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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...

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Autores principales: Fu, Yufang, Shi, Weiqing, Zhao, Jing, Cao, Xuyong, Cao, Yuncen, Lei, Mingxing, Su, Xiuyun, Cui, Qiu, Liu, Yaosheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
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.
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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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