ObjectiveTo analyze risk factors associated with prognosis of appendiceal adenocarcinoma using data from the Surveillance, Epidemiology, and End Results (SEER) database. MethodsThe patients pathologically diagnosed with appendiceal adenocarcinoma from 2005 to 2015 were extracted from the SEER database and then randomly divided into a training cohort and validation cohort in a 7∶3 ratio. The univariate and multivariate Cox regression analyses were performed in the training cohort to identify the independent risk factors for overall survival and cancer-specific survival. Based on these factors, a nomogram prediction model was constructed and subsequently internally validated. The statistical significance was defined as α=0.05. ResultsA total of 749 patients with appendiceal adenocarcinoma were enrolled, with 524 in the training cohort and 225 in the validation cohort. The multivariate Cox regression analysis identified that the T, N, M stages, and surgery as the independent prognostic factors for both overall survival and cancer-specific survival. Additionally, the age was identified as an independent prognostic factor for overall survival, and tumor size for cancer-specific survival. Based on these factors, the nomogram prediction models for the overall survival rate and cancer-specific survival rate were developed. The nomogram of overall survival rate achieved a C-index of 0.716 [95%CI=(0.689, 0.743)] in the training cohort and 0.695 [95%CI=(0.649, 0.740)] in the validation cohort, while the nomogram of cancer-specific survival rate showed C-index values of 0.749 [95%CI=(0.716,0.782)] and 0.746 [95%CI=(0.699, 0.793)], respectively. The area under the receiver operating characteristic curves (AUCs) for 3- and 5-year overall survival rates were 0.780 [95%CI=(0.739, 0.821)] and 0.773 [95%CI=(0.732, 0.814)] respectively in the training cohort, were 0.789 [95%CI=(0.726, 0.852)] and 0.776 [95%CI=(0.715, 0.837)] respectively in the validation cohort, which for 3- and 5-year cancer-specific survival rates were 0.813 [95%CI=(0.768, 0.858)] and 0.796 [95%CI=(0.753, 0.839)] respectively in the training cohort, were 0.813 [95%CI=(0.750, 0.876)] and 0.811 [95%CI=(0.750, 0.872)] respectively in the validation cohort. The calibration curves demonstrated good agreements between predicted and observed outcomes for both overall survival rate and cancer-specific survival rate. ConclusionsThrough analysis results of appendiceal adenocarcinoma patients from the SEER database reveal that advanced T, N, and M stages, as well as lack of surgery are significant risk factors for both overall survival and cancer-specific survival. The constructed nomograms for predicting overall survival and cancer-specific survival rates, which incorporate these risk factors, demonstrate strong predictive accuracy.
Objective To evaluate the predictive performance of the geometric characteristics, centerline (CL) of pulmonary nodules for prognosis in patients with surgically treatment in the National Lung Screening Trial (NLST). MethodsCT images of 178 patients who underwent surgical treatment and were diagnosed with non-small cell lung cancer (NSCLC) in the low-dose CT (LDCT) cohort from the NLST image database were selected, including 99 males and 79 females, with a median age of 64 (59, 68) years. CT images were processed using commercial software Mimics 21.0 to record the volume, surface area, CL and the area perpendicular to the centerline of pulmonary nodules. Receiver operating characteristic (ROC) curve was used to compare the predictive performance of LD, AD and CL on prognosis. Univariate Cox regression was used to explore the influencing factors for postoperative disease-free survival (DFS) and overall survival (OS), and meaningful independent variables were included in the multivariate Cox regression to construct the prediction model. ResultsThe area under the curve (AUC) of CL for postoperative recurrence and death were 0.650 and 0.719, better than LD (0.596, 0.623) and AD (0.600, 0.631). Multivariate Cox proportional risk regression analysis showed that pulmonary nodule volume (P=0.010), the maximum area perpendicular to the centerline (MApc) (P=0.028) and lymph node metastasis (P<0.001) were independent risk factors for DFS. Meanwhile, age (P=0.010), CL (P=0.043), lymph node metastasis (P<0.001), MApc (P=0.022) and the average area perpendicular to the centerline (AApc) (P=0.016) were independently associated with OS. ConclusionFor the postoperative outcomes of NSCLC patients in the LDCT cohort of the NLST, the CL of the pulmonary nodule prediction performance for prognosis is superior to the LD and AD, CL can effectively predict the risk stratification and prognosis of lung cancer, and spheroid tumors have a better prognosis.
