The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Development and Validation of a Nomogram for Predicting Survival in Patients With Resected Non–Small-Cell Lung Cancer
Open accessAbstract
Purpose: A nomogram is a useful and convenient tool for individualized cancer prognoses. We sought to develop a clinical nomogram for predicting survival of patients with resected non–small-cell lung cancer (NSCLC). Patients and Methods: On the basis of data from a multi-institutional registry of 6,111 patients with resected NSCLC in China, we identified and integrated significant prognostic factors for survival to build a nomogram. The model was subjected to bootstrap internal validation and to external validation with a separate cohort of 2,148 patients from the International Association for the Study of Lung Cancer (IASLC) database. The predictive accuracy and discriminative ability were measured by concordance index (C-index) and risk group stratification. Results: A total of 5,261 patients were included for analysis. Six independent prognostic factors were identified and entered into the nomogram. The calibration curves for probability of 1-, 3-, and 5-year overall survival (OS) showed optimal agreement between nomogram prediction and actual observation. The C-index of the nomogram was higher than that of the seventh edition American Joint Committee on Cancer TNM staging system for predicting OS (primary cohort, 0.71 v 0.68, respectively; P < .01; IASLC cohort, 0.67 v 0.64, respectively; P = .06). The stratification into different risk groups allowed significant distinction between survival curves within respective TNM categories. Conclusion: We established and validated a novel nomogram that can provide individual prediction of OS for patients with resected NSCLC. This practical prognostic model may help clinicians in decision making and design of clinical studies.
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Jemal, A., Siegel, R., Xu, J., & Ward, E. (2010) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.20073 · Cited by 12,596
Harrell, F. E. (2001) · Springer Series in Statistics · doi:10.1007/978-1-4757-3462-1 · Cited by 9,195
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Travis, W. D., Brambilla, E., Noguchi, M., Nicholson, A. G., Geisinger, K. R., Yatabe, Y., Beer, D. G., Powell, C. A., Riely, G. J., Van Schil, P. E., et al. (2011) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e318206a221 · Cited by 4,792
Goldstraw, P., Crowley, J., Chansky, K., Giroux, D. J., Groome, P. A., Rami-Porta, R., Postmus, P. E., Rusch, V., & Sobin, L. (2007) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e31812f3c1a · Cited by 3,655
How To Build and Interpret a Nomogram for Cancer Prognosis
Iasonos, A., Schrag, D., Raj, G. V., & Panageas, K. S. (2008) · Journal of Clinical Oncology · doi:10.1200/jco.2007.12.9791 · Cited by 3,222
Prognostic Nomogram for Intrahepatic Cholangiocarcinoma After Partial Hepatectomy
Wang, Y., Li, J., Xia, Y., Gong, R., Wang, K., Yan, Z., Wan, X., Liu, G., Wu, D., Shi, L., et al. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.41.5984 · Cited by 1,057
Valentini, V., van Stiphout, R. G. P. M., Lammering, G., Gambacorta, M. A., Barba, M. C., Bebenek, M., Bonnetain, F., Bosset, J.-F., Bujko, K., Cionini, L., et al. (2011) · Journal of Clinical Oncology · doi:10.1200/jco.2010.33.1595 · Cited by 563
Multi-Institutional Validation of a New Renal Cancer–Specific Survival Nomogram
Karakiewicz, P. I., Briganti, A., Chun, F. K.-H., Trinh, Q.-D., Perrotte, P., Ficarra, V., Cindolo, L., De La Taille, A., Tostain, J., Mulders, P. F. A., et al. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2006.06.1218 · Cited by 536
Chansky, K., Sculier, J.-P., Crowley, J. J., Giroux, D., Van Meerbeeck, J., & Goldstraw, P. (2009) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e3181a7716e · Cited by 456
Cited by
Gemenetzis, G., Bagante, F., Griffin, J. F., Rezaee, N., Javed, A. A., Manos, L. L., Lennon, A. M., Wood, L. D., Hruban, R. H., Zheng, L., et al. (2017) · Annals of Surgery · doi:10.1097/sla.0000000000001988 · Cited by 127
Self-citationFrom past to future: Bibliometric analysis of global research productivity on nomogram (2000–2021)
Wang, X., Lu, J., Song, Z., Zhou, Y., Liu, T., & Zhang, D. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.997713 · Cited by 140
“Liang WH constructed a nomogram based on the clinical data of 6,111 patients with non-small cell lung cancer (NSCLC) in China to identify 6 independent prognostic factors, including gender, age, and pathological type (17).”
Method
Metadata
- Authors
- Liang, W., Zhang, L., Jiang, G., Wang, Q., Liu, L., Liu, D., Wang, Z., Zhu, Z., Deng, Q., Xiong, X., Shao, W., Shi, X., & He, J.
- Venue
- Journal of Clinical Oncology
- Published
- 2015-03-10
- Volume
- 33
- Issue
- 8
- Pages
- 861-869
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W1975266543
- Cited by
- 649
- References
- 23
- FWCI
- 26.64
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Development and Validation of a Nomogram for Predicting Survival in Patients With Resected Non–Small-Cell Lung Cancer. https://app.cochat.ai/papers/10.1200/jco.2014.56.6661
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- Liang, W., Zhang, L., Jiang, G., Wang, Q., Liu, L., Liu, D., Wang, Z., Zhu, Z., Deng, Q., Xiong, X., Shao, W., Shi, X., & He, J. (2015). Development and Validation of a Nomogram for Predicting Survival in Patients With Resected Non–Small-Cell Lung Cancer. Journal of Clinical Oncology. https://doi.org/10.1200/jco.2014.56.6661
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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