Nomograms for Estimating Cause-Specific Death Rates of Patients With Inflammatory Breast Cancer: A Competing-Risks Analysis

Abstract

Purpose: Inflammatory breast cancer (IBC) is a rare, aggressive and special subtype of primary breast cancer. We aimed to establish competing-risks nomograms to predict the IBC-specific death (BCSD) and other-cause-specific death (OCSD) of IBC patients. Methods: We extracted data on primary IBC patients from the SEER (Surveillance, Epidemiology, and End Results) database by applying specific inclusion and exclusion criteria. Cumulative incidence function (CIF) was used to calculate the cumulative incidence rates and Gray’s test was used to evaluate the difference between groups. Fine-Gray proportional subdistribution hazard method was applied to identify the independent predictors. We then established nomograms to predict the 1-, 3-, and 5-year cumulative incidence rates of BCSD and OCSD based on the results. The calibration curves and concordance index (C-index) were adopted to validate the nomograms. Results: We enrolled 1699 eligible IBC patients eventually. In general, the 1-, 3-, and 5-years cumulative incidence rates of BCSD were 15.3%, 41.0%, and 50.7%, respectively, while those of OCSD were 3.0%, 5.1%, and 7.4%. The following 9 variables were independent predictive factors for BCSD: race, lymph node ratio (LNR), AJCC M stage, histological grade, ER (estrogen receptor) status, PR (progesterone receptor) status, HER-2 (human epidermal growth factor-like receptor 2) status, surgery status, and radiotherapy status. Meanwhile, age, ER, PR and chemotherapy status could predict OCSD independently. These factors were integrated for the construction of the competing-risks nomograms. The results of calibration curves and C-indexes indicated the nomograms had good performance. Conclusions: Based on the SEER database, we established the first competing-risks nomograms to predict BCSD and OCSD of IBC patients. The good performance indicated that they could be incorporated in clinical practice to provide references for clinicians to make individualized treatment strategies.

The loss of progesterone receptor predicts more aggressive biological features and worse outcomes in estrogen receptor-positive and HER2-negative inflammatory breast cancer

“…In addition to PR status, older age and black race were also prognostic risk factors for patients with ER + and HER2negative IBC. Poor histological grade and visceral metastasis were recognized as poor prognostic factors for IBC [14,17], which was also demonstrated by our study. As mentioned above, the patients with ER+/PR-IBC presented poor histological grade and more visceral metastasis, which may also explain the worse outcomes for patients with ER+/PR-phenotype in our study.…”

“…As previous studies[6, 7, 13], the loss of PR also predicted unfavorable biological characteristics in IBC. In our study, the patients with ER+/PR-phenotype were prone to be poor histological grade ( -), which often predicts worse survival [14,15]. In addition, the tendency of distant metastasis for ER+/PR-phenotype differed from ER+/PR + phenotype.…”

“…Consistent with previous studies [17,18], the survival for IBC was very poor in our research (5-year BCSS and OS rate, 47.3% and 42.5%, respectively). On account of the poor prognosis for IBC, previous researches tried to nd the risk factors and demonstrated many independent predicted factors, such as race, lymph node ratio, AJCC stage, histological grade, ER status, PR status, HER2 status, surgery status, and radiotherapy status [14,17].…”

Characteristics, Prognosis, and Competing Risk Nomograms of Cutaneous Malignant Melanoma: Evidence for Pigmentary Disorders

“…In practice, the treatment and surveillance of those patients should be different. Although the causal inference method could explicitly unveil the effect modification of different types of CMM on patient outcomes and identify vulnerable groups at the population level ( 32 ), comprehensive nomograms could provide estimation of the cumulative incidence of death at an individual patient level ( 33 ).…”

A nomogram for predicting survival in patients with skin non-keratinizing large cell squamous cell carcinoma: A study based on the Surveillance, Epidemiology, and End Results database

“…Nomograms are highly accurate and easy-to-use tools that are based on many types of tumor prediction models (10) and make it possible to estimate the survival probability of a specific patient. Many researchers have established nomograms for various cancers, including of the tonsils, parotid gland, and breast (11)(12)(13), but no nomogram specifically designed for NKLCSCC has been developed. Therefore we developed and evaluated a nomogram for NKLCSCC using pertinent data from the Surveillance, Epidemiology, and End Results (SEER) database to further investigate the prognosis factors for NKLCSCC and its specific treatment.…”