ObjectiveTo compare the the effectiveness of robot-assisted thoracic surgery (RATS) with video-assisted thoracic surgery (VATS), in stageⅠ lung adenocarcinoma.MethodsFrom January 2012 to December 2018, 291 patients were included. The patients were allocated into two groups including a RATS group with 125 patients and a VATS group with 166 patients. Two cohorts (RATS, VATS ) of clinical stageⅠ lung adenocarcinoma patients were matched by propensity score. Then there were 114 patients in each group (228 patients in total). There were 45 males and 69 females at age of 62±9 years in the RATS group; 44 males, 70 females at age of 62±8 years in the VATS group. Overall survival (OS) and disease-free survival (DFS) were assessed. Univariate and multivariate analyses were performed to identify factors associated with the outcomes.Results Compared with the VATS group, the RATS group got less blood loss (P<0.05) and postoperative drainage (P<0.05) with a statistical difference. There was no statistical difference in drainage time (P>0.05) or postoperative hospital stay (P>0.05) between the two groups. The RATS group harvested more stations and number of the lymph nodes with a statistical difference (P<0.05). There was no statistical difference in 1-year, 3-year and 5-year OS and mean survival time (P>0.05). While there was a statistical difference in DFS between the two groups (1-year DFS: 94.1% vs. 95.6%; 3-year DFS: 92.6% vs. 75.2%; 5-year DFS: 92.6% vs. 68.4%, P<0.05; mean DFS time: 78 months vs. 63 months, P<0.05) between the two groups. The univariate analysis found that the number of the lymph nodes dissection was the prognostic factor for OS, and tumor diameter, surgical approach, stations and number of the lymph nodes dissection were the prognostic factors for DFS. However, multivariate analysis found that there was no independent risk factor for OS, but the tumor diameter and surgical approach were independently associated with DFS.ConclusionThere is no statistical difference in OS between the two groups, but the RATS group gets better DFS.
ObjectiveTo analyze the impact of neoadjuvant regimens on prognosis in patients with rectal cancer in the current version of the Database from Colorectal Cancer (DACCA) database. MethodsPatient information was extracted from the updated version of DACCA on November 24, 2022 according to the established screening criteria, and the following items were analyzed: gender, age, body mass index (BMI), marriage, economic conditions, degree of differentiation, neoadjuvant treatment regimen, and pTNM staging. According to the neoadjuvant treatment regimen, the patients were divided into three groups: chemotherapy group, chemotherapy combined radiotherapy group, and chemotherapy combined targeted therapy group, and the overall survival (OS) and disease-specific survival (DSS) of patients in the three groups were analyzed, and the influencing factors of OS and DSS were analyzed by univariate and multivariate Cox proportional hazard regression models. ResultsAccording to the screening criteria, 1 716 valid data were obtained from the DACCA database, of which 954 (55.6%) were in the chemotherapy group, 332 (19.3%) in the chemotherapy combined radiotherapy group, and 430 (25.1%) in the chemotherapy combined targeted therapy group. The differences in the Kaplan-Merier survival curves of patients with different neoadjuvant regimens for OS and DSS in the three groups were statistically significant (χ2=142.142, P＜0.001; χ2=129.528, P＜0.001). There were significant differences in OS rate and DSS rate between the three groups in 3 years and 5 years (P<0.001). Further comparison of different neoadjuvant therapy groups showed that the OS of the chemotherapy combined targeted therapy group was slightly better than that of the chemotherapy group in 3 years, however, OS and DSS in 5 years were slightly worse than those the chemotherapy group, but the difference were not statistically significant (P>0.05). The OS and DSS of the chemotherapy group and the chemotherapy combined targeted therapy group were better than those of the chemotherapy combined radiotherapy group in 3 years and 5 years, and the differences were statistically significant (P<0.01). The results of multivariate analysis showed that patients’ age, economic conditions, degree of tumor differentiation, new auxiliary scheme and pTNM staging were the influencing factors of OS and DSS. ConclusionNeoadjuvant treatment regimen will affect the long-term survival prognosis of rectal cancer patients.
