Survival Nomogram for Stage IB Non-Small-Cell Lung Cancer Patients, Based on the SEER Database and an External Validation Cohort

Zuo, Zhichao; Zhang, Guochao; Song, Peng; Yang, Jing; Li, Shuiting; Zhong, Zhihai; Tan, Qinghao; Wang, Liming; Xue, Qi; Gao, Shugeng; Sun, Nan; He, Jie

doi:10.1245/s10434-020-09362-0

Cited by 81 publications

(67 citation statements)

References 33 publications

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“…In all, six independent risk factors (age, race, sex, tumor histological, grade, surgery, and group) were concluded from MVA and contributed for nomogram model. Recently, study considering stage IB NSCLC concluding similar independent risk factors, including age, sex, histology, tumor differentiation (19), and it was widely proved that among lung cancer patients, female patients have a better prognosis (20), which was also revealed in our research.…”

Section: Discussionsupporting

confidence: 73%

The clinical prognostic factors of patients with stage IB lung adenocarcinoma

Sui¹,

Liang²,

Hu³

et al. 2021

Transl Cancer Res TCR

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Background Lung adenocarcinoma (ADC) at stage IB has its own prognostic characteristics. This study aimed to investigate the clinical factors that may affect the prognosis of patients with stage IB ADC. Methods The data of ADC cases were selected from the Surveillance, Epidemiology, and End Results (SEER) database (2010–2016) and patients in Zhongshan Hospital, Fudan University (Department of Thoracic Surgery, 2015–2016). Kaplan-Meier method was used to obtain the overall survival (OS). Factors that significantly related to the prognosis were evaluated by univariate and multivariate analysis (UVA, MVA) using the Cox model. A nomogram was developed and validated to predict the 3-year OSs of those patients. Results 7,605 patients with stage IB ADC were included ultimately and were divided into two groups, a training cohort (n=5,324) and a test cohort (n=2,281). Besides, there was a validation cohort (n=272) for the verification of the nomogram model. Those with significantly older age, male, the white race, lower grades of tumor differentiation, larger tumor size (31–40 mm) without pleural layer (PL) invasion as well as receiving sublobectomy suffered from poorer survival (P<0.001), which were identified as independent factors for stage IB ADC (P<0.001), and according to which, a nomogram model was created. Conclusions Age, sex, race, histological grade, surgery to the primary site, and tumor size combined with PL invasion were independent risk factors for stage IB ADC, based on which a nomogram was constructed to predict the prognosis.

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Section: Discussionsupporting

confidence: 73%

The clinical prognostic factors of patients with stage IB lung adenocarcinoma

Sui¹,

Liang²,

Hu³

et al. 2021

Transl Cancer Res TCR

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“…A premature mortality prediction model has become essential for patients with advanced EOC in order to guide oncologists to personalize treatments for patients. The Surveillance, Epidemiology, and the End Results (SEER) database (https://seer.Cancer.gov/) have been widely used in the study of tumor pathogenesis and survival (6,7). The SEER database registers ∼34.6% of U.S. cancer patients and contains a wealth of clinical information.…”

Section: Introductionmentioning

confidence: 99%

A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer

et al. 2021

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Background: Ovarian cancer is a common gynecological malignancy, most of which is epithelial ovarian cancer (EOC). Advanced EOC is linked with a higher incidence of premature death. To date, no effective prognostic tools are available to evaluate the possibility of early death in patients with advanced EOC.Methods: Advanced (FIGO stage III and IV) EOC patients who were enrolled in the Surveillance, Epidemiology, and End Results database between 2004 and 2015 were regarded as subjects and studied. We aimed to construct a nomogram that can deliver early death prognosis in patients with advanced EOC by identifying crucial independent factors using univariate and multivariate logistic regression analyses to help deliver accurate prognoses.Results: In total, 13,403 patients with advanced EOC were included in this study. Three hundred ninety-seven out of a total of 9,379 FIGO stage III patients died early. There were 4,024 patients with FIGO stage IV, 414 of whom died early. Nomograms based on independent prognostic factors have the satisfactory predictive capability and clinical pragmatism. The internal validation feature of the nomogram demonstrated a high level of accuracy of the predicted death.Conclusions: By analyzing data from a large cohort, a clinically convenient nomogram was established to predict premature death in advanced EOC. This tool can aid clinicians in screening patients who are at higher risk for tailoring treatment plans.

