Incidence, prognostic factors, and a nomogram of lung cancer with bone metastasis at initial diagnosis: a population-based study

Abstract

Background: Bone is one of the common metastatic sites of lung cancer, and its prognosis is not optimistic. We performed a study to evaluate the incidence, survival, and prognostic factors of lung cancer with bone metastasis (LCBM) at initial diagnosis, and to develop a nomogram to predict its outcomes. Methods: We conducted a retrospective study choosing 13,541 patients with LCBM from the Surveillance, Epidemiology, and End Results (SEER) 18 registry database. An X-tile analysis provided the optimal age cutoff point. The incidence, overall survival, and prognosis of bone metastasis were evaluated according to the patient information, characteristics of the tumor, and therapy. We also used multivariable Cox regression to estimate mortality hazard ratios (HRs) among patients with LCBM, while a visual nomogram was established to judge the prognosis. Results: The incidence of disease increased with age, but survival rates show the opposite trend. The median survival time was about 4 months. In addition, although the differences for patient race is not significant (P=0.445), White patients are prone to have bone metastases from lung cancer according to the incidence analysis. The difference for laterality is also not significant (P=0.534), while the factors of age, gender, the total number of sites, histological types, grade, tumor size, and treatment are significantly related to the outcome of patients with LCBM. Furthermore, our nomogram could predict the probability of surviving to the median survival time of the population with a c-index of 0.72. Conclusions: Age, characteristics of the tumor, and therapy should be considered for prediction of prognosis for patients with lung cancer bone metastasis. Putatively, the younger patients and the patients with chemotherapy and surgery may indicate improved survival.

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm

“…According to our study, tumor size is a significant factor affecting the patient prognosis, which has not been recognized previously [11][12][13]. T stage roughly classifies tumor size or depth of invasion, but it cannot reflect the specific character of NSCLC patients with BM and accurately predict the prognosis, because the tumor size of the same period varies greatly [23][24][25].…”

“…More importantly, many other factors should be considered and involved in predicting the prognosis of patients [ 9 , 10 ]. Survival prediction models designed for lung cancer with BM specifically have been reported previously [ 11 – 13 ]. However, the performance of these models is barely satisfactory as these models are based on the simple Cox regression model but not established as a survival prediction model for NSCLC with BM particularly.…”

Bronchoscopic treatment of inoperable nonsmall cell lung cancer

“…A recent analysis using data from the Surveillance, Epidemiology, and End Results database from 2010 to 2016 sought to assess the incidence of metastatic disease in lung cancer at time of diagnosis and evaluate survival and prognostic factors [9]. In this analysis, bone was the most common site of metastasis, with an incidence of nine cases per 100 000 people, followed by lung, liver and brain [9]. Most patients with distant metastatic disease are not surgical candidates [10,11].…”

Nomogram for Predicting Brain Metastases in Lung Squamous Cell Carcinoma Patients: A SEER -Based Study

“…Therefore, the nomogram should be renewed with more clinical data, such as surgery pattern, radiotherapy dosage, chemotherapy regimens, etc. Next, due to the insu cient data, our nomogram could only be validated internally (24,25). So, validation with datacohorts of large size and longer follow-up remains to be done.…”