ObjectiveTo compare the long-term survival of elderly patients with esophageal squamous cell carcinoma (ESCC) treated with surgical versus non-surgical treatment. MethodsA retrospective analysis was conducted on the clinical data of elderly patients aged ≥70 years with ESCC who underwent esophagectomy or radiotherapy/chemotherapy at Sichuan Cancer Hospital from January 2009 to September 2017. Patients were divided into a surgical group (S group) and a non-surgical group (NS group) according to the treatment method. The propensity score matching method was used to match the two groups of patients at a ratio of 1∶1, and the survival of the two groups before and after matching was analyzed. ResultsA total of 726 elderly patients with ESCC were included, including 552 males and 174 females, with 651 patients aged ≥70-80 years and 75 patients aged ≥80-90 years. There were 515 patients in the S group and 211 patients in the NS group. The median follow-up time was 60.8 months, and the median overall survival of the S group was 41.9 months [95%CI (35.2, 48.5)], while that of the NS group was only 24.0 months [95%CI (19.8, 28.3)]. The 1-, 3-, and 5-year overall survival rates of the S group were 84%, 54%, and 40%, respectively, while those of the NS group were 72%, 40%, and 30%, respectively [HR=0.689, 95%CI (0.559, 0.849), P<0.001]. After matching, 138 patients were included in each group, and there was no statistical difference in the overall survival between the two groups [HR=0.871, 95%CI (0.649, 1.167), P=0.352]. ConclusionCompared with conservative treatment, there is no significant difference in the long-term survival of elderly patients aged ≥70 years who undergo esophagectomy for ESCC. Neoadjuvant therapy combined with surgery is still an important choice to potentially improve the survival of elderly patients with ESCC.
ObjectiveTo systematically evaluate the potential value of C-reactive protein to albumin ratio (CAR) as an indicator of prognosis and survival in patients with pancreatic cancer. MethodsThe literatures were searched comprehensively in the PubMed, Embase, Web of Science, Cochrane Library, CBM, Wanfang, CNKI, and CQVIP databases from the establishment of the databases to May 20, 2021. The combined hazard ratio (HR) and 95% confidence interval (95%CI) were used to evaluate the correlation between the CAR and the overall survival (OS), progression-free survival (PFS), or disease-free survival (DFS) in the patients with pancreatic cancer. The Newcastle-Ottawa scale (NOS) was used to evaluate the quality of the non-randomized controlled studies, and the Stata SE 15.0 software was used for meta-analysis. ResultsA total of 2 985 patients with pancreatic cancer were included in this meta-analysis of 15 studies. The results of meta-analysis showed that the higher CAR value, the shorter OS [effect size (ES)=0.60, 95%CI (0.50, 0.69), Z=12.04, P<0.001], DFS [ES=0.63, 95%CI (0.47, 0.78), Z=3.61, P<0.001], and PFS [ES=0.41, 95%CI (0.19, 0.63), Z=7.91, P<0.001] in the patients with pancreatic cancer. The results of subgroup analysis of OS according to different countries, sample size, mean age, follow-up time, CAR cut-off value, and NOS score showed that the higher CAR value was related to the shorter OS (P<0.05). The result of linear regression analysis showed that there was no correlation between the CAR cut-off value and lnHR of OS (r2=0.947, P=0.455). Conclusion From results of this study, CAR is closely related to OS of patients, and it is expected to be used as a new reference index for monitoring and judging prognosis of patients with pancreatic cancer.
