ObjectiveTo explore the risk factors affecting the prognosis of patients with metastatic breast cancer (MBC) and construct a nomogram survival prediction model.MethodsThe patients with MBC from 2010 to 2013 were collected from surveillance, epidemiology, and end results (SEER) database, then were randomly divided into training group and validation group by R software. SPSS software was used to compare the survival and prognosis of MBC patients with different metastatic sites in the training group by log-rank method and construct the Kaplan-Meier survival curve. The Cox proportional hazards model was used to analyze the factors of 3-year overall survival, then construct a nomogram survival prediction model by the independent prognostic factors. The C-index was used to evaluate its predictive value and the calibration curve was used to verify the nomogram survival prediction model by internal and external calibration graph.ResultsA total of 3 288 patients with MBC were collected, including 2 304 cases in the training group and 984 cases in the validation group. The data of the two groups were comparable. The median follow-up time of training group and validation group was 34 months and 34 months, respectively. In the training group, the results of Cox proportional hazards model showed that the older, black race, higher histological grading, without operation, ER (–), PR (–), HER-2 (–), and metastases of bone, brain, liver and lung were the risk factors of survival prognosis (P<0.05) and constructed the nomogram survival prediction model with these independent prognostic factors. The nomogram survival prediction showed a good accuracy with C-index of 0.704 [95%CI (0.691, 0.717)] in internal validation (training group) and C-index of 0.691 [95%CI (0.671, 0.711)] in external validation (validation group) in predicting 3-year overall survival. All calibration curves showed excellent consistency.ConclusionNomogram for predicting 3-year overall survival of patients with MBC in this study has a good predictive capability, and it is conducive to development of individualized clinical treatment.
ObjectiveTo compare the clinical therapeutic efficacy of radiofrequency ablation (RFA) and external beam radiation (XRT) in the treatment of early hepatocellular carcinoma (HCC). MethodsThe early HCC patients were collected in the SEER (Surveillance, Epidemiology, and End Results) database, from 2010 to 2015, according to the established inclusion and exclusion criteria. The patients were assigned into an XRT group and a RFA group according to according treatment plans. The propensity score matching (PSM) was performed at a ratio of 1∶4 based on age, gender, race, alpha-fetoprotein (AFP), cirrhosis, and tumor diameter. The overall survival of the patients of the two groups was compared, and the risk factors affecting the long-term prognosis for the early HCC patients were analyzed. ResultsA total of 2 861 early HCC patients were collected, including 2 513 in the RFA group and 348 in the XRT group. After PSM, a total of 1 582 patients were enrolled, including 343 in the XRT group and 1 239 in the RFA group. After PSM, the proportion of tumor with larger diameter (>5 cm) in the XRT group was still higher than that in the RFA group (P<0.001), but there were no statistically significant differences in the other clinical pathological characteristics between them (P>0.05). The Kaplan-Meier survival curves of the RFA group was better than that of the XRT group (HR=1.65, P<0.001); The stratified analysis based on the tumor diameter revealed that the survival curves of the RFA group were superior to those of the XRT group in the HCC patients with tumor diameters <3 cm, 3–5 cm, and >5 cm (<3 cm: HR=1.79, P<0.001; 3–5 cm: HR=1.50, P<0.001; >5 cm: HR=1.67, P=0.003). The results of the multivariate Cox regression model analysis showed that the older age (≥65 years), higher AFP level (≥400 μg/L), larger tumor diameter (≥3 cm), and later AJCC stage (stage Ⅱ) were the risk factors for overall survival in the early HCC patients (HR>1, P<0.05), while the XRT treatment was a risk factor for shortening overall survival in the HCC patients [HR(95%CI)=1.62(1.41, 1.86), P<0.001]. ConclusionThe data analysis results from the SEER database suggest that the long-term overall survival of RFA treatment is superior to XRT treatment for patients with AJCC stage Ⅰ or Ⅱ.
