Nomograms to Predict Survival in Patients with Lung Squamous Cell Cancer: A Population-Based Study

et al. 2022

Preprint

Background Lung squamous cell carcinoma is a common subtype of non-small cell lung cancer. Our study aimed to construct and validate a nomogram model and to predict overall survival for patients with lung squamous cell carcinoma undergoing surgical treatment. Methods A total of 8,078 patients eligible for recruitment between 2010 and 2015 were selected from the Surveillance, Epidemiology and End Results database. They were further randomly divided into training and validation cohorts. Univariable and multivariable Cox regression analyses were used to identify the risk factors affecting the prognosis for constructing the nomogram. The discrimination and calibration of the established nomogram were evaluated using receiver the operating characteristic curve and calibration plots. In addition, decision curve analysis was performed to evaluate the clinical utility. Finally, we plotted Kaplan-Meier survival curves and developed risk stratification systems. Results Seven variables were selected to establish the nomogram for lung squamous cell carcinoma. The area under the curve in the receiver the operating characteristic curve analysis revealed 0.658, 0.651, and 0.647 in the training cohort and 0.673, 0.667, and 0.658 in the validation cohort at 1-, 2-, and 3-year survival, respectively. The calibration curves showed satisfactory consistencies between nomogram-predicted and observed survival probability at 1-, 2-, and 3- year overall survival in training and validation cohorts. The decision curve analysis showed the established nomogram had great clinical net benefit, indicating high clinical application value. In risk stratification systems, patients were divided into three risk groups. The Kaplan-Meier survival curves indicated that a significant difference in overall survival were observed among the three groups (P༜0.001). Conclusions A prognostic nomogram for overall survival of lung squamous cell carcinoma patients after surgical treatment was developed and validated, which may assist clinicians in evaluating prognosis of and facilitate doctors to provide highly individualized therapy.

Section: Discussionmentioning

confidence: 54%

A nomogram for predicting postoperative overall survival of patients with lung squamous cell carcinoma: a SEER-based study

et al. 2022

Preprint

“…This study focused on the brain metastasis while our study excluded M1, N2, and N3 stage LSCC patients who were not suitable for surgical treatment and focused on the patients' survival. Zheng, Gu, Wang, Hu, Xu 24 performed a nomogram study that had several similarities to ours, which satisfactorily predicted 3-, 5-, and 7-year cancer-speci c survival and OS rates for patients with LSCC. This study applied limited methods to evaluate the quality of predicted models and paid attention to all-stage lung cancer patients regardless of whether there were any indications for surgery or not.…”

Section: Discussionmentioning

confidence: 55%

A nomogram for predicting postoperative overall survival of patients with lung squamous cell carcinoma: a SEER-based study

et al. 2022

Preprint

Background Lung squamous cell carcinoma (LSCC) is a common subtype of non-small cell lung cancer. Our study aimed to construct and validate a nomogram for predicting overall survival (OS) for postoperative LSCC patients. Methods A total of 8,078 patients eligible for recruitment between 2010 and 2015 were selected from the Surveillance, Epidemiology and End Results database. The study outcomes were 1-, 2-, and 3-year OS. Analyses performed included univariable and multivariable Cox regression, receiver the operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA), and Kaplan-Meier survival curves. Results Seven variables were selected to establish the nomogram for LSCC. The area under the curve in ROC curve revealed 0.658, 0.651, and 0.647 in the training cohort and 0.673, 0.667, and 0.658 in the validation cohort at 1-, 2-, and 3-year survival. The calibration curves showed satisfactory consistencies between nomogram-predicted and observed survival probability. DCA showed great clinical net benefit. In risk stratification systems, patients were divided into three risk groups with a significant difference in OS in Kaplan-Meier curves (P༜0.001). Conclusions A prognostic nomogram for OS of postoperative LSCC patients was developed and validated, which may assist clinicians in evaluating prognosis and providing highly individualized therapy.

“…This study focused on the brain metastasis while our study excluded M1, N2, and N3 stage LSCC patients who were not suitable for surgical treatment and focused on the patients' survival. Zheng [24] performed a nomogram study that had several similarities to ours, which satisfactorily predicted 3-, 5-, and 7-year cancer-speci c survival and OS rates for patients with LSCC. This study applied limited methods to evaluate the quality of predicted models and paid attention to all-stage lung cancer patients regardless of whether there were any indications for surgery or not.…”

Section: Discussionmentioning

confidence: 72%

A nomogram for predicting postoperative overall survival of patients with lung squamous cell carcinoma: a SEER-based study

et al. 2022

Preprint

Background Lung squamous cell carcinoma (LSCC) is the most common histological subtype of all lung cancer. Although the overall prognosis of lung cancer has improved, the predictable nomogram model of LSCC has not improved significantly. Our study aimed to construct and validate a nomogram model and to predict overall survival (OS) for patients with LSCC undergoing surgical treatment. Methods A total of 8,078 patients identified to have LSCC between 2010 and 2015 were selected from the Surveillance, Epidemiology and End Results (SEER) database. They were further randomly divided into training and validation cohorts. Univariable and multivariable Cox regression analyses were used to identify the risk factors affecting the prognosis for constructing the nomogram. The discrimination and calibration of the established nomogram were evaluated using receiver operating characteristic (ROC) curve, area under ROC curve (AUC), and calibration plots. In addition, decision curve analysis (DCA) was performed to evaluate the clinical utility. Finally, we plotted Kaplan-Meier survival curves and developed risk stratification systems. Results Seven variables were selected to establish the nomogram for LSCC. The AUC value in the ROC curve analysis revealed 0.658, 0.651, and 0.647 in the training cohort and 0.673, 0.667, and 0.658 in the validation cohort at 1-, 2-, and 3-year survival, respectively. The calibration curves showed satisfactory consistencies between nomogram-predicted and observed survival probability at 1-, 2-, and 3- year OS in training and validation cohorts. The DCA curve showed the established nomogram had great clinical net benefit, indicating high clinical application value. In risk stratification systems, patients were divided into three risk groups: low risk (total points༜95), middle risk (95 ≤ total points༜143), high risk (total points ≥ 143). The Kaplan-Meier survival curves indicated that significant difference in OS were observed among the three groups (P༜0.001). Conclusions A prognostic nomogram for OS of LSCC patients after surgical treatment was developed and validated, which may assist clinicians in evaluating prognosis of and facilitate doctors to provide highly individualized therapy.