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. 2023 May 6;9(5):e15924.
doi: 10.1016/j.heliyon.2023.e15924. eCollection 2023 May.

Development and validation of a novel nomogram to predict the overall survival of patients with large cell lung cancer: A surveillance, epidemiology, and end results population-based study

Hongxia Zhou  1 , Pengxiang Gao  2 , Fangpeng Liu  2 , Liangliang Shi  3 , Longhua Sun  2 , Wei Zhang  2   4   5 , Xinping Xu  2   4   5 , Xiujuan Liu  1
Affiliations

Development and validation of a novel nomogram to predict the overall survival of patients with large cell lung cancer: A surveillance, epidemiology, and end results population-based study

Hongxia Zhou et al. Heliyon. .

Abstract

Background: Large cell lung cancer (LCLC) is a rare subtype of non-small cell lung carcinoma (NSCLC), and little is known about its clinical and biological characteristics.

Methods: LCLC patient data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. All patients were randomly divided into a training group and a validation group at a ratio of 7:3. The independent prognostic factors that were identified (P < 0.01) by stepwise multivariate Cox analysis were incorporated into an overall survival (OS) prediction nomogram, and risk-stratification systems, C-index, time-ROC, calibration curve, and decision curve analysis (DCA) were applied to evaluate the quality of the model.

Results: Nine factors were incorporated into the nomogram: age, sex, race, marital status, 6th AJCC stage, chemotherapy, radiation, surgery and tumor size. The C-index of the predicting OS model in the training dataset and in the test dataset was 0.757 ± 0.006 and 0.764 ± 0.009, respectively. The time-AUCs exceeded 0.8. The DCA curve showed that the nomogram has better clinical value than the TNM staging system.

Conclusions: Our study summarized the clinical characteristics and survival probability of LCLC patients, and a visual nomogram was developed to predict the 1-year, 3-year and 5-year OS of LCLC patients. This provides more accurate OS assessments for LCLC patients and helps clinicians make personal management decisions.

Keywords: Large cell lung cancer; Nomogram; Overall survival; Prognostic.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
The nomogram to predict 1-, 3-, 5-year overall survival of large cell lung cancer patients.
Fig. 2
Fig. 2
The Kaplan Meier curve for re-grouped patients with large cell lung cancer according to the nomogram scores. OS, cancer-specific survival. Risk score level:3:high risk (total nomo scores＞250) 2:medium risk (150＜total nomo scores ≤250) and 1: low risk (total nomo scores≤150).
Fig. 3
Fig. 3
Calibration curves for OS by using traindata (A, B, C) and testdata (D, E, F).
Fig. 4
Fig. 4
Time-ROC of 1-, 3-, 5-year AUC for OS by using traindata(A) and testdata(B), Decision curve analysis of the current nomogram model and the 6th edition AJCC TNM staging system for predicting 12,36 and 60 months overall survival probability(C).
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References

    1. Sung H., Ferlay J., Siegel R.L., Laversanne M., Soerjomataram I., Jemal A., Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA A Cancer J. Clin. 2021;71(3):209–249. doi: 10.3322/caac.21660. - DOI - PubMed
    1. Liang R., Chen T.-X., Wang Z.-Q., Jin K.-W., Zhang L.-Y., Yan Q.-N., Wang .W.-P. A retrospective analysis of the clinicopathological characteristics of large cell carcinoma of the lung. Exp. Ther. Med. 2015;9(1):197–202. - PMC - PubMed
    1. Pelosi G., Barbareschi M., Cavazza A., Graziano P., Rossi G., Papotti M. Large cell carcinoma of the lung: a tumor in search of an author. A clinically oriented critical reappraisal. Lung Cancer. 2015;87(3):226–231. doi: 10.1016/j.lungcan.2015.01.008. - DOI - PubMed
    1. Travis W.D., Brambilla E., Nicholson A.G., Yatabe Y., Austin J.H.M., Beasley M.B.…W.H.O. Panel The 2015 world Health organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. J. Thorac. Oncol. 2015;10(9):1243–1260. doi: 10.1097/JTO.0000000000000630. - DOI - PubMed
    1. Zuo Z., Zhang G., Song P., Yang J., Li S., Zhong Z.…He J. Survival nomogram for stage IB non-small-cell lung cancer patients, based on the SEER database and an external validation cohort. Ann. Surg Oncol. 2021;28(7):3941–3950. doi: 10.1245/s10434-020-09362-0. - DOI - PubMed

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