ObjectiveTo investigate the impact of surgical treatment on the prognosis of patients with gastric signet-ring cell carcinoma (GSRC). MethodsThe clinicopathologic and prognosis data of patients pathologically diagnosed with GSRC from 2000 to 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The Cox proportional hazards regression model was used to analyze the impact of surgery on overall survival (OS) and cancer-specific survival (CSS) of patients with GSRC. ResultsA total of 3 457 patients with GSRC were included, including 2 048 cases in the operation group and 1 409 cases in the non-operation group. The propensity-score matching by a 1∶1 nearest neighbour algorithm was conducted to control for confounding baseline differences. There were 802 cases in the operation group and 802 cases in the non-operation group after matching. The OS and CSS curves drawn by Kaplan-Meier method of the operation group were better than those of the non-operation group (χ2=434.3 P<0.001; χ2=412.4, P<0.001). The multivariate Cox proportional hazards regression analysis showed that the elderly (≥ 60 years old), late AJCC tumor stage (stage Ⅰ as reference), and patients with bone metastasis of GSRC increased the risk of shortening OS and CSS (P<0.05), while patients treated with surgery and chemotherapy decreased the risk of shortening OS and CSS (P<0.05). ConclusionAccording to the analysis results of SEER database in this study, surgical treatment is beneficial to improve the prognosis for patients with GSRC.
ObjectiveTo investigate the prognostic factors of primary gastric squamous cell carcinoma (SCC) and develop a nomogram for predicting the survival of gastric SCC.MethodsData of 199 cases of primary gastric SCC from 2004 to 2015 were collected in the National Cancer Institute SEER database by SEER Stat 8.3.5 software. X-tile software was used to determine the best cut-off value of the age, SPSS 25.0 software was used to analyze the prognostic factors of gastric SCC and draw a Kaplan-Meier curve, and then the Cox proportional hazard regression model analysis was performed to obtain independent prognostic factors of gastric SCC. We used R studio software to visualize the model and draw a nomogram. C-index was used to evaluate the prediction effect of the nomogram. Bootstrap analyses with 1 000 resamples were applied to complete the internal verification of the nomogram.ResultsAmong the 199 patients, survival rates for 1-, 3-, and 5-year were 40.7%, 22.4%, and 15.4%, respectively. Age (χ2=6.886, P=0.009), primary site (χ2=14.918, P=0.037), race (χ2=7.668, P=0.022), surgery (χ2=16.523, P<0.001), histologic type (χ2=9.372, P=0.009), T stage (χ2=11.639, P=0.009), and M stage (χ2=31.091, P<0.001) had a significant correlation with survival time of patients. The results of the Cox proportional hazard regression model showed that, age [HR=1.831, 95%CI was (1.289, 2.601)], primary site [HR=1.105, 95%CI was (1.019, 1.199)], M stage [HR=2.222, 95%CI was (1.552, 3.179)], and surgery [HR=0.561, 95%CI was (0.377, 0.835)] were independent prognostic factors affecting the survival of gastric SCC. Four independent prognostic factors contributed to constructing a nomogram with a C-index of 0.700.ConclusionIn this research, a reliable predictive model is constructed and drawn into a nomogram, which can be used for clinical reference.
ObjectiveBased on a large sample of data, study the factors affecting the survival and prognosis of patients with rectal cancer and construct a prediction model for the survival and prognosis.MethodsThe clinical data of 26 028 patients with rectal cancer were screened from the Surveillance, Epidemiology, and End Results (SEER) clinical database of the National Cancer Institute. Univariate and multivariate Cox proportional hazard regression analysis were used to screen related risk factors. Finally, the Nomogram prediction model was summarized and its accuracy was verified.ResultsResult of multivariate Cox proportional hazard regression analysis showed that the risk factors affecting the survival probability of rectal cancer included: age, gender, marital status, TMN staging, T staging, tumor size, degree of tissue differentiation, total number of lymph nodes removed, positive lymph node ratio, radiotherapy, and chemotherapy (P<0.05). Then we further built the Nomogram prediction model. The C index of the training cohort and the validation cohort were 0.764 and 0.770, respectively. The area under the ROC curve (0.777 and 0.762) for 3 years and 5 years, and the calibration curves of internal and external validation all indicated that the model could effectively predict the survival probability of rectal cancer.ConclusionThe constructed Nomogram model can predict the survival probability of rectal cancer, and has clinical guiding significance for the prognostic intervention of rectal cancer.