Objective To evaluate the relationship of systemic immune inflammatory index (SII) with the clinical features and prognosis of osteosarcoma patients. Methods The clinical data of patients with osteosarcoma surgically treated in Fuzhou Second Hospital between January 2012 and December 2017 were retrospectively collected. The preoperative SII value was calculated, which was defined as platelet × neutrophil/lymphocyte count. The best critical value of SII was determined by receiver operating characteristic (ROC) curve analysis, and the relationship between SII and clinical features of patients was analyzed by χ2 test. Kaplan-Meier method and Cox proportional hazard model were used to study the effect of SII on overall survival (OS). The nomogram prediction model was established according to the independent risk factors of patients’ prognosis. Results A total of 108 patients with osteosarcoma were included in this study. Preoperative high SII was significantly correlated with tumor diameter, Enneking stage, local recurrence and metastasis (P<0.05). The median follow-up time was 62 months. The 1-, 3-, 5-year survival rates of the low SII group were significantly higher than those of the high SII group (100.0%, 96.4%, 85.1% vs. 95.4%, 73.7%, 30.7%), and the survival of the two groups were statistically different (P<0.05). Univariate Cox regression analyses showed that tumor diameter, Enneking stage, local recurrence, metastasis and SII were associated with OS (P<0.05). Multiple Cox regression analysis showed that Enneking stage (P=0.031), local recurrence (P=0.035) and SII (P=0.001) were independent risk factors of OS. The nomogram constructed according to the independent risk factors screened by the Cox regression model had good discrimination and consistency (C-index=0.774), and the calibration curve showed that the nomogram had a high consistency with the actual results. In addition, the ROC curve indicated that the nomogram had a good prediction efficiency (area under the curve=0.880). Conclusions The preoperative SII level is expected to become an important prognostic parameter for patients with osteosarcoma. The higher the SII level is, the worse the prognosis of patients will be. The nomogram prediction model built on preoperative SII level, Enneking stage and local recurrence has a good prediction efficiency, and can be used to guide the diagnosis and treatment of clinical osteosarcoma.
Objective To analyze the relationship between age and prognosis of colorectal patients in the database from colorectal cancer (DACCA). Methods The DACCA version selected for this data analysis was updated on January 5, 2022. The data items analyzed included age, sex, tumor site, tumor pathological nature, obstruction, pathological TNM (pTNM) stage, positive lymph node ratio, survival status and survival time. According to China’s age segmentation standard, the included data were grouped into younger group (<35 years old), middle-aged group (35–59 years old) and elderly group (>59 years old). Overall survival (OS) and disease specific survival (DFS) were analyzed in three age group, and OS and DSS in three age group were analyzed in pTNM stage stratification. Results Three thousand six hundred and twenty-five rows of data were obtained from DACCA database according to the screening conditions. The survival analysis results of different age groups show that: The middle-aged group had better OS compared with the elderly group at 1-year (97.4% vs. 96.0%, P=0.037), 3-year (90.9% vs. 88.0%, P=0.030) and 5-year (81.7% vs. 75.7%, P=0.002). Also, the middle-age group had better 5-year DSS (82.2% vs. 77.7%, P=0.020). There was no statistical difference in survival between the younger group and the elderly group (P>0.05). The survival analysis results of different age groups in each pTNM stage show that: ① The middle-aged group had better medium-term and long-term OS than the elderly group. In the pTNM Ⅰ stage, the 3- and 5-year OS in the middle-aged group were better than those in the elderly group (100% vs. 93.4%, P=0.004; 100% vs. 91.4%, P=0.005). In the pTNM Ⅱ stage, the 5- and 10-year OS in the middle-aged group were better than those in the elderly group (96.5% vs. 91.3%, P=0.018; 88.2% vs. 54.3%, P<0.001). In pTNM Ⅲ stage, 10-year OS in the middle-aged group was better than that in the elderly group (36.5% vs. 36.0%, P<0.001). In pTNM Ⅳ stage, the 5- and 10- year of OS in the middle-aged group were better than those in the elderly group (67.7% vs. 58.4%, P=0.016; 19.1% vs. 7.2%, P=0.049). ② The middle-aged group had better medium-term and long-term DSS than the elderly group. In the pTNM Ⅰ stage, the 3- and 5- year DSS in the middle-aged group wrer better compared to the elderly group (100% vs. 96.9%, P=0.047; 100% vs. 94.9%, P=0.049). In the pTNM Ⅱ stage, the 10-year DSS in the middle-aged group outperformed that in the elderly group (88.2% vs. 61.9%, P=0.002). In the pTNM Ⅳ stage, the 5- and 10-year DSS in the middle-aged group were better than the elderly group (68.3% vs. 59.1%, P=0.020; 20.9% vs. 7.7%, P=0.040). ③ Except pTNM I stage, there was no significant difference in survival of other pTNM stages between young group and old group (P>0.05). In the pTNM Ⅰ stage, 3- and 5- year OS were better in the younger group compared with the elderly group (100% vs. 93.4%, P=0.004; 100% vs. 91.4%, P=0.005), and better 3- and 5- year DSS in the younger group (100% vs. 96.9%, P=0.047; 100% vs. 94.9%, P=0.049). Conclusions The age of colorectal cancer patients may have an impact on long-term survival. Middle-aged patients have better prognosis compared with elderly patients, and the younger group patients have better prognosis in pTNM stage Ⅰ only.
