survival of HCC patients. The above factors were included for further multivariate COX analysis, and the results showed that HBeAg, surgical procedure, maximum tumor diameter were independent factors affecting postoperative survival of HCC patients ( HR=1.770, 8.799, 1.142, 95% CI: 1.049- 2.987, 1.203-64.342, 1.051-1.242, P<0.05). ② Construction and evaluation of COX nomogram prediction model: the clinicopathological factors of P≤0.1 in the COX multivariate analysis were induced to Rstudio software and rms software package to construct COX nomogram prediction model in the training dataset. The COX nomogram prediction model for predicting postoperative overall survival had an consistency index of 0.723 (se=0.028), an AUC of 0.760 for postoperative overall survival of 3 years in the training dataset, an AUC of 0.795 for postoperative overall survival of 3 years in the validation dataset. The verification of the calibration plot in the training dataset showed that the COX nomogram prediction model had a good prediction performance for postoperative survival. COX nomogram score=0.627 06×HBeAg (normal=0, abnormal=1)+ 0.134 34×maximum tumor diameter (cm)+ 2.107 58×surgical procedure (laparoscopy=0, laparotomy=1)+ 0.545 58×perioperative blood transfusion (without blood transfusion=0, with blood transfusion=1)-1.421 33×high differentiation (non-high differentiation=0, high differentiation=1). The COX nomogram risk scores of all patients were calculated. Xtile software was used to find the optimal threshold of COX nomogram risk scores. Patients with risk scores ≥2.9 were assigned into high risk group, and patients with risk scores <2.9 were assigned into low risk group. Results of Kaplan-Meier overall survival curve showed a significant difference in the postoperative overall survival between low risk group and high risk group of the training dataset ( χ2=33.065, P<0.05). There was a significant difference in the postoperative overall survival between low risk group and high risk group of the validation dataset ( χ2=6.585, P<0.05). Results of further analysis by the decision-making curve showed that COX nomogram prediction model based on the combination of HBeAg, surgical procedure, perioperative blood transfusion, maximum tumor diameter, and degree of tumor differentiation was superior to any of the above individual factors in prediction performance. (5) Evaluation of prediction performance between RF machine learning algorithm prediction model and COX nomogram prediction model: prediction difference between two models was investigated by analyzing maximun tumor diameter (the important variable shared in both models), and by comparing the predictive error curve of both models. The results showed that the postoperative 3-year survival rates predicted by RF machine learning algorithm prediction model and COX nomogram prediction model were 77.17% and 74.77% respectively for tumor with maximum diameter of 2.2 cm ( χ2=0.182, P>0.05), 57.51% and 61.65% for tumor with maximum diameter of 6.3 cm ( χ2=0.394, P>0.05), 51.03% and 27.52% for tumor with maximum diameter of 14.2 cm ( χ2=12.762, P<0.05). With the increase of the maximum tumor diameter, the difference in survival rates predicted between the two models turned larger. In the validation dataset, the AUC for postoperative overall survival of 3 years of RF machine learning algorithm prediction model and COX nomogram prediction model was 0.723 and 0.795, showing a significant difference between the two models ( t=3.353, P<0.05). Resluts of Bootstrap cross-validation for prediction error showed that the integrated Brier scores of RF machine learning algorithm prediction model and COX nomogram prediction model for predicting 3-year survival were 0.139 and 0.134, respectively. The prediction error of COX nomogram prediction model was lower than that of RF machine learning algorithm prediction model. Conclusion:Compared with machine learning algorithm prediction models, the COX nomogram prediction model performs better in predicting 3 years postoperative survival of HCC, with fewer variables, which is easy for clinical use.

