Objective To investigate the clinical characteristics, short-term therapy outcome and survival in patients of lung cancer with different smoking status. Methods 3751 cases were enrolled and the differences in age, sex, pathological type, stage, treatment modality, efficiency and survival were compared according patients′smoking status. Results 1206 ( 32. 2% ) patients were never smokers and 2545 ( 67. 8% ) were smokers. 80. 3% male patients and 10. 5% female patients were smokers. Among never smoking lung cancer patients, proportion of female gender, adenocarcinoma, second primary neoplasm,advanced stages and non-operative treatment were high. In the smokers, much more COPD and pulmonary tuberculosis, squamous cancer and operative treatmentwere found. No statistical differences were detected in overall outcome and survival. Conclusions The clinical characters and treatmentmodalities of patients with lung cancer of different smoking status were significant different, but had the same survival. Patients’smoking status should be accountted into the diagnosis and treatment of lung cancer.
Objective To investigate the prognostic factors of severe chronic obstructive pulmonary disease ( COPD) in elderly patients, and to guide the clinical assessment and appropriate interventions. Methods A prospective cohort study was carried out from May 1993 to December 2010. A total of 178 elderly patients with severe COPD were recruited for baseline survey, and followed up for the living conditions, whether used non-invasive ventilation, and causes of death. A survival analysis was performed on all patients stratified by lung function. The significant factors on survival rate were analyzed. Results In this cohort the survival rates were 49% and 12% in five and ten years, respectively. The important factors for prognosis were age [ relative risk( RR) = 1. 043, 95% confidence intervals( 95% CI = 1. 010-1. 050] , forced expired volume in one second ( FEV1 , RR = 0. 019, 95% CI = 0. 007-0. 052) , FEV1% pred ( RR = 1. 045, 95% CI = 1. 012-1. 079) , lung function grade ( RR = 2. 542, 95% CI = 1. 310-4. 931) , body mass index ( BMI, RR= 0. 945, 95% CI = 0. 895-0. 952) , and pulmonary heart disease ( RR = 1. 872, 95% CI = 1. 188- 2. 959) . In severe COPD, non-invasive ventilation ( NIV, RR = 1. 167, 95% CI = 0. 041-1. 674) , pulmonary heart disease ( RR = 3. 805, 95% CI = 1. 336-10. 836) , FEV1 ( RR = 0. 081, 95% CI = 1. 001-1. 168) , and arterial partial of oxygen ( PaO2 , RR=0. 956, 95% CI =0. 920-0. 993) were the independent predictors.The patients using NIV had longer survival than those without NIV. The 5 and 10 years survival rate in the patients with NIV were 78% and 50% , much higher than those without ventilation which were 30% and 25% , respectively. In extremely severe COPD, FEV1 ( RR=1. 059, 95% CI =1. 015-1. 105) , arterial partial of carbon dioxide ( PaCO2 , RR=1. 037, 95% CI = 1. 001-1. 074) , age ( RR= 1. 054, 95% CI = 1. 013-1. 096) and pulmonary heart disease ( RR = 1. 892, 95% CI = 1. 125-3. 181) were the independent predictors. Conclusions Age, BMI, FEV1 , PaO2 , PaCO2 , pulmonary heart disease, and NIV were prognostic factors in elderly patients with severe COPD. The prognostic factors between severe and extremely severe COPD were not identical. Patients with severe COPD should be given early intervention, including progressive nutritional support, and long-term home oxygen therapy combining with NIV.
Objective To analyze the clinical features and survival of lung cancer with pleural effusions. Methods A total of 982 consecutive patients with a newly diagnosed lung cancer from January 2008 to December 2014 were retrospectively reviewed. To analyze the clinical features and survival differences, the total patients were divided into the following two groups: with (n=204) or without (n=778) pleural effusions. Results Lung cancer comprised 682 (69.5%) males and 300 (30.5%) females, with an average age of 59.74 years (19–93 years). There were 487(49.6%) squamous carcinoma, 254 (25.9%) adenocarcinoma and 166 (16.9%) small cell lung cancer; 113 (11.5%) lung cancer at early stage (Ⅰ–Ⅱ), 247 (25.2%) cases at stage Ⅲ and 567 (57.7%) at stage Ⅳ. The median survival time of all patients was 12 months. Patients with pleural effusions had a worse prognosis compared to patients without (median survival time: 11 vs.12 months, P=0.003), the median survival time could be reduced by 1 month in males (P=0.004), 3 months in elder patients over 60 years (P<0.001), 4 to 8 months in carcinoma and small cell lung cancer (P≤0.001), and 2 to 3 months in advanced lung cancer (stage Ⅲ and Ⅳ) (P<0.05). Any or combined treatment of surgery, radiotherapy, chemotherapy and targeted therapy was associated with an improved overall survival of about 2 months (P=0.009), and targeted therapy could even improve the median survival time by 1 to 8 months (P=0.002). Conclusions About 20.8% of the patients developed pleural effusion at the same time during the course of lung cancer. Pleural effusion is a poor prognostic factor of lung cancer.
