Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis

Wen, Junmiao; Liu, Di; Xu, Xinyan; Chen, Donglai; Chen, Yongbing; Sun, Liang; Chen, Jiayan; Fan, Min

doi:10.2147/cmar.s186546

Cited by 19 publications

(32 citation statements)

References 40 publications

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“…Variables were entered into a multivariate Cox proportional hazards regression model using backward stepwise selection with the Akaike information criterion (AIC), and coefficients of the predictors were calculated. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated . We then constructed the nomogram using the identified prognostic factors to predict one‐year and three‐year survival rates.…”

Section: Methodsmentioning

confidence: 99%

Survival analysis via nomogram of surgical patients with malignant pleural mesothelioma in the Surveillance, Epidemiology, and End Results database

et al. 2019

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Background Malignant pleural mesothelioma (MPM) is a rare but aggressive tumor that originates from the pleura and has a poor prognosis. Eligible patients can benefit from surgery, but their survival is affected by many factors. Therefore, we created a graphic model that could predict the prognosis of surgically treated patients. Methods We retrospectively analyzed data from the Surveillance, Epidemiology, and End Results database from 2004 to 2014 to identify the key factors affecting the prognosis of surgically treated MPM patients. On this basis we built a nomogram to predict survival. We then evaluated the performance of the nomogram in a validation cohort. Results In a training cohort of 828 cases, independent prognostic factors, including age, gender, histological type, differentiation, N stage, chemotherapy, type of surgery, and lymph node dissection, were identified. We then developed a nomogram to evaluate individual patient survival. In Kaplan–Meier analysis, a higher score in the nomogram was associated with a worse prognosis. We also used a validation cohort consisting of 312 patients to evaluate the performance of the nomogram, which was well calibrated and had good discrimination ability, with concordance indices of 0.715 and 0.656 for the training and validation cohorts, respectively. Conclusion This study has improved our understanding of resected MPM and shown that key factors, including age and histological type, are associated with overall survival. The nomogram is a reliable tool that can help clinicians turn individualized prediction into reality and maximize patient benefit by identifying the most beneficial treatment approach.

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Section: Methodsmentioning

confidence: 99%

Survival analysis via nomogram of surgical patients with malignant pleural mesothelioma in the Surveillance, Epidemiology, and End Results database

et al. 2019

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“…Bhattacharyya et al ( 16 ) suggested that positive nodal disease had a significant negative effect on OS for primary tracheal malignancies, as positive regional nodal disease diminished survival by greater than 50% compared to N0 disease. Wen et al ( 17 ) also indicated that lymph node involvement was important for the prognosis of primary tracheal tumors. Our study confirms this view in primary tracheal small cell tumors.…”

Section: Discussionmentioning

confidence: 98%

Clinical features and prognosis of primary tracheal small cell carcinoma: a population-based analysis

Chen¹,

Yang²,

Zhang³

et al. 2020

Transl Cancer Res TCR

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Background: Primary tracheal small cell carcinoma (SCC) is an uncommon malignancy; therefore, its clinical features and prognosis are still unclear.Methods: We used the population-based Surveillance, Epidemiology, and End Results (SEER) database to elucidate the clinical features and prognosis of primary tracheal SCC. The clinical features were assessed by using the chi-square test. Overall survival (OS) was computed using the Kaplan-Meier method, and a Cox proportional hazards analysis was performed to evaluate the prognostic factors.Results: From 1973 to 2015, 1,392 primary tracheal tumor cases were reported in the SEER database, 75 (5.4%) of which were SCC. Age, sex, race, extent of disease, lymph node involvement, surgery and radiation treatment were similar between patients with SCC and those with squamous cell carcinoma (SQC), but patients with SCC were more likely to receive chemotherapy (65.8% vs. 28.2%, respectively; P<0.001).The 1-, 3-and 5-year OS rates of patients with SCC were 37.8%, 12.4% and 7.1%, respectively, and the median survival duration was 10.0 months, which was much worse than that observed for patients with other histopathological types of tracheal cancer. Among patients aged 60-100 years and those with regional lymph node involvement, the OS for patients with SQC was superior to that for patients with SCC (P=0.034 and P=0.016, respectively). According to the multivariate analysis, age and lymph node involvement are independent prognostic factors of SCC. Conclusion:Primary tracheal SCC is a rare carcinoma with a poor prognosis. Age and lymph node involvement are independent prognostic factors of SCC.

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“… 20 The prognostic variables identified by the multivariate analyses were used to develop nomograms to predict OS and cancer-specific mortality. 21 A calibration plot described the fitting degree between the actual survival and the nomogram predicting survival. The clinical utility of the nomograms was assessed by decision curve analysis (DCA).…”

Section: Methodsmentioning

confidence: 99%

Comprehensive analysis of prognostic value of lymph node classifications in esophageal squamous cell carcinoma: a large real-world multicenter study

Wen

Chen

et al. 2021

Ther Adv Med Oncol

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Background: We aim to assess the prognostic ability of three common lymph node–based staging algorithms, namely, the number of positive lymph nodes (pN), the lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) in patients with esophageal squamous cell carcinoma (ESCC). Methods: A total of 3902 ESCC patients treated at 10 Chinese institutions between 2003 and 2013 were included, along with 2465 patients from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic ability of the aforementioned algorithms was evaluated using time-dependent receiver operating characteristic (tdROC) curves, R2, Harrell’s concordance index (C-index), and the likelihood ratio chi-square score. The primary outcomes included cancer-specific survival (CSS), overall survival (OS), and CSS with a competing risk of death by non-ESCC causes. Results: LODDS had better prognostic performance than pN or LNR in both continuous and stratified patterns. In the multicenter cohort, the multivariate analysis showed that the model based on LODDS classification was superior to the others in predictive accuracy and discriminatory capacity. Two nomograms integrating LODDS classification and other clinicopathological risk factors associated with OS as well as cancer-specific mortality were constructed and validated in the SEER database. Finally, a novel TNLODDS classification which incorporates the LODDS classification was built and categorized patients in to three new stages. Conclusion: Among the three lymph node–based staging algorithms, LODDS demonstrated the highest discriminative capacity and prognostic accuracy for ESCC patients. The nomograms and novel TNLODDS classification based on LODDS classification could serve as precise evaluation tools to assist clinicians in estimating the survival time of individual patients and improving clinical outcomes postoperatively in the future.

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Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis

Cited by 19 publications

References 40 publications

Survival analysis via nomogram of surgical patients with malignant pleural mesothelioma in the Surveillance, Epidemiology, and End Results database

Survival analysis via nomogram of surgical patients with malignant pleural mesothelioma in the Surveillance, Epidemiology, and End Results database

Clinical features and prognosis of primary tracheal small cell carcinoma: a population-based analysis

Comprehensive analysis of prognostic value of lymph node classifications in esophageal squamous cell carcinoma: a large real-world multicenter study

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