4.
Article in Chinese | WPRIM | ID: wpr-791588

ABSTRACT

Objective To estimate the mean annual expenditure of patients with prevalent liver cancer in China on the perspective of the natural progression of the disease and to provide baseline information for liver cancer?related disease burden estimation and evaluation of prevention strategies. Methods A multicenter survey on liver cancer was conducted between 2012 and 2014 in 13 sites where the cancer screening program was conducted in Urban China, by face?to?face interviews with hospitalized patients. Data on basic information, clinical diagnosis and treatment, direct medical expenditure, and direct non?medical expenditure were collected. By?year expenditure and number of visits from the first visit to the end of the survey were analyzed. The trend for the two indicators in each year was analyzed. The subgroup analysis of factors such as sex and age was conducted. All the expenditure data were discounted to the year 2014 and presented in Chinese yuan. The statistical analysis was performed using the SAS 9.4 software. Results A total of 2 222 patients with liver cancer, with a mean age of 55.7±11.2 years, were included. Men accounted for 79.2% (1 759 cases) of the patients, women accounted for 20.8% (463 cases) of the patients, and 75.6% (1 679 cases) of the cases were from cancer hospitals. Stage Ⅰ cases only accounted for 14.1% (299 cases) of all the cases, and most cases were stageⅢorⅣ(62.6%, 1 325 cases). Of the cases, 64.4% (1 430 cases) had pathological information, and 83.6%(1 195 cases) were pathologically hepatocellular carcinoma. The sample sizes for the first 3 years from the first visit were 2 222, 149, and 57, respectively (by?year sample sizes thereafter were<50). The annual total medical expenditures for the first 3 years were 49 091 yuan (95% confidence interval [CI]: 47 376-50 806), 30 506 yuan (95% CI: 26 462-34 549), and 32 100 yuan (95% CI: 25 917-38 283) (P<0.001). The corresponding number of visits were 1.9, 1.6, and 1.5 (P<0.001). The trend for each province was consistent with the overall trend, while the down trend from years 1 to 2 varied among provinces, ranging from 1.4 (Zhejiang province) to 5.6 times (Henan province). For the trend in the first 3 years, differences were found in subgroups such as region (P<0.001) and treatment (P<0.05), instead of sex, age, stage, and other subgroups. Conclusions For liver cancer patients in China, the annual expenditure for the first year in the whole disease course was 1.6 times higher than that for the second year, which varied among provinces. However, information on annual expenditure for the later course of liver cancer is still limited.

5.
Zhonghua zhong liu za zhi ; (12): 365-371, 2018.
Article in Chinese | WPRIM | ID: wpr-806575

ABSTRACT

Objective@#To investigate the correlation between postoperative peripheral blood neutrophil to lymphocyte ratio (NLR) and recurrence and prognosis of patients with hepatocellular carcinoma (HCC).@*Methods@#The clinicopathological and follow-up data of 344 patients with HCC who underwent radical liver resection from May 2010 to April 2014 were analyzed retrospectively.@*Results@#Of the 344 patients, 104 had early recurrence and 84 had late recurrence. Receiver operating characteristic (ROC) curve analysis showed that the NLR predicted area under the curve (AUC) of early recurrence was 0.622 (P<0.001), the optimal cut-off value was 2.41. The AUC of late recurrence was 0.634 (P=0.001), the optimal cut-off value was 2.15. Cox multivariate analysis showed the serum concentration of hepatitis B surface antigen (HR=2.508, 95% CI: 1.311-4.798), microvascular invasion (HR=2.422, 95% CI: 1.239-4.734), Milan criteria (HR=2.373, 95% CI: 1.427-3.948) and postoperative NLR (HR=2.285, 95% CI: 1.379-3.788) were independent risk factors of early recurrence after HCC resection. Postoperative NLR (HR=2.927, 95% CI: 1.630-5.255), liver cirrhosis (HR=2.531, 95% CI: 1.291-4.962) and serum concentration of albumin (HR=2.257, 95% CI: 1.251-4.073) were independent risk factors of late recurrence after HCC resection. The median recurrence-free survival (RFS) of the 344 patients was 45.0 months, and the median overall survival (OS) was 63.2 months. ROC curve analysis showed that the postoperative NLR predicted 5-year survival AUC was 0.689 (P<0.05), with an optimal cutoff of 2.29. Cox multivariate analysis showed microvascular invasion (HR=2.247, 95% CI: 1.534-3.291), postoperative NLR (HR=2.217, 95% CI: 1.653-2.974), and liver cirrhosis (HR=1.685, 95% CI: 1.168-2.431), Milan criteria (HR=1.679, 95% CI: 1.238-2.277), serum concentration of hepatitis B surface antigen (HR=1.623, 95% CI: 1.102-2.392), serum concentration of albumin (HR=1.43, 95% CI: 1.066-1.918) were independent factors of RFS after HCC resection, while microvascular invasion (HR=3.862, 95% CI: 2.407-6.197), Barcelona staging (HR=2.864, 95% CI: 1.600-5.125), postoperative NLR (HR=2.688, 95% CI: 1.782-4.055), liver cirrhosis (HR=2.039, 95% CI: 1.184-3.514), serum concentration of albumin (HR=1.81, 95% CI: 1.204-2.720) were independent factors of OS.@*Conclusions@#For HCC patients who receive radical liver resection, postoperative NLR ≥2.29 implicates poor prognosis. Moreover, postoperative NLR ≥2.41 suggests early recurrence, while NLR ≥2.15 suggests late recurrence.