Objective To improve esophageal lymph node staging and investgate an ideal esophageal lymph node metastasis staging method. Methods The clinical pathological data and followup data of the 236patients who had undergone thoracic esophagectomy with at least 6 lymph nodes (LN) removed from January 1985 to December 1989 were analyzed retrospectively. Cox proportional hazard model was used to screen risk factors, and Logrank test was applied to perform survival analysis according to lymph node metastasis staging (number, distance and extent). Results The 10-year follow-up rate was 92.3%（218/236）. The overall 1-year, 5-year and 10-year survival rates were 80.2%, 43.1% and 34.2% respectively. One hundred and twelve (47.4%) patients had LN metastasis, and their 5-year survival rates were lower than that of patients without LN metastasis (14.8% vs. 66.6%; χ2=77.18, P=0.000). Cox regression analysis showed that besides depth of invasion, differentiation grade and LN metastasis, the number, distance and extent of LN metastasis were the independent risk factors which could influence prognosis. A further analysis was given via univariate Logrank test. When grouped according to the number of LN metastasis, there were significant differences in overall survival rates (χ2=96.00,P=0.000), but no significant difference was found in survival rates between N2 and N3 group(Pgt;0.05). When grouped according to the distance of LN metastasis, there were significant differences in overall survival rates (χ2=79.29, P=0.000), but no significant difference was found in survival rates among S1, S2 and S3 group(Pgt;0.05). When grouped according to the extent of LN metastasis (0, 1, and ≥2 fields), there were significant differences in overall survival rates (χ2=87.47, P=0.000), and so were the survival rates among groups (χ2=5.14, P=0.023). Conclusion Revising the current Nclassification of TNM staging of esophageal cancer according to the extent of LN metastasis(0, 1, and ≥2 fields) is more reasonable, and can reflect the prognosis of patients with esophageal cancer after esophagectomy better.
Objective To investigate the expression of Jumonji domain-containing protein 3 ( JMJD3) in lung cancer tissue. Methods The cancer tissue slides from 53 lung cancer patients with different TNMstages were immunostained with JMJD3 antibody. The relationship between the expression of JMJD3 and type of pathology, TNM stage, survival time was analyzed. Results 94. 3% lung cancer tissue expressed JMJD3 protein. The expression of JMJD3 was negatively correlated with TNMstage( r = - 0. 347,P =0. 002) . The patients with decreased JMJD3 expression had shorter survival time than the patients with high JMJD3 expression ( X2 = 17. 83, P = 0. 001) . Conclusion Decreased expression of JMJD3 may promote the lung cancer progression.
ObjectiveTo summarize and explore the application of machine learning models to survival data with non-proportional hazards (NPH), and to provide a methodological reference for large-scale, high-dimensional survival data. MethodsFirst, the concept of NPH and related testing methods were outlined. Then the advantages and disadvantages of machine learning algorithm-based NPH survival analysis methods were summarized based on the relevant literature. Finally, using real-world clinical data, a case study was conducted with two ensemble machine learning models and two deep learning models in survival data with NPH: a study of the risk of death within 30 days in stroke patients in the ICU. ResultsEight commonly used machine learning model-based NPH survival analyses were identified, including five traditional machine learning models such as random survival forest and three deep learning models based on artificial neural networks (e.g., DeepHit). The case study found that the random survival forest model performed the best (C-index=0.773, IBS=0.151), and the permutation importance-based algorithm found that age was the most important characteristic affecting the risk of death in stroke patients. ConclusionSurvival big data in the era of precision medicine presenting NPH are common, and machine learning model-based survival analysis can be used when faced with more complex survival data and higher survival analysis needs.
