scholarly journals Overall survival and cancer-specific survival in patients with surgically resected pancreatic head adenocarcinoma: A competing risk nomogram analysis

2018 ◽  
Vol 9 (17) ◽  
pp. 3156-3167 ◽  
Author(s):  
Chaobin He ◽  
Yu Zhang ◽  
Zhiyuan Cai ◽  
Xiaojun Lin ◽  
Shengping Li
Keyword(s):  
Overall Survival ◽  
Pancreatic Head ◽  
Competing Risk ◽  
Cancer Specific Survival

Survival among colorectal cancer patients with a history of previous cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16146-e16146
Author(s):  
Sandi Pruitt ◽  
David E. Gerber ◽  
Hong Zhu ◽  
Daniel Heitjan ◽  
Bhumika Maddineni ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
Population Based ◽  
Competing Risk ◽  
Cancer Specific Survival ◽  
Risk Of Death ◽  
Number Of Patients ◽  
Significant Difference ◽  
The Impact

e16146 Background: A growing number of patients with colorectal cancer (CRC) have survived a previous cancer. Although little is known about their prognosis, this population is frequently excluded from clinical trials. We examined the impact of previous cancer on overall and cancer-specific survival in a population-based cohort of patients diagnosed with incident CRC. Methods: We identified patients aged ≥66 years and diagnosed with CRC between 2005-2015 in linked SEER-Medicare data. For patients with and without previous cancer, we estimated overall survival using Cox regression and cause-specific survival using competing risk regression, separately by CRC stage, while adjusting for numerous covariates and competing risk of death from previous cancer, other causes, or the incident CRC. Results: Of 112,769 CRC patients diagnosed with incident CRC, 15,935 (14.1%) had a previous cancer – most commonly prostate (32.9%) or breast (19.4%) cancer, with many 7505 (47.1%) diagnosed ≤5 years of CRC. For all CRC stages except IV in which there was no significant difference in survival, patients with previous cancer had modestly worse overall survival (hazard ratios from fully adjusted models range from 1.11-1.28 across stages; see Table). This survival disadvantage was driven by deaths due to previous cancer and other causes. Notably, most patients with previous cancer had improved CRC-specific survival. Conclusions: CRC patients who have survived a previous cancer have generally worse overall survival but superior CRC-specific survival. This evidence should be considered concurrently with concerns about trial generalizability, low accrual, and heterogeneity of participants when determining exclusion criteria. [Table: see text]

Survival among breast cancer patients with a history of previous cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14080-e14080
Author(s):  
Sandi Pruitt ◽  
Hong Zhu ◽  
David E. Gerber ◽  
Daniel Heitjan ◽  
Bhumika Maddineni ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Competing Risk ◽  
Cancer Stage ◽  
Newly Diagnosed ◽  
Cancer Specific Survival ◽  
Risk Of Death ◽  
The Impact ◽  
Incident Breast Cancer ◽  
Over Time

e14080 Background: A growing number of women newly diagnosed with breast cancer have survived a previous cancer. Although little is known about their prognosis, this population is frequently excluded from clinical trials. Among women diagnosed with incident breast cancer, we examined the impact of previous cancer on overall and cancer-specific survival. Methods: This population-based cohort study included patients age ≥66 years and diagnosed with breast cancer between 2005-2015 in linked SEER-Medicare data. Separately by breast cancer stage, we estimated overall survival using Cox regression and cause-specific survival using competing risk regression for women with and without previous cancer, adjusting for numerous covariates and competing risk of death from previous cancer, other causes, or the incident breast cancer. Results: Of 138,576 women diagnosed with incident breast cancer, 10,822 (7.8%) had a previous cancer of another organ site and many of these (n = 5,014, 46.3%) were diagnosed ≤5 years of breast cancer. For all breast cancer stages except IV in which there was no significant survival difference, women with vs. without previous cancer had worse overall survival (see Table). This survival disadvantage was driven by deaths due to the previous cancer and other causes. In contrast, while women with previous cancer generally had favorable breast-cancer specific survival, the impact of previous cancer on this outcome varied over time. Conclusions: Many women newly diagnosed with breast cancer are already cancer survivors. These women have generally worse overall survival, worse survival from other causes, but their disease-specific survival varies depending on their breast cancer stage and over time. Future analyses will explore time-varying effect of previous cancer on breast cancer survival. [Table: see text]

scholarly journals Nomograms predicting overall survival and cancer-specific survival for patients with appendiceal cancer after surgery

All Life ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 428-440
Author(s):  
Yuan Zhou ◽  
Dan Wang ◽  
Chongshun Liu ◽  
Tingyu Yan ◽  
Chenglong Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
Appendiceal Cancer ◽  
Cancer Specific Survival

scholarly journals Dynamic nomograms combining N classification with ratio-based nodal classifications to predict long-term survival for patients with lung adenocarcinoma after surgery: a SEER population-based study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Suyu Wang ◽  
Yue Yu ◽  
Wenting Xu ◽  
Xin Lv ◽  
Yufeng Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
External Validation ◽  
Predictive Performance ◽  
Information Criterion ◽  
Curve Analysis ◽  
Tnm Stage ◽  
Concordance Index ◽  
Cancer Specific Survival ◽  
Decision Curve Analysis