Objective To establish a prediction model for the 1-, 3-, and 5-year survival rates in patients with gastric cancer liver metastases (GCLM) by analyzing prognostic factors based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods Clinical and pathological data from 591 patients diagnosed with GCLM between 2010 and 2015 were obtained from the SEER database. The population was randomly divided into a training cohort and an internal validation cohort at a 7 to 3 ratio. Independent predictors of GCLM were analyzed using univariate and multifactorial Cox regression. Consequently, nomograms were constructed. The model's accuracy was verified by calibration curve, ROC curve, and the C-index, and the clinical utility of the model was analyzed through decision curve analysis. Results Tumor differentiation grade, surgical status, and chemotherapy were significantly associated with the prognosis of GCLM patients, and these three factors were included in constructing the prognostic model and plotting the nomogram. The C-index was 0.706 (95%CI 0.677 to 0.735) and 0.749 (95%CI 0.710 to 0.788) for the training set and the internal validation cohort, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) was over 0.7 at 1, 3, and 5 years for both the training and validation cohorts. Conclusion The prediction model of the GCLM is developed based on the 3 factors, i.e., tumor differentiation grade, surgery, and chemotherapy, and shows good prediction accuracy and thus may promote clinical decision making and individualized treatment of GCLM patients.
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 predict the patients who can benefit from local surgery for bone-only metastatic breast cancer (bMBC). Methods Patients newly diagnosed with bMBC between 2010 and 2019 in SEER database were randomly divided into a training set and a validation set at a ratio of 7∶3. The Cox proportional hazards model was used to analyze the independent prognostic factors of overall survival in the training set, and the variables were screened and the prognostic prediction model was constructed. The concordance index (C-index), time-dependent clinical receiver operating characteristic curve and area under the curve (AUC), calibration curve and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical applicability of the model in the training set and validation set, respectively. The model was used to calculate the patient risk score and classify the patients into low-, medium- and high-risk groups. Survival analysis was used to compare the survival difference between surgical and non-surgical patients in different risk groups. Results A total of 2057 patients were enrolled with a median age of 45 years (interquartile range 47-62 years) and a median follow-up of 32 months (interquartile range 16-53 months). Totally 865 patients (42.1%) died. Multivariate Cox proportional hazards model analysis showed that the overall survival of patients with surgery was better than that of patients without surgery [hazard ratio=0.51, 95% confidence interval (0.43, 0.60), P<0.001]. Chemotherapy, marital status, molecular subtype, age, pathological type and histological grade were independent prognostic factors for overall survival (P<0.05), and a prognostic prediction model was constructed based on the independent prognostic factors. The C-index was 0.702 in the training set and 0.703 in the validation set. The 1-, 3-, and 5-year AUCs of the training set and validation set were 0.734, 0.727, 0.731 and 0.755, 0.737, 0.708, respectively. The calibration curve showed that the predicted survival rates of 1, 3, and 5 years in the training set and the validation set were highly consistent with the actual survival rates. DCA showed that the prediction model had certain clinical applicability in the training set and the validation set. Patients were divided into low-, medium- and high-risk subgroups according to their risk scores. The results of log-rank test showed that local surgery improved overall survival in the low-risk group (training set: P=0.013; validation set: P=0.024), but local surgery did not improve overall survival in the medium-risk group (training set: P=0.45; validation set: P=0.77) or high-risk group (training set: P=0.56; validation set: P=0.94). Conclusions Local surgery can improve the overall survival of some patients with newly diagnosed bMBC. The prognostic stratification model based on clinicopathological features can evaluate the benefit of local surgery in patients with newly diagnosed bMBC.