ObjectiveTo establish a predictive model for survival and study it’s clinical value by reviewing the information of patients with hilar cholangiocarcinoma. MethodsMedical record of 196 patients with hilar cholangiocarcinoma were analyzed retrospectively. Seventeen possible clinicopathologic factors were selected. Cox model was used for univariate and multivariate analysis. Prognostic index (PI) was calculated based on the results of multivariate analysis. Patients with different PI were divided into three different risk level groups in order to compare the survival rate. Individual expected survival rate was calculated based on the median PI. Log cumulative hazards function plot was used to test Cox model proportional hazards assumption (PH assumption). ResultsThe significant prognostic factors influencing the survival rate were surgical procedure, surgical margin, and preoperative total bilirubin level (Plt;0.05). The predictive formula was PI=0.815×preoperative total bilirubin level+0.580×surgical margin－0.713×surgical procedure. According to the value of PI, all patients were divided into 3 groups, low risk group (PI≤－0.642), middle risk group (－0.642lt;PIlt;1.364), high risk group (PI≥1.364), and survival rate declined between groups and in groups with statistically significant difference (Plt;0.05). ConclusionThis model for survival can predict the prognosis of patients with hilar cholangiocarcinoma individually and help to conduct individual clinical therapy.
Objective To compare the oncologic results between laparoscopic and open approach for the treatment of rectal cancer. Methods Five hundred and twenty patients with rectal cancer from Jan. 2003 to Dec. 2008 were non-randomly divided into laparoscopic (LS) and open surgery (OS) group. Local recurrence, distant metastasis and survival rate were compared between two groups. Results One hundred and eighty-six cases received laparoscopic resection and 334 cases received open operation. There were no statistically significant differences (SSD) of demographic data between two groups (Pgt;0.05). Mean follow-up was 30.3 months. No SSD was observed in 3-year cumulative survival rate (83% in LS and 80% in OS, P=0.549), distant metastasis rate (12.5% in LS and 15.6% in OS, P=0.368), incidence of incision seeding (0.6% in LS and 0 in OS, P=0.189), or cumulative survival (P=0.142). The differences of local recurrences rate (4.8% in LS and 10.7% in OS, P=0.028), 3-year cumulative disease-free survival rate (81% in LS and 68% in OS, P=0.009), and cumulative disease-free survival (P=0.010) between two groups were statistical significant. The differences of cumulative survival, cumulative disease-free survival, local recurrences， and distant metastasis according to the TNM stageⅠ or Ⅱ between two groups were not statistical significant. The differences of cumulative disease-free survival and local recurrences according to the TNM stage Ⅲ reached statistical significance (P=0.045 and P=0.047, respectively). Conclusion Oncologic results of laparoscopic resection are similar to those of open resection for rectal carcinoma．
Survival data include the occurrence and duration of an event. As most survival data are distributed irregularly, the Kaplan-Meier method is often used in survival analysis; however, studies usually only report the Kaplan-Meier curve and median survival time and do not provide the original survival data, which creates issues for subsequent secondary research. This study introduced a systematic method whereby image processing software and R software were used to process and extract survival data from published Kaplan-Meier curves. It also introduced the specific steps required to obtain survival data using an example to show the accuracy and feasibility of the extraction method and provided references for the effective secondary use of survival data.
ObjectiveTo investigate the prognostic factors for inflammatory breast cancer based on the data from West China Hospital with a relatively large sample. MethodsClinical data of 41 patients with histopathologically confirmed inflammatory breast cancer (IBC) who received treatment at West China Hospital Oncology Center of Sichuan University between January 2009 and December 2014 were collected and analyzed. Log-rank test and Cox regression model were used for statistical analysis. ResultsIn the study, negative estrogen receptor, negative progestrone receptor and positive human epidermal growth factor receptor-2 were identified in 58.5%, 61.0% and 34.2% of the inflammatory breast cancer tissues, respectively. Progress free survival (PFS) were between 2 and 60 months, with a median of 35 months. Univariate analysis showed that Tumor Node Metastasis (TNM) stage (P=0.016) and therapeutic effect (P=0.002) influenced the survival. Multivariate analysis showed that TNM stage (P=0.006), therapeutic effect (P=0.002), and anthracycline-taxane based chemotherapy (P=0.041) were the significant prognostic factors. ConclusionTNM stage is the major prognostic factor for IBC. Preoperative chemotherapy with paclitaxel-epirubicin combination can improve the PFS of IBC. Comprehensive treatment mode with operation is recommended for the treatment of IBC.