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Prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer
BACKGROUND: Health-related quality of life (HRQoL) is a critical aspect of overall well-being for patients with lung cancer, particularly those with metastatic spinal cord compression (MSCC). However, there is currently a lack of universal evaluation of HRQoL in this specific patient population. The...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502718/ https://www.ncbi.nlm.nih.gov/pubmed/37720536 http://dx.doi.org/10.3389/fendo.2023.1206840 |
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author | Fu, Yufang Shi, Weiqing Zhao, Jing Cao, Xuyong Cao, Yuncen Lei, Mingxing Su, Xiuyun Cui, Qiu Liu, Yaosheng |
author_facet | Fu, Yufang Shi, Weiqing Zhao, Jing Cao, Xuyong Cao, Yuncen Lei, Mingxing Su, Xiuyun Cui, Qiu Liu, Yaosheng |
author_sort | Fu, Yufang |
collection | PubMed |
description | BACKGROUND: Health-related quality of life (HRQoL) is a critical aspect of overall well-being for patients with lung cancer, particularly those with metastatic spinal cord compression (MSCC). However, there is currently a lack of universal evaluation of HRQoL in this specific patient population. The aim of this study was to develop a nomogram that can accurately predict HRQoL outcomes in patients with lung cancer-related MSCC. METHODS: A total of 119 patients diagnosed with MSCC secondary to lung cancer were prospectively collected for analysis in the study. The least absolute shrinkage and selection operator (LASSO) regression analysis, along with 10-fold cross-validation, was employed to select the most significant variables for inclusion in the nomogram. Discriminative and calibration abilities were assessed using the concordance index (C-index), discrimination slope, calibration plots, and goodness-of-fit tests. Net reclassification index (NRI) and integrated discrimination improvement (IDI) analyses were conducted to compare the nomogram’s performance with and without the consideration of comorbidities. RESULTS: Four variables were selected to construct the final nomogram, including the Eastern Cooperative Oncology Group (ECOG) score, targeted therapy, anxiety scale, and number of comorbidities. The C-index was 0.87, with a discrimination slope of 0.47, indicating a favorable discriminative ability. Calibration plots and goodness-of-fit tests revealed a high level of consistency between the predicted and observed probabilities of poor HRQoL. The NRI (0.404, 95% CI: 0.074–0.734, p = 0.016) and the IDI (0.035, 95% CI: 0.004–0.066, p = 0.027) confirmed the superior performance of the nomogram with the consideration of comorbidities. CONCLUSIONS: This study develops a prediction nomogram that can assist clinicians in evaluating postoperative HRQoL in patients with lung cancer-related MSCC. This nomogram provides a valuable tool for risk stratification and personalized treatment planning in this specific patient population. |
format | Online Article Text |
id | pubmed-10502718 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105027182023-09-16 Prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer Fu, Yufang Shi, Weiqing Zhao, Jing Cao, Xuyong Cao, Yuncen Lei, Mingxing Su, Xiuyun Cui, Qiu Liu, Yaosheng Front Endocrinol (Lausanne) Endocrinology BACKGROUND: Health-related quality of life (HRQoL) is a critical aspect of overall well-being for patients with lung cancer, particularly those with metastatic spinal cord compression (MSCC). However, there is currently a lack of universal evaluation of HRQoL in this specific patient population. The aim of this study was to develop a nomogram that can accurately predict HRQoL outcomes in patients with lung cancer-related MSCC. METHODS: A total of 119 patients diagnosed with MSCC secondary to lung cancer were prospectively collected for analysis in the study. The least absolute shrinkage and selection operator (LASSO) regression analysis, along with 10-fold cross-validation, was employed to select the most significant variables for inclusion in the nomogram. Discriminative and calibration abilities were assessed using the concordance index (C-index), discrimination slope, calibration plots, and goodness-of-fit tests. Net reclassification index (NRI) and integrated discrimination improvement (IDI) analyses were conducted to compare the nomogram’s performance with and without the consideration of comorbidities. RESULTS: Four variables were selected to construct the final nomogram, including the Eastern Cooperative Oncology Group (ECOG) score, targeted therapy, anxiety scale, and number of comorbidities. The C-index was 0.87, with a discrimination slope of 0.47, indicating a favorable discriminative ability. Calibration plots and goodness-of-fit tests revealed a high level of consistency between the predicted and observed probabilities of poor HRQoL. The NRI (0.404, 95% CI: 0.074–0.734, p = 0.016) and the IDI (0.035, 95% CI: 0.004–0.066, p = 0.027) confirmed the superior performance of the nomogram with the consideration of comorbidities. CONCLUSIONS: This study develops a prediction nomogram that can assist clinicians in evaluating postoperative HRQoL in patients with lung cancer-related MSCC. This nomogram provides a valuable tool for risk stratification and personalized treatment planning in this specific patient population. Frontiers Media S.A. 2023-09-01 /pmc/articles/PMC10502718/ /pubmed/37720536 http://dx.doi.org/10.3389/fendo.2023.1206840 Text en Copyright © 2023 Fu, Shi, Zhao, Cao, Cao, Lei, Su, Cui and Liu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Fu, Yufang Shi, Weiqing Zhao, Jing Cao, Xuyong Cao, Yuncen Lei, Mingxing Su, Xiuyun Cui, Qiu Liu, Yaosheng Prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer |
title | Prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer |
title_full | Prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer |
title_fullStr | Prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer |
title_full_unstemmed | Prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer |
title_short | Prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer |
title_sort | prediction of postoperative health-related quality of life among patients with metastatic spinal cord compression secondary to lung cancer |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502718/ https://www.ncbi.nlm.nih.gov/pubmed/37720536 http://dx.doi.org/10.3389/fendo.2023.1206840 |
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