Objective To explore the relationship between the metastatic sites and prognosis in newly diagnosed stage Ⅳ breast cancer. Methods The data of newly diagnosed female patients with stage Ⅳ invasive breast cancer with complete follow-up data from SEER database from 2010 to 2015 were grouped according to different metastatic sites, and the differences of breast cancer-specific survival (BCSS) in different metastatic sites were analyzed by univariate and multivariate Cox. Kaplan-Meier method was used to draw the survival curve, and log-rank test was used to analyze the prognostic factors of BCSS in newly diagnosed stage ⅳ breast cancer. Results A total of 8 407 patients were included in the final analysis. Among them, 5 619 (66.84%) patients were confirmed with bone metastasis only, 1 483 (17.64%) patients with lung metastasis only, 1 096 (13.04%) patients with liver metastasis only, and 209 (2.49%) patients with brain metastasis only. The median follow-up time was 22 months, with 4 180 (49.72%) breast cancer-related deaths and a median BCSS of 39 months in those patients. The location of metastasis in newly diagnosed stage Ⅳ invasive breast cancer was significantly correlated with BCSS (χ2=151.07, P<0.001). Multivariate Cox model analysis showed that the BCSS was worse in patients with liver metastasis [HR=1.34, 95%CI (1.21, 1.49), P<0.001], lung metastasis [HR=1.09, 95%CI (1.04, 1.14), P<0.001] and brain metastases [HR=1.28, 95%CI (1.20, 1.36), P<0.001] than in patients with bone metastases. Further subgroup analysis showed that the BCSS of breast cancer patients with different molecular subtypes and different metastatic sites were also significantly different (P<0.05). Patients with brain and liver metastases in the HR+/HER2– subtype had worse BCSS than those with bone metastases (P<0.001). Patients with brain metastases in the HR+/HER2+ subtype had worse BCSS than those with bone metastases (P=0.001). In HR–/HER2+ subtype, the BCSS of patients with liver metastasis, lung metastasis and brain metastasis were worse than that of patients with bone metastasis (P<0.05). In HR–/HER2– subtype, the BCSS of patients with brain metastasis and liver metastasis were worse than that of patients with bone metastasis (P<0.05) . Conclusion The prognosis of newly diagnosed stage ⅳ breast cancer patients with different metastatic sites is different, and the prognosis of different molecular subtypes and different metastatic sites is also different.
Objective To explore the value of surgical treatment in rectal small cell neuroendocrine carcinoma (RSCC). Method The clinical data of patients with pathologically diagnosed as RSCC from 2000 to 2019 were extracted from the Surveillance, Epidemiology and End Results (SEER) database, to explore the effect of surgical treatment on cancer-specific survival (CSS) and overall survival (OS). Results A total of 348 cases were included with the median follow-up of 8 months (IQR: 3–16 months). Of the 101 patients in the operation group, 84 died (83.2%), including 56 tumor-related deaths (55.4%). Of the 247 patients in the non-operation group, 215 died (87.0%), including 131 tumor-related deaths (53.0%). The estimated 1-year OS of the operation group and the non-operation group were 49.6% and 34.4%, respectively, and the estimated 1-year CSS of those were 62.2% and 49.2%, respectively. There were significant differences between the two groups (both P<0.05). Results of multivariate prognostic analysis by Cox proportional hazard model showed that differentiation, SEER stage, receiving operative treatment or not, receiving chemotherapy or not, and receiving radiotherapy or not were independent influencing factors for OS, and SEER stage, receiving operative treatment or not, receiving chemotherapy or not, and receiving radiotherapy or not were independent influencing factors for CSS (all P<0.05). The OS [RR=0.61, 95%CI was (0.45, 0.81), P<0.001] and CSS [RR=0.67, 95%CI was (0.47, 0.95), P=0.025] in RSCC patients were significantly improved by surgical treatment. Conclusion Surgical treatment can improve the OS and CSS in RSCC patients.