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“…As a new form of prediction models, a nomogram can directly visualize the predicted LNM and DM, which provides a reference for further examinations and clinical decision-making. At present, many nomograms can be used to predict the diagnosis and prognosis of cancers, but there are many problems like the sample size ( 21 ), low C-index and the prediction accuracy of the model ( 22 ), insufficient inclusion and exclusion criteria ( 23 ), lack of cutoff values ( 24 – 26 ), and latest evidence ( 27 ). To our knowledge, this is the only published study to establish a nomogram to predict the incidence and survival rate of LNM and DM in T1–2 ESCA patients by analyzing latest cancer data from 1975 to 2018 in the SEER database.…”

Section: Discussionmentioning

confidence: 99%

“…), low C-index and the prediction accuracy of the model(22), insufficient inclusion and exclusion criteria(23), lack of cutoff values(24)(25)(26), and latest evidence(27). To our knowledge, this is the only published study to establish a nomogram to predict the incidence and survival rate of LNM and DM in T1-2 ESCA patients by analyzing latest cancer data from 1975 to 2018 in the SEER database.…”

mentioning

confidence: 99%

A Population-Based Study: How to Identify High-Risk T1–2 Esophageal Cancer Patients?

Tao

et al. 2021

Front. Oncol.

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BackgroundDue to individualized conditions of lymph node metastasis (LNM) and distant metastasis (DM), the following therapeutic strategy and diagnosis of T1–2 esophageal cancer (ESCA) patients are varied. A prediction model for identifying risk factors for LNM, DM, and overall survival (OS) of high-risk T1–2 ESCA patients is of great significance to clinical practice.MethodsA total of 1,747 T1–2 ESCA patients screened from the surveillance, epidemiology, and end results (SEER) database were retrospectively analyzed for their clinical data. Univariate and multivariate logistic regression models were established to screen out risk factors for LNM and DM of T1-2 ESCA patients, while those of OS were screened out using the Cox regression analysis. The identified risk factors for LNM, DM, and OS were then subjected to the establishment of three nomograms, respectively. The accuracy of the nomograms was evaluated by depicting the calibration curve, and the predictive value and clinical utility were evaluated by depicting the clinical impact curve (CIC) and decision curve analysis (DCA), respectively.ResultsThe age, race, tumor grade, tumor size, and T-stage were significant factors for predicting LNM of T1–2 ESCA patients (p < 0.05). The age, T-stage, tumor grade, and tumor size were significant factors for predicting DM of T1–2 ESCA patients (p < 0.05). The age, race, sex, histology, primary tumor site, tumor size, N-stage, M-stage, and surgery were significant factors for predicting OS of T1–2 ESCA patients (p < 0.05). The C-indexes of the three nomograms constructed by these factors were 0.737, 0.764, and 0.740, respectively, suggesting that they were clinically effective.ConclusionsThe newly constructed nomograms can objectively and accurately predict the LNM, DM, and OS of T1–2 ESCA patients, which contribute to the individualized decision making before clinical management.

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Survival Nomogram for Stage IB Non-Small-Cell Lung Cancer Patients, Based on the SEER Database and an External Validation Cohort

Cited by 81 publications

References 33 publications

The clinical prognostic factors of patients with stage IB lung adenocarcinoma

The clinical prognostic factors of patients with stage IB lung adenocarcinoma

A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer

A Population-Based Study: How to Identify High-Risk T1–2 Esophageal Cancer Patients?

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