Nomogram Predicting Cause-Specific Mortality in Nonmetastatic Male Breast Cancer: A Competing Risk Analysis

Sun, Wei; Cheng, Ming; Zhou, Huaqiang; Huang, Wenqi; Qiu, Zeting

doi:10.7150/jca.28991

Cited by 25 publications

(24 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Competing risk analysis is a better statistical method to reduce the impact of death from other causes, once all the death cause data are available from the SEER database. [34]…”

Section: Discussionmentioning

confidence: 99%

Nomograms to predict survival of stage IV tongue squamous cell carcinoma after surgery

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…Competing risk analysis is a better statistical method to reduce the impact of death from other causes, once all the death cause data are available from the SEER database. [34]…”

Section: Discussionmentioning

confidence: 99%

Nomograms to predict survival of stage IV tongue squamous cell carcinoma after surgery

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, superior discriminatory capacity was observed in our nomogram compared to the SEER or TNM staging classification, with respect to OS prediction. Two other studies have also established prognostic nomograms for MBC (Sun et al, 2019; Wang et al, 2018). Sun et al (2019) established a nomogram for predicting breast cancer-specific death and other cause-specific deaths of non-metastatic MBC.…”

Section: Discussionmentioning

confidence: 99%

A prognostic nomogram for overall survival in male breast cancer with histology of infiltrating duct carcinoma after surgery

Chai¹,

Sun²,

Jia

et al. 2019

PeerJ

View full text Add to dashboard Cite

Objective The study was designed to construct and validate a nomogram for predicting overall survival (OS) of male breast cancer (MBC) patients with infiltrating duct carcinoma (IDC). Methods The cohort was selected from the Surveillance, Epidemiology, and End Results (SEER) database between January 1, 2004 and December 31, 2013. Univariate and multivariate Cox proportional hazard (PH) regression models were performed. A nomogram was developed based on the significant prognostic indicators of OS. The discriminatory and predictive capacities of nomogram were assessed by Harrell’s concordance index (C-index), calibration plots, area under the curve (AUC) and the decision curve analysis (DCA). Results The median and maximal survival time of 1862 eligible patients were 49 and 131 months, respectively. Multivariate analysis showed that age (P < 0.0001), marital status (P = 0.002), T stage (P < 0.0001), N stage (P = 0.021), M stage (P < 0.0001), progesterone receptor (PR) (P = 0.046), human epidermal growth factor receptor-2 (HER2) (P = 0.009), and chemotherapy (P = 0.003) were independent prognostic indicators of IDC of MBC. The eight variables were then combined to construct a 3-and 5-year nomogram. The C-indexes of the nomogram were0.740 (95% confidence interval [CI] [0.709–0.771]) and 0.718 (95% CI [0.672–0.764]) for the internal validation and external validation, respectively. A better discriminatory capacity was observed in the nomogram compared with the SEER summary stage (P < 0.001) and AJCC TNM staging systems (6th edition; P < 0.001) with respect to OS prediction. Good consistency was detected between the nomogram prediction and actual findings, as indicated by calibration curves. The AUC for 3-and 5-year OS was 0.739 (95% CI [0.693–0.786]) and 0.764 (95% CI [0.725–0.803]) in the training cohort and 0.737 (95% CI [0.671–0.803]) and 0.735 (95% CI [0.678–0.793]) in the validation cohort, respectively. The DCA demonstrated that the survival nomogram was clinically useful. Conclusions The nomogram was able to more accurately predict 3-and 5-year OS of MBC patients with IDC histology than were existing models.

show abstract

“…With the aid of a prognostic nomogram, clinicians can more expediently devise treatment protocols and follow-up strategies. Notably, competing risk nomograms have been developed for various cancers, such as nasopharyngeal carcinoma, breast cancer, gastrointestinal stromal tumours and melanoma [25][26][27][28]. However, as far as we know, this is the first study that constructed a competing risk nomogram based on a proportional subdistribution hazard model to predict the individual probabilities of LC-SM for lung ASC patients.…”

Section: Discussionmentioning

confidence: 99%

A competing risk nomogram predicting cause-specific mortality in patients with lung adenosquamous carcinoma

Petersen

et al. 2020

BMC Cancer

View full text Add to dashboard Cite

Background Adenosquamous carcinoma (ASC) is an uncommon histological subtype of lung cancer. The purpose of this study was to assess the cumulative incidences of lung cancer-specific mortality (LC-SM) and other cause-specific mortality (OCSM) in lung ASC patients, and construct a corresponding competing risk nomogram for LC-SM. Methods Data on 2705 patients with first primary lung ASC histologically diagnosed between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The cumulative incidence function (CIF) was utilized to calculate the 3-year and 5-year probabilities of LC-SM and OCSM, and a competing risk model was built. Based on the model, we developed a competing risk nomogram to predict the 3-year and 5-year cumulative probabilities of LC-SM and the corresponding concordance indexes (C-indexes) and calibration curves were derived to assess the model performance. To evaluate the clinical usefulness of the nomogram, decision curve analysis (DCA) was conducted. Furthermore, patients were categorized into three groups according to the tertile values of the nomogram-based scores, and their survival differences were assessed using CIF curves. Results The 3-year and 5-year cumulative mortalities were 49.6 and 55.8% for LC-SM and 8.2 and 11.8% for OCSM, respectively. In multivariate analysis, increasing age, male sex, no surgery, and advanced T, N and M stages were related to a significantly higher likelihood of LC-SM. The nomogram showed good calibration, and the 3-year and 5-year C-indexes for predicting the probabilities of LC-SM in the validation cohort were both 0.79, which were almost equal to those of the ten-fold cross validation. DCA demonstrated that using the nomogram gained more benefit when the threshold probabilities were set within the ranges of 0.24–0.89 and 0.25–0.91 for 3-year and 5-year LCSM, respectively. In both the training and validation cohorts, the high-risk group had the highest probabilities of LC-SM, followed by the medium-risk and low-risk groups (both P < 0.0001). Conclusions The competing risk nomogram displayed excellent discrimination and calibration for predicting LC-SM. With the aid of this individualized predictive tool, clinicians can more expediently devise appropriate treatment protocols and follow-up schedules.

show abstract

Nomogram Predicting Cause-Specific Mortality in Nonmetastatic Male Breast Cancer: A Competing Risk Analysis

Cited by 25 publications

References 32 publications

Nomograms to predict survival of stage IV tongue squamous cell carcinoma after surgery

Nomograms to predict survival of stage IV tongue squamous cell carcinoma after surgery

A prognostic nomogram for overall survival in male breast cancer with histology of infiltrating duct carcinoma after surgery

A competing risk nomogram predicting cause-specific mortality in patients with lung adenosquamous carcinoma

Contact Info

Product

Resources

About