ObjectiveTo analyze the relation between marital status and prognosis of patients with colorectal cancer (CRC) in the Database from Colorectal Cancer (DACCA). MethodsThe DACCA version selected for this data analysis was updated on January 13, 2023. The data items analysis included the age, gender, marital status, tumor location, tumor property, pathological TNM (pTNM) stage, survival status, and survival time. According to the marital status, the patients were assigned into five marital statuses: the first marriage, unmarried, divorced, remarriage, and widowed groups. The overall survival (OS) and disease specific survival (DSS) of the 5 marital statuses were analyzed, and then the risk factors affecting OS and DSS were analyzed by the Cox proportional hazards regression model. ResultsA total of 7 373 data were obtained from the DACCA according to the screening conditions, of which 6 696 (90.8%) were first marriage, 108 (1.5%) were unmarried, 198 (2.7%) were divorced, 22 (0.3%) were remarriage, and 349 (4.7%) were widowed. The OS and DSS curves had no statistical differences among the CRC patients with 5 marital statuses (χ2=2.692, P=0.611; χ2=2.927, P=0.570). The 3-year cumulative overall survival rate and disease specific survival rate among the 5 marital status patients had statistical differences among the patients with five marital statuses (χ2=24.65, P<0.001; χ2=18.63, P=0.001), further pairwise comparison showed that the 3-year cumulative overall survival rate and disease specific survival rate in the CRC patients with first marriage were higher than those in the widowed patients (Z=3.36, P<0.01; Z=3.02, P<0.01). The multivariate analysis results by the Cox proportional hazards regression model did not find the marital status was associated with the OS and DSS (P>0.05). ConclusionsFrom the real-world analysis results of this study, it is found that 3-year cumulative overall survival rate and disease specific survival rate in patients with first marriage are higher as compared with widowed patients. It is necessary to pay more attention to the long-term follow-up of CRC patients in unmarried or widowed status.
Objection To analyze the relationship between blood type and prognosis of colorectal cancer patients in the Database from Colorectal Cancer (DACCA). Methods The DACCA version selected for this data analysis was updated on January 5, 2022. The data items analysis included age, gender, blood type, tumor location, tumor pathological nature, pathological TNM (pTNM) stage, survival status and survival time. According to the ABO blood type classification, it was divided into four blood type groups: A blood type group, B blood type group, AB blood type group, and O blood type group. The overall survival (OS) and disease specific survival (DSS) were analyzed in four blood type groups, and the OS and DSS of each blood type group were analyzed in pTNM stage stratification. Results A total of3 486 rows of data were obtained from the DACCA database according to the screening conditions. There was no significantdifference in OS and DSS among blood typy A, B, AB and O group (P>0.05); At specific time points, the 1-year OS of the blood type A group was worse than that of blood type B (95.8% vs. 99.6%), the 1-year OS of the blood type B group was better than that of blood type O group (99.6% vs. 96.9%), and the differences were statistically significant (P<0.008 7), but the differences between OS and DSS in the remaining 1, 3, 5 and 10 years of patients with different blood type groups were not statistically significant (P>0.008 7). In each pTNM staging subgroup, the differences between 1, 3, 5 and 10-year OS and DSS were not statistically significant among different blood type groups (P>0.008 7). Conclusions Overall, there was no significant difference in prognosis among the blood type A, B, AB, and O groups. Comparing specific blood types and follow-up time, patients with blood type B have slightly better 1-year OS than patients with blood type A or blood type O. Comparisons between other ABO blood groups and between ABO blood groups classified by the pTNM staging subgroup did not show a difference.