Abstract Background The prognostic roles of three lymph node classifications, number of positive lymph nodes (NPLN), log odds of positive lymph nodes (LODDS), and lymph node ratio (LNR) in lung adenocarcinoma are unclear. We aim to find the classification with the strongest predictive power and combine it with the American Joint Committee on Cancer (AJCC) 8th TNM stage to establish an optimal prognostic nomogram. Methods 25,005 patients with T1-4N0–2M0 lung adenocarcinoma after surgery between 2004 to 2016 from the Surveillance, Epidemiology, and End Results database were included. The study cohort was divided into training cohort (13,551 patients) and external validation cohort (11,454 patients) according to different geographic region. Univariate and multivariate Cox regression analyses were performed on the training cohort to evaluate the predictive performance of NPLN (Model 1), LODDS (Model 2), LNR (Model 3) or LODDS+LNR (Model 4) respectively for cancer-specific survival and overall survival. Likelihood-ratio χ2 test, Akaike Information Criterion, Harrell concordance index, integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were used to evaluate the predictive performance of the models. Nomograms were established according to the optimal models. They’re put into internal validation using bootstrapping technique and external validation using calibration curves. Nomograms were compared with AJCC 8th TNM stage using decision curve analysis. Results NPLN, LODDS and LNR were independent prognostic factors for cancer-specific survival and overall survival. LODDS+LNR (Model 4) demonstrated the highest Likelihood-ratio χ2 test, highest Harrell concordance index, and lowest Akaike Information Criterion, and IDI and NRI values suggested Model 4 had better prediction accuracy than other models. Internal and external validations showed that the nomograms combining TNM stage with LODDS+LNR were convincingly precise. Decision curve analysis suggested the nomograms performed better than AJCC 8th TNM stage in clinical practicability. Conclusions We constructed online nomograms for cancer-specific survival and overall survival of lung adenocarcinoma patients after surgery, which may facilitate doctors to provide highly individualized therapy.

scholarly journals Nomograms predicting the overall survival and cancer-specific survival of patients with stage IIIC1 cervical cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yifan Feng ◽  
Ye Wang ◽  
Yangqin Xie ◽  
Shuwei Wu ◽  
Yuyang Li ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Overall Survival ◽  
Random Sampling ◽  
Tumour Size ◽  
Training Group ◽  
Data Sets ◽  
Prognostic Variables ◽  
Cancer Specific Survival ◽  
External Data ◽  
Seer Data

Abstract Background To explore the factors that affect the prognosis of overall survival (OS) and cancer-specific survival (CSS) of patients with stage IIIC1 cervical cancer and establish nomogram models to predict this prognosis. Methods Data from patients in the Surveil-lance, Epidemiology, and End Results (SEER) programme meeting the inclusion criteria were classified into a training group, and validation data were obtained from the First Affiliated Hospital of Anhui Medical University from 2010 to 2019. The incidence, Kaplan-Meier curves, OS and CSS of patients with stage IIIC1 cervical cancer in the training group were evaluated. Nomograms were established according to the results of univariate and multivariate Cox regression models. Harrell’s C-index, calibration plots, receiver operating characteristic (ROC) curves and decision-curve analysis (DCA) were calculated to validate the prediction models. Results The incidence of pelvic lymph node metastasis, a high-risk factor for the prognosis of cervical cancer, decreased slightly over time. Eight independent prognostic variables were identified for OS, including age, race, marriage status, histology, extension range, tumour size, radiotherapy and surgery, but only seven were identified for CSS, with marriage status excluded. Nomograms of OS and CSS were established based on the results. The C-indexes for the nomograms of OS and CSS were 0.687 and 0.692, respectively, using random sampling of SEER data sets and 0.701 and 0.735, respectively, using random sampling of external data sets. The AUCs for the nomogram of OS were 0.708 and 0.705 for the SEER data sets and 0.750 and 0.750 for the external data sets, respectively. In addition, AUCs of 0.707 and 0.709 were obtained for the nomogram of CSS when validated using SEER data sets, and 0.788 and 0.785 when validated using external data sets. Calibration plots for the nomograms were almost identical to the actual observations. The DCA also indicated the value of the two models. Conclusions Eight independent prognostic variables were identified for OS. The same factors predicted CSS, with the exception of the marriage status. Both OS and CSS nomograms had good predictive and clinical application value after validation. Notably, tumour size had the largest contribution to the OS and CSS nomograms.

scholarly journals Prognostic Nomograms for Predicting Overall Survival and Cancer-Specific Survival of Patients with Major Salivary Gland Mucoepidermoid Carcinoma

2019 ◽  
Vol 10 (18) ◽  
pp. 4380-4388 ◽  
Author(s):  
Jia-Qian Hu ◽  
Peng-Cheng Yu ◽  
Xiao Shi ◽  
Wan-Lin Liu ◽  
Ting-Ting Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Salivary Gland ◽  
Mucoepidermoid Carcinoma ◽  
Major Salivary Gland ◽  
Cancer Specific Survival
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