6.
Article in Chinese | WPRIM | ID: wpr-710575

ABSTRACT

Objective To investigate the clinical features,diagnosis and treatment strategies for primary retroperitoneal neurofibromas.Methods The clinical data of 7 patients with primary retroperitoneal neurofibromas admitted to Cancer Institute & Hospital,Chinese Academy of Medical Sciences,from Jan 2000 to Jul 2017,were retrospectively analyzed.Results The average age was (42 ± 11) years and six were female.6 cases were with solitary tumor and 1 case was with multiple tumors.Clinical symptoms and imaging were of no help in determining tumor type.All patients underwent surgical resection.Postoperative pathology confirmed retroperitoneal neurofibroma in all seven patients,including 1 case with neurofibromatosis type Ⅰ and retroperitoneal malignant peripheral nerve sheath tumor.On immunohistochemistry all of the tumors were S-100 protein positive.At the end of the follow-up period ranging from 14 months to 166 months,sevent patients were alive and two patients experienced tumor recurrence.The longest disease-free survival time was 166 months.Conclusion Primary retroperitoneal neurofibromas are a rare type of primary retroperitoneal tumors that require diagnosis at pathology.Clinical symptoms and imaging of primary retroperitoneal neurofibromas patients were found to be ineffective at determining tumor type.Patients had a good prognosis after tumor resection.

7.
Zhonghua Wai Ke Za Zhi ; (12): 521-527, 2017.
Article in Chinese | WPRIM | ID: wpr-808982

ABSTRACT

Objective@#To investigate the clinical value of intraoperative radiofrequency ablation (RFA) in the treatment of colorectal liver metastasis (CLM).@*Methods@#A retrospectively analysis of 187 patients with CLM who underwent liver resection with or without RFA from January 2009 to August 2016 in Department of Hepatobiliary Surgery, Cancer Hospital, Chinese Academy of Medical Sciences was performed. According to whether RFA was used intraoperatively, patients were divided into resection only group and combined treatment group. The clinical and pathological characteristics of the two groups were compared to explore factors influencing survival and recurrence. Imbalance of background characteristics between the two groups was further overcome by propensity score matching method (PSM).@*Results@#The number of liver metastases (267), simultaneous liver metastases (100%), bilobar involvement (73.3%) and preoperative chemotherapy (93.3%) rates were significantly higher in the combined treatment group than those in the resection only group(471, 74.7%, 42.0% and 63.1%)(all P<0.05). In the combined treatment group, median overall survival (OS) was 25.7 months; and 3-year and 5-year OS were 47.9% and 28.8%, respectively. In the resection only group, the median survival time was 46.9 months; and 3-year and 5-year OS rate was 59.1% and 42.4%, respectively (χ2=4.579, P=0.034). Median disease-free survival (DFS) was 5.4 months in the combined treatment group, and 10.1 months in the resection only group (χ2=5.399, P=0.023). In multivariate analysis, intraoperative RFA was not an independent prognostic factor for OS and DFS (HR=0.98, 95%CI: 0.47-2.08, P=0.965; HR=1.21, 95%CI: 0.71-2.07, P=0.465). After PSM, the median OS of the resection only and the combined treatment groups were 30.2 and 25.7 months (χ2=0.876, P=0.350). The median DFS in the two groups was 5.3 and 4.2 months, respectively (χ2=0.199, P=0.650).@*Conclusion@#In patients with similar tumor burden, liver resection combined with intraoperative RFA for unresectable CLM can achieve long-term outcomes similar to hepatectomy alone for resectable CLM.

8.
Zhonghua zhong liu za zhi ; (12): 903-909, 2017.
Article in Chinese | WPRIM | ID: wpr-809700

ABSTRACT

Objective@#To establish a new scoring system based on the clinicopathological features of hepatocellular carcinoma (HCC) to predict prognosis of patients who received hepatectomy.@*Methods@#A total of 845 HCC patients who underwent hepatectomy from 1999 to 2010 at Cancer Hospital, Chinese Academy of Medical Sciences were retrospectively analyzed. 21 common clinical factors were selected in this analysis. Among these factors, the cut-off values of alpha-fetoprotein (AFP), alkaline phosphatase (ALP) and intraoperative blood loss were evaluated by using a receiver operating characteristic (ROC) curve analysis.The Kaplan-Meier method and Cox regression model were used to evaluate the independent risk factors associated with the prognosis of HCC patients after hepatectomy. HCC postoperatively prognostic scoring system was established according to the minimum weighted method of these independent risk factors, and divided the patients into 3 risk groups, including low-risk, intermediate-risk and high-risk group. The relapse-free survival (RFS) and overall survival (OS) were compared among these groups.@*Results@#The univariate analysis showed that clinical symptoms, preoperative α-fetoprotein (AFP) level, serum alkaline phosphatase (ALP) level, tumor size, tumor number, abdominal lymph node metastasis, macrovascular invasion or tumor thrombus, extrahepatic invasion or serosa perforation, the severity of hepatic cirrhosis, intraoperative blood loss, the liver operative method, pathological tumor thrombus, intraoperative blood transfusion, perioperative blood transfusion were significantly associated with median RFS of these HCC patients (P<0.05). Alternatively, clinical symptoms, preoperative AFP level, serum ALP level, tumor size, tumor number, abdominal lymph node metastasis, macrovascular invasion or tumor thrombus, extrahepatic invasion or serosa perforation, the severity of hepatic cirrhosis, intraoperative blood loss, the liver operative method, pathological lymphocyte invasion, pathological tumor thrombus, intraoperative blood transfusion, perioperative blood transfusion were significantly associated with the median OS of these HCC patients (P<0.05). The multivariate analysis showed that AFP ≥20 ng/ml, clinical symptoms, tumor diameter ≥5 cm, multiple tumors, macrovascular invasion or tumor thrombus, extrahepatic invasion or serosa perforation, moderate and severe liver cirrhosis, non- anatomic resection were the independent risk factors of RFS and OS (P<0.05). The independent risk factor of RFS was intraoperative bleeding loss ≥325 ml (P<0.05); The independent risk factors of OS were abdominal lymph node metastasis and pathological tumors thrombus (P<0.05). The respective weight of 11 independent factors was used to establish the scoring system (scores range from 0 to 26). In the score system, 0 to 5 points were defined as the low-risk group (286 cases), 6 to 12 points were determined as the intermediate-risk group (503 cases), more than 13 points were classified as the high-risk group (56 cases). The median RFS of the low-risk, intermediate-risk and high-risk group were 80, 27 and 6 months, respectively. The differences were statistically significant (P<0.001). The median OS of the three groups were 134, 51 and 15 months, respectively, and the differences were statistically significant (P<0.001).@*Conclusion@#This new score system provides effective prediction of postoperative prognosis for HCC patients.

9.
Article in Chinese | WPRIM | ID: wpr-463296

ABSTRACT

Objective:Occult breast cancer (OBC) accounts for 0.3%-1.0%of all breast cancers. Because of the rarity of this dis-ease, its treatment and prognosis remain unclear. Our study evaluated the treatment outcomes and prognostic factors associated with OBC. Methods:A total of 82 patients diagnosed with OBC based on available criteria were treated at the Cancer Hospital of Chinese Academy of Medical Sciences, Beijing, China, between January 1968 and June 2014. Except for 16 patients who were treated by needle biopsy or excisional biopsy only and were subsequently excluded, all of the cases reported were included in the study. Of the remaining 66 patients, one was male. Patient data, tumor characteristics, and treatment and outcome variables were evaluated. Overall survival (OS) and disease-free survival (DFS) were analyzed. A unicentric retrospective review of 66 patients with OBC was performed. Re-sults:The median follow-up was 75.5 months (7.0-328.0). No significant differences in OS and DFS were observed between patients who underwent mastectomy plus axillary lymph node dissection (Mast+ALND) and those who underwent breast conservation surgery (P>0.05). Univariate analysis revealed that nodal status is a significant prognosis factor of DFS (P=0.031). Conclusion:No significant difference in treatment outcomes between mastectomy+ALND and breast conservation surgery was observed. Nodal status may be an independent predictor of poor outcomes in OBC patients.

10.
Zhonghua zhong liu za zhi ; (12): 207-211, 2014.
Article in Chinese | WPRIM | ID: wpr-328985

ABSTRACT

<p><b>OBJECTIVE</b>To explore the clinicopathological features and prognostic factors of three rare and poor-prognostic pathological subtypes of primary liver carcinoma, and improve the clinical diagnosis and surgical treatment.</p><p><b>METHODS</b>A retrospective analysis of clinicopathological data of 69 patients with rare pathological subtypes of primary liver carcinoma, diagnosed by postoperative pathology in our hospital from October 1998 to June 2013 was carried out. The data of 80 cases of common poorly differentiated hepatocellular carcinoma treated in the same period were collected as control group. Kaplan-Meier method was used to analyze the survival rate, and Cox proportional hazards model was used for prognostic analysis in the patients.</p><p><b>RESULTS</b>Thirty-four cases were combined hepatocellular carcinoma and cholangiocarcinoma (CCC, 28 males, 6 females), with a median age of 52 years (range, 33 to 73). Ninteen cases were giant cell carcinoma (GCC, 16 males and 3 females), with a median age of 59 years (range, 38 to 66). Sixteen cases were sarcomatoid carcinoma (SC, 14 males and 2 females), with a median age of 57 years (range, 46 to 70). The survival analysis revealed that median survival time and the 1-, 3-, 5-year survival rates for these 3 groups were 20 months, 61.8%, 29.4%, and 20.6% in the CCC patients, 13 months, 52.6%, 31.6%, and 0% in the GCC patients, and 8 months, 31.3%, 0%, 0% in the SC patients, respectively. The median survival time and survival rate of the SC group were significantly lower than those of the other three groups (P < 0.05). However, in the SC group, the incidences of hilar lymph nodes metastasis, vascular tumor emboli and invasion of adjacent organs were significantly higher than those in the other three groups (P < 0.05). There were no statistically significant differences among the other three groups (P > 0.05). The levels of carcino-embryonic antigen were higher in the three rare subtype groups than that of the control group. The incidences of multiple tumors of the three rare subtype groups were higher than that of the control group (P < 0.05). Positive surgical margin was an independent unfavorable prognostic factor.</p><p><b>CONCLUSIONS</b>The combined hepatocellular carcinoma and cholangiocarcinoma, giant cell carcinoma and sarcomatoid carcinoma have a poor prognosis. Among them sarcomatoid carcinoma is the most malignant and poor prognostic one. Radical resection is recommended.</p>


Subject(s)
Adult , Aged , Female , Humans , Male , Middle Aged , Carcinoembryonic Antigen , Metabolism , Carcinoma, Giant Cell , Metabolism , Pathology , General Surgery , Carcinoma, Hepatocellular , Metabolism , Pathology , General Surgery , Carcinosarcoma , Metabolism , Pathology , General Surgery , Cholangiocarcinoma , Metabolism , Pathology , General Surgery , Follow-Up Studies , Hepatectomy , Methods , Liver Neoplasms , Metabolism , Pathology , General Surgery , Lymph Node Excision , Lymphatic Metastasis , Neoplasm Invasiveness , Neoplastic Cells, Circulating , Proportional Hazards Models , Retrospective Studies , Risk Factors